Salinity tolerance of wild rice accessions from northern

Salinity tolerance of wild rice

accessions from northern

Australia

A thesis submitted in partial fulfilment of requirements for the degree of

Doctor of Philosophy

Yoav Yichie

School of Life and Environmental Sciences

Faculty of Science

University of Sydney

Australia

February 2020

Statement of Originality

This is to certify that to the best of my knowledge the content of this thesis is my own work

This thesis has not been submitted for any degree or other purposes

I certify that the intellectual content of this thesis is the product of my own work and that all

the assistance received in preparing this thesis and sources have been acknowledged

Yoav Yichie

3th February 2020

Dedication

ldquoDid you feel the limelight

Slipping away from your hold

Did you feel the darkness sinking into your soul

Glowing isnt easy and nobody wants

To feel forgotten to be forgot

Amy died running through the night

Trying to hide from the quiet inside

But you never can you never will its yours

Takes its toll all that rock n roll

It takes another little piece of your heart and soul

But were all climb but not the fallrdquo

The Climb the Fall

Luke Thompson

This PhD thesis is in memory of my dearest friend Yonatan Goren who was always there by

my side when I needed him but unfortunately left us too soon Yonatan I hope yoursquore still

climbing high snowy mountains reaching fresh peaks and watching the horizon as you always

loved You are a true inspiration for those wanting to live their life to its fullest Yoursquore deeply

missed

Acknowledgments

The successful completion of this dissertation would not have been possible without the

contribution of many people First and foremost I would like to thank my supervisors AProf

Tom Roberts (University of Sydney) and Prof Brian Atwell (Macquarie University) for their

support enthusiasm encouragement and life advice I deeply appreciate the research skills

you taught me your patience and giving me the opportunity to develop my hypothesis

Both Tom Roberts and Brian Atwell provided editorial assistance during the writing of this

thesis

I would also like to express my gratitude to Dr Mafruha Hasan (University of Sydney) for her

patience support and kindness in giving me her precious time and input Mafruha also

provided editorial assistance for Chapter 4 To Dr Bettina Berger from the Plant Accelerator

for making me feel welcome and supported To the team at the Plant Accelerator who helped

me through my time in Adelaide and subsequent data analysis Dr Chris Brien George

Sainsbury Lidia Mischis Nicky Bond Dr Guntur Tanjung Fiona Groskreutz and Dr Nicholas

Hansen

A big thanks to Dr Ben Crossett and Dr Angela Connolly from the Mass Spectrometry Core

Facility at the University Sydney for their valuable inputs into my project

I would also like to extend my gratitude to Dr Dana Pascovici (Macquarie University) for her

expert help with the statistical analysis of my proteomics results I would also like to

acknowledge Dr Steve Van Sluyter (Macquarie University) Dr Peri Tobias (University of

Sydney) and Dr Hugh Goold (Macquarie University) for providing guidance and support during

my laboratory work I have learned a great deal from them much of the success of my work

can be attributed to their insights and laboratory experience I would also like to thank Iona

Gyorgy for her help and knowledge in the laboratory

My deepest gratitude goes to my parents Judy and Iftach whose unconditional love and

support has kept me strong and focused to pursue my goals Thank you for educating me to

love and appreciate nature and agriculture To my siblings Hagai Tamar and Roni and their

partners who were always supporting regardless of the distance I would also like to thank my

three Australian lsquosistersrsquo Hila Mandy and Shimrit for always being there to lift my spirit laugh

hug and surf Thank you for making me feel at home away from home

Special thanks to my beloved and beautiful wife Neta for her patience understanding and

support through this challenging yet rewarding journey Thank you for bearing with me through

thick and thin sharing the joyful moments of life and for weekends spent watering and looking

after rice plants

I would like to express my gratitude to Dr Abdelbagi Ismail and Dr Kshirod Jena for being warm

hosts for my visit to IRRI (2016) I am grateful for letting me work closely with your teams to

take my first steps in rice research I would also like to thank the IRRI team members James

Egdane and Marjorie De Ocampo for making sure I received hands-on experience in the best

rice research practices Lastly I thank Dr Sung-Ryul Kim who is taking our collaboration

forward at IRRI

I would like to pay respect to the late Evan van Regenmorter who was the first person to read

and provide feedback on Chapter 1 of this thesis Evan thanks for your kind help your valuable

comments contributed to the shape of this entire project RIP dear friend

Finally I wish to acknowledge The Australian Government and The University of Sydney for

awarding me an International Postgraduate Research Scholarship which provided financial

support during this project I also gratefully acknowledge the financial support provided by The

Plant Accelerator (Australian Plant Phenomics Network) to use the facility and achieve some

of my research goals and to the Norman Matheson Student Support Award for helping me to

pursue a valuable collaboration with IRRI

Abbreviations

ABA Abscisic acid

ACN Acetonitrile

AGR Absolute growth rate

ANOVA Analysis of variance

BCA Bicinchoninic acid

CTAB Cetyl trimethylammonium bromide

DAS Days after salting

DAT Days after transplanting

DTT Dithiothreitol

DF Degrees of freedom

DNA Deoxyribonucleic acid

EC Electrical conductivity

EDTA Ethylenediaminetetraacetic acid

FDR False discovery rate

FLUO Fluorescence

GC-MS Gas chromatography mass spectrometry

InDel InsertionDeletion

IRRI International Rice Research Institute

KEGG Kyoto Encyclopaedia of Genes and Genomes

LR Leaf rolling

MALDI Matrix-assisted laser desorptionionisation

MS Mass spectrometry

mz Mass to charge ratio

Nano-LC-MSMS Nano flow liquid chromatography tandem mass spectrometry

NCBI National Centre for Biotechnology Information

NSAF Normalised spectral abundance factor

Oa-D Oryza australiensis- Derby

Oa-VR Oryza australiensis- Victoria River

PCA Principal component analysis

PEG Polyethylene glycol

PloGO Plotting gene ontology annotation

PM Plasma membrane

PRIDE Proteomics Identifications

PSA Projected shoot area

PVC Polyvinyl chloride

QTL Quantitative trait locus

REML Restricted maximum likelihood

RGB Red-green-blue

RGR Relative growth rate

RNA Ribonucleic acid

ROS Reactive oxygen species

RT-qPCR Reverse transcription quantitative polymerase chain reaction

SDW Shoot dry weight

SES Standard evaluation system

SFW Shoot fresh weight

SNP Single nucleotide polymorphism

sPSA Smoothed projected shoot area

ST Salinity tolerance

TFA Trifluoroacetic acid

TMT Tandem mass tag

WUI Water use index

YFL Youngest fully expanded leaf

Journal articles

Parts of this thesis have been published elsewhere

Peer-reviewed publications

Yichie Y Brien C Berger B Roberts TH Atwell BJ (2018) Salinity tolerance in Australian

wild Oryza species varies widely and matches that observed in O sativa Rice 1166 (See

Chapters 2 and 3)

Yichie Y Hasan MT Tobias PA Pascovici D Goold HD Van Sluyter SC Roberts TH Atwell

BJ Salt-treated roots of Oryza australiensis seedlings are enriched with proteins involved in

energetics and transport Proteomics 19 1ndash12 (See Chapters 4 and 5)

Copies of these journal articles can be found in the Appendix

Presentations awards and visits Presentations

Y Yichie CJ Brien ND Jewell T H Roberts and BJ Atwell High-throughput non-

invasive phenotyping reveals seedling-stage salinity tolerance in Australian wild rice

species Poster presentation at the Annual Meeting of the American Society of Plant

Biologists (14ndash18 July 2017) Honolulu USA

species Poster presentation at the Higher Degree by Research Symposium for the

School of Life and Environmental Sciences (20 September 2017) at The University

Sydney Australia

species Poster presentation at ComBio conference (3ndash5 October 2017) Adelaide

Australia

Y Yichie T H Roberts and BJ Atwell Salinity tolerance in Australian wild Oryza

species from physiology to mechanisms Poster presentation at the Annual Meeting of

the American Society of Plant Biologists (3ndash7 August 2019) Cal USA

Awards

University of Sydney International Postgraduate Research Scholarship (IPRS) (March

2016 - August 2019)

Postgraduate Research Support Scheme (PRSS) for travel to international

conferences (August 2016 ndash August 2019)

2nd place best poster presentation Higher Degree Research Symposium School of

Life and Environmental Sciences The University of Sydney (2017)

Best Poster Award in Plant Phenotyping ComBio conference Adelaide Australia

(2017)

2nd place best poster presentation Sydney Institute of Agriculture The University of

Sydney (2018)

Norman Matheson Research Support Fund award (2018)

Research visits

30th November ‒ 8th December 2016 International Rice Research Institute Crop and

Environmental Sciences Division Los Bantildeos Philippines

February ‒ April 2017 The Australian Plant Phenomics Facility (APPF) The University

of Adelaide Australia

Abstract

Salinity is a limiting factor for rice production globally Cultivated rice (Oryza sativa) is highly

sensitive to salinity I studied the salt tolerance of Australian wild Oryza species to identify

diversity in salt tolerance and target genes for molecular breeding I first performed two

physiological salt-screening experiments on nine wild accessions from a range of sites across

northern Australia for growth responses to NaCl up to 120 mM Screens at 40ndash100 mM NaCl

revealed considerable variation in salt sensitivity in accessions of O meridionalis (Om) and O

australiensis (Oa) Growth of an Oa accession (Oa-VR) was especially salt tolerant compared

with other accessions including a salt-tolerant lsquocontrolrsquo of O sativa Pokkali At 80 mM NaCl

the shoot Na+K+ ratio was the lowest in Oa-VR and Pokkali An image-based screen was then

conducted to quantify plant responses to different levels of salinity over 30 d This revealed

striking levels of salt tolerance supporting the earlier screens

Root membrane fractions of two Oa accessions with contrasting salinity tolerance (Oa-VR and

Oa-D) were subjected to quantitative proteomics to identify candidate proteins contributing to

salt tolerance Plants were exposed to 80 mM NaCl for 30 d Root proteins were analysed via

tandem mass tag (TMT) labelling Gene Ontology (GO) annotations of differentially abundant

proteins showed those in the categories lsquometabolic processrsquo lsquotransportrsquo and lsquotransmembrane

transporterrsquo were highly responsive to salt mRNA quantification validated the elevated protein

abundances of a monosaccharide transporter and a VAMP-like antiporter in the salt-tolerant

genotype The importance of these two proteins was confirmed by measuring growth

responses to salt in two yeast mutants in which genes homologous to those encoding these

two proteins in rice had been knocked out

This study provided insights into physiological and molecular mechanisms of salinity

responses in Australian native rice species

Table of Contents Statement of Originality ii Dedication iii Acknowledgments iv

Abbreviations vi Journal articles ix

Presentations awards and visits x

Abstract xii Table of Contents xiii List of Figures xvii List of Tables xx

Chapter 1 Literature review 1

11 Introduction 2

111 Vulnerability of crop production to salinity 2

112 Plant responses to salt stress 3

113 Importance of rice production 4

114 Wild species as a resource to improve crop productivity 5

12 Background 6

121 Origin of rice 6

122 Development of the rice plant 6

123 Rice as a major staple food 7

124 Rice production in Australia 8

125 Can rice continue to feed the world 9

13 Australian wild rice species 10

131 Exploring the Australian native wild rice species 10

132 Australian wild species as a source of plant breeding 13

14 Soil salinity impact and management 15

141 The scale of soil salinity worldwide and its impact 15

142 Management of saline soils 15

15 Salt tolerance genetic variation and mechanisms 16

151 The genetic basis of salt tolerance 16

152 The genetics of salt tolerance in rice 16

153 Salt tolerance mechanisms 17

154 Physiological responses to salinity 18

155 Salinity tolerance in different plant species 20

156 Genetic variation as a tool of plant breeding 23

157 Wild rice species as a source for improving abiotic stress tolerance 24

16 Conclusion 26

17 Aims of the project 27

Chapter 2 Preliminary salt screening 29

21 Introduction 30

22 Materials and methods 32

221 Experimental setup 32

222 Tiller number and seedling height 34

223 Salinity tolerance (ST) leaf rolling (LR) and standard evaluation system (SES) scale 34

224 Gas exchange parameters 35

225 Biomass harvest parameters 35

226 Analysis of inorganic ions 36

227 Chlorophyll content 36

228 Data analysis 37

23 Results and discussion 37

231 First salt screening to establish a core collection of salt-tolerant accessions 37

232 Second salt screening to validate the salt tolerance accessions core collection 48

233 Conclusion 60

Chapter 3 High-throughput image-based phenotyping 63

31 Introduction 64

321 Plant materials 67

322 The plant accelerator greenhouse growth conditions 68

323 Phenotyping 68

324 Image capturing and processing 70

325 Image processing for senescence analysis 70

326 Data preparation and statistical analysis of projected shoot area (PSA) 71

327 Functional modelling of temporal trends in PSA 72

33 Results 74

34 Discussion 83

35 Conclusion 86

Chapter 4 Proteomics 88

41 Introduction 89

411 Proteomics studies of plant response to abiotic stresses 89

412 Quantitative proteomics approaches in rice research 89

413 Rice salt tolerance studies using quantitative proteomics approaches 91

421 Growth and treatment conditions 92

422 Proteomic analysis 93

423 Protein extraction and microsomal isolation 95

424 Protein quantification by bicinchoninic acid (BCA) assay 96

425 Lys-Ctrypsin digestion 96

426 TMT labelling reaction 97

427 NanoLC-MS3 analysis 98

428 Proteinpeptide identification 99

429 Database assembly and protein identification 99

4210 Analysis of differently expressed proteins between the accessions and salt treatments 100

4211 Functional annotations 101

43 Results 102

431 Physiological response to salt stress 102

432 Protein identification through database searches 102

433 Statistically significant differentially expressed proteins 105

434 Functional annotation and pathway analysis 108

44 Discussion 112

441 Similarities in the genome of O australiensis and other Oryza species 112

442 Membrane-enriched purification protocol 113

443 Assessment of the assembled databases for protein discovery 115

444 Proteins most responsive to salt 116

445 Up-regulation of protein clusters involved in energy metabolism vesicle trafficking and membrane phagosomes under salt stress 118

45 Conclusion 120

Chapter 5 Validation of salt-responsive genes 122

51 Introduction 123

511 Proteomics as a powerful tool but with limitations 123

512 Validation of proteomics studies 123

521 Quantitative reverse-transcription PCR (RT-qPCR) 124

522 Validation of salt growth phenotypes using a yeast deletion library 128

523 Protein sequence alignment 129

53 Results 130

532 RNA extraction 130

533 Alignment and phylogenetic analysis 130

534 Primer screening assay and amplicon gel electrophoresis 131

535 RT-qPCR 132

536 Validation of candidate salt-responsive genes using a yeast deletion library 135

54 Discussion 139

541 RT-qPCR 139

542 First yeast validation salt screening 143

543 Second yeast validation salt screening 146

55 Conclusion 146

Chapter 6 Towards QTL mapping for salt tolerance 149

61 Introduction 150

611 QTL mapping concept and principles 150

621 Bi-parental mapping population construction 152

622 Salt screening field trial 153

623 Genotyping using the Illumina Infinium 7K SNP chip array 153

63 Results 154

631 Mapping population construction 154

632 Plant growth and hybrid viability 156

Chapter 7 General discussion and future directions 160

71 Conclusions and future perspectives 161

72 Closing Statement 168

Chapter 8 Bibliography 169

Appendix 193

List of Figures

Figure 1-1 Paddy rice production worldwide in 2017 by country in millions of

tonneshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip8

Figure 1-2 2015 global rice consumptionhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip10

Figure 1-3 The distribution of Oryza species in Australiahelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip12

Figure 1-4 An Oryza phylogenetic tree generated from matK gene sequences of 23 rice

specieshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip12

Figure 1-5 Illustration of the genetic bottlenecks that have constrained crop plants

during early domestication processes and modern plant-breeding

practiceshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip14

Figure 1-6 A schematic response of a plant to abiotic

stresshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip17

Figure 1-7 A schematic presentation of the shoot growth responses to salinity stress by

osmotic and ionic phaseshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip19 Figure 1-8 Published shoot and root plant major tolerance mechanisms found in

cerealshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip22

Figure 1-9 Effects of salt stress on sensitive and tolerant ricehelliphelliphelliphelliphelliphelliphelliphelliphellip26

Figure 2-1 Shoot phenotype responses to three salt treatments at 30 DAS for the salt-

sensitive (IR29) Om-HS and Oa-VR accessions and salt-tolerant O sativa cv

Pokkalihelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip41

Figure 2-2 Comparison of (a) SES scores and (b) leaf rolling of the tested wild rice

accessions and domesticated rice controls at 75 and 120 mM NaClhelliphelliphelliphelliphelliphelliphellip42

Figure 2-3 Comparison of shoot fresh weight (SFW) and dry shoot weight (DSW) yields

for all salt treatmentshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip43

Figure 2-4 Phenotypic changes in response to three salt treatments at 28 DAS for all

tested accessions and the O sativa controlshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip52

Figure 2-5 Comparison of (a) SES scores and (b) Leaf Rolling of the different tested

accessions and controls among 40 (black) and 80 (grey) mM salt treatmentshelliphelliphellip53

Figure 2-6 Comparison of Fresh Shoot Weight (FSW) (black) and Dry Shoot Weight

(DSW) (gray) yields for all salt treatments tested in the screening abovehelliphelliphelliphelliphellip55

Figure 2-7 Linear regression of Salinity Tolerance (ST) against (a) leaf

Na+ concentrations [μmol Na+ g-1 (SDW)] (R2 = 075) and (b) leaf K+ concentrations

[μmol Na+ g-1 (SDW)] (R2 = 069)helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip56

Figure 3-1 Experimental setup at the Plant Accelerator facilityhelliphelliphelliphelliphelliphelliphelliphelliphellip71

Figure 3-2 Example of rice shoot biomass images taken 20 DAS in The Plant

Accelerator facilityhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip73

Figure 3-3 Relationships between Projected Shoot Area (PSA kpixels) 28 and 30thinspdays

after salting with (shoot fresh and dry weight) based on 168 individual plants using

fluorescence images helliphelliphelliphelliphelliphellip helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip75

Figure 3-4 Correlations between RGB- and FLUO-based measurements of PSAhellip76

Figure 3-5 Smoothed projected shoot area (PSA) values for each biological replicate to

which splines had been fitted through the experimenthelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip78

Figure 3-6 Relationship between PSA and (a) compactness and (b) centre of

masshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip79

Figure 3-7 Absolute growth rates in kpixels per day of all tested genotypes from 0 to 30

DAS including non-salinised controlshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip80

Figure 3-8 Relationship between growth and water use during salt treatment for each of

the six tested intervalshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip82

Figure 3-9 Average of relative senescence of each tested genotype in three salt

treatmentshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip83

Figure 4-1 Schematic diagram of the TMT-labelled quantitative proteomics

workflowhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip94

Figure 4-2 Diagram of the TMT-labelling strategy used in the

experimentshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip98 Figure 4-3 Gene ontology classification of all 2030 proteins derived from the Oryza

database and annotated to cellular component functions utilising the UniProt

platformhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip105

Figure 4-4 Summary of the statistical tests performed using the PloGO toolhelliphelliphellip107

Figure 4-5 Oxidative phosphorylation pathways from the KEGG mapperhelliphelliphelliphellip110

Figure 4-6 SNARE interactions in vacuolar transport pathways from the KEGG

mapperhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip111

Figure 5-1 Protein sequence alignment of homologues of significantly differentially

expressed proteins in the O australiensis accessionshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip131

Figure 5-2 RT-qPCR mean Ct values (with standard errors) for each of the tested

genes for the two O australiensis accessions under 80 mM salt and control

conditionshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip133

Figure 5-3 Linear regression of mean neat Ct values vs log10 of RNA template

dilutions (starting quantity=100 ng) for reference gene eEF-1a across all four

genotypesalt treatment sampleshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip134

Figure 5-4 Colony growth of wild type BY4742 yeast and the eleven tested

strainshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip136

Figure 5-5 Colony growth of all tested yeast knockout strains and wild type BY4742

after 72 h in YPD medium with three different NaCl concentrations and no salt

controlhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip137

Figure 5-6 Colony growth of wild type BY4742 yeast and strains YLR081W and

YLR268W which have deletions in a gene homologue to the rice OsMST6 gene and a

V-SNARE gene respectivelyhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip138

Figure 5-7 Top four final models predicted by multiple algorithm by I-TASSER for the

OsMST6 proteinhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip142

Figure 6-1 PCR products amplified using markers RM153 and RTSV-pro-F1R1 were

generated for parents and putative F1 plantshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip155

Figure 6-2 Plants used in production of IR24 x Om-T hybridshelliphelliphelliphelliphelliphelliphelliphelliphellip157

Figure 6-3 Phenotype of mature pollen grains of six different hybrid plants (each square

represents an individual hybrid) using iodine staininghelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip158

List of Tables Table 2-1 Modified scoring scheme for seedling-stage salinity tolerance based on visual

symptoms using the International Rice Research Institute (IRRI) standard evaluation

system (SES) scoreshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip37

Table 2-2 List of accessions selected for the first screeninghelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip40

Table 2-3 Number of tillers net photosynthetic rate and plant height of the nine wild Oryza

accessions and three O sativa controlshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip44

Table 2-4 Number of tillers net photosynthetic rate and plant height under of the four wild

Oryza accessions and two O sativa controlshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip54

Table 2-5 Correlation of different traits at seedling-stage under the same salinised

conditionhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip54

Table 4-1 Comparison of the four databases used to match proteins identified and

quantified by multiple peptides for O australiensis accessions using the TMT quantification

method (FDR lt1)helliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip103

Table 5-1 Primer names and locations UniProt accessions O sativa gene name and

expected amplicon size for RT-qPCRhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip126

Table 5-2 Summary of all genes analysed in the RT-qPCR experiment and their respective

protein abundanceshelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip127

Table 5-3 All tested yeast deletion strains in the preliminary screening for differences

(compared to wildtype) in colony growth under salinityhelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphelliphellip129

Chapter 1 Literature review

A literature review of the magnitude of saline soils and salinity-tolerance studies currently available in rice and other crops

11 Introduction

Efficient food production systems require the cultivation of locally adapted germplasm under

optimal atmospheric and soil conditions Sophisticated genetic tools and management

practices are essential to maximise crop performance especially when environmental factors

such as poor irrigation practices climate change and biotic and abiotic stresses have to be

considered A major contributor to improvement of crops throughout the remainder of this

century will be introgression of a broader range of genetic diversity than has been done to

date this can be achieved by harnessing crop relatives

Abiotic stresses can dramatically diminish crop yields as has been the case since the dawn

of agriculture when droughts salinity and the unpredictability of river systems made and

destroyed civilisations (Zaman et al 2018) Frosts and heatwaves as well as imbalances in

inorganic nutrients and waterlogging continue to cause spasmodic catastrophic yield losses

However the most common abiotic stresses limiting crop production globally are probably

drought and soil salinity which are therefore targets for selection of novel genotypes and

genetic engineering of new cultivars

111 Vulnerability of crop production to salinity

Continuing shifts in the worldrsquos climate system exacerbate the occurrence frequency and

intensity of abiotic stresses such as drought floods and salinisation Soil salinity affects more

than one billion hectares worldwide (Zhu 2001 FAO 2008) and poses a particular risk to those

crops that are especially salt sensitive (Mass et al 1977 Katerji et al 2000) Salinised soils

contain enough salts to interfere with normal plant growth they are divided into saline soils

mostly caused by excess free ions of sodium and chloride and sodic soils which have a

disproportionate amount of sodium in their cation exchange complex Excess sodium

compromises soil structure and thus internal drainage Soils are categorised as saline once

the measured electrical conductivity (EC) is 4 dSm or higher (httpwwwarsusdagov) which

is approximately equivalent to 40 mM NaCl Overall soil salinity has dire economic

consequences with annual income losses of approximately USD 12 billion globally (Ghassemi

et al1995) In Australia soil salinity income losses were estimated more than ten years ago

to be about AUD 133 billion per annum (Rengasamy 2006) and it has been estimated that

more than 50 of arable land worldwide would be affected by salinity by 2050 (Jamil et al

In the early 21st century Zhu stated that no less than 20 of the worldrsquos cultivated land and

almost half of all irrigated fields are affected by salinity (Zhu 2001) Approximately 20 of

irrigated lands globally are salt-affected equal to roughly 12 billion hectares (FAO Database

2008) with an annual loss of more than USD 27 billion (Qadir et al 2014) The latest report

suggests that contributing to this loss 54 million hectares are classified as highly saline soils

(Campbell et al 2015)

112 Plant responses to salt stress

Plant responses to salt stress occur in two distinct phases First is the osmotic phase which is

an immediate hydraulic response to the high external osmotic pressure caused by the

difference in salt concentration between the soil solution and the plant tissue Secondly the

ion accumulation phase begins to take effect in a time-dependent manner resulting in the

accumulation of salts to toxic levels in leaves (Munns et al 2008) The osmotic phase is

associated with a hydraulic crisis and consequent decrease in turgor pressure and the rate of

leaf expansion while the ionic phase is associated with cell damage and increased

senescence of mature leaves (Munns et al 1988) Signalling influences the downstream

effects of salinisation on physiological processes (Peleg et al 2011)

lsquoSalt tolerancersquo implies an ability of plants to grow and complete their life cycles in the presence

of persistent and substantial sodium chloride concentrations in the root zone However the full

range of acclimation mechanisms are complex and incompletely understood Key biochemical

pathways are under polygenic control with signal transcription factors and

structuralanatomical changes also playing into tolerance (Tester et al 2003 Wang et al

2003a Munns et al 2016 Liang et al 2018 Alqahtani et al 2019) Moreover gene

expression and membrane-transport phenomena vary between plant tissues (eg roots vs

leaves) and through time For example once salts have been delivered to the leaf tissues ion

partitioning and biochemical (tissue) tolerance become critically important Logically species

that evolved in saline or sodic soils exhibit the broadest range of morphological physiological

anatomical and metabolic adjustment adaptations to survive under high salt levels

The substitution of specific traits from a poorly adapted species carrying many undesirable

genes involves multiple backcrosses and selections to reduce linkage drag Despite these

difficulties the contribution of wild relatives to breeding programs is substantial and growing

rapidly (Zamir 2001 Colmer et al 2006 Lundstroumlm et al 2017) Much research on salt

tolerance has been focused on the model plant Arabidopsis thaliana and key crop plants such

as durum wheat (Triticum durum) tomato (Solanum lycopersicum) grain legumes (eg

Lupinus sp) and rice In these major food crops the use of wild relatives in breeding for salt

tolerance is attracting increasing attention (Saranga et al 1992 Kumar et al 2005)

113 Importance of rice production

Rice is a monocot in the family Poaceae (Gramineae) and belongs to the genus Oryza which

contains two cultivated species the Asian cultivated rice Oryza sativa and the African

cultivated species Oryza glaberrima These domesticated species both with an AA genome

are distinguished by a wide range of desirable agronomic traits O sativa is overwhelmingly

the dominant rice species worldwide but has itself evolved from multiple introgressions from

wild relatives notably Oryza rufipogon (Nishikawa et al 2005 Jacquemin et al 2013) O

sativa includes two major subspecies japonica broadly from East Asia and indica from the

Indian sub-continent (Cheng et al 2003 Fuller et al 2010) Genetic variation and evolutionary

dynamics between japonica and indica have been studied by identifying and analysing in silico

~50000 polymorphic SSR markers of the rice genome (Grover et al 2007 Wang et al 2018

Carpentier et al 2019) using genomes from the 3000 Rice (Osativa) Genomes Projects

Rice is the most widely cultivated cereal grain worldwide and is a mainstay for the rural

economies of much of the developing world and therefore the food security of many poor

societies In 2017 the worldwide production of rice was more than 984 million tonnes which

is the second largest grain production after maize (139 billion tonnes) and approximately equal

to wheat (960 million tonnes) (wwwfaostatfaoorg)

Approximately 90 of the consumption of rice worldwide is in Asia where rice is a staple food

for more than 600 million people who live in extreme poverty (Mohanty et al 2013) A major

part of the caloric intake for those societies and others in Africa and Latin America is based on

rice as a meal at least twice a day (Khush 2005) Since the world population is expected to

increase by at least 25 by 2050 (United Nations World Population Prospects 2017) a

commensurate increase in rice production is required to meet demand (FAOSTAT 2009)

114 Wild species as a resource to improve crop productivity

The introgression of exotic genetics into commercial cultivars is time-consuming and

challenging because of incompatibility barriers The substitution of specific traits from a poorly

adapted species carrying many undesirable genes involves multiple backcrosses and

selections to reduce linkage drag Despite these difficulties the contribution of wild

introgression for breeding programs has been tremendous in recent years (Hake et al 2019)

expanding research well beyond salt-tolerance mechanisms in Arabidopsis thaliana In the last

two decades there has been growing recognition of the value of wild genetic germplasm as a

source of novel mechanisms of salt tolerance Examples of wild relatives of key crop plants

that have natural allelic variations related to salt tolerance include durum wheat (Triticum

durum) and tomato (Solanum lycopersicum) (Saranga et al 1992 Kumar et al 2005)

Despite the recognition of Australian endemic rice species as potential contributors to abiotic

stress tolerance (Henry et al 2010 Atwell et al 2014) they have been poorly characterised

These wild relatives represent a dynamic resource that could extensively enrich traditional crop

improvement (Huang et al 2012) Highly targeted GM technologies are a desirable alternative

to conventional breeding if regulatory hurdles can be cleared Furthermore studies of wild

relatives of rice are likely to inform molecular breeding in other cereal crops

In Asia where there is strong dependence on rice abiotic stresses including salinity frequently

compromise rice yields Exacerbating this problem rice is also one of the most salt-sensitive

major agricultural species (Munns et al 2008) making it vulnerable to poor irrigation practices

and marine inundation Indeed rice grain yield can be reduced by half in a soil salt

concentration as little as 50 mM NaCl (Yeo amp Flowers 1986 Radanielson et al 2018) A large

number of enormous rice fields in Asia are no longer suited for rice growth due to the high salt

concentration of the soil (Hoang et al 2016)

This chapter aims to provide detailed information on the worldwide salinity problem with

suggestions for novel approaches to build salinity tolerance in rice Several studies have been

conducted to reveal the salt tolerance mechanisms of rice (Fukuda et al 2004 Ren et al

2005 Thomson et al 2010) but much more needs to be learned I will make a case for the

use of wild relatives to improve salt tolerance of elite varieties by focusing on the unexplored

genetic variation stored in Australian endemic Oryza species

12 Background

121 Origin of rice

Rice domestication is believed to have commenced approximately 10000 years ago when

ancient civilisations initiated agriculture and consumed the wild grass Oryza rufipogon from

swamps and marshes species in Asia (Sang et al 2007 Kovach et al 2007) Studies have

been carried out to reveal the demographic history of rice domestication and the phylogenetic

relationships between the species in the genus Oryza (Piegu et al 2006 Trivers et al 2009

He et al 2011 Huang et al 2012 Stein et al 2018) A demographic study of single

nucleotide polymorphisms (SNP) suggested a single origin for rice domestication (Molina et

al 2011) On the other hand several genome-wide studies have suggested that indica and

japonica had independent phylogenetic origins (He et al 2011 Xu et al 2012) Overall indica

rice was presumed to be domesticated in the Indian Himalayas while japonica originated in

southern China (Khush 1997) Today the specific origin of rice is still a point of contention

between researchers (Kovach et al 2007) but with all theories taken together the current data

support the recently proposed rsquocombination modelrsquo for rice domestication (Sang et al 2007

Choi et al 2018)

122 Development of the rice plant

Rice is cultivated as an annual However O sativa is often grown twice a year in some

agricultural systems to improve production and other Oryza species can be perennial such as

Oryza rufipogon (Yamanaka et al 2003) A key characteristic of rice is that it is the only grain

crop that can grow well in extremely wet soil or even in standing water It is commonly cultivated

in coastal belts if they have not been exposed to inundation by sea water at high tides

Plants tiller to various degrees depending upon genetics and environment Environmental

factors such as light nutrient (especially nitrogen) supply density of planting and predation

interact with genetics to determine the number of tillers on each plant Among the wild Oryza

relatives there are widely divergent rates of tillering with O meridionalis and O rufipogon

being abundant producers of tillers and O australiensis tillering only very sparingly

In the reproductive phase of all Oryza species flowers are borne on single panicles for each

tiller and then generally self-pollinated Thus the typical sexual reproductive pattern seen in

other cereals is observed in rice In favourable environmental conditions the result is multiple

panicles each bearing large numbers of caryopses

123 Rice as a major staple food

O sativa comprises two major subspecies long-grained non-sticky indica and short-grained

sticky japonica Varieties from the sub-species japonica are usually cultivated in dry fields

(such as China Japan Korea Taiwan) while indica varieties are mainly grown in lowland

areas mostly rainfed and often submerged throughout tropical Asia such as India

Bangladesh and Indonesia

Rice production globally is almost three times higher today (122019) compared with 1965

(httpwwwfaoorg) This increase is mostly due to varietal improvement made by the

International Rice Research Institute and other breeding institutions Today there are more

than 130000 accessions of rice globally (httpswwwirriorginternational-rice-genebank)

Thousands of these are being grown across several continents including Asia Africa South

and North America (Fig 1-1) in diverse growing conditions including lowland and upland rain-

fed irrigated and flood-prone ecosystems

Figure 1-1 Paddy rice production worldwide in 2017 by country in millions of tonnes

Source Food and Agriculture Organization of the United Nations 2019 (httpwwwfaoorg)

124 Rice production in Australia

Cultivated rice varieties were first introduced to Australia in 1850 by Asian workers of the Gold

Rush Today rice is a relatively minor crop in Australia the sixth most important after wheat

oats barley sorghum and maize with approximately AUD 800 million in revenue per year The

crop relies heavily on irrigation thus the total Australian production is highly variable due to

variation in the availability of water The estimated average area of 800000 hectares used for

rice is mostly in the states of New South Wales (NSW) and Victoria with production of

approximately 700000 tonnes per year The highest total rice production in Australia was

recorded in 2013 with more than 12 million tonnes (httpwwwabsgovau) In 2017 an

ongoing drought restricted the harvested area to only 80000 ha with an average yield of 98

tonnesha (httpwwwfaoorg)

In addition to meeting a large part of domestic demand most Australian rice (60ndash80) is

exported predominantly to the Middle East North America and Asia representing 2 of world

rice trade (httpwwwagriculturegovau) Eighty percent of the rice produced in Australia

0 50 100 150 200 250

ChinaIndia

IndonesiaBangladesh

VietnamThailand

MyanmarPhilippines

NigeriaBrazil

PakistanUnited States of America

JapanCambodia

Republic of KoreaEgyptNepal

Lao Peoples Democratic RepublicMadagascar

PeruColombiaTanzania

MaliMalaysia

KoreaGuinea

Australia

Rice production [Millions of tonnes]

comprises varieties from the sub-species japonica with several niche cultivars developed for

aroma and glutinous properties such as Koshihikari varieties for the Japanese market While

production is entirely dependent on irrigation the Australian rice industry leads the world in

terms of water use efficiency (WUE) using 50 less water per tonne of grain yield than the

global average (wwwagriculturegovau) Rice growing in Australia is technologically

sophisticated and will have an important place in the nationrsquos agriculture into the long-term

future because of ongoing domestic and international demand

125 Can rice continue to feed the world

It is estimated that for every one billion people added to the worldrsquos population an additional

100 million tonnes of rice need to be produced each year (McLean et al 2013) In less than

four decades the worldrsquos population is predicted to reach 9 billion raising the ldquo9-billion-peoplerdquo

concern (Muir et al 2010) There are immense challenges even to maintain global rice

production let alone increase it It is clear to both the scientific community and farmers that to

provide food security reduce poverty and strengthen vulnerable populations to adapt to the

effects of climate change higher rice yields are required on existing arable land (Fig 1-2)

It is projected that food production overall must increase by 87 globally by 2050 from current

levels with the burden falling mainly on crops such as rice wheat soy and maize (Kromdijk et

al 2016) A large part of the challenge will entail adaptation to abiotic stresses such as

drought heat salinity and cold These stresses cause significant but unpredictable yield

penalties across large areas especially when they co-occur resulting in the most severe

examples in total crop losses (Wang et al 2003b) inundations of rice crops by insurgency of

seawater are a case in point These events are expected to be more frequent and severe in

the future

Figure 1-2 2015 global rice consumption (in million tons of milled rice) and predictive demand for the next twenty years (source IRRI)

13 Australian wild rice species

131 Exploring the Australian native wild rice species

In Australia there are four endemic species of the Oryza genus O meridionalis O rufipogon

O australiensis and O officinalis The first three species are widespread across the northern

and the western regions of the continent (Fig 1-3)

O meridionalis is found at the edges of freshwater lagoons temporary pools rivers and

swamps It usually grows in a clay soil in open habitats and can survive as seed in the dry

seasons It is an annual species with rare secondary branching and a diploid AA genome

comprising of 24 chromosomes (2n=2X=24) O meridionalis has been found in Queensland

as well as the Northern Territory and Western Australia It also occurs in Papua New Guinea

and Indonesia

O australiensis is a perennial species which is found only in Australia in the north and the

west parts of the continent mostly in wet environments such as swamps or beside lakes and

under stands of Eucalyptus and Leptochloa It can also be found in relatively drier areas

(compared with the other Oryza species) such as dry pools or behind river levees It is

distinguished from the other Australian relatives by its EE diploid genome (Fig 1-4)

(2n=2X=24) the largest of any Oryza species due to retrotransposons which have effectively

doubled the size of the genome (Piegu et al 2006)

O officinalis is a perennial that grows in seasonally wet areas near swamps and along

lakesides or rivers in the north of Queensland and in the Northern Territory Within the O

officinalis complex there are ten species ranging from diploid (2n=2X=24) to tetraploid

(2n=4X=48) with six different types of genomes BB CC BBCC CCDD EE and FF (Jena

2010) (Fig 1-4) O officinalis can be found in forests and in abandoned (or rarely on the edge

of) cultivated rice fields In Southeast Asia it grows in coastal regions It is also endemic to

various countries apart from Australia including India Bangladesh China The Philippines

Papua New Guinea Thailand Vietnam Nepal Myanmar Indonesia and Malaysia

O rufipogon is a perennial that can reach five metres in height depending on the depth of the

water in which it grows It has an AA diploid genome (2n=2X=24) (Fig 1-4) It is strongly

hydrophytic growing in swamps and marshes in open ditches grassland pools along river

banks or at side lakes in margins of rice fields commonly in deep water areas In Australia it

is mostly found in Queensland through the Northern Territory and Western Australia mostly

near the coast Outside of Australia it is native to The Philippines Vietnam Myanmar Nepal

Papua New Guinea Sri Lanka Thailand Bangladesh China India Indonesia and Malaysia

Figure 1-3 The distribution of Oryza species in Australia (Adapted from Henry et al

Figure 1-4 An Oryza phylogenetic tree based on nine shared inversion events in the

Oryza species tree Nodes are labelled with blue letters and the branch lengths are indicated

beneath the branches while the number of scored inversion events is indicated above the

branches in black The estimated inversion rate is shown in red (Adapted from Stein et al

132 Australian wild species as a source of plant breeding

Although the Australian Oryza species are a potentially valuable source of genes for both biotic

and abiotic stress resistance (Brar et al 1997) and thereby enrich the rice genetic pool they

have so far seen very limited use Brar and Khush demonstrated the use of O australiensis

and O officinalis as a source of resistance for bacterial blight brown and white planthopper

(Brar et al 1997) Another study introgressed two brown planthopper resistance genes from

O australiensis (Rahman et al 2009) O rufipogon has been used as a source of biotic and

abiotic stress resistance genes in several studies (Brar el al 1997 Ram et al 2007 Wang et

al 2017) Recently an O australiensis heat-tolerance gene was overexpressed in O sativa

where it improved tolerance response to heat stress (Scafaro et al 2018) Atwell et al

described the limited genetic diversity of O sativa compared with its progenitors and indicated

the high vulnerability caused by the genetic bottleneck during the early stages of domestication

(Atwell et al 2014) In this study the authors showcased the use of wild rice relatives such as

O rufipogon in the context of introducing genes and traits via crossing with well-known

varieties

Zhu et al (2007) recognised low nucleotide diversity in O sativa compared with its wild

relatives which presented a sharp contrast to other important crops For example maize has

maintained approximately 80 of the genetic diversity found in its wild ancestor (Wright et al

2005) and the cultivated sunflower (Helianthus annuus) has retained around 50 of the

diversity present in its wild species (Liu et al 2006) The consequences of domestication (Fig

1-5) on the relevant genetic pool are likely to vary across taxa with several independent

studies of nucleotide diversity in crop plants and their wild ancestors providing only preliminary

information On the basis of data from the major cereal crops the genome-wide reductions in

diversity were evaluated to be of the order of 30ndash40 (Buckler et al 2001)

The wide genetic diversity within the Oryza species has been identified by a recent study which

showed that Australia may be the centre of origin and segregation of the AA genome of the

Oryza genus (Brozynska et al 2017) Additional levels of genetic diversity could be projected

in the species O australiensis the sole species with an EE genome (Huang et al 2012

Jacquemin et al 2013 Choi et al 2018 Stein et al 2018) The discovery of many

domesticated alleles within the wild species (Atwell et al 2014 Scafaro et al 2018)

strengthens the assumption that wild relatives are a key tool for crop improvement (Brozynska

et al 2016)

Despite the genetic blocks that may have been constructed over the years and the linkage

drag that might have resulted from these blocks rice breeders and researchers should focus

on finding innovative QTLs and genes stored in the endemic germplasm and introduce them

into cultivated varieties The use of the full sequences of the Oryza genus and its wild species

with saturated molecular markers will allow fine mapping of QTLs This will narrow the relevant

genetic segments into high-resolution regions to identify putative gene(s) within QTLs Even

though previous studies implied high abiotic stress tolerance in Australian endemic rice

ecotypes they are poorly characterized For my PhD research I focused on the Australian

endemic germplasm in terms of salt tolerance thereby allowing enrichment of the genetic

diversity of cultivated rice and to improve its production

during early domestication processes and modern plant-breeding practices Different

box colours represent the allelic variations of genes originally found in the wild (left hand side)

compared with the variation after a gradual loss through domestication and breeding The only

way to overcome the loss of allelic variation is to incorporate the wild species into breeding

programs and crossings Adapted from (Henry et al 2010)

14 Soil salinity impact and management

141 The scale of soil salinity worldwide and its impact

Soil salinity can indicate the presence of sulfates chlorides nitrates and bicarbonates of

sodium (Na) calcium (Ca) potassium (K) and magnesium (Mg) Although the tolerance of

saline conditions varies widely with species all crops have threshold salt concentrations

beyond which they cannot yield adequately Among cereals rice is the most salt-sensitive

species (Munns et al 2008) with an estimated 12 reduction in grain yield for every unit (dS

m-1) increase in salinity (Redfern et al 2012)

142 Management of saline soils

Soil amelioration is one methodology to combat salinisation Engineering soil hydraulics can

reduce excessive accumulation of salts at the rootndashrhizosphere interface However physical

practices to improve infiltration and permeability of the soil surface and in the root zone are

impracticably expensive Chemical practices such as application of calcium sulfate (gypsum)

are highly effective as a way to ameliorate physical properties but are not cost-effective for

low-technology agriculture Biological strategies to manage salinisation include applying an

organic material such as farm manure to improve the soil permeability and using salt-tolerant

varieties in place of current cultivars

Since most farmers do not have sufficient resources to implement engineering technologies

the most plausible approach for rice growers in developing countries to manage salinity is to

adopt cultivars that yield adequately under these conditions Consistent with this need this

thesis focusses on screening for and mechanisms of salt tolerance in wild germplasm to

discover new resources for rice breeders

15 Salt tolerance genetic variation and mechanisms

151 The genetic basis of salt tolerance

Of the cereals barley (Hordeum vulgare) is the most tolerant and rice is the most sensitive to

salt stress especially during the early seedling and reproductive stages (Moradi et al 2007)

while bread wheat (Triticum aestivum) has intermediate tolerance (Munns et al 2008)

The first attempt to evaluate the inheritance of a salt tolerance trait was made using an

interspecific cross between a wild and cultivated tomato from the Solanaceae (Lyon 1941)

The parents and the hybrid (F1) were grown in a nutrient solution with gradually increasing

concentrations of sodium sulfate F1 plants were more sensitive to the increased supply of salt

relative to the parents especially to the wild species parent Solanum pimpinellifolium Later

studies of salt tolerance in tomato revealed heterosis in an F1 hybrid between the wild species

S cheesmanii S peruvianum S pennellii and the cultivated S lycopersicum (Tal et al 1998

Saranga et al 1991) reinforcing earlier reports that heterosis interacts with abiotic stress

tolerance These discoveries validate the use of wild speciesrsquo genetics as a means of improving

cultivated varieties In cultivated sorghum (Sorghum bicolor) evidence from diallel population

analysis was found for a dominant mode of inheritance for salt tolerance related to root length

(Azhar et al 1988) Other examples of variations in salt tolerance have been found in maize

(Hoffman et al 1983) wheat (Munns et al 2006) and soybean (Flowers 1977)

152 The genetics of salt tolerance in rice

The small genome size of rice relative to wheat and barley together with its variable but

generally high salt sensitivity makes it an ideal candidate for mechanistic studies The first

report of salt tolerance inheritance was published in the early 1970s (Akbar et al 1972) The

authors demonstrated the mode of inheritance of delayed-type panicles using F2 and

backcross populations revealing that this trait is controlled by a limited number of genes with

a dominant pattern

A subsequent study using two crosses between tolerant and sensitive genotypes and two

generations of selfing implied that salt tolerance is polygenic (Mishra et al 1998) Gupta (1999)

evaluated heterosis in rice growing in saline soils as a screening treatment He found a

significant effect over the best parent in almost all studied characters Today there are several

novel approaches for rapid identification and mapping of QTLs using a mapping population

such as bi-parental recombinant inbred lines (RIL) (Gimhani et al 2016) This mapping

population can be used to conduct bulked segregate analysis (BSA) with the use of next-

generation sequencing (Tiwari et al 2016)

153 Salt tolerance mechanisms

Complementing evidence for genetic diversity in rice physiological information also supports

the fact that salt tolerance is the product of multiple responses that are difficult to elucidate

Generally plant responses to abiotic stresses involve multiple genes transcription factors and

post-translational biochemical mechanisms (Fig 1-6)

Figure 1-6 A schematic response of a plant to abiotic stress The initial phase of salt stress

causes functional and structural damage and secondary stresses Signals activate

transcriptional controls which trigger stress-responsive mechanisms to be activated and other

factors that protect and repair the damaged proteins and membranes The activation of stress-

response genes will determine the scale of tolerance or resistance of the plant Adapted from

(Wang et al 2003b)

The mechanisms that control salinity tolerance require a combination of molecular and

physiological processes first an increase in external osmotic pressure triggers an initial stress

response entailing synthesis of compatible solutes second the accumulation of ions for

osmotic adjustment in leaves third the restricted entry of salt ions into the transpiration stream

by exclusion mechanisms

154 Physiological responses to salinity

Osmotic effects of salinity

The osmotic phase caused by high ion loads is a rapid almost immediate response to the

increase of external osmotic pressure in the roots (Munns et al 2008) This phase starts as

soon as the salt concentration in the rhizosphere has passed a certain threshold causing an

immediate closure of the stomata and reduction of shoot growth The high concentration of

soluble salts in the soil results in a decrease in soil water potential (ie more negative) and as

a result limits water uptake across membranes reduces cell expansion and triggers hormonal

signalling that induces stomatal closure This in turn leads to a reduction in evapotranspiration

water transport and carbon sequestration These processes cause a significant decrease in

shoot growth (Fig 1-7) The reduction in external water potential often triggers lowering of the

cell osmotic potential typically through the production of solutes such as trehalose or proline

alternatively some plants accumulate ions to counteract low water potential Consequently

the osmotic potential of the cell is lowered which in turn draws water into the leaf cells and

restores turgor pressure This mechanism known as an osmotic adjustment is a major

component of drought tolerance (Babu et al 1999)

osmotic and ionic phases (a) A swift response to the increase in external osmotic pressure

(b) A slower response as a consequence to the accumulation of Na+ in leaves (c) Tolerance

to both phases The broken line shows a plant with a tolerance response to the salt stress The

change in the growth rate after the addition of NaCl represented by the green solid line (Munns

et al 2008)

Ionic effects of salinity

The stress caused by ion accumulation due to the uptake of salts occurs later than the osmotic

phase because it is a cumulative phenomenon The ion accumulation phase accelerates

senescence of mature leaves when salt reaches toxic levels and disturbs essential cellular

processes such as enzyme activity protein synthesis and photosynthesis (Horie et al 2012)

Ultimately a high concentration of NaCl in leaves causes cell death and leaf necrosis Once

the rate of death of the mature leaves is greater than the rate at which new leaves are

produced whole-plant photosynthesis will no longer be able to supply the carbohydrate

required for the young stems which further reduces the growth rate of the young leaves and

the entire plant (Munns et al 2008)

The ionic phase and the corresponding tolerance mechanisms within cereals have been well

characterised (Colmer et al 2005) and result from two independent phenomena tissue

tolerance and sodium exclusion (Flowers 2004) Tissue tolerance is the ability of a tissue to

accumulate Na+ (and in some cases Cl-) This tolerance describes the compartmentalisation

of the toxic ions at the cellular and intracellular level to avoid toxic levels within the cytoplasm

usually in mesophyll cells Sodium exclusion (and sometimes also Cl- exclusion) ensures that

within leaves Na+ does not accumulate to toxic levels Failure to exclude toxic ions (either Na+

or Cl-) results in a chain reaction response and causes premature death of older leaves

The osmotic stage has a greater effect on shoot growth rates compared with the ionic phase

especially at moderate salinity levels (Munns et al 2008) On the other hand for a sensitive

species such as rice in which transpiration rates are high the ionic phase soon dominates over

the initial period of osmotic stress

The three strategies (tolerance to osmotic stress tissue tolerance and Na+ exclusion) have

different impacts according to the species in question and its genetic propensity to respond to

salts in the root zone Importantly the engagement of each mechanism is also related to the

time of exposure to the salt stress a recent study on rice concluded that all three strategies

play a role in the range of salt tolerance that we observe in rice (Pires et al 2015)

155 Salinity tolerance in different plant species

Arabidopsis

In Arabidopsis several studies have revealed different mechanisms of salt tolerance For

example the salt overly sensitive (SOS1) gene which encodes a plasma membrane Na+H+

antiporter increased salt tolerance by transporting accumulated Na+ in the outer cell layers of

the roots back into the soil solution (Jiang et al 2013) Various other genes were found to

encode proteins that helped direct Na+ from the shoot back to the root and eventually back to

the soil (such as HKT11) while another gene was found to encode a protein that retrieved the

sodium before it reached the shoot (Moslashller et al 2009) Similar studies indicate that the ability

of plants to maintain tissue potassium concentrations correlates with plant salinity tolerance

This involves the depolarisation of membranes causing loss of K+ (Chen et al 2005 Munns

et al 2006) In addition salt stress can cause accumulation of reactive oxygen species (ROS)

which leads to oxidative stress Jiang et al (2012) found a gene that encodes an NADPH

oxidase that plays a critical role in salt tolerance Recently a new insight into a salt stress

signalling mechanism was made in which GIGANTEA (GI) a protein involved in sustaining the

plant circadian clock was shown to play a role in salt sensing as well as controlling the switch

to flowering (Park et al 2016)

Phytohormones also play a role in salt stress tolerance as they are critical factors in regulating

ionic homeostasis For instance salicylic acid can prevent potassium (K+) loss caused by

salinity thereby increasing plant tolerance to salt (Jayakannan et al 2013) Also the DELLA

proteins which are negative regulators of gibberellin (GA) signalling can improve plant

tolerance to salt stress by a general mechanism that inhibits plant growth during salt stress

(Harberd et al 2009 Tang et al 2017) Ethylene is reported to play a key role in several

pathways and mechanisms which enhance salt tolerance via the DELLAs a growth-inhibitory

protein family particularly related to gibberellin signalling (Jiang et al 2012) Recently several

studies highlighted the importance of the regulation of the expression of genes encoding key

membrane proteins such as Na+K+ transporters and water channels (Maurel et al 2008 Ward

et al 2009 Assaha et al 2017)

More recent studies which explored the mechanism of the Plant Growth Promoting

Rhizobacteria (PGPR) enhanced tolerance against abiotic stresses such as heat and salt

They suggested that in wheat Arthrobacter protophormiae (SA3) and Dietzia natronolimnaea

(STR1) strains can improve crop tolerance to salt stress while Bacillus subtilis (LDR2) provides

tolerance to drought stress by enhancing photosynthetic efficiency and regulation of several

other signalling pathways (Bharti et al 2013 Nadeem et al 2014 Barnawal et al 2017)

Cereals

In cereals other than rice a few osmotic-phase mechanisms have been found such as

adjustments of reduction in external water potential by lowering the cell water potential as well

as tissue tolerance through the ionic phase (Chandra Babu et al 1999 Tester et al 2003

Cramer 2006 Munns et al 2008) (Fig 1-8)

Figure 1-8 Published shoot and root plant major tolerance mechanisms found in

cereals Some mechanisms have been found in other cereals and have yet to be confirmed in

rice Ψ refers to water potential Adapted from (Campbell 2017)

Several studies have examined the genetic variation for osmotic adjustment during water

deficits in various rice varieties (Lilley et al 1996 Lilley et al 1996 Chandra Babu et al

1999) One study suggested that salt tolerance in rice can be achieved by enhanced

accumulation of proline and soluble sugars to tolerate the osmotic stress and maintain turgor

(Li et al 2017) The authors proposed that the compatible solutes can stabilise proteins and

cellular structures as well as counteract oxidative stress associated with abiotic stress (Li et

al 2017)

One of the studies in rice found a novel vacuolar antiporter increased salt tolerance by pumping

protons out of vacuoles and simultaneously pumping Na+ and K+ into these organelles (Fukuda

et al 2004) Other transporters regulate K+Na+ homeostasis under salt stress thereby

increasing salt tolerance (Ren et al 2005 Thomson et al 2010) for example through Na+

direct exclusion by HKT transporters (Suzuki et al 2016 Kobayashi et al 2017 Oda et al

2018) The OsHAK21 potassium transporter has been found to maintain ion homeostasis and

as a result improve the salt tolerance of rice (Shen et al 2015 He et al 2018) A recent study

showed that the salt-tolerant rice PL177 maintains a low Na+K+ ratio in shoots and Na+

translocation attributed largely to better ion exclusion from the roots and salt

compartmentation in the shoots (Wang et al 2016)

A recent study explored miRNA-target networks that were induced by salinity stress in the

African rice O glaberrima demonstrating the potential use of wild species as a natural source

of salinity tolerance (Mondal et al 2018a) In addition a few other studies found that the

regulation of proteases (Mishra et al 2017) as well as calcium-dependent protein kinases

(Chen et al 2017) were linked to salinity tolerance in rice by modulating ABA and signalling

the expression of several downstream stress-response genes (Asano et al 2011)

Despite all the research described above on mechanisms of salt tolerance in rice the

mechanisms in wild relatives of rice are still largely unknown

156 Genetic variation as a tool of plant breeding

As the human population reaches critical levels that cannot be sustained by current arable

land and deterioration of cultivated land continues effective solutions for feeding the planet

must be found (Ludewig et al 2016) To this end genetic improvement of crop plants and the

use of wild relatives are essential to boost agricultural output Quantitative trait loci (QTL)

derived from mapping populations including those that use landraces can lead us to gene

targets required to improve important agronomic traits

In the recent years despite some genetic barriers between species there have been notable

cases where wild natural species variation significantly improved crop field performance For

example resistance genes to Tomato Yellow Leaf Virus (TYLCV) were introduced from S

chilense to the cultivated tomato S lycopersicum (Michelson et al 1994 Anbinder et al

2009) sugar content was increased by using the Brix9-2-5 QTL from the introgression line (IL)

population derived from S pennellii (Fridman et al 2000) resistance to various stresses

(Fernie et al 2006) and to Phytophthora infestans (originated from S pimpinellifolium) (Zhang

et al 2014) have been introduced to tomato These examples support the argument that

exotic species variation can be used to improve the performance of cultivated crop varieties

157 Wild rice species as a source for improving abiotic stress tolerance

Salinity

The identification and characterization of the novel QTL named saltol on chromosome 1 of rice

was made within a mapping population derived from 140 IR29Pokkali recombinant inbred

lines (RIL) (Thomson et al 2010) (Fig 1-9) This QTL which explained most of the variation

in salt uptake has had a tremendous effect in dealing with the salinity problem (Thi et al

2013) A recent study identified fourteen additional QTLs in the landrace Pokkali using SSR

and SNP markers (De Leon et al 2017) Surprisingly even though this work has had

prodigious success other similar studies related to salt-tolerance genes within the rice species

are limited A recent study tested a wide range of wild rice species under several salt

treatments and found that some of these species employ tissue tolerance mechanisms to

manage salt stress (Prusty et al 2018) These newly isolated wild rice accessions were found

to have higher or similar level of tolerance compared with the tolerant controls (Pokkali and

Nora Bokra) They will therefore be important materials for not only rice improvement to salinity

stress but also the study of salt tolerance responses and mechanism in other plants The study

evaluated only one accession for each of the 27 wild species (Fig 1-7) and classified both the

O meridionalis and O australiensis accessions as sensitive to salt stress

Submergence

One of the ongoing problems in rice fields is the submergence of plants in water which causes

annual losses of more than USD 1 billion which is particularly damaging to the poorest rice

farmers in India Bangladesh Myanmar Vietnam China and other countries (Evenson 1996)

One of the most successful examples of the introduction of a gene to farmersrsquo cultivated rice

was made by the mapping of QTL for submergence tolerance named sub1 (Xu et al 1996

Xu et al 2000) The gene involved in the regulation of the submergence response and can be

introduced efficiently to target modern cultivars without linkage drag using genetic markers

This example is a case where a single gene derived from QTL analysis controls yield stability

in rice fields Similar genes are still be sought for salt tolerance

Drought

In addition to submergence drought is another damaging environmental stress causing grain

losses of 20ndash25 million tonnes in China alone affecting 200ndash300 million people and economic

losses of CNY 15ndash20 billion each year (Zhang et al 2015) Through the use of wild relatives

in a doubled-haploid population derived from a cross between two rice cultivars researchers

in Thailand were able to map QTLs for grain yield which has had a tremendous effect on

drought tolerance (Lanceras et al 2004)

Chilling

Chilling (low temperatures above freezing) occurring in different growth stages can also cause

significant yield losses and are a major problem in high-altitude areas (Xu et al 2008) In 1980

Korea lost an average yield of 39 tonnes of rice per hectare as a result of cold stress

(wwwirriorg) Cold tolerance is a complex trait that is controlled by various genes and factors

Several years ago researchers managed to identify three main effect QTLs for cold tolerance

on chromosomes 3 7 and 9 respectively by using recombinant inbred lines (RILs) and QTL

analysis (Suh et al 2010) These QTLs are facilitating selection for improved cold-tolerant

genotypes Additionally cold-regulated genes were identified in rice (O sativa) germinating

seeds by RNAseq analysis of two indica rice genotypes with contrasting levels cold tolerance

(Dametto et al 2015) A recent study has identified that a variant of a particular bZIP gene

induces japonica adaptation to cold climates (Liu et al 2018)

Another major concern threatening rice production is global warming Temperatures of more

than 35degC especially in the reproductive stages cause low seed set resulting in yield loss in

rice With F2 and BC1F1 progenies researchers discovered several main-effect QTLs

associated with heat tolerance (Ye et al 2012) Another approach to mitigate heat stress was

made by the detection of novel QTLs for early morning flowering (EMF) which escapes heat

stress of the day for this critical event (Hirabayashi et al 2014) This QTL was found in a

population of near-isogenic lines (NILs) derived from the indica genetic background and the

wild rice accession (O officinalis) Under heat stress (up to 45degC) throughout the vegetative

phase a recent study managed to improve the yield of O sativa after overexpressing a

Rubisco activase gene from O australiensis (Scafaro et al 2018)

Figure 1-9 Effects of salt stress on sensitive and tolerant rice Salt-tolerant IR65192 and

salt-susceptible IR29 seedlings were exposed to highly saline conditions for two weeks

(wwwirriorg)

16 Conclusion

Salinity causes major yield losses all over the world in both irrigated and rainfed fields The

added effect of climate change over recent decades and the associated uncertainties around

rainfall and temperature place rice production at a substantial risk The fact that rice is a highly

salt-sensitive crop together with the vast consumption of rice globally poses a major challenge

for basic and applied research

There are three options to increase rice production (1) expand irrigation areas (2) use

currently unfavourable fields and (3) increase rice productivity The first option is unlikely since

the shortage of available fresh water in many parts of the world and the competition for water

by industrial and urban usage Both other options demand the generation of high-yield and

abiotic stress-tolerant crop varieties Hence future studies should focus on soil and water

management combined with generating salt tolerance varieties which can considerably

enhance and sustain yield quality and productivity for relatively infertile fields as shown in other

important crops

The first step in fine mapping of QTLs and genes is to identify the donor parent and to

understand the mechanism that controls the tolerance Revealing salt-tolerance mechanisms

and the development of salt-tolerant varieties will have direct impacts such as improving

farmersrsquo rice production on salt-affected lands and yield thereby improving the economies of

the poorest countries of the world

17 Aims of the project

The overall objective of this PhD project was to identify and study the mechanisms of salinity

tolerance within Australian wild rice species The use of these wild relatives in future research

is expected to contribute to the study of plant responses to salinity stress and to provide novel

germplasm for breeding programs The information gained will further our understanding of

rice salt tolerance which will potentially lead to improved rice varieties

Specifically the aims of the project were to

i) screen and evaluate the variation in salinity tolerance within an Australian rice wild relatives

collection (Chapter 2)

ii) deepen our understanding of salt stress responses and mechanisms through time-series

phenotyping (Chapter 3)

iii) identify quantify and evaluate proteins underlying the salinity tolerance trait in the most

tolerant and sensitive accessions (Chapter 4)

iv) validate the candidate salt-responsive genes using RT-qPCR and a yeast gene deletion

library (Chapter 5)

vi) associate a genomic region that spans the salt tolerance trait using a mapping population

(Chapter 6)

Chapter 2 Preliminary salt screening

Preliminary screening of Australian wild rice accessions for seedling-stage salt

tolerance

The second part for this chapter is reported in Yichie et al (2018) Salinity tolerance in

Australian wild Oryza species varies widely and matches that observed in O sativa Rice

1166 which is included as an appendix in this thesis The journal article can also be viewed

online at httpsdoiorg101186s12284-018-0257-7 Additional material included in this

chapter represents supporting information for a more detailed understanding of the research

reported in the journal article

Author contributions YY designed and executed the first experiment YY also phenotyped

the plants (for both experiments) performed the data analyses for the first experiment and

wrote the manuscript CB designed the second experiment performed the spatial correction

and conceived of and developed the statistical analyses for the phenotypic data of the second

experiment BB assisted with the phenotypic analyses and revised the manuscript THR and

BJA contributed to the original concept of the project and supervised the study BJA conceived

the project and its components and provided the genetic material

21 Introduction

Soil salinity is a major constraint across many cropping systems globally It is manifested

through the interaction of salt concentrations in the soil and salt sensitivity of the genotype

under investigation (Munns et al 2008) According to the FAO (2008) more than 12 billion

hectares globally have been affected by soil salinity either as a result of improper irrigation

practices or by natural causes such as rising sea levels leading to salt intrusion into coastal

zones and increasing impact of storms as well as dryland salinity in low-rainfall zones (Smajgl

et al 2015) Two or more factors acting together such as intensive irrigation on poorly drained

soils coupled with erratic heavy rainfall events and clearing of deep-rooted perennial species

often induce soil salinity As a result of salt stress on crops significant yield losses have been

recorded with an annual income penalty of more than USD 27 billion globally (Qadir et al

The primary impact of salt on plant tissues occurs by two distinctive mechanisms firstly by

making it more difficult for roots to absorb water and secondly by the eventual accumulation

of salts to toxic concentrations in aerial tissues (Flowers 2004) Inevitably high salt

concentrations during vegetative plant development negatively influence growth and

reproductive performance Specifically accumulation of sodium is toxic for basic metabolic

function by disrupting protein conformation and displacement of potassium which initially

causes the death of specific tissues such as older leaves (Munns et al 1986) and eventually

the entire plant (Jiang et al 2013)

Rice (Oryza sativa) is a globally important cereal grain providing a primary source of nutrition

for more than one-third of the worldrsquos population More than 190 million hectares of rice fields

were grown worldwide in 2014 (USDA 2014) Salt stress in rice plants caused by both osmotic

imbalance and accumulation of toxic ions affects rice productivity over vast areas largely

because the species as a whole lacks effective defence mechanisms Due to a declining

proportion of healthy photosynthetic tissue over time when grown in saline soils rice is

considered to be one of the most salt-sensitive major annual crops (Munns et al 2008) It is

especially sensitive to salinity during early seedling and reproductive stages (Zeng et al

2001) where it is mainly associated with a decline in cell expansion and related metabolic

processes A significant deceleration in plant growth does not only occur through lower rates

of photosynthesis but also because of an increase in reactive oxygen species that damage

primary metabolic functions

Millions of hectares in the humid regions of South and Southeast Asia are suitable for rice

production but are left uncultivated due to the salt sensitivity of rice (wwwirriorg) Shereen et

al (2005) observed a reduction of 77 in rice grain yield at 50 mM sodium chloride after 14 d

of salt exposure at the reproductive growth stage At higher salt concentrations (75 mM NaCl)

some of the tested lines yielded no grain and significantly fewer panicles compared with the

control plants (Shereen et al 2005) Another study reported grain yields were reduced by 26ndash

67 under an EC of 8 dS m-1 depending on the cultivar and the pH in addition to a significant

reduction in the 1000-grain weight Thus it is now a priority to develop rice genotypes which

are salt-tolerant specifically at the seedling and reproductive stages to enable crop production

on salinity-affected land and to meet increasing global food demand which has been forcing

expansion of cropping systems into marginal areas

The use of exotic genetic resources including wild species to improve plant performance has

proven to be a key solution in various crops (Rick 1974 Zamir 2001 Koornneef and Stam

2001 Huang et al 2003 Wuumlrschum 2012) For rice less than 20 of the genetic diversity in

the Oryza genus can be found in O sativa (Zhu et al 2006) The necessity of using germplasm

representing 27 Oryza species in particular the many wild relatives in order to improve

domesticated rice has been recognised (Henry et al 2010 Atwell et al 2014) For this

approach breeding for abiotic stress-tolerant rice varieties will rely heavily on the identification

of QTLs (and thereby novel genes) in wild germplasm and their introduction to elite cultivars

Attempts to improve salinity tolerance of rice and other crops through conventional breeding

programs have met with limited success due to the complexity of the genetic and physiological

networks underpinning tolerance (Flowers 2004) The discovery of genes encoding novel ion

transporters or other proteins conferring salt tolerance will provide a new impetus for gene-

targeted molecular breeding particularly when pyramided in elite cultivars To this extent the

naturally occurring variation among wild relatives of rice is still an under-exploited resource in

plant breeding

The mechanical and physiological bases of rice seedling-stage salt tolerance are fairly well

established key traits include compartmentation of ions in older tissues ion exclusion and

tissue tolerance (Yeo et al 1987 1990 Fukuda et al 2004) However limited information is

available on salt tolerance regarding the potential novel sources and mechanisms of the

Australian endemic germplasm To better understand the potential and mechanisms of salinity

tolerance among the Australian wild germplasm it is essential to study the growth responses

ion accumulation and plant performance under saline conditions These experiments aimed

to (1) establish a core collection of salt-tolerant accessions for future studies and (2) study the

growth parameters and response for salt stress in a wide range of accessions within the

Australian wild rice germplasm

Screening for plant traits under controlled conditions has the benefit of controlling for other

stresses that might normally co-occur in the field (eg drought and heat) thereby improving

the chance of identifying genotypically meaningful contrasts Selection for salinity-tolerant

genotypes of rice based on phenotypic performance can be used as a pre-breeding step prior

to a Marker-Assisted Selection (MAS) breeding strategy (Collard et al 2008) In a survey prior

to this PhD study 30 genotypes were broadly screened in a pot-based experiment to examine

growth response and survival in a range of treatments from 25ndash100thinspmM NaCl over a four-week

treatment

22 Materials and methods

221 Experimental setup

This chapter presents the results of two consecutive salt-screening experiments conducted at

Macquarie University Sydney Australia (lat 337deg S long 1511deg E) in winter and spring 2016

respectively The first experiment was performed in order to evaluate a wide range of

accessions under saline conditions and to narrow down the selection of genotypes for in-depth

screenings and future molecular investigations The first screening included the indica variety

Pokkali which has been widely used as salt-tolerant reference (Demiral et al 2005) and as a

donor in breeding programs as well as the inbred rices IR29 (indica) and Nipponbare

(japonica) as sensitive controls with salt treatments up to 120 mM NaCl The second screening

experiment involved a less stringent salt treatment (up to 80 mM NaCl) to validate the results

of the first screening and to test more aspects of the response to salt in fewer accessions All

procedures described below were performed for both first and second screenings unless

otherwise mentioned

To avoid delayed or poor seedling emergence and establishment seeds of the wild accessions

were dehulled and kept at 45degC dry heat for 7 d to break seed dormancy Seeds were then

washed for 30 min followed by soaking for 30 min in 4 sodium hypochlorite and rinsed

thoroughly with distilled water Seedlings were then grown for 7 d in Petri dishes under a dark

controlled condition of 29ndash36degC

At day 8 two to four seedlings per accession were sown in a 15-L polyvinyl chloride (PVC)

pots with drainage holes containing 13 L of a clay-loam krasnozem (lsquoRobertson soilrsquo)

supplemented with slow-release fertiliser (Nutricote Standard Blue Yates 004) After 8 d

pots were placed into the greenhouse At 15 d after transplanting (DAT) plants were thinned

leaving one healthy and uniformly sized seedling in each pot In the field rice plants are likely

to be exposed to gradually increasing salinity levels as the dry season progresses therefore

salt treatments were applied in four incremental steps from 25 DAT to the top of the pots (25

up to 50 up to 75 and up to 120 mM in daily increments) Sudden exposure to high

concentrations of salt may not only be artificial but also adversely affect or mask adaptive

responses The final treatments for the first screening were a no salt lsquocontrolrsquo 25 50 75 and

120 mM NaCl with the total electrolyte concentration resulting in an electrical conductivity of

05 25 57 73 and 131 dS m-1 respectively Plants were watered once a day with about 50

mL of solution (including 04 gL of Aquasol Soluble Fertiliser Yates) per pot Each group of

pots belonging to the same salt treatment were placed in a 3 times 3 m drip tray and the drainage

was removed every 3 d to prevent algal growth

Salt treatments were applied for 30 d in a controlled environment greenhouse with 3022degC

daynight and relative humidity of 62 (plusmn 6 SD) during the day and 80 (plusmn 3 SD) at night

Supplementary lighting (LEDs with an intensity of about 600 micromol m-2 s-1) was used for 12 h a

day to amplify the light intensity and daylight A completely randomised experimental design

was utilised with five replicates (pots) or more for each genotype x treatment combination

The locations of each pot (within trays) and the trays were randomly changed every 3 d to

subject each plant to the same conditions and to prevent neighbour effects Growth-related

traits were recorded throughout the experiment while post-harvest parameters were evaluated

at time of harvest 30 d after salting (30 DAS)

222 Tiller number and seedling height

Number of tillers and seedling height values were recorded for each plant at 1 and 30 DAS

For each plant the addition of new tillersincreased height were recorded over time

223 Salinity tolerance (ST) leaf rolling (LR) and standard evaluation system (SES)

Each rice plant was evaluated for seedling-stage salinity tolerance at 1 and 30 DAS based on

visual symptoms using the International Rice Research Institute (IRRI) standard evaluation

system (SES) scores (IRRI 2013) as described in Table 2-1 The SES scale was designed

for the general purpose of recording various responses to stressors in rice It is a uniform

descriptive scale for measuring plant lsquoinjuriesrsquo some of which can be very complex to measure

quantitatively Traditionally SES and LR observations are recorded as a proxy for relative

stress response between plants in the same experiment Salinity tolerance (ST) was

determined by the percentage ratio of mean shoot dry weight (SDW) (80thinspmM NaCl) divided by

mean shoot dry weight (no salt) as per the following formula

119878119878119878119878119878119878 (119904119904119904119904119904119904119904119904 119904119904119905119905119905119905119904119904119904119904119905119905119905119905119905119905119904119904)119878119878119878119878119878119878 (119888119888119888119888119905119905119904119904119905119905119888119888119904119904)

119909119909 100

224 Gas exchange parameters

For the first and second screening respectively plants were tagged at 4 and 2930 DAS for

gas exchange measurements between 1000thinspam to 1230 pm (Australian Eastern Standard

Time) The youngest two fully expanded leaves (YFL) of each plant were chosen and gas

exchange parameters such as net photosynthesis rate (Pn) stomatal conductance (gs)

intercellular CO2 concentrations (Ci) and transpiration rate (E) were measured and collected

with an infrared open gas exchange system (LI-6400 LICOR Inc Lincoln NE USA) A pulse

amplitude modulated (PAM) leaf chamber fluorometer sensor head was utilised in these

experiments Prior to usage sensor variables were adjusted to ambient external conditions to

provide an effective comparison between samples with minimum false-readings The reference

CO2 concentration was set at 400 micromol CO2 mol-1 using a CO2 external mixer Relative

humidity followed ambient conditions The optimal day temperature was set to 28degC according

to a previous study (Wise et al 2004) To maintain a vapour pressure deficit between 15 and

25 kPa the system flow rate was adjusted accordingly before use Light intensity of the Licor-

6400 leaf chamber was fixed at 1600 micromol m-2 s-1 for all experiments The average value for

two leaves per plant was calculated and used for the statistical tests

225 Biomass harvest parameters

Plants were harvested and weighed immediately at 30 DAS to record the SFW values DFW

was recorded after plant material was oven-dried for 4 d in 70degC Main-tiller leaf blades were

separated into green and dead leaf portions with leaves considered dead if more than 50 of

the leaf was dry Dead leaf percentage was calculated as the weight of dead leaf as a

percentage of total leaf weight

119878119878119905119905119904119904119863119863 119871119871119905119905119904119904119871119871 119878119878119905119905119882119882119882119882ℎ119904119904119879119879119888119888119904119904119904119904119904119904 119871119871119905119905119904119904119871119871 119878119878119905119905119882119882119882119882ℎ119904119904

119909119909 100

The following methods were used only in the second screening experiment

226 Analysis of inorganic ions

For Na+ and K+ analysis samples of YFL from each plant were harvested at 30 DAS rinsed

thoroughly with deionised water and oven-dried at 70degC for 4 d Dry samples were weighed

and extracted with 10 mL 01 N acetic acid for every 10 mg of dried tissue leaves in 50-mL

falcon tubes Samples were placed in a water bath at 90degC for 3 h to digest and then diluted

10-fold after the extracted tissues were cooled to room temperature Sodium and potassium

concentrations were measured by an Agilent 4200 Microwave Plasma Atomic Emission

Spectrometer (Agilent Technologies Melbourne Australia) Element calibration standards of

potassium and sodium were prepared and diluted between the concentration range on 0 to 10

ppm with 1 ppm increments (11 standards altogether for each element) and were diluted with

the extraction matrix containing 001 N acetic acid Two wavelengths were tested for each

element 776491 and 589592 nm for K+ and 558995 and 769897 nm for Na+ After testing

the reads of all wavelengths 766491 and 588995 nm were chosen for K+ and Na+

determination respectively All calibration curves were obtained using a linear calibration fit

All operating parameters were used as recommended by the application note for macro and

microelement detection using the Agilent 4200 MP AES (Liberato et al 2017) and are

summarised (Appendix Table 2-1) The following equation was used to obtain the final ion

concentration in each leaf sample

119864119864119904119904119905119905119905119905119905119905119905119905119904119904 119905119905119905119905119888119888119904119904119882119882 =

119905119905119904119904119905119905119905119905119905119905119905119905119904119904 119905119905119905119905119904119904119863119863 [119901119901119901119901119905119905] lowast 001119871119871 lowast 10

119905119905119888119888119904119904119905119905119888119888119898119898119904119904119904119904119905119905 119905119905119904119904119904119904119904119904 119905119905119882119882119905119905119905119905119888119888119904119904 lowast 119904119904119904119904119905119905119901119901119904119904119905119905 119908119908119905119905119882119882119882119882ℎ119904119904 [119882119882]

where 001 L represents the extraction volume and 10 represents the dilution factor

227 Chlorophyll content

Leaf samples were collected at 30 DAS and immediately frozen in liquid nitrogen freeze dried

and ground to a fine powder using a mortar and pestle Thirty millilitres of 95 ethanol was

added for each ground sample before total chlorophyll determination was measured by reading

the absorbance at wavelengths of 470 649 664 nm (Synergy H1 Hybrid Multi-Mode

microplate reader BioTek VT USA) as described (Mackinney 1941)

228 Data analysis

An average value was calculated for each linesalt treatment combination in both experiments

for each tested trait One-way Analysis of Variance (ANOVA) was performed to identify the

significant changes in growth and yield components between treatments and lines using the

statistics program SAS JMP v13 (SAS Institute Cary NC USA) Respective means were

compared using Studentlsquos t and Tukeyrsquos HSD tests

Table 2-1 Modified scoring scheme for seedling-stage salinity tolerance based on visual

system (SES) scores (IRRI 2013) Adapted from (Gregorio et al 1997)

23 Results and discussion

231 First salt screening to establish a core collection of salt-tolerant accessions Results of the first salt screening

The first screening experiment (conducted in winter 2016) was performed to examine a wide

range of potential accessions from the Australian wild species panel assembled over many

years at Macquarie University These accessions were collected from savannah in the north

and northwest of the Australian continent including transiently saline waterways and were

obtained from the Australian Grains Genebank in Victoria The panel was screened for

symptoms and survival for several abiotic stresses in preliminary experiments (unpublished

data) displaying a broad range of responses to various abiotic stresses such as drought heat

and seedling-stage salinity (unpublished data) As a result nine accessions were chosen

(Table 2-2) to be evaluated for salinity tolerance characteristics Due to low germination rates

one of the accessions (Om-T) was not tested in the first screening Thus eight accessions

along with three O sativa controls were evaluated under the five treatments of 0 25 50 75

and 120 mM NaCl for 30 d (first screening)

Seedlings were germinated and grown without salt application for the first 25 d (DAT 25) all

plants were a healthy green and no growth penalties were observed In the control treatment

plants grew robustly without any visible affects throughout the experiment In all salt treatments

(25 to 120 mM NaCl) wide phenotypic variation was demonstrated in response to salt stress

amongst the tested accessions and genotypes (Fig 2-1) Seedlings were evaluated for

seedling-stage salinity tolerance based on visual symptoms using IRRIrsquos SES scheme (IRRI

2013) ranging from score 1 (highly tolerant) to score 9 (highly susceptible) as described in

section 228 and in Table 2-1

Oryza sativa controls (relatively salt-susceptible cultivars IR29 and Nipponbare) exhibited the

highest SES scores in both 75 and 120 mM NaCl (Fig 2-2a) In addition to SES an LR score

was recorded for each plant based on the same visual symptoms scheme (IRRI 2013)

spanning from score 1 (healthy leaves) to 9 (tightly rolled leaves) (Fig 2-2b) Moderate visual

scores of leaf symptoms (both SES and LR) were presented in all lines at the lower salt

treatments 25 and 50 mM NaCl (unpublished data) while more severe effects were observed

at the high salt concentrations 75 and 120 mM NaCl (Fig 2-2)

Oa-VR Oa-KR and Oa-T3 accessions gave significantly lower SES values (less injury)

compared with Pokkali at 75 mM NaCl the lowest recorded average value for Oa-VR was 24

compared with 43 for Pokkali None of the accessions showed a distinctively better

performance in terms of SES under 120 mM NaCl compared with the salt-tolerant control

Pokkali possibly because of more extreme salt stress masked genotypic differences Both

salt-sensitive controls exhibited severe leaf symptoms resulting in high and significant values

of SES and LR in both 75 and 120 mM NaCl salt treatments

For LR Oa-KR and Oa-VR again displayed the best performance with the lowest scores (15

and 22 respectively) both significantly lower (p lt 001) than the salt-tolerant Pokkali (53)

under 75 mM NaCl In addition Oa-VR presented a significantly lower average value also

under 120 mM NaCl (compared to Pokkali) along with Oa-CH and Oa-D (Fig 2-2)

In addition to leaf symptoms Oa-VR was the only line without significant biomass reductions

(FSW and DSW) in both 25 and 50 mM NaCl treatments compared with the control condition

(Fig 2-3) A wide range of responses to salt applications was observed including a gradual

reduction in biomass (Oa-CH) a rapid reduction in biomass at moderate salt stress of 50 mM

NaCl (Oa-GR) and plants that maintained biomass under a moderate salt level of 50 mM NaCl

(Oa-VR and Pokkali) (Fig 2-3)

Number of tillers net photosynthetic rate and plant height were reduced by salinity (Table 2-3)

for all tested lines The smallest salt-induced reduction in tiller number was found in Oa-CH

and Oa-GR (40 and 50 respectively) both significantly (p lt 005) lower than the reduction

seen in Pokkali (64) Oa-VR Oa-D and Om-CY had the same degree of reduction (67 not

significant from Pokkali) In both photosynthetic rate and plant height Oa-VR had the lowest

average reduction (48 and 62 respectively) while photosynthesis was most affected by salt

in the IR29 landrace (79 reduction) For plant height the greatest inhibitory effect of salt was

recorded for Nipponbare (93 reduction) (Table 2-3)

Main tiller leaves were collected at harvest and visually assessed for leaf injury and

senescence as described in section 225 to identify accessions with the least leaf injury and

to associate this trait with other salt-tolerance characteristics Significant variation in average

proportion of dead leaves was found between the tested genotypes ranging from 17 (Oa-VR

75 mM NaCl) to 100 (IR29 and Om-CY under 120 mM NaCl) (Appendix Table 2-2) Oa-VR

also exhibited the lowest proportion of dead leaves under 120 mM (46 dead leaves)

compared with two-fold higher proportion of dead leaves (92) for Pokkali under the same salt

treatment Under salinity the relationship between photosynthetic rates and percent dead

leaves was examined using regressions between these traits for all plants This correlation (R2

= 061 for all plants or 04 for only salinised plants) may provide a convenient proxy for

photosynthetic rates by counting the number of dead leaves (Appendix Figure 2-1)

Table 2-2 List of accessions selected for the first screening The species classification collection date and location are given for each

accession tested in this chapter All lines in the above were tested in the first screening except Om-T due to poor germination

Accession Taxon Collection date Collection directions lat long Origin stateOa -VR O australiensis 23041996 100 km W of Victoria Riv Wayside Inn on Victoria Hwy -166245 1304497 Northern TerritoryOa -CH O australiensis 24041996 185 km N of Carlton Hill Rd on Weaber Plain Rd

Kununurra 100 m into depression from Rd-155047 1288428 Northern Territory

Oa -D O australiensis 30041996 84 km NW of Derby on Gibb River Rd -174462 124423 Western AustraliaOa -KR O australiensis 1041978 SE Kimberley Research Station -144 1288 Western AustraliaOm -T O meridionalis NA Townsville NA NA Queensland

Om -HS O meridionalis NA Howard Springs NA NA Northern TerritoryOm -CY O meridionalis NA Cape York Peninsula 25 km W of Cooktown -1542 14503 Northern TerritoryOa -T3 O australiensis NA Townsville NA NA QueenslandOa -GR O australiensis 1051996

120 km E of Derby -17398 1247437 Western Australia

sensitive (IR29) Om-HS and Oa-VR accessions and salt-tolerant O sativa cv Pokkali All

photographs are shown to the same scale (pot diameter = 15 cm)

Figure 2-2 Comparison of (a) SES scores and (b) leaf rolling of the tested wild rice accessions and domesticated rice controls at 75

and 120 mM NaCl (EC = 73 and 131 dS m-1 respectively) Trait means (plusmn standard errors) are shown for each genotype along with the salt-

sensitive controls (IR29 and Nipponbare) and the salt-tolerant (Pokkali) at the seedling stage Asterisks indicate a significant difference from the

mean for the salt-tolerant variety Pokkali at the same salt level based on Studentlsquos t test (p lt 005 p lt 001)

Figure 2-3 Comparison of shoot fresh weight (SFW) and dry shoot weight (DSW) yields (in

grams) for all salt treatments Trait means (plusmn standard errors) are shown for each genotype at

the seedling-stage Asterisks indicate significant different mean values from the non-salinised

treatment (0 mM NaCl) per genotype based on Studentlsquos t test (p lt 005 p lt 001)

accessions and three O sativa controls All three traits were evaluated on 30 DAS in the non-

salinised (0 mM NaCl) and salinised condition (75 and 120 mM NaCl) Values for the salt-treated

plants were calculated as the mean of both 75 and 120 mM NaCl for each trait Reduction values

were rounded to the nearest integer All pairs comparisons had p value lt 001 based on Studentlsquos

t test

First screening discussion

Due to the severe rice yield losses caused by salinity as discussed previously it is vital to find

new genetic sources for salt tolerance to increase the resilience of commercial cultivars through

breeding Plant breeding produces new varieties that have increased productivity and quality The

first (and maybe the most important) step in every breeding program is the creation of genetic

variation This can be achieved by several approaches such as inducing mutation polyploidy

genetic engineering and introgression of wild germplasm (Jackson 1997) The potential of wild

species as a source of genetic variation to improve crop performance was recognised early in the

twentieth century (Bessey 1906) Despite linkage drag and a complex timing procedure

numerous studies have demonstrated the effectiveness of wild species for crop improvement

(Saranga et al 1992 Tanksley 1997 Mauricio 2001 Zamir 2001) By this approach individual

plants containing desirable traits are chosen from an available pool of genetic variation and

crossed to generate novel phenotypes Therefore fundamental research is required to assess

LineTraitNon-salinised Salinised Reduction () Non-salinised Salinised Reduction () Non-salinised Salinised Reduction ()

IR29 8 2 75 32 7 79 20 5 75Nipponbare 11 2 82 32 7 78 75 5 93

Oa -VR 9 3 67 31 16 48 66 25 62Oa -CH 5 3 40 37 9 76 60 14 77Oa -D 6 2 67 30 9 70 106 38 64

Oa -KR 9 2 78 30 9 70 67 16 76Om -HS 12 3 75 29 14 52 33 4 88Om -CY 6 2 67 32 11 66 55 4 93Oa -T3 4 1 75 28 7 75 51 3 94Oa-GR 6 3 50 28 12 57 39 6 85Pokkali 11 4 64 29 13 55 113 22 81

Plant Height [cm]Number of tillers Net photosynthetic rate [μmol (CO2) m-2 s-1]

and exploit the given genetic diversity and find novel germplasm to serve as donors to enrich the

genetic variation of a desired trait

The 27 Oryza species span ~15 million years of evolution with eleven genome types six of which

are diploid and five polyploid (Stein et al 2018) Considering the wide range of habitats in which

these species have evolved (Wing et al 2005 Atwell et al 2014) it is likely that variation in

responses to salt would be observed In this study the wild species represent two genomes and

multiple accessions from contrasting environments

Seedling-stage salinity tolerance is an essential element to understand salt tolerance in rice This

screening confirmed the hypothesis that prodigious phenotypic variation in response to salt stress

can be found within a wild rice species selection An improved performance of several accessions

exposed to saline conditions was found in terms of yield biomass parameters gas exchange rates

and visual symptoms compared with the known salt-tolerant cultivar Pokkali

Sodium chloride was chosen as the dominant salt because it prevails in the root zone throughout

Australian cropping areas (Niknam et al 2000) and in coastal regions worldwide Biomass

reductions were clear after exposure to relatively low salt levels (50 and 75 mM) for 30 d Salt

stress also inhibited tillering and plant height to varying degrees in all tested lines resulting in

lower mass accumulation as previously reported in various crops (Flowers 2004 Maggio et al

2007 Munns et al 2008 Jiang et al 2013 Roy et al 2014) These salt regimes were found to

discriminate the salt sensitivity of the rice accessions most effectively In contrast the highest salt

treatment of 120 mM NaCl (EC 131 dS m-1) discriminated between genotypes less sensitively

with a severe response in all tested parameters from all accessions and limited differences

regardless of tolerance characteristics Previous rice salt screenings used an EC of 12 dS m-1

however plants were exposed to salt for only seven days (Moradi et al 2007 Sabouri et al

2008) compared to 30 d in this experiment The longer acclimation time was deemed to reflect the

field situation more realistically

At the lower salt treatments Oa-VR was the only wild relative that did not show a significant

reduction of SFW and SDW in 25 and 50 mM NaCl salt compared with the no-salt control Om-

HS Oa-T3 Oa-GR Nipponbare and even Pokkali displayed a significant reduction under 50 mM

but not under 25 mM NaCl IR29 was salt-sensitive but had a distinctive developmental phenotype

compared with the other O sativa cultivars Pokkali and Nipponbare IR29 is an inbred indica

variety developed at IRRI (Los Batildenos Philippines) used as a salt-sensitive standard (Senadheera

et al 2009) This dwarf cultivar has vigorous tiller growth even without saline conditions but grew

only 30 cm tall while Pokkali and Nipponbare grows up to 150 cm in standard conditions Despite

these development differences growth of IR29 can be used to understand mechanisms of salinity

tolerance

The visual SES scores in this experiment showed a continuous distribution highlighting the

potential polygenic nature of salinity tolerance as described in a previous ricendashsalt study (Platten

et al 2013) The responses of the accessions to various salt treatments in this experiment support

the basic premise that wild relatives harbour wide genotypic variation Judged by visual

phenotyping Oa-VR and Oa-KR are the more resilient accessions when tested at 75 mM NaCl

This finding was further verified by the SES and LR where these same accessions presented

significantly lower values (p lt 001) (under 75 mM NaCl) compared to the salt-tolerant control

Pokkali (Fig 2-2) Surprisingly despite the fact that the 120 mM NaCl treatment showed less

variation in leaf symptoms as discussed above the leaf rolling effect was significantly smaller in

Oa-VR and Oa-CH compared with Pokkali Even Oa-D had a significantly lower LR compared with

Pokkali (p lt 001) although it was considered overall to be more salt sensitive than Oa-VR and

Oa-CH This reinforces the complexity of screening experiments in that leaf symptoms integrate

a hierarchy of salinity effects which do not necessarily accord with rankings derived from tissue

sodium concentrations

The net photosynthetic rate (CO2 assimilation in mature leaves) declined with increasing salinity

This was more marked in the salt-sensitive cultivars (IR29 and Nipponbare) than the salt-tolerant

Pokkali (Appendix Table 2-3) as shown previously using Hitomebore IR28 and Bankat as salt-

sensitive cultivars at 6 and 12 dS m-1 (Dionisio-Sese et al 2000) High and relatively uniform

photosynthetic rates were found for all genotypes under the control conditions with values of 28-

37 compared to 6-16 μmol (CO2) m-2 s-1 under salinised conditions The lowest net photosynthetic

rate reduction under salinised treatments (80 mM NaCl) was found for Oa-VR (48) and the

highest for IR29 (79) Similarly the smallest effect on plant height was found in Oa-VR (62

reduction) closely followed by Oa-D (64) A previous study also found decreased net

photosynthetic rates in leaves of four O sativa varieties after 7 d exposure to 60 and 120 mM

NaCl (Dionisio-Sese et al 2000) This effect on photosynthesis may be due to a direct effect of

salt on stomatal resistance via reduction in guard cell turgor leading to a decrease in intercellular

CO2 pressure Photosynthetic inhibition decreases carbon gain and disrupts source-sink relations

of stressed plants (Richardson et al 1985) Despite this a direct impact of ion toxicity on

photosynthetic metabolism cannot be ruled out For instance the activity of Rubisco decreased in

bean plants grown at 100 mM NaCI (Downton et al 1985 Yeo et al 1985) and rice membrane

structure changes drastically (leading to changes in permeability) by substitution of K+ with Na+

(Flowers et al 1985)

Necrosis of leaf tissue is a central feature of salt damage to glycophytes and therefore

determination of the percentage of dead leaves was used to further validate the purported salt

tolerance of Oa-VR having the lowest rates of senescence among all genotypes in both 75 and

120 mM NaCl salt treatments Saline stress first induces stomatal closure through ABA which

acts as an endogenous messenger (Tuteja 2007) This leads to reductions in gas exchange and

assimilation as part of the osmotic impact of salt Later the accumulation of the ions in the leaves

(ion toxicity) causes cell damage (Horie et al 2012) Sodium may build up in the mesophyll cell

walls and dehydrate the cell contents and can thereby exert a direct effect on photosynthetic

machinery (Munns et al 2008) In this experiment I recorded the number of dead leaves on the

main tiller The correlation across a range of salt treatments reported here between mean net

photosynthetic rates and percent of dead leaves suggests a simple and swift non-destructive

method to predict photosynthetic performance and growth rate

Interestingly the wild accessions had very similar (and sometimes even higher) gas exchange

photosynthetic rates compared with the cultivated O sativa genotypes tested (Table 2-3) These

findings contradict a common assumption that wild relatives cannot be used for breeding purposes

since they have ldquolostrdquo their yield-associated traits and thus an interspecies cross would cause a

strong unwanted linkage drag According to this theory early domestication processes followed

by modern plant breeding programs have led to substantial genetic and phenotypic barriers

(Tanksley 1997) Furthermore whilst transgenic approaches have been widely used success is

not guaranteed due to the reported low efficiencies of transformation and regeneration of indica

rice the subspecies most popular in South Asia and Bangladesh (Biswas et al 2018)

A recent study showed that Australia may be a Centre of Diversity for rices with the AA genome

(Brozynska et al 2017) Given the adverse environments in which many of these Australian

accessions evolved I hypothesise that they constitute a rich source of genetic variation in salt

stress tolerance The potential use of these accessions in breeding programs is enhanced by their

naturally high basal rates of photosynthesis

232 Second salt screening to validate the salt tolerance accessions core collection

A second screening was conducted immediately after the first one to (1) validate the first

experiment findings and (2) offer the first clues to the mechanism(s) of seedling-stage salt

tolerance This experiment was conducted in the spring of 2016 at the same greenhouse as the

first screening (section 22) All pre-planting treatments including germination sowing and

thinning procedures were executed in the same way In this screening only four selected

accessions (Oa-VR Oa-CH Oa-D and Oa-KR) were tested under three salt treatments 0 mM

lsquocontrolrsquo 40 mM and 80 mM NaCl (electrical conductivity of 05 27 and 89 dS m-1) Salts were

applied gradually in three daily steps (25 up to 40 and up to 80 mM NaCl) Plants were grown in

the same temperature and watering regime conditions as above with 3022degC daylight and a

mean relative humidity of 59 (plusmn 13 SD) during the day and 74 (plusmn 5 SD) at night Salt

treatments were applied for 30 d

Results

Seedlings grown without the salt treatment for 30 d had healthy green leaves and grew at normal

rates no necrosis or nutrient deficiencies were observed (Fig 2-4) In both salt treatments (40

and 80 mM NaCl) clear phenotypic variations were found in response to salt amongst this

narrower range of accessions (Fig 2-4) Consistent with the first salt screening IR29 had the most

severe visual effects of salt stress with a clear senescence and leaf rolling at 40 and 80 mM NaCl

(Fig 2-5) Oa-VR and Pokkali maintained healthy green leaf tissue under both 40 and 80 mM

NaCl (Fig 2-4) while Oa-CH and Oa-KR had an intermediate leaf phenotypic response to salt

stress (Fig 2-4)

Salt-stress symptoms were most prominent on the third to fifth leaves and were visualised by leaf

rolling reduction of new leaves growth browning of leaf tip drying and senescence of old leaves

as well as reduction in root growth As expected plants were shorter in salinised conditions for all

genotypes compared with control plants (Table 2-4) Number of tillers net photosynthetic rate and

plant height of susceptible genotypes (IR29 and Oa-KR) showed proportionately more reduction

than tolerant genotypes Pokkali and Oa-VR (Table 2-4) Lower reductions in tiller number were

recorded in genotypes Oa-CH and Oa-VR (33 and 37 respectively) followed by genotypes Oa-

D and Pokkali (43 and 46 respectively)

On the other hand the greatest impact on tillering was found for Oa-KR and IR29 (77 and 61

respectively) Reductions in net photosynthetic rates ranged from 27 - 87 the lowest found for

Pokkali (27) followed by Oa-VR (43) In contrast photosynthesis was strongly inhibited in Oa-

KR and Oa-CH with rates 87 and 78 lower after growth in 80 mM salt respectively A significant

positive correlation was found between plant height and (i) SDW (ii) number of tillers and (iii)

photosynthetic rate based on Pearsonrsquos correlation test with p lt 001 (Table 2-5) A significant

negative correlation was found between SES and all other tested parametersmdashplant height SDW

tillers number and net photosynthetic ratemdashmeaning that a higher SES (more severe salt stress

symptoms) will reflected effects on each of these traits

Oa-VR was the only genotype to return a significantly lower SES in both 40 and 80 mM NaCl

compared with values of the salt-tolerant Pokkali (Fig 2-5a) In contrast IR29 showed significant

higher values of SES in both salt treatments compared with Pokkali whilst Oa-D and Oa-KR had

significantly higher SES values than the salt-tolerant control but only in 80 mM NaCl IR29 showed

the same trend of significant higher values of LR in both salt treatments compared with Pokkali

while LR in Oa-VR Oa -CH and Oa-D were significantly lower compared with Pokkali under 40

mM and but not at 80 mM (Fig 2-5b) Chlorophyll concentrations followed an identical pattern

(Fig 1b Yichie et al 2018) with a 34 reduction at 40thinspmM and a 72 reduction at 80thinspmM for

IR29 while no change in chlorophyll concentration was found when Oa-VR was exposed to 40thinspmM

(cf control plants) and only a 19 reduction was seen at 80thinspmM NaCl

The accessions showed wide phenotypic variation in response to salt at relatively low

concentrations Growth in some was less affected than others under salinised conditions (Oa-VR

and Oa-CH) with non-significant reductions of SFW and SDW under 40 mM NaCl compared with

the control plants (Fig 2-6) SFW and SDW were significantly reduced in the other accessions by

the lowest salt concentration (40 mM) as well as a higher salt level (80 mM) including Pokkali

where weights were 29 and 56 lower at 40 and 80 mM salt respectively

Salinity in rice is mainly associated with Na+ exclusion and increased absorption of K+ to maintain

a metabolically compatible Na+K+ balance in the shoot under salinity as described in Chapter 1

In this experiment I investigated the accumulation of Na+ and K+ in shoots across the tested salt

treatments and genotypes The accumulation of Na+ ions in the shoots in relation to genotypic

salinity tolerance (ST) has been described (Yichie et al 2018) A strong negative relationship

between ST and leaf Na+ concentration was revealed with r2 values of 075 whilst a weaker

positive relationship was seen between K+ concentrations in shoots and salinity tolerance (r2 =

069 Fig 2-7) I ascribe this weaker relationship to the narrow range of shoot K+ concentrations

compared with Na+

The three most salt-sensitive genotypes had leaf Na+ concentrations of 300 - 500 micromol g-1 DW

but low value of ST in contrast to the other genotypes that had roughly three times less Na+

accumulation and higher ST value Ion concentrations were used to calculate Na+K+ in leaf tissues

of plants at both 40 and 80thinspmM NaCl The lowest Na+K+ ratios indicating effective ion exclusion

were found in Oa-VR and Pokkali while the other wild rice genotypes and IR29 had progressively

higher ratios reaching an average of 241 for Oa-CH (Fig 1d Yichie et al 2018)

As for SES and LR values Na+ and K+ concentrations were varied over a wide range with a

continuous distribution Weak positive and negative correlations were observed between SES

scores and leaf Na+ and K+ concentration respectively (Appendix Figure 2-2) with slightly higher

R2 values when Na+ was correlated with SES Similar correlation coefficients were found between

concentrations of the two ions and LR scores (Appendix Figure 2-2)

Figure 2-4 Phenotypic changes in response to three salt treatments at 28 DAS for

all tested accessions and the O sativa controls

accessions and controls among 40 (black) and 80 (grey) mM salt treatments Trait means (plusmn

standard errors) are shown for each genotype along with the salt-sensitive controls (IR29) and the

salt-tolerant (Pokkali) at the seedling stage Asterisks indicate significant difference mean from

salt-tolerant Pokkali at the same salt level based on Tukeyrsquos HSD test (p lt 005 p lt 001)

Table 2-4 Number of tillers net photosynthetic rate and plant height under of the four wild Oryza accessions and two O sativa controls

Net photosynthetic rates were measured on 20 DAS while number of tillers and plant height were evaluated on 30 DAS in the non-salinised (0

mM NaCl) and salinised condition (80 mM NaCl) Reduction values were rounded to the nearest integer All pairs comparisons had p lt 0001

based on Studentlsquos t test

Table 2-5 Correlation of different traits at seedling-stage under the same salinised condition Net photosynthetic rates were measured

on 29 DAS while plant height number of tillers and SES values were evaluated on 30 and shoot dry weight was measured after harvest on 30

DAS and 4 d in the oven in 70deg C Asterisks indicate significant difference mean between two selected genotypes based on Pearsonrsquos correlation

test (p lt 005 p lt 001)

LineTraitNon-salinised Salinised Reduction () Pvalue Non-salinised Salinised Reduction () Pvalue Non-salinised Salinised Reduction () Pvalue

IR29 10 4 61 0030 16 7 56 lt0001 52 22 57 001Oa -VR 8 5 37 0002 20 11 43 0005 95 55 43 lt0001Oa -CH 6 4 33 01 18 4 78 lt0001 85 25 70 lt0001Oa -D 7 4 43 012 17 9 47 0012 98 53 46 006

Oa -KR 14 3 77 lt0001 18 2 87 lt0001 91 31 66 lt0001Pokkali 10 5 46 0004 15 11 27 0006 77 25 68 lt0001

Number of tillers Net photosynthetic rate [μmol (CO2) m-2 s-1] Plant Height [cm]

Parameter Plant Height Shoot Dry Weight Number of Tillers Net photosynthetic ratePlant Height NA

Shoot Dry Weight 065 NANumber of Tillers 035 063 NA

Photosynthetic rate 066 026 066 NASES -060 -042 -067 -067

Figure 2-6 Comparison of Fresh Shoot Weight (FSW) (black) and Dry Shoot Weight (DSW)

(gray) yields (in grams) for all salt treatments tested in the screening above Trait means (plusmn

standard errors) are shown for each genotype at the seedling-stage and asterisks indicate

significant difference mean from the non-salinised treatment per genotype based on Tukeyrsquos HSD

4 0 mM

8 0 Mm

O a -V R

4 0 mM

8 0 Mm

O a -C H

4 0 mM

8 0 Mm

O a -D

F re s h W e ig h t

D ry W e ig h t

4 0 mM

8 0 Mm

O a -K R

4 0 mM

8 0 Mm

P o k k a li

4 0 mM

8 0 Mm

IR 2 9

Figure 2-7 Linear regression of Salinity Tolerance (ST) against (a) leaf Na+ concentrations

[μmol Na+ g-1 (SDW)] (R2 = 075) and (b) leaf K+ concentrations [μmol Na+ g-1 (SDW)] (R2 =

069) ST values were calculated as the percentage ratio of mean SDW (salt treatment 80 mM

NaCl) divided by mean shoot dry weight (control no salt) ie [SDW (salt treatment) (SDW

(control)] x 100 Adapted from (Yichie et al 2018)

Discussion

Several studies indicated that rice is highly sensitive to salt during seedling and reproductive

stages (Heenan et al 1988 Pearson et al 1966 IRRl 1967) However there is no clear evidence

that tolerance at one stage implies tolerance at the other Moreover the response of different

genotypes to salinity varies phenologically (Gregorio et al 1997) This chapter specifically

investigates the response of some Oryza Australian wild relatives to seedling-stage salinity and

therefore claims of sensitivity at all phenological stages remains open to further experimentation

To investigate the impact of ion accumulation on salinity tolerance of six contrasting rice

genotypes Na+ and K+ were extracted from leaves after exposing the plants to moderate salt levels

for 30 d Morphological and physiological responses were recorded over the same period and

related to ion levels to infer a measure of tissue tolerance The accumulation of Na+ and the

lsquodisplacementrsquo of K+ (Na+K+ ratio) was of particular interest because it serves as a measure of

tissue tolerance to salt

Sodium chloride is highly water soluble and almost ubiquitous on the planet (Munns et al 2008)

so it is unsurprising that plants have evolved mechanisms to suppress accumulation of Na+ (less

is known about how plants regulate Cl- which has distinct metabolic functions) and to select

against Na+ in favour of K+ as well as other key ions like Ca2+ It is generally considered that much

of the damage to leaves of plants on salinised soil can be attributed to transport of Na+ from root

to transpiring surfaces in shoots where it becomes highly concentrated over time (Lin et al 2004

Ma et al 2018) As for many other species that have been tested leaf Na+ and K+ concentrations

together with shoot phenotypic observations provided insights into possible mechanisms of

tolerance for the four Australian Oryza accessions tested Moreover the two O sativa genotypes

behaved consistently with their reputations for salt tolerance In rice only part of the Na+ load is

taken up symplastically by the roots and reaches the leaves (Krishnamurthy et al 2009) after

which it enters the transpiration stream from the xylem parenchyma By this route its uptake can

be regulated under the control of a suite of transporters that are expressed The significantly low

Na+K+ ratios found in both salt-tolerant Pokkali and Oa-VR (p lt 005) indicate that some

membrane-associated mechanisms help the roots to exclude Na+ even in the highest salt

treatment of 80thinspmM NaCl

Previous studies provide clues as to how this Na+ exclusion is achieved For example a QTL that

was later mapped to the OsHKT15 gene (Ren et al 2005) was found to enhance Na+ exclusion

in rice (Hauser et al 2010 Kobayashi et al 2017) and OsHAK16 was found to maintain K+

homeostasis and salt tolerance in the rice shoot by mediation of K+ uptake and root-to-shoot

translocation (Feng et al 2019) The same transporter family (HKT1) was found in Arabidopsis to

retrieve Na+ from the xylem (Sunarpi et al 2005 Davenport et al 2007) High-affinity K+ uptake

has a key role in salinity management (Suzuki et al 2016 Feng et al 2019) by mediation of K+

uptake and root-to-shoot translocation in rice as well as in other species such as

wheat Arabidopsis and barley (Epstein et al 1963 Byrt et al 2007 Munns et al 2008 Hauser

et al 2010)

In this experiment Na+ exclusion by the leaves appears to function effectively in both O sativa

salt-tolerant Pokkali as well as O australiensis (Oa-VR) but failed in other tested wild rice

accessions (and O sativa IR29) where Na+K+ ratios exceeded a value of 2 in the highest salt

treatment of 80thinspmM NaCl A Na+K+ ratio of 44 in 21 indica rice genotypes after 48 d growth at

about 35thinspmM NaCl was reported in an earlier study (Asch et al 2000) supporting the hypothesis

that Oa-VR is tolerant to salt Moreover Na+ concentrations in Pokkali and Oa-VR on a tissue-

water basis were half those in the external solution under 80thinspmM NaCl These opposing degrees

of Na+ exclusion and the resulting plant performance are demonstrated by the strong relationship

between physiological tolerance and the accumulation of Na+ (Fig 2 Yichie et al 2018) Based

on the observation that moderated apoplastic uptake of Na+ in the roots of Pokkali enables

Na+ exclusion (Krishnamurthy et al 2011) the degree of lsquobypass flowrsquo through passage cells in

roots of Oa-VR is a priority for future research (see Yadav et al 1996) The genetic basis of

endodermal development and specifically Casparian Bands in Oa-VR and therefore their role in

impeding entry of toxic Na+ concentrations is a research priority The penalties of Na+ loads in

leaves for shoot physiology (SES chlorophyll content tiller development and photosynthesis

parameters) was apparent across the spectrum of the Oryza genotypes used in this experiment

with strong correlations between ion levels and leaf damage

In this screening chlorophyll levels were almost 50 lower in IR29 at the low-salt treatment

(40thinspmM NaCl) but were not affected in Oa-VR similar to contrasts in salt-stress response reported

in O sativa previously (Lutts et al 1996) where 50thinspmM NaCl lowered chlorophyll levels by up to

70 in some O sativa salt-sensitive genotypes The resilience of chlorophyll retention in Oa-VR

is further re-assuring evidence of its tissue tolerance to salt Photosynthetic activity is highly linked

with abiotic stress and specifically with salinity tolerance in monocots (Yeo et al 1990 Davenport

et al 2007) This is partially explained by stomatal closure which is often a rapid and initial

response to osmotic stress Swift osmotic adjustment can follow salt stress in both roots and

leaves contributing to the maintenance of water uptake and cell turgor and allowing physiological

processes such as stomatal opening and cell expansion to resume after an osmotic shock (Serraj

et al 2002)

Longer term effects of salinity are more complex and normally require acclimation to toxic ion

effects In wheat a study demonstrated that after the immediate stress-induced reduction in

stomatal conductance there was a further decline in this trait caused by the response to ion

accumulation (James et al 2002) In this experiment net photosynthetic under 0 mM NaCl on 29

DAS ranged from 146 to 235thinspμmolthinspmminusthinsp2thinspsminusthinsp1 (Appendix Table 2-3) Under salt treatments (80 mM

NaCl) on 29 DAS net photosynthetic rates ranged from 21 μmolthinspmminusthinsp2thinspsminusthinsp1 for Oa-CH (reduction of

87) to 134 μmolthinspmminusthinsp2thinspsminusthinsp1 for IR29 with a reduction of only 15 High photosynthetic rates in Oa-

VR in optimal conditions might contribute to its resilience under salt consistent with the general

observation that salt tolerance is linked with shoot vigour (Flowers 2004)

Curiously the impact of 80 mM NaCl on photosynthesis in IR29 was minimal I have no

explanation for this As opposed to net photosynthetic rates which were robust in the salt-treated

plants stomatal conductance was reduced by 55 at 80 mM for IR29 (Appendix Table 2-3) Thus

the rate of CO2 assimilation was probably reduced in this experiment by salinity partly due to

reduced stomatal conductance (as shown) and consequent restriction of the availability of CO2 for

carboxylation (Brugnoli et al 1991)

Without salt application transpiration rates values ranged 23 mmol (H2O) m-2 s-1 at 4 DAS to 12

mmol (H2O) m-2 s-1 29 DAS Under 80 mM NaCl the average transpiration rate was only 42 mmol

(H2O) m-2 s-1 across all genotypes with the highest reduction due to salt application being 65 in

Oa-D Interestingly Pokkali was the only genotype with no reduction in transpiration rates under

salt treatments (Appendix Table 2-3) Notably these transpiration rates under salt treatment did

not reliably predict the accumulation of Na+ in leaf tissues consistent with a report in wheat

cultivars where salt uptake was largely independent of transpiration rate (Nicolas et al 1993)

These findings are consistent with a previous study where net photosynthetic rate of the youngest

fully expanded leaves of four rice varieties declined with increasing salinity stress (Dionisio-Sese

et al 2000) The conclusion appears to be that damage to the photosynthetic system regardless

of the manner in which Na+ enters leaf tissues predicts salt tolerance

233 Conclusion

First salt screening

In this experiment I tested an Australian endemic rice collection for salt stress responses under

various salt treatments I revealed some of the behaviour of these accessions by measuring a

wide range of physiological parameters throughout the experiment This demonstrated wide

phenotypic variation as a response to salt stress when comparisons were made with salt-tolerant

and -sensitive cultivars of O sativa Remarkably a few accessions of O australiensis such as

Oa-VR exhibited a higher biomass compared with the domesticated salt-tolerant Pokkali under

salinity In addition scores corresponding to the least leaf injury were recorded for Oa-VR While

no single accession was uniquely superior for all traits linked to salt tolerance Oa-VR was judged

to be the best overall performer

This phenotyping experiment reveals surprising degrees of variation within Australian wild rice

accessions grown under salt stress As a result the accessions have been ranked accordingly to

select contrasting genotypes for future studies The selected accessions were investigated

extensively in the chapters that follow to deepen our understanding of salt tolerance and to obtain

insights into mechanisms

Plant response to the environment involves interacting transcriptional and biochemical networks

and signalling pathways resulting in a wide range of observed phenotypes Many methodologies

can be used to assess these phenotypes and from them we deduce stress-tolerance mechanisms

(Fiorani et al 2013 Walter et al 2015) In this set of experiments I report biomass accumulation

photosynthesis parameters and ion accumulation in response to salt stress in a wide range of wild

rice genotypes from two Oryza species and O sativa controls with contrasting salt tolerance

Multiple strands of evidence including plant growth visual symptoms gas exchange values and

ion concentrations revealed variations in the response to applied salt Biomass reductions were

recorded for all tested genotypes as a result of salt stress However some genotypes such as Oa-

VR and Pokkali were relatively tolerant to salt stress as illustrated by small growth reductions Salt

tolerance was graphically illustrated in Oa-VR after 30 d at 80thinspmM NaCl where shoot fresh

biomass was marginally less affected than in the salt-tolerant landrace Pokkali Moreover

symptoms of leaf damage in Oa-VR caused by NaCl were less noticeable than in Pokkali In a

different aspect chlorophyll levels were dramatically reduced in the salt-sensitive IR29 at only

40thinspmM NaCl whilst they were unaffected in Oa-VR even at 80 NaCl This experiment supports

the long-established view that Pokkali is highly tolerant to salt (Yeo et al 1990 Kumar et al

2005) but importantly it makes a case that a wild O australiensis accession (Oa-VR) has at least

the same level of salt tolerance

The impact of salt on leaf symptoms was roughly equivalent in the two screenings at moderate

NaCl levels (75ndash80 mM) with progressively more damage at 120 mM NaCl These salt levels

were therefore deemed appropriate to reveal tolerance mechanisms without being lethal Hence

these treatments were applied to accessions of rice collected from a wide range of remote

savannah sites in northern Australia including transiently saline waterways in the north and

northwest of Australia These wild accessions are probably subject to low rates of cross pollination

because of physical isolation and the generally strong selfing properties of rice (Beachell et al

1938) Quite consistent correlations between the salinity tolerance traits reported in this chapter

indicate that there is a high proportion of homozygosity for stress tolerance genes in wild rice

populations

For self-pollinated crops as rice it is advantageous if the alleles are naturally homozygous if they

are to be useful in plant breeding in bulk and single-seed descent breeding methods it usually

takes 5ndash6 self-pollinating generations to get to a steady-state when most loci are homozygous

(Collard et al 2008) The findings in this chapter suggest this germplasm is already fixed to a

certain degree providing scope for salinity tolerance in cultivated rice by rapid introgression of

wild germplasm

Among the tested physiological traits ion exclusion has been proposed as an important trait for

enhancing salt tolerance in crops (Noble and Rogers 1992) Another theoretically useful target

trait is leaf photosynthesis since it leads directly to yield (Yeo and Flowers 1986) Leaf gas

exchange variables such as assimilation rate and water use in addition to leaf Na+ uptake may

be useful criteria in salt-stress screens

Encouragingly Oa-VR had equivalent or superior salt tolerance to Pokkali This improves the

likelihood of using key genes Oa-VR in molecular breeding programs with a relatively low risk of

linkage drag Because Oa-VR has the unique EE genome and is genetically incompatible with the

AA genome Oryza species novel stress tolerance traits should ideally be identified at the gene

level for inclusion in breeding endeavours To further examine the potential of Oa-VR and others

as a source of salinity tolerance donor growth dynamics and phenology must be accounted for

using a time-series approach This is discussed in the next chapter

Chapter 3 High-throughput image-

based phenotyping

High-throughput non-invasive phenotyping of Australian wild rice species reveals

contrasting phenotypes in salinity tolerance during seedling growth

The core research for this chapter is reported in Yichie et al (2018) Salinity tolerance in Australian

wild Oryza species varies widely and matches that observed in O sativa Rice 1166 which is

included as an appendix in this thesis The journal article can also be viewed online at

httpsdoiorg101186s12284-018-0257-7 Additional material included in this chapter

represents supporting information for a more detailed understanding of the research reported in

the journal article

Author contributions YY designed and executed the first experiment YY also phenotyped the

plants (for both experiments) performed the data analyses for the first experiment and wrote the

manuscript CB designed the second experiment performed the spatial correction and conceived

of and developed the statistical analyses for the phenotypic data of the second experiment BB

assisted with the phenotypic analyses and revised the manuscript THR and BJA contributed to

the original concept of the project and supervised the study BJA conceived the project and its

components and provided the genetic material

31 Introduction

As previously discussed (Chapter 1) with increasing human population a substantial increase in

rice production will be required to meet global demands in the next decade To improve crop

resilience we first need to understand better how shoot phenotype responds to stress and to

highlight the sensitive growth stages In spite of the general salt sensitivity of rice there is a wide

range in salinity tolerance both between and within Oryza species reflected in rates of growth

and development

Rice is particularly sensitive to salt stress during early seedling development and reproductive

stages (Moradi et al 2007) Seedling vigour defined as the ability to rapidly increase shoot

biomass during early development is critical during crop development to achieve leaf area

photosynthetic capacity high WUE and yield potential Seedling vigour under salt stress is

therefore predicted to be a good indicator of salinity tolerance at this growth stage (Mishra et al

2019) Many studies have examined the differences in growth response to salinity using

conventional destructive harvest techniques but this approach limits the number of traits that can

be assessed The use of novel non-destructive phenotyping has potential to identify more salinity-

resistant genotypes by capturing subtle dynamic traits over time

In rice numerous studies have investigated the physiological biochemical molecular and

genomic responses of seedling-stage salinity tolerance using destructive techniques partially

elucidating the underlying genetic basis of this trait under field and greenhouse conditions (Ko et

al 2003 Cairns et al 2009 Rebolledo et al 2015 Lu et al 2007 Heenan et al 1988 Gregorio

et al 1997) In a recent study twelve rice (Oryza sativa) cultivars were subjected to salinity stress

at 100 mM NaCl for 14 d (Chunthaburee et al 2016) Evaluation of the physiological changes

observed allowed four salt-tolerance clusters to be identified using principal component analysis

(PCA)-based salt-tolerance indices The authors classified each rice variety for its degree of salt

tolerance according to comparisons of measurements taken before and after the salt treatment

including the activity of catalase (CAT) concentrations of anthocyanin hydrogen peroxide and

proline the K+Na+ ratio and chlorophyll abundance

Another study evaluated the physiological responses of 131 rice accessions to two salt treatments

EC of 12 and 10 dS m-1 Root and shoot length as well as ion accumulation were measured after

14 d of salt treatment Three O sativa accessions were found to have superior salinity tolerance

characteristics based on the evaluated morphological and physiological traits (Krishnamurthy et

al 2016)

In recent years the lack of reliable and reproducible techniques for identifying salt tolerance

germplasm for breeding programs has become apparent (Singh et al 2011) In addition the use

of destructive plant biomass measurements makes it difficult to analyse and quantify the dynamic

time-dependent responses in plant growth to salt treatment Complex and non-linear plant

responses to salt stress require dissection of the effect into a series of time periods which can be

measured using non-destructive imaging technologies

Recent developments in image-based technologies have enabled the non-destructive

phenotyping of plant responses to abiotic stresses over time (Berger et al 2010) These novel

methods which allow approximation of shoot biomass development without having to terminate

the whole plant (Rajendran et al 2009 Tuberosa et al 2014) have been demonstrated in wheat

and barley (Rajendran et al 2009 Sirault et al 2009 Golzarian et al 2011) chickpea (Atieno

et al 2017) and sorghum (Neilson et al 2015) A number of other salt-screening methods for

numerous morpho-physiological traits have been used to assess the salinity tolerance of rice

including measurements of leaf area (Zeng et al 2003) leaf injury and survival rate (Gregorio et

al 1997) as well as bypass flow in the root (Faiyue et al 2012) Yet these phenotyping strategies

do not allow the dissection of the two-phase plant response to salinity (ie lsquoosmoticrsquo and lsquoionicrsquo)

and they usually require hundreds to thousands of plants and are thus highly labour-intensive

The use of phenotyping platforms has been demonstrated to be an effective complementary

technique to field trials partly because experimental conditions can be precisely controlled in ways

that are not possible or practical in the field A study in maize evaluated the relationship between

water deficiency tolerance in the field and using a phenotyping platform (Chapuis et al 2012)

Resilience estimated in the field was correlated with differences in leaf growth to soil water deficit

in short-term experiments using this phenotyping platform It was concluded that continuous

phenotyping under controlled conditions produces results consistent with those in the field and

thus could serve as a proxy of resilience under field conditions

In rice a few studies have used an image-based approach to assess plant response to salinity

stress Infrared thermography has been used to measure leaf temperature in response to three

salt treatments (Siddiqui et al 2014) The authors found that stomatal conductance relative water

content and photosynthetic parameters all of which are important traits for salinity-tolerance

assessment were highly correlated (R2 = ndash0852) with average plant temperature In another

study red-green-blue (RGB) and fluorescence images were used to assess the response of

different salinity tolerance traits in rice (Hairmansis et al 2014) The authors showcased the ability

of image analysis to discriminate between the different aspects of salt stress such as the osmotic

and ionic response and thus to be used as part of screening to develop salt-tolerant rice cultivars

Several studies have used high-throughput phenotyping to analyse the genetic architecture of

salinity responses in rice in a time-series manner A recent report revealed a transpiration use

efficiency (TUE) QTL by screening 553 rice genotypes using a 700k SNP high-density array (Al-

Tamimi et al 2016) The use of high-throughput time-series phenotyping and a longitudinal

statistical model allowed the identification of this previously undetected locus affecting TUE on

chromosome 11 This discovery provided insights into the early responses of rice to salinity stress

in particular into the effects of salinity on plant growth and transpiration (Al-Tamimi et al 2016)

Another study in rice investigated the physiological responses to salt stress by using temporal

imaging data from 378 diverse genotypes across 14 d under 90 mM NaCl (Campbell et al 2015)

The results revealed salinity tolerance QTLs on chromosomes 1 and 3 that control the early growth

response and regulate the leaf fluorescence phenotype indicative of the ionic phase during salinity

stress respectively

When plants roots are exposed to salt their shoot growth immediately slows due to osmotic stress

Over time a second component of the salinity response called the ionic phase occurs During

this phase ions mainly Na+ and Cl- can accumulate to toxic concentrations in the shoot resulting

in premature leaf damage and senescence (Munns et al 2008) In the experiment reported in this

chapter and in the accompanying journal article I used high-throughput phenotyping to observe

differences in osmotic and ionic responses to salt in five accessions and two controls over time at

high-resolution By imaging daily I was able to quantify plant growth under several salt treatments

and control conditions

In this chapter high-resolution growth analysis was utilised to explore and validate the salinity

tolerance response of pre-screened accessions from an Australian wild rice panel The two O

sativa cultivars Pokkali and IR29 were used as a positive and negative control respectively in a

range of salt treatments for 30 d during the seedling stage

321 Plant materials

High-throughput phenotyping screening was conducted after the two glasshouse-based

screenings reported in Chapter 2 The experiment was performed in the Smarthouse greenhouse

at The Plant Accelerator (Australian Plant Phenomics Facility University of Adelaide Adelaide

Australia lat 349deg S long 1386deg E) in the summer of 2017 (Fig 3-1a) All pre-planting

treatments including germination sowing and thinning procedures were executed as per Chapter

2 In this screening a subset of five selected accessions (Oa-VR Oa-CH Oa-D Oa-KR and Om-

T) was tested with two controls (Pokkali and IR29) under four salt treatments (0 40 80 and 100

mM NaCl) applied gradually in four daily steps (0 rarr 25 rarr 40 rarr 80 rarr 100 mM NaCl) (Fig 3-1b)

Altogether the performance of 168 plants was evaluated in this experiment

322 The plant accelerator greenhouse growth conditions

The same greenhouse conditions and treatments were applied as in the second screening in

Chapter 2 but with an additional salt treatment of 100thinspmM (ECthinsp=thinsp105 dS mminusthinsp1) Plants were grown

in the same temperature and watering regime conditions ie 3022degC daylight with measured

relative humidity of 59 (plusmn13 SD) during the day and 74 (53 SD) at night Seedlings were

grown without any salt treatment for 30 d (lsquoDays After Plantingrsquo (DAP)) followed by the salt

treatments for an additional 30 d (lsquoDays after Saltingrsquo (DAS))

323 Phenotyping

Each plant was imaged using two types of non-destructive imaging systems RGB (red-green-

blue)visible spectrum and fluorescence (FLUO) using LemnaTec system (Fig 3-1c) Due to the

height of plants in later stages of the experiment I decided to base the projected shoot area (PSA)

first on RGB images at the beginning of the experiment (DAS 4 - 19) and then on fluorescence

towards the end of the experiment (DAS 20 onwards) (Yichie et al 2018) The following

phenotypic traits were measured in addition to those described in the second screening in Chapter

Plant water use

Water levels were monitored and adjusted daily by the Scanalyzer 3D system weighing (using a

digital scale) and watering system (LemnaTec GmbH Aachen Germany) Pot water content was

adjusted to the target weight (giving a water volume of 600 mL) to maintain a constant salt

concentration in each pot (Fig 3-1b) and to ensure that the pot + soil + water weight was held

constant This allowed the estimation of water loss for each plant during the experiment

Projected shoot area (PSA)

PSA is the area identified as being part of the plant in each image Its value was calculated based

on two side view images (at 90deg from each other) and one top view image (Fig 3-1d) where 400

pixels correspond to ~1 cm2 leaf area

Absolute growth rate (AGR)

AGR was measured by the accumulation of pixels through the experiment

Relative growth rate (RGR)

RGR was calculated by subtracting the sum of pixels on a certain day with that for the previous

day and defined here as 1A (dAdt) where A is the area and t the time

Plant height

Plant height was measured as the maximum distance above a horizontal line corresponding to

the pot rim which was identified by the image analysis software The height is given in pixels and

an approximation of the real height (in cm) could be calculated by dividing the pixel value by 20

Centre of mass

The centre of mass is a position defined relative to the plant vegetation and was calculated giving

each pixel of the object the same weight The centre of mass Y value was measured from the top

of the image and converted to plant height above the pot using the plant height technique above

Convex hull and compactness

The convex hull describes a set of X points in a given area to be connected by line segments of

each pair of its points The convex area encloses the plant and describes the area the plant

occupies in space Compactness was calculated as the ratio of plant area to convex hull area It

provides an important quantitative value describing the subjective visual assessment of being

compact For example on side images of plants it integrates both openingsholes and cuts eg

between leaves A low value in compactness describes a compact plant while a high value

represents a big and bushy phenotype

Minimum enclosing circle diameter

This parameter was measured as the minimum enclosing circle around the plant canopy and

can serve as a proxy for plant compactnessbushiness

324 Image capturing and processing

Imaging using a fluorescent (FLUO) and a red-green-blue (RGB) camera was carried out daily

from 2 to 30 DAS where DAS 0 corresponds to the commencement of salting Shoot images were

taken using the LemnaTec 3D Scanalyzer system (LemnaTec GmbH Aachen Germany) using

two 5-megapixel RGB cameras and a fluorescent camera (Basler Pilot piA2400-17gm) Three

images per camera were taken per plant two images from the side at 90deg to each other and one

from the top (Fig 3-1d) From these images the PSA of the plant was obtained A total of 35280

images were captured and processed using ImageHarvest

325 Image processing for senescence analysis

To assess the effects of salinity stress on rice leaf senescence non-destructively plant images

were processed and analysed using ImageHarvest This enabled the extraction of several spectral

metrics from the RGB and fluorescence images and the classification of each pixel to colour

ranges that indicate healthy or senescent tissue (Fig 3-2) Pixels were allocated to one of the two

categories depending on the colour value The number of pixels for each bin were summed from

each image and expressed as a percentage of the plant area from the two side view images (Fig

Figure 3-1 Experimental setup at the Plant Accelerator facility (a) Plants (29 DAS in this

image) were grown at the South East Smarthouse at the Plant Accelerator Facility and were

divided into 12 lanes (b) Schematic illustration of salt application into the pots (modified from

Campbell (2017)) Salt treatment was applied by adding the four salt treatments (0 40 80 and

100 mM NaCl) to the square dish beneath the pot (c) The LemnaTec system was used to capture

plant images daily (d) Projected shoot area was calculated based on two side view images (at

90deg from each other) and one top view image where only the orange colour was considered to be

the plant shoot as described (Yichie et al 2018)

326 Data preparation and statistical analysis of projected shoot area (PSA)

The experiment occupied 12 Lanes times 14 Positions in the South-East Smarthouse and employed

a split-unit design with six replicates to assign the factorial set of treatments as described (Yichie

et al 2018)

To produce phenotypic means adjusted for the spatial variation measured in the greenhouse a

mixed-model analysis was performed for each trait utilising the R package ASReml-R (Butler et

al 2009) and asremlPlus (Brien 2018) as described (Yichie et al 2018)

For all traits REML ratio tests with 120572120572 = 005 were used to determine whether the residual

variances differed significantly for both treatments and genotypes for just one of them or not at

all The model was modified to reflect the results of these tests The residual-versus-fitted value

plots and normal probability plots of the residuals were inspected to check that the assumptions

underlying the analysis were met Wald F-tests were conducted for an interaction between

treatments and genotypes and if the interaction was not significant for their main effects The

predicted means were obtained for the selected model for treatments and genotypes effects LSDs

were calculated for comparing predictions Nevertheless in cases of unequal variances LSDs

were computed for each prediction with the average variance of the pairwise differences as

described (Yichie et al 2018)

327 Functional modelling of temporal trends in PSA

The smoothed PSA was obtained by using the R function smoothspline to fit a spline with five

degrees of freedom (DF) to the PSA values for each plant for all days of imaging The smoothed

AGR was determined by taking the first derivative of the fitted spline for each day while the

smoothed RGR was the smoothed AGR divided by the smoothed PSA for each day

The maximal mixed model used for this analysis was of the form

119858119858 = 119831119831119831119831 + 119833119833119833119833 + 119838119838

where 119858119858 is the response vector of parameters for the trait being analysed 119833119833 is the vector of random

effects and 119838119838 is the vector of residual effects 119831119831 is the vector of fixed effects 119831119831 and 119833119833 are the

design matrices corresponding to 119831119831 and 119833119833 respectively The fixed-effect vector 119831119831 is divided

as [120583120583 119831119831primeR 119831119831primeRℓ 119831119831primeM 119831119831primeL 119831119831primeS 119831119831primeLS] where 120583120583 is the overall mean and the 119831119831 sub-vectors correspond

to the respective effects of Replicates Lanes within Replicates Mainposns Lines Salinities and

Line times Salinity interaction Thus 119831119831 subvectors 4ndash6 are of intrinsic interest (Line Salinity) while

subvectors 1ndash3 correct for any spatial variation within the Smarthouse The random-effects vector

119833119833 comprises the single component 119833119833RM the vector of Main-unit random effects within each

replicate according to the assumptions described previously (Brien 2018) The design matrix 119831119831 is

partitioned to conform to the partitioning of 119831119831 This allowed each Line-Salinity combination to have

a different residual variance or for the variance to differ between sets of the combinations and be

the same within sets

Figure 3-2 Example of rice shoot biomass images taken 20 DAS in The Plant Accelerator

facility (A) Side view RGB of Oryza sativa cv Fatmawati (B) Identified leaves for image

processing (C) Top view of the same plants and date as shown in A (D) Corresponding

fluorescent images of the same rice plants (E) Colour classification using LemnaTec Grid

software where green represents healthy tissue and purple indicates senescent areas Adapted

from (Hairmansis et al 2014)

33 Results

To learn whether the shoot biomass of the rice plants was related to the measurements of

projected shoot area correlation analysis was performed on PSA at 28 and 30 DAS for both

destructive harvest measurements of SFW and SDW Strong positive correlations were found

between the FLUO PSA obtained by image analysis at 28 and 30 DAS for both SFW (R2 = 0927

and R2 = 0966 respectively) and for SDW (R2 = 0921 and R2 = 0956) respectively (Fig 3-3)

As found in other studies (Berger et al 2010 Hairmansis et al 2014 Al-Tamimi et al 2016) I

was able to confirm the suitability of this platform to approximate rice shoot biomass by PSA In

addition a systematic comparison was undertaken of the two sets of measurements (RGB vs

FLU) and the findings showed that for the period of interest the correlations between the two

measurements were R2 = 0945 or greater (Fig 3-4)

Figure 3-3 Relationships between Projected Shoot Area (PSA kpixels) 28 and 30thinspdays after

salting with (shoot fresh and dry weight) based on 168 individual plants using fluorescence

images Pearson correlation coefficients are given on the right for each comparison Each pixel

represents an individual plant treatment combination

Figure 3-4 Correlations between RGB- and FLUO-based measurements of PSA A daily

comparison from 4 to 30 DAS was evaluated to establish the relationship between images taken

by the two cameras and to produce a line for the regression of PSA for FLUO vs PSA for RGB

(kpixels) Each panel in this figure represents a comparison of a single day where every black dot

represents one plant of the 168 tested individual plants

Individual performances of the two O sativa standard lines and all tested accessions are

represented at all four salt levels in Fig 3-5 Plant response between replicates varied eg while

Pokkali biological replicates were highly consistent in each salt treatment Om-T plants were more

inconsistent (Fig 3-5) A wide variation in response to the different salt levels between all the

seven genotypes imaged was observed (Yichie et al 2018 Additional file 6 Fig S4) where IR29

was the slowest growing genotype and had a more compact shoot architecture compared with

Pokkali and the tested wild species accessions (Fig 3-6a-b) Plants of Oa-VR had the highest

recorded PSA as well as compactness and centre of mass values which were associated with big

bushy plants (Fig 3-6a b)

The reduction in shoot growth as measured by PSA was most noticeable at the higher salt

treatments of 80 and 100thinspmM NaCl with only a smaller reduction at 40thinspmM NaCl (Fig 3-7) No

visual leaf symptoms in any genotype 4 d after salt was applied were seen but interestingly the

control plants average growth rates during the two first intervals tested (DAS 0 to 4 and 4 to 9)

were significantly greater (pthinspltthinsp005) than any of the salt treatments (Fig 3-7 and Yichie et al

2018 and Additional file 4 Fig S2) Plants growth were significantly faster in all genotypes without

salt by 12 DAS Pokkali Oa-VR and Oa-D grew substantially faster than IR29 as described

(Yichie et al 2018)

which splines had been fitted through the experiment PSA was processed and calculated

using the fluorescence images on a daily basis after applying the salt treatments for 30 d (30

Figure 3-6 Relationship between PSA and (a) compactness and (b) centre of mass Compactness was defined as the ratio between the

total leaf area divided by the convex hull area while centre of mass was calculated as the position of each pixel relatively to the plant vegetation

Both traits were plotted against projected shoot area using all tested plants in the last nine days of imaging

DAS including non-salinised controls Values of smoothed AGR were calculated from

projected shoot area (PSA) values to which splines had been fitted Thin lines represent individual

plants Bold lines indicate the average of the six replicates plants for each tested treatment

Vertical broken lines represent the tested time intervals used in this study

Oa-VR showed substantially lower inhibition of growth in response to salinity when compared with

Oa-D Oa-Ch Oa-KR and Om-T supporting the observation from the first two screening

experiments (Chapter 2) in which Oa-VR was the most salt tolerant of the explored wild rice

accessions (Fig 3-7) The most severe reduction recorded in PSA across all accessions tested in

the Plant Accelerator study was for an O meridionalis genotype (Om-T) where there was more

than 25 reduction after DAS 9 and a further reduction of almost 20 by DAS 18 under 100thinspmM

A daily calculation of PSA water use index (WUI) by dividing the PSA AGR by the water use was

carried out WUI was decreased in all genotypes compared with controls (Fig 5 Yichie et al

2018) Although WUI values continued to increase in Oa-VR through the experiment at all tested

salt levels (in Oa-D at 80 and 100thinspmM NaCl) it accelerated only after 14 d of salt treatment Control

plants exhibited a better WUI than salt-treated plants up until 18 DAS and 24 DAS in Oa-VR

and Oa-D respectively (Yichie et al 2018) Although the same WUI trend was found in the first

interval (0 to 4 DAS) for both Oa-VR and Oa-D a more efficient WUI (higher value) was found for

Oa-VR in the second interval 0 to 9 DAS onwards (Fig 3-8)

Figure 3-8 Relationship between growth and water use during salt treatment for each of the

six tested intervals A smoothed PSA Water Use Index (y axis) is shown for the selected

genotypes under all tested salt treatments and non-salinised control conditions (x axis) Lines

represent the total average of the six replicates for each treatment

Evidence for different growth patterns was found for the various genotypes by looking at growth-

related traits such as compactness and centre of mass For both traits IR29 had the lowest values

exhibited by small and bushy plants (Fig 3-6) In contrast all other genotypes showed similar

compactness although there was some exceptionally high variation in Oa-VR under control

conditions (Fig 3-6a) Oa-VR as well as Om-T growth phenotypes had the higher centre of mass

values while Oa-KR exhibited the lowest values among the wild relative accessions (Fig 3-6b)

Based on the senescence classification system used Oa-D had the highest senescence values

in all salt treatments (Fig 3-9) Interestingly the salt-sensitive variety IR29 exhibited the lowest

senescence values and in most genotypes the 80 mM NaCl treatment gave slightly greater values

for senescence than the high salt treatment of 100 mM NaCl (Fig 3-9)

Figure 3-9 Average of relative senescence of each tested genotype in three salt treatments

Values were calculated using the one of the two side-view RGB cameras ImageHarvest software

was utilised to process the images and classify each pixel to healthysenescence tissue for the

last three days of the experiment (DAS 27 - 30)

34 Discussion

Measuring the impact of environmental stresses on plants is complicated by the cumulative impact

of the stress on plant size and phenology That is the phenotype is the cumulative result of many

time-dependent processes including physiological and development processes and biological

interactions In grasses the switch from vegetative to tiller initiation then development of

reproductive organs has a large influence on vigour and plant size (Ren et al 2016) With the use

IR29 Oa-CH Oa-D Oa-KR Om-T Oa-VR Pokkali

of high-throughput phenomics platforms high-resolution temporal data can be collected non-

destructively for large numbers of plants with relative ease (Berger et al 2012) Bioinformatic

tools and mathematical analysis can then be used to describe developmental or physiological

processes at different growth stages in relation to an induced stress Imaging of shoots using this

approach can be coupled with other physiological measurements (eg ion concentrations as

described in Chapter 2) to provide a powerful approach for abiotic stress analysis

Using much more sophisticated technologies this chapter followed the approach used in Chapter

2 to provide multiple strands of evidencemdashincluding biomass accumulation leaf senescence

water use and plant growth ratesmdashto reveal a wide range of tolerances to salt in a small selection

of wild and cultivated rice genotypes For example WUE was substantially greater in Oa-VR

than Oa-D especially in the first two weeks after salt was applied This might be due to the fact

that the resilience of photosynthesis observed in salt-treated Oa-VR plants sustained growth

(PSA) even as stomatal conductance decreased by 60 Contrastingly Oa-D plants at 100thinspmM

NaCl exhibited notably lower WUI values than those at 40 and 80thinspmM NaCl reflecting the

gradually higher impact of NaCl on hydraulics in this sensitive accession as concentrations

increased from 40 to 100thinspmM NaCl The tendency of low WUI in salt-treated plants is believed to

be linked to a disproportionate reduction in leaf area (Munns et al 2008) and is consistent with

previous studies of indica and aus rice (Al-Tamimi et al 2016) as well as wheat and barley

(Harris et al 2010) A detailed time-course analysis of ion concentrations in young and mature

leaf tissues would help reveal the mechanisms of salt-induced damage in these two cultivars

Plant performance in saline substrates is dynamic integrating relative tissue tolerance to toxic

ions and the energy efficiency of osmotic adjustment (Munns et al 2016) For example in the

experiment I managed to show that values for non-destructive measurements exhibited a

relationship between control and salt-treated plants that varied noticeably over the time course of

treatment in all tested plants reflecting an interaction between genetics phenology and

environment For example IR29 was characterised by slow growth and small plants with multiple

tillers enabling it to avoid toxic salt loads and leaf senescence The paradox of a salt-sensitive

genotype not showing leaf symptoms could be the result of stomatal closure early in development

causing reduced water loss by transpiration and thus lower salt uptake this remains to be tested

The effect in IR29 can be compared with vigorous early growth and an early transition to flowering

in Pokkali Such developmental contrasts between genotypes confound comparisons under salt

stress For instance there was a small effect of 100 mM NaCl on absolute growth rates during the

early stages of vegetative development in IR29 presumably because there was a rapid

adjustment to the osmotic effects of salt while toxicity had not taken hold Therefore relative

growth rates in IR29 were modest (Fig 3-7) even though leaf senescence was very severe in later

stages of canopy development (Fig 3-9) By extension such developmental effects are likely to

be a factor in how salinity affects yield (Khatun et al 1995)

Among both the wild rices I observed a variation between the biological replicates resulting in

some differences in duration of vegetative growth I speculate that this would be a result of the

stability of some genetic regions spanning these growth-related traits Pokkali is a well-known

Indian landrace and its germplasm has been used in many domesticated rice accessions

of pokkali-type varieties (Shylaraj et al 2005) This along with the use of Pokkali in breeding

programs has led to the assumption of its homozygous genetic steady-state The same

hypothesis is valid for the salt-sensitive IR29 since it has been widely used in breeding programs

Plant responses across biological replicates were very similar in these O sativa controls whereas

some variation was found in the wild relative within replicates of the tested salt concentrations

(Fig 3-5) This may have implications for the genetic states of some loci within the wild relatives

as they were exposed to cross pollination in nature For future development of new salinity-tolerant

varieties using the Australian wild relatives panel there is a need to conduct a few self-pollination

generations of the best-preforming accessions to make these a useful and genetically stable

resource for plant breeders

I speculate that the physiological phenotypes found in this experiment provide indications that

there might have been a degree of domestication of the wild relatives by indigenous communities

For example the absolute growth rate of Oa-VR was found to be almost the same as Pokkali in

the control treatment in addition to photosynthetic and biomass values determined in the

experiments reported in Chapter 2 These findings suggest that some of the Australian wild

relatives of rice were exposed to a degree of selective evolutionary pressure as described

previously for thermotolerance of photosynthesis in other species (Hikosaka et al 2006) This is

made more plausible by the fact that the locations from which Oa-VR and Oa-D were collected

are neither salt-affected as far as we can determine or particularly different physically or

geographically Thus their contrasting salt tolerance is difficult to explain from natural selective

forces However there are obvious effects of domestication in Pokkali where water use index

was higher in the first 14 d (Fig 3-9) providing evidence of domestication Other key traits that

were removed via selection under rice cultivation such seed shattering seed dormancy and

indeterminate growth (Harlan et al 1973) still exist in all the wild rice accessions

35 Conclusion

This chapter underlines the power of automated imaging as a tool to quantify the phenomes of

closely related accessions In this case early seedling growth dynamics in wild rice relatives was

tested at multiple salt levels by repeated imaging of the same plants The statistical advantage of

such an approach in wild crop relatives is that plant-to-plant variation becomes manageable High-

resolution image-based phenotyping was coupled to other phenotypic measurements (non-

destructive and destructive analysis) to understand complex traits such as phenology across five

wild relatives and two domesticated rice cultivars This chapter focused on genotypes selected

from Chapter 2 applying deeper analysis at a range of salt levels during seedling development

These chapters led to the premise of Chapter 4 where the mechanism of salt tolerance is

investigated in selected genetic material using a membrane-targeted proteomics approach in

roots For example ion and senescence presented in Chapters 2 and 3 suggested that Oa-D had

twice as much Na+ in leaves as the salt-tolerant genotypes (Pokkali and Oa-VR) suggesting

multiple levels of sensitivity to NaCl including both root and shoot factors shoot tissue tolerance

and root exclusion traits are not necessarily linked (Munns 2011) The Plant Accelerator

experiment provided salt tolerance traits and rates of shoot development (Yichie et al 2018)

pointing to Oa-VR and Oa-D as complementary O australiensis genotypes representing

contrasting tolerance to salt

Chapter 4 Proteomics

Comparative proteomics assessing Oryza

australiensis roots exposed to salinity stress

The core research for this chapter is reported in Yichie et al (2019) Salt-treated roots of Oryza

australiensis seedlings are enriched with proteins involved in energetics and transport

Proteomics 19 1ndash12 which is included as an appendix in this thesis Additional material included

in this chapter represents supporting information for a more detailed understanding of the research

reported in the journal article Author contributions YY led the experimental design grew and

collected the tissue and co-led the protein extraction coordinated the experimental

implementation data analysis and writing of the manuscript MTH assisted with the conceptual

framework of the study and writing of the manuscript PAT led the Rt-qPCR experiment DP led

the data analysis and assisted with the conceptual framework HDG provided access to the yeast

deletion library and led the yeast validation experiment SCVS developed the protocol for the

preparation of the microsomal fractions and led the TMT labelling and mass spectrometry

workflow THR and BJA supervised the study and contributed to the writing of the manuscript BJA

conceived the project and its components provided the genetic material and contributed to the

data analysis All authors read and contributed to the manuscript

41 Introduction

411 Proteomics studies of plant response to abiotic stresses

The first proteomic studies on abiotic stress in plants were carried out on the model

species Arabidopsis thaliana and rice (Agrawal et al 2009) Since then numerous plant

proteomes have been investigated for their responses to cold (Thomashow 1999 Apel et al

2004) heat (Baniwal et al 2004 Skylas et al 2006) drought (Bonhomme et al 2009 Ford et

al 2011 Wu et al 2019) waterlogginganoxia (Chang et al 2000 Ahsan et al 2007 Alam et

al 2010) salinity (Dani et al 2005 Ndimba et al 2005 Sobhanian et al 2010) ozone stress

(Agrawal et al 2002 Bohler et al 2010) high light (Murchie et al 1997 Giacomelli et al 2006)

mineral nutrition (Yang et al 2007 Brumbarova et al 2008 Fuumlhrs et al 2008) heavy metal

toxicity (Hajduch et al 2001 Kieffer et al 2008) and more However the changes in the proteome

of wild rice relatives in response to abiotic stress have yet to be described

412 Quantitative proteomics approaches in rice research

Rice with a major socio-economic impact on human civilisation is a representative model of

cereal food crops and is widely used in functional genomics and proteomics studies of cereal

plants Substantial research has been carried out to analyse the entire protein profile of cells or

tissues of rice and remarkable progress has been made in the functional characterization of

proteins in these samples (Komatsu 2005 Komatsu and Yano 2006)

In the early 2000s a pioneering study of quantitative proteomics was carried out in O sativa

where different tissue samples were analysed using two independent technologies two-

dimensional gel electrophoresis followed by tandem mass spectrometry and multidimensional

protein identification technology (Koller et al 2002) This allowed the detection and identification

of more than 2500 unique proteins (Koller et al 2002) and revolutionised large-scale proteomic

analyses of plant tissue using complementary and multidimensional technologies with available

genomic databases Since then quantitative proteomics has been applied in numerous aspects

of rice research Luo et al investigated the overexpression of the human foreign protein

granulocyte-macrophage colony stimulation factor in rice endosperm cells utilising a quantitative

mass spectrometry-based proteomic approach (Luo et al 2009) This study identified 103

proteins that displayed significant changes between the transgenic and wild type rice with the

endogenous storage proteins and most carbohydrate metabolism-related proteins down-regulated

in the wild type

Since rice is susceptible to cold stress various studies have explored the cold response of rice

leaves using quantitative proteomics to identify key proteins underlying this trait A two-

dimensional gel electrophoresis (2-DE) spot volume comparison technique has been used

primarily in rice roots (Lee et al 2009 Neilson et al 2010) leaves (Hashimoto et al 2007 Lee

et al 2007) and anthers (Imin et al 2004 2006) The differential expression of many common

proteins and other proteins involved in molecular responses to low temperature in processes

including photosynthesis reactive oxygen species (ROS) detoxification and translation have been

found in these studies However there are many disadvantages of using 2-DE analysis which

limits the amount of proteomic information generated The use of two complementary approaches

of label-free and iTRAQ in the analysis of the rice protein expression profile enabled Neilson et al

to identify 236 cold-responsive proteins using the label-free approach compared to 85 in iTRAQ

with only 24 proteins in common (Neilson et al 2011)

Long-distance drought signalling has been explored in rice roots (Mirzaei et al 2012) Utilising

nanoLC-MSMS this study concluded that water supply can alter protein abundance and gene

expression remotely by eliciting and inhibiting signals Another drought-related study on rice roots

examined two O sativa genotypes with contrasting drought response (Rabello et al 2008)

Proteins were separated by 2-DE and analysed by MALDI-TOF This study revealed that the

drought-susceptible genotype showed a higher diversity in protein profiles with more unique

proteins expressed than the resistant genotype (Rabello et al 2008)

413 Rice salt tolerance studies using quantitative proteomics approaches

In rice salinity tolerance has been explored widely using qualitative proteomics approaches

(Munns et al 2008) The DELLA proteins which mediate the growth-promoting effects of

gibberellins in a number of species were found to integrate signals from a range of hormones

under salinity (Achard et al 2006) In some studies plasma membrane proteins were found to

have a crucial role in salinity tolerance (Thomson et al 2010) In addition studies of osmotin-like

proteins have shown that they are widely distributed in plants and improve resilience by quenching

reactive oxygen species and free radicals (Wan et al 2017)

Although salinity is a major factor limiting rice production worldwide and quantitative proteomics

is a powerful approach to study the function and regulation of proteins only a few studies have

examined the proteome profile of rice during salinity stress through quantitative proteomics

approaches One such study on the roots of the salt-tolerant rice cultivar Pokkali and the sensitive

IR29 identified 42 proteins that responded to salt stress involved in cell elongation metabolism

photosynthesis and lignification (Salekdeh et al 2002) Another study on rice roots tested the

effect of 150 mM NaCl for 24 48 and 72 h on 3-week-old Nipponbare (Oryza sativa) seedlings

(Yan et al 2005) Using MS analysis and database searching ten highly differentially expressed

proteins were found of which four were previously confirmed as salt stress-responsive proteins

while six were novel proteins involved in various pathways such as nitrogen and energy

metabolism regulation cytoskeleton stability and mRNA and protein processing

A quantitative rice plasma membrane proteomics study identified eight proteins most of which

were likely to be PM-associated involved in several important mechanisms of plant acclimation to

salinity stress such as regulation of PM pumps and channels oxidative stress defence signal

transduction membrane and protein structure and others (Nohzadeh et al 2007) The glycolytic

enzyme aldolase was identified in a quantitative proteomics analysis of rice root tonoplast proteins

induced by gibberellin treatment (Tanaka et al 2004) In addition fructose bisphosphate

aldolases were identified to be upregulated by 1 to 3-fold in rice leaf sheaths exposed to 50 mM

NaCl for 24 h (Abbasi et al 2004) Another study examined the ubiquitin-related proteins in salt-

treated roots of rice and found that the mechanism of protein ubiquitination are important against

salt stress in O sativa seedlings (Liu et al 2012)

A comprehensive study on the abundance of membrane proteins of rice roots under salt stress

using quantitative proteomics has not yet been carried out Given the transporters that were found

in the past (Chapter 1) this approach is highly important in seeking novel mechanisms for salinity

tolerance in rice In this chapter a microsomal fraction of roots was used to study the protein

expression of two contrasting rice relatives Oa-VR and Oa-D (Yichie et al 2018) under salt

treatment While the salt-tolerant genotype (Oa-VR) is from the Northern Territory and the salt-

sensitive accession is from the Gibb RIver region of Western Australia there is no basis and

immediate linkage for predicting their respective tolerances to salinity without an in-depth

investigation of the potential mechanism as described in this chapter

421 Growth and treatment conditions

Two wild accessions derived from the wild relative of rice Oryza australiensis were chosen from

the Australian endemic wild rice species collection The wild accessions were selected from a

widespread range of sites including transiently saline waterways in the north and west of Australia

and extensively screened for salinity tolerance traits (Chapter 2) The two selected wild accessions

for this study Oa-VR and Oa-D were found earlier to be salinity tolerant and sensitive

respectively (Yichie et al 2018) Seeds were germinated on Petri dishes and transferred to dark

containers with a Yoshida hydroponic solution (Yoshida et al 1976) at the three-leaf stage Plants

were grown in a temperature-controlled growth room with a 14-h photoperiod and daynight

temperatures of 2822degC for the duration of the experiment with an external light intensity

exceeding 700 μmol m-2 s-1 throughout Fifteen days after germination (15 DAG) salt treatment

was imposed gradually in daily increments to concentrations of 25 40 and finally 80 mM by adding

NaCl to a final electrical conductivity (EC) of 10 dS m-1 in Yoshida nutrient solution (Yoshida et al

1976) to half of the seedlings While the remaining half (the lsquocontrolrsquo plants) were grown without

any addition of salt resulting with fifteen plants per genotype times treatment (60 seedlings in total)

Roots from both treatments were harvested for protein extraction after 30 d of salt treatments (30

DAS) All other details of the growing conditions have been described (Yichie et al 2019)

422 Proteomic analysis

A schematic diagram of the TMT-labelled proteomics workflow is provided in Figure 4-1 which

included the cultivation of samples extraction fractionation and in-gel digestion of proteins

analysis of peptides by nanoflow liquid chromatography-tandem mass spectrometry (nanoLC-

MSMS) peptide identification and functional annotation

Figure 4-1 Schematic diagram of the TMT-labelled quantitative proteomics workflow The

workflow includes growing rice accession on saltcontrol treatments extraction and digestion of

proteins nanoLC-MS3 analysis of peptides identification of peptides quantitative analysis and

pathway mapping

423 Protein extraction and microsomal isolation

Approximately 1 g (fresh weight) of whole root systems was used for protein extractions for each

genotype times treatment combination with three biological replicates Roots were harvested and

rinsed throughout with deionised water Proteins were extracted by grinding the roots using a

mortar and pestle in 2 mL g ice-cold extraction bufferroot comprising 250 mM sucrose 250 mM

KI 2 mM EGTA 10 (vv) glycerol 05 (wv) BSA 2 mM DTT protease inhibitor (Roche) 15

mM β-mercaptoethanol 1 mM sodium sulfite and 50 mM 13-bis(Tris(hydroxymethyl)-

methylamino)propane (BTP) with the pH adjusted to 78 with MES Homogenates were filtered

through two layers of cheesecloth and centrifuged at 11500 x g for 15 min at 4degC The pellet was

discarded and samples were centrifuged again at 87000 x g for 35 min The pellet was washed

with the same extraction buffer (without BSA) and centrifuged at 87000 g for 35 min The

resuspension and ultra-centrifugation steps were repeated three times to remove soluble proteins

and BSA from the samples so that transmembrane proteins were concentrated in the final pellet

as described before (Cheng et al 2009)

Pellets were dissolved with sonication in 100 μL 8 M urea 2 SDS 02 M N-methylmorpholine

01 M acetic acid 10 mM tris(2-carboxyethyl)phosphine (TCEP) then incubated at room

temperature for 1 h to reduce disulphide bonds Cysteines were alkylated by addition of 4 μL 25

2-vinylpyridine in methanol followed by incubation for 1 h at room temperature then addition of 2

μL 2-mercaptoethanol to quench the 2-vinylpyridine

Alkylated proteins were extracted by acetate solvent protein extraction (ASPEX) as described

earlier (Aspinwall et al 2019) with two modifications volumes of solvents were doubled and

ammonium acetate were used

424 Protein quantification by bicinchoninic acid (BCA) assay

The ASPEX-extracted pellets were re-dissolved in 100 μL 8 M urea 2 SDS 02 M N-

methylmorpholine 01 M acetic acid and a BCA assay (Thermo Scientific Rockford IL) was

performed as per the manufacturerrsquos protocol to determine protein concentration Briefly bovine

serum albumin (BSA) standards were prepared in 5 (vv) SDS in the range of 0 to 2 mg mL-1

Three technical replicates of 25 μL each were pipetted into wells of a Greiner CELLSTARreg 96-

well flat-bottomed polystyrene plate for the BSA standards and the unknown protein samples To

each well 200 μL of the BCA working reagent was added and the plate was covered and shaken

on a micro-plate shaker for about 30 s The plate was incubated at 37degC cooled to room

temperature and the absorbance was measured at 562 nm in a BMG FLUOstar Galaxy multi-

functional plate reader (BMG Lab technologies Germany) BSA standards were used to plot a

standard curve against the unknown protein concentrations of the samples (Appendix Figure 4-

1) The average of the technical replicates of each biological replicate was calculated and protein

concentrations were determined

425 Lys-Ctrypsin digestion

Fifty micrograms total protein per sample was aliquoted into 15-mL low-protein-binding

microcentrifuge tubes (Eppendorf) and re-extracted by a modification described (Wessel et al

1984) in order to recover protein in the absence of the urea buffer Then 250 microL of 67

methanol25 chloroform8 water was added and mixed gently for each sample Immediately

after mixing 500 microL ice cold 10 M ammonium acetate was added followed by mixing by inversion

and centrifugation for 1 min at 15000 x g The top aqueous phase was discarded completely but

without disturbing the precipitated protein at the interphase Ice-cold water-saturated diethyl ether

(500 microL) was added to the bottominterphase phase followed by mixing for 10 s Then 100 microL

ice cold containing 25 TFA in ethanol was added to protonate the residual acetate followed by

centrifugation at 15000 g for 10 min The supernatant was discarded and the pellets were washed

in 800 microL ice cold 11 ethanoldiethyl ether 01 M triethylamine 01 M acetic acid 1 water 1

DMSO vortexed for a few seconds and centrifuged The final step (pellet suspension) was

performed twice the supernatants were discarded and the pellets stored at -20degC prior to

digestion

Fifty micrograms of protein pellet from each sample was partially air dried and dissolved in 25 μL

of 04 RapigestTM (Waters) 02 M N-methylmorpholine 40 ngμL Lys-C (Wako) The pellets

were then suspended and digested by incubation in a Thermomixer (Eppendorf Germany) at

1200 rpm at 45degC for 15 min followed by sonication at 45degC in a water bath (Liquid Glass Oz

ultrasonic cleaner Australia) Following the Lys-C digestion 5 microL 025 microgmicroL trypsin (Sigma

Aldrich Australia) in 01 M acetic acid was added as described (Aspinwall at al 2019) The trypsin

digests were incubated overnight at 37degC Digestion was stopped by adding 6 microL 125 TFA

followed by 45 min incubation at 37degC Samples were chilled on ice centrifuged at 17000 x g for

10 min 4degC The supernatant was carefully transferred to a fresh microcentrifuge tube and

samples were stored at -20degC

426 TMT labelling reaction

Twenty-three microlitres of digested protein from each sample was labelled with Amine-Reactive

Tandem Mass Tag Reagents (TMT10plextrade Isobaric Label Reagent Set Thermo Scientific

90110) as described (Yichie et al 2019) The samples of each genotype were labelled randomly

using a designated TMT channel A MasterMix of all twelve samples (both genotypes and

treatments) was made and reacted in TMT label 126 in both channels using 4 microL of each of sample

(Fig 4-2) The TMT reagent was resuspended in 41 microL of dry acetonitrile (ACN) per 08 mg vial

according to the manufacturerrsquos protocol (Thompson et al 2003) Samples were incubated at

room temperature for 1 h and the reaction was quenched with the addition of 2 microL of 5 (vv)

hydroxylamine for 15 min at room temperature The samples were combined for each set of 10-

plex the Rapigest was hydrolysed and pooled samples were evaporated as described (Yichie et

al 2019)

An Oasis hydrophilicndashliphophilic balance (HLB Oasistrade Waters USA) polymer cartridge was

activated and peptides were desalted as described (Yue et al 2013) Samples were then dried

to completion overnight in a centrifugal evaporator and reconstituted in water for hydrophilic

interaction liquid chromatography (HILIC) fractionation Aliquots of 25 μL of peptide for the total

proteome analysis were fractionated as described previously (Palmisano et al 2010) resulting in

seven fractions per each sample (Yichie et al 2019) Fractions were collected in a V-bottom 96-

well plate (Greiner Bio-One Gloucestershire UK) at 2-min intervals after UV detection (80-nL flow

cell) and the plate was dried by vacuum centrifugation before LC-MSMS analysis

Figure 4-2 Diagram of the TMT-labelling strategy used in the experiments Peptides from the

triplicates of each accessions (control and salt) were labelled with one TMT 10plex set TMT label

126 contained a MasterMix of all twelve samples from both sets

427 NanoLC-MS3 analysis

Each TMT-labelled HILIC fraction was resuspended in 6 μL of MS Loading Buffer (3 (vv) ACN

01 (vv) formic acid) and analysed by nanoLC-MSMSMS using a Dionex Ultimate 3000 HPLC

system coupled to a Thermo Scientific Orbitrap Fusion Tribridtrade Mass Spectrometer (Thermo

scientific CA USA) The orbitrap Fusion machine was first calibrated with BSA samples

(Appendix Figure 4-2a-b) followed by a test run to adjust the gradient time and sample

concentration to the machine (Appendix Figure 4-3) Ten microlitres of peptide sample was

injected onto a peptide trap reversed-phase column (75 μm id times 40 cm) packed in-house with

C18AQ material of particle size 19 μm (Dr Maisch Germany) and eluted as described(Yichie et

al 2019) The MS1-2 scans were performed as described (Yichie et al 2019)

428 Proteinpeptide identification

For quantitation of TMT reporter ions SN for each TMT channel was extracted by discovering the

closest matching centroid to the expected mass of the TMT reporter ion in a window of 006 mz

using Proteome Discoverer v22 with local Sequest HT and Mascot servers (Pappin et al 1999)

The reporter ions were then adjusted to account for isotopic impurities in each TMT label as per

the manufacturerrsquos instructions Peptides were assembled into proteins guided by principles of

parsimony to generate the smallest set of proteins required to account for all observed peptides

Reporter ion counts across all identified peptides were summed in order to quantify the proteins

Peptides that did not have a TMT reporter ion signal in all channels were excluded from further

quantitation Summed signal intensities were normalised to the channel that contributed the

highest overall signal

429 Database assembly and protein identification

Since the samples were derived from O australiensis for which the genome had not been

sequenced four different databases were assembled as the search databases utilising UniProt

(downloaded from httpwwwuniprotcom in August 2018) and Phytozome 121 version

(downloaded from httpsphytozomejgidoegov in August 2018) proteomics resources The

following databases were constructed against which the peptide mass spectra queries were

searched

i Oryza database Oryza barthii Oryza glaberrima Oryza nivara Oryza punctata

Oryza rufipogon Oryza sativa sp indica Oryza sativa sp japonica and Oryza

meridionalis

ii Grasses database Brachypodium distachyon Panicum virgatum Setaria italica

Setaria sviridis and Zostera marina

iii Salt-tolerant species database Beta vulgaris Brassica napus Chenopodium

quinoa Gossypium_raimondii Hordeum vulgare and Sorghum_bicolor

iv Arabidopsis database Arabidopsis thaliana

Genomes were assembled using CD-HIT software with 90 identity threshold (Wu et al 2011)

and search parameters were set (Yichie et al 2019) Fixed modifications were set as

carbamidomethylation of cysteine and potential modifications as oxidation of methionine Peptide

results were filtered to 1 false discovery rate (FDR) and 005 p-value Proteome Discoverer 22

The seven fractions of each sample were processed consecutively with output files for each

fraction in addition to a simple merged non-redundant output file for peptide and protein

identifications with log(e) values less than -1

4210 Analysis of differently expressed proteins between the accessions and salt

treatments

The TMTPrepPro (Mirzaei et al 2017) scripts implemented in the R programming language were

utilised to identify significantly expressed proteins with the different samples and to carry out

multivariant analysis (Yichie et al 2019) between the two accessions and treatments

(i) Oa-VR salt vs Oa-VR control

(ii) Oa-D salt vs Oa-D control

(iii) Oa-VR salt vs Oa-D salt

(iv) (Oa-VR salt vs Oa-VR control) (Oa-D salt vs Oa-D control) ie the salt times genotype interaction

Student t-tests were performed for each comparison and the fold changes were determined for

each identified protein Proteins were functionally annotated to categories (BINs) using the

MapMan scheme and the Mercator 3 online tool (Lohse et al 2014) Protein differential

expression between treatments was determined for each individual protein separately using the

known statistical tests (Yichie et al 2019)

4211 Functional annotations

Sequential BLASTP searching with an E-value cut-off of 1e-10 was used to map the sequences to

corresponding identifiers in the UniProt O sativa database Gene Ontology (GO) information was

mined from the UniProt database and matched to the list of identified proteins and used to

categorise the biological processes associated with differentially expressed proteins These

proteins were categorised into a selected number of biological processes of interest using the

PloGO tool (Mirzaei et al 2017) an in-house software developed using the R statistical

programming framework (httpwwwr-projectorg) The proteins were categorised into a selected

number of biological processes of interest as described (Yichie et al 2019)

The PloGO tool was further used to identify enriched representation of proteins in two specific

categories lsquomolecular functionsrsquo and lsquobiological processrsquo This entailed two complementary

approaches to assess the enrichment of categories in response to salt one based on numbers of

proteins only and another based on quantitation of all proteins within each functional category

Under the first approach enriched categories were determined by comparing the numbers of

proteins identified in each protein subset of interest with the total number of proteins in that

category identified in the experiment by means of Fisherrsquos exact test lsquoFunctionalrsquo or lsquoprocessrsquo

categories with a Fisherrsquos exact test p-value lt005 and present in higher proportion in the

respective subset than in the whole protein subset were deemed to be lsquoenrichedrsquo

Secondly protein abundance was considered by summing overall log-transformed protein ratios

of saltcontrol for each molecular function or biological process category of interest and by

comparing the overall salt-induced response of each functional category between the two

accessions by means of an unpaired student t-test applied to the log-transformed protein ratios

Categories with a difference in total salt response (t-test p-value lt005) were deemed as

significantly differentially expressed in terms of their overall salt response between the two

accessions Proteins were then classified into pathways based on biological process information

available on the KEGG database (Zhang et al 2013)

43 Results

431 Physiological response to salt stress

Both accessions showed green and healthy root and shoot growth in the non-salinised control

plants A clear difference between the accessions became apparent after exposing the plants to

80thinspmM NaCl for 7 d consistent with the previous screening discussed in Chapters 2 and 3 (Yichie

et al 2018) Phenotypical symptoms of salt exposure were present in both accessions but the

shoot and root growth were more drastically inhibited in the salt-sensitive Oa-D accession than

the salt-tolerant Oa-VR

432 Protein identification through database searches

Only peptides with p-values below the Mascot significance threshold filter of 005 were included

in the search result In order to perform a comprehensive database search of the O australiensis

proteins four different databases described above (section 428) were assembled to match the

generated mass spectra The Oryza database yielded the highest number of peptides and

quantified proteins (Table 4-1) The Salt-tolerant database derived from six species with known

salinity tolerance characteristics gave the second largest number of hits for queried peptides but

less quantified proteins than the Grasses database which was derived from five different species

(Table 4-1) Top protein patterns for each dataset can be seen in Appendix Figures 4-5 to 4-8 All

individual identified proteins for each explored dataset can be found in the following link

(httpscloudstoraarneteduauplussemxmuasNAu1nAqb)

Database accession

Total redundant peptides

Unique peptides

Total redundant proteins

Proteins quantified

by multiple peptides

Oryza Oa-VR 57498 43788 11046 2680

Oa-D 52925 40113 9986 2473

Grasses Oa-VR 22125 14901 5068 1873

Oa-D 19646 13626 4515 1683

Salt-tolerant

Oa-VR 23296 16477 5857 1338

Oa-D 20828 14809 5109 1187

Arabidopsis Oa-VR 3328 2671 898 501

Oa-D 3136 2411 807 446

quantified by multiple peptides for O australiensis accessions using the TMT

quantification method (FDR lt1)

Within the Oryza database a total of 260 proteins significantly increased in abundance by at least

the 15-fold cut-off under an ANOVA test with three replicates at p lt005 (Appendix Table 4-1)

The highest fold change in protein abundance was a 645-fold increase in an uncharacterised

protein (UniProt A0A0D3H139) in the sensitive accession (Oa-D) with salt compared to the same

accession grown without salt (Appendix Table 4-1)

Within the Grasses database 298 proteins passed the threshold criteria mentioned above with a

highest fold-change of 748 for a cupin domain protein (Phytozome Pavir9KG0416001)

between the salt-treated Oa-D and the control treatment of the same accession (Appendix Table

4-2) This protein was derived from Panicum virgatum species in the database (Appendix Table

Using the Salt-tolerant species database 220 proteins were found to be significantly enriched with

more than 15-fold change The highest fold-change of 65 occurred for a protein annotated to the

Hordeum vulgare (Phytozome HORVU7Hr1G0367201) genome in the Oa-D accession under

salt treatment vs no salt This protein (encoded by a cupin domain gene) was also enriched in the

Oa-VR accession but with a fold change of 20 in the salt-treated plants compared to the control

(Appendix Table 4-3)

The highest fold-change found using the Arabidopsis database was attributed to the ribosomal

protein L7Ae encoded by the gene RPL7AA (UniProt P28188) which was enriched by 425-fold

in Oa-VR control vs Oa-D salt (Appendix Table 4-4) Within this database 73 proteins passed the

statistical threshold (Appendix Table 4-4)

Within the Oryza dataset a total of 2680 and 2473 proteins were quantified (FDR lt1) in the Oa-

VR and Oa-D accessions respectively (Table 1A Yichie et al 2019) with a total of 3355 non-

redundant proteins Each protein was annotated to one of the eight Oryza species within the

database The highest number of annotated proteins for both accessions matched to O punctata

as described (Yichie et al 2019) Using the UniProt Gene Ontology tool

(httpswwwuniprotorguniprot) the hits were classified to molecular function (2452 results)

cellular component (2030 results) and biological process (91474 results) For the proteins

belonging to the cellular component category 1925 were membrane parts followed by 993 cell

parts (Fig 4-3) Of all the quantified proteins 10 were categorised as transporters 8 as

signalling proteins and 4 as stress-related proteins

About 6 of all identified protein had at least one transmembrane region (Figure 1B Yichie et al

2019) as determined using TMHMM V20 online tool (httpwwwcbsdtudkservicesTMHMM)

Figure 4-3 Gene ontology classification of all 2030 proteins derived from the Oryza

database and annotated to cellular component functions utilising the UniProt platform

(httpswwwuniprotorguniprot)

433 Statistically significant differentially expressed proteins

In order to assess experimental reproducibility the abundance of the sample replicates (control

and salt) were plotted to evaluate the consistency of the TMT experiment within the biological

replicates For both the O australiensis accessions minor deviations were observed between

replicates with R2 values of 0718 and 0724 for Oa-VR in salt and control respectively and 0685

and 0814 for Oa-D in the respective treatments (Fig 4-4d) All tested genotype and treatment

combinations had similar log ratio distributions which made them suitable for the subsequent

statistical analyses (Fig 4-4d) In addition heatmap analyses and principal component analysis

(PCA) underpinned that biological replicates of each type of treatment were clustered except in

the case of Oa-D under salt treatment where the replicates were somewhat more divergent (Fig

4-4a and 4-4e) For the 1825 proteins present reproducibly in all replicates genotypes and

treatments density plots and box plots were generated to determine the data distribution (Fig 4-

4b and Fig 4-4c) All of the samples showed a reasonable distribution among replicates

Figure 4-4 Summary of the statistical tests performed using the PloGO tool (a) Heatmap of

the abundances of identified proteins among the replicates of the two accessions under the two

respective treatments (b) Density and (c) boxplots of the log ratios of all samples indicating a

consistent pattern and reasonable distribution across the groups (d) Correlations between

replicates of Oa-D without salt application (control treatment) with a correlation of R2 = 0814 for

this specific example above (e) Principal component analysis (PCA) of clusters showing a clear

separation between the replicates of the accessions and the treatments

Comparative quantitative proteomic analysis was used to investigate the protein profiles of both

accessions under salt stress The overall TMT hits resulted in a multivariate overview of the data

which could be represented as four unsupervised cluster patterns (Fig S2 Yichie et al 2019)

While 1132 proteins responded to a similar degree in both genotypes 116 proteins were

significantly up-regulated and 88 proteins were significantly down-regulated in Oa-VR relative to

Oa-D under salt treatment (Table 2 Yichie et al 2019)

434 Functional annotation and pathway analysis

The identified proteins were classified into several biological processes and molecular functions

of interest with the most up-regulated proteins associated with the lsquometabolic processrsquo lsquoprotein

metabolic processrsquo lsquotransportrsquo and lsquotransmembrane transporter activityrsquo categories (Fig 2 Yichie

et al 2019) When all identified proteins from both genotypes were combined more than 10 of

all proteins could be assigned as lsquotransportersrsquo (Fig 2 Yichie et al 2019) These were further

divided into ten subcategories as described (Fig 3 Yichie et al 2019)

Proteins found to be differentially accumulated in the root in only one or both accessions were

further classified based on their main functional role using the KEGG pathway mapper Of the 363

hits for transport proteins quantified oxidative phosphorylation (Fig 4-5a and b) and SNARE

interactions in vacuolar transport (Fig 4-6a and b) were the pathways with the most proteins

affected by salt treatment These proteins were also highly enriched relative to other transport

proteins in terms of protein numbers (Fisher exact test p-value lt10-10)

While in both accessions the same number of V-type ATPase subunits were up-regulated (three)

and down-regulated (five) for the F-type ATPase Oa-VR had five enriched subunits under salt

while Oa-D had four enriched subunits and one subunit (subunit d) down-regulated under salt (Fig

4-5a and b) Moreover eight key subunits of vacuolar-type H+-ATPase were enriched in the

tolerant genotype compared to only five in the sensitive accession Oa-D under salt treatment (Fig

4-6a and b)

The third pathway that was highly enriched within the transporter proteins in KEGG (after oxidative

phosphorylation and SNARE interactions in vacuolar transport) was the phagosome pathway In

the salt-tolerant accession three independent V-type proton ATPases were enriched in this

pathway as well as the Ras-related protein RABF2a However in the salt-sensitive accession

while the three V-type ATPase were enriched the Ras-related protein was not significantly

differentially expressed

Figure 4-5 Oxidative phosphorylation pathways from the KEGG mapper

(httpwwwgenomejp keggmapper) showing up- and down-regulated proteins in (a) Oa-

VR and (b) Oa-D accessions Proteins in red indicate up-regulation while those in blue represent

down-regulation Proteins in green indicate the presence of genes in the reference genome and also the completeness of the pathway while

white boxes represent all enzymes and reactions in the metabolic pathways regardless of the reference genome used

Figure 4-6 SNARE interactions in vacuolar transport pathways from the KEGG mapper (httpwwwgenomejp keggmapper) showing

up- and down-regulated proteins in (a) Oa-VR and (b) Oa-D accessions Proteins in red represent up-regulation while those in blue represent

(b) (a)

435 Most highly enriched salt-responsive proteins

Within the Oryza dataset the highest fold change among all comparisons (section 429) was a

645-fold increase for UniProt A0A0D3H139 in the salt-sensitive genotype Oa-D under salt

treatment vs control This UniProt accession was identified in the O barthii database as an

uncharacterised protein however using the BLAST tool (httpswwwuniprotorgblast) it was

determined to be a homologue of germin-like protein 8-14 (O sativa subsp japonica E-value

26e-148) The second highest fold change of 641 occurred in the same comparison of Oa-D salt

vs Oa-D control for the protein UniProt A0A0E0NZW3 This hit identified in the O rufipogon

database as an uncharacterised protein was determined to be a homologue of Germin-like protein

3-6 (UniProt Q851K1) from the O sativa genome using BLAST

Within the salt times genotype interaction comparison (section 429) the most enriched protein was

a peroxidase (UniProt A2XEA5) that increased 54-fold more in salt-treated Oa-VR than in salt-

treated Oa-D followed by a 413-fold enrichment of an uncharacterised protein with a

transmembrane transporter activity This latter hit (UniProt A0A0D3GSD4) was identified in the

O barthii database as an uncharacterised protein however using the BLAST tool it was

annotated to the monosaccharide transporter gene OsMST6 The third most enriched protein

within the same salt-genotype interaction was identified from O punctata This uncharacterised

protein hit (UniProt A0A0E0K4K2) which was annotated as having aspartic-type endopeptidase

activity showed a fold change of 40 and was determined to be homologous to an aspartyl

protease protein from O sativa using BLAST

44 Discussion

441 Similarities in the genome of O australiensis and other Oryza species

The research reported in this chapter and the accompanying journal article aimed to reveal novel

mechanisms of salt tolerance in rice by identifying proteins that enable a salt-tolerant O

australiensis accession (Oa-VR) to perform better than the relatively salt-sensitive accession (Oa-

D) in up to 100 mM NaCl (Yichie et al 2018) The hypothesis was that salt tolerance in Oa-VR

resides largely in root characteristics and is likely to be regulated by ion exclusion as observed

for O sativa (Mikio et al 1994 Roy et al 2018 Chandra et al 1999) Since the genome of O

australiensis has not yet been fully sequenced and annotated a tailored database comprising

other Oryza species was constructed and used to search for the peptides identified by the TMT-

labelled shotgun proteomics analysis

O australiensis is the only Oryza species with an EE genome (Qihui et al 2007) as described in

Chapter 1 which is known to be considerably larger than the AA genome of O sativa and O

meridionalis and the BB genome of O punctata (Nishikawa et al 2005) Stringent natural

selection as a result of environmental stresses as well as significant historical structural genomic

changes of O australiensis (Piegu et al 2006) have rendered this species a strong candidate for

the discovery of novel stress tolerance mechanisms

With most protein hits matched to O punctata annotations presented in this chapter suggest that

O australiensis may be more closely related to O punctata (BB genome) than the other Oryza

species that contain the AA chromosome set This is consistent with a previous study that showed

that the EE genome (O australiensis) is genetically closer to the BB genome (O punctata) than

the AA genome (such as O sativa and O meridionalis) (Nishikawa et al 2005) and underscores

the strategy of searching among wild germplasm for tolerance genes In addition although O

australiensis is clearly distinguishable morphologically from CC genome species while O punctata

is not both O australiensis and the diploid form of O punctata appear widely divergent in some

chloroplast genomic sections (Dally et al 1990)

442 Membrane-enriched purification protocol

Plasma membrane proteins are critical in cellular control and differentiation and are especially of

interest in signal transduction and osmoregulation mechanisms (Mitra et al 2009) The highly

hydrophobic nature of membrane proteins and the dynamics of those proteins containing multiple

transmembrane domains pose great complexity in assessing the purification efficiency in a given

sample (Masson et al 1995) In previous studies a few methods have been used to evaluate the

effectiveness of membrane-enriched purification For instance membrane-specific enzyme

markers associated with various intracellular membranes have been used to evaluate the

extracted sample purity (Cheng et al 2009) but could not be used to quantify the proportion of

the total extracted proteins that were derived from cell membranes (Cheng et al 2009) These

authors employed immunoblotting using antibodies against the cytoplasmic marker UDP-glucose

pyrophosphorylase (UGPase) and PM marker H1-ATPase but these could only evaluate the

presence of specific PM proteins and therefore were not suitable for discovery studies

Membranes can be isolated using a free-flow electrophoresis procedure to separate cellular

membranes according to their charge (Bardy et al 1998) since some membranes are more

negatively charged than others However this approach may exclude some important membranes

which are not PM and this method also requires a specific free-flow electrophoresis instrument

In this study the differences in size and density between membranes and other cell components

were used to isolate a fraction of enriched membranes (Hodges et al 1986) This protocol

required centrifugation of a microsomal fraction through a continuous density gradient as

described previously (Fukuda et al 2004 Cheng et al 2009) In the present study centrifugation

was carried out three times at 87000 times g for 35 min to ensure a good separation between

membranes and soluble proteins

The membrane-enriched fraction was evaluated by parallel sequence searches against reference

databases using Mercator and by predicting the number of transmembrane helices in the

extracted root proteins using the TMHMM transmembrane (TM) platform

(httpwwwcbsdtudkservicesTMHMM) In the first approach the Mercator tool provided

evidence that membrane proteins were enriched with about 10 of the extracted proteins (363

unique proteins) categorised as participating in transport A previous study in pea with a similar

protocol to create a microsomal-enriched fraction resulted in an estimate of around 5

transporters (Meisrimler et al 2017) while another study found that 7 of total proteins extracted

from rice roots were transport proteins (Huang et al 2017) In the second approach the TM

platform was used to determine that around 40 of the enriched samples had at least one

membrane-spanning region similar to the 35 found in Arabidopsis (Chiou et al 2013) and the

20 found in pea (Meisrimler et al 2017) The findings reported here showcase that although

there exist several complexities and limitations in the membrane-enriched purification protocols

the preparation of the microsomal fraction here was successful in terms of membrane protein

enrichment

443 Assessment of the assembled databases for protein discovery

Every comparative proteomics study requires a reference proteome to search against the

identified hits However genomic resources of O australiensis species are very limited and the

full sequence is yet to be published Today de novo protein sequencing is available using

computer programs that have been developed to meet the need for higher throughput However

although this is a powerful tool for species lacking reference sequence databases de novo

sequencing can usually only determine partially correct sequence tags as a result of imperfect

tandem mass spectra (Ma et al 2012) Other limitations in this technique include low resolution

low sensitivity and partial coverage in peptide detection (Frank et al 2005) An alternate strategy

using the de novo assembly of the transcriptome from RNA-Seq data has also been followed

(Brinkman et al 2015) for other Oryza species however this RNA-seq data was not available for

O australiensis

Given the limitations of de novo sequencing here several existing datasets of closely related

organisms were combined and used as a database for identifying peptides from mass

spectrometry data using a stringent protein quality threshold The first database comprised of

combined Oryza genus proteins with hits likely to match other Oryza species Two other

databases were constructed with the aim of looking at other known species with variable degrees

of salinity tolerance characteristics (lsquoSalt-tolerant speciesrsquo database) and other grass species

(lsquoGrasses databasersquo) respectively A database for the proteome of the species A thaliana was

used as well since this model plant is widely used to map characterise and dissect genetic

variation for salinity tolerance (Derose-Wilson et al 2011)

From the results of the analyses done here using the same database search parameters the

Oryza database comprising eight Oryza species (with AA and BB chromosomes sets) resulted in

the highest number of annotated proteins (Table 4-1) The use of the non-Oryza databases served

as an attractive option to identify novel peptides not found before in rice and have led to a lower

number of annotated hits as expected In addition when combining all of the different databases

of the fifty highest fold-changes for Oa-VR salt vs Oa-D salt only two were annotated to non-

Oryza species This and the low number of annotated hits to the Arabidopsis database led to a

focus on the Oryza database for further analysis of data quality and protein abundance

444 Proteins most responsive to salt

A total of 268 identified proteins significantly increased in abundance by at least 15-fold across

the four treatmentgenotypic comparisons The highest fold change as a result of salt treatment

was a 64-fold increase for a homologue of a germin-like protein This finding is consistent with

the reported up-regulation of germin-like proteins in wheat seedlings (root and leaves) (Hena et

al 2012) barley roots (Hurkman et al 1997) pea (Wisniewski et al 2007) and oat (Bai et al

2017) leaves under salt treatment A few other DEPs had a significant response to salt within each

of the genotypes when comparing salt vs control For example the protein homologous to UniProt

A0A0E0GUU4 was enriched 6-fold in Oa-VR in salt-treated plants compared to Oa-VR control

This uncharacterised protein from O nivara was annotated as a homologue to cupincin (UniProt

B8AL97) in O sativa using BLAST This protein is located in the extracellular matrix and

regulates seed storage by acting as a zinc metalloprotease and is associated with stress

response in O sativa (Sreedhar et al 2016)

Within the sensitive genotype Oa-D the highest fold-change was recorded for the starch synthase

protein (UniProt A0A0D3GCE6) which was ten times more abundant in the salt-treated plants

than the controls although this protein was not found in any of the Oa-VR samples This finding

contradicts a previous study in which rice seedling roots under salinity had decreased starch

accumulation (Dubey et al 1999) This decline in starch accumulation is associated with

increased accumulation of sugars in many plant species exposed to salinity (Flowers 1977) either

because of increased energy-dependent processes or for osmotic adjustments It is believed that

the accumulation of sugars along with other compatible solutes under salinity stress contributes

to plant homeostasis by allowing the plant to maximise sufficient storage reserves to support basal

metabolism under stressed conditions (Hurry et al 1995) This finding might provide a clue to the

mechanism behind the salinity stress response of the Oa-D accession

The most strongly differentially expressed protein between genotypes was a peroxidase that

increased 54-fold in Oa-VR than in Oa-D This was calculated using the formula ([Oa-VR salt vs

Oa-VR control] [Oa-D salt vs Oa-D control]) Peroxidase activity is essential in providing

protection against ROS generated during salt stress A previous study of O sativa seedlings

reported an increase in peroxidase activity in shoots after plants were grown in a salt solution of

12 dS m-1 which equates to about 110 mM NaCl (Meloni et al 2003) Similarly increased

abundance of a homologous peroxidase was observed after exposing cotton seedlings to 200 mM

NaCl for 21 d (Mulkidjanian et al 2008)

The second highest fold-change within this comparison was 413 for the protein UniProt

A0A0D3GSD4 and was annotated using BLAST as the protein product of the monosaccharide

transporter (MST) gene OsMST6 This gene is a member of the MST gene family whose protein

products are known to mediate transport of a variety of monosaccharides across membrane

barriers (Sperotto et al 2009) The MST family has been reported to confer hypersensitivity to

salt in Arabidopsis (Wormit et al 2006 Bu 2007) and rice (Cao et al 2011) Under abiotic stress

environments soluble sugars (derived from starch breakdown) accumulate in some plants in order

to increase stress tolerance (Yamada et al 2010) Following this process sugar transporters play

key roles in carbohydrate reallocation to both subcellular and long-distance levels via the phloem

(Lalonde et al 2004) The enriched starch synthase protein discussed above coupled with the

sugar transport up-regulation reveal a complex but effective mechanism to address salt stress in

O australiensis

445 Up-regulation of protein clusters involved in energy metabolism vesicle trafficking

and membrane phagosomes under salt stress

The Mercator tool (Lohse et al 2014) was utilised to annotate the classified O australiensis

protein sequences into BINs and sub-BINs with non-redundant functional and for the generation

of a lsquomappingrsquo file to be then used in MapMan (Thimm et al 2004 Usadel et al 2005) This

allowed for the identification of biological processes that responded most strongly to the induced

salt stress The proteins found in these four bins represented more than 60 of the total proteins

identified

To visualise the distribution of differentially expressed foreground proteins according to the

Mercator mapping output file the KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway

mapper was used (Kanehisa et al 2000) The O australiensis identifiers were BLASTed to match

O sativa UniProt accessions and then these accessions were used for KEGG analysis A total of

3355 protein sequences were mapped to 118 KEGG pathways The identifiers that were

categorised as transporters in UniProt were then further analysed Within the identified

transporters the most enriched KEGG pathways were lsquometabolic processrsquo lsquooxidative

phosphorylationrsquo lsquoSNARE interactions in vacuolar transportrsquo and lsquophagosome pathwaysrsquo

Metabolic process

Both V-type and F-type ATPase subunits were differentially expressed under salt stress in salt-

tolerant and -sensitive accessions V-ATPase and F-ATP synthases are highly related enzymes

involved in energy transduction (Mulkidjanian et al 2008) The subunits of both these ATPase

complexes are reversible and can act as proton (or Na+)-pumping complexes (Dimroth 1997) In

addition they transform potential energy from a gradient of ions across the membrane to

synthesise ATP (Ruppert et al 1999) Conversely the free energy of ATP hydrolysis can generate

an ion-motive force In this study it was revealed that some ATPase subunits were up-regulated

while others decreased in abundance within the same genotype under salt stress This finding

corresponds to a previous study that showed the activity of some ATPase subunits of M

crystallinum leaves decreased while others increased in abundance under salinity stress (Low et

al 2002) in contrast to other patterns for the subunits in roots In addition a similar modulation

of activity by subunit composition alteration of enzyme complexes was found in tobacco (Reuveni

et al 1990) The finding in the present study also pinpoints a similar non-coordinated regulation

of expression of V-ATPase and F-ATPase subunits in response to salt

SNARE interactions in vacuolar transport

Among the 363 proteins identified as transporters KEGG pathway analysis identified 13 SNARE

interaction proteins in the vacuolar transport pathway which was one of the pathways most

affected by salt treatment The Soluble N-ethylmaleimide-Sensitive Factor Attachment protein

Receptors (SNAREs) as well as other trafficking regulators have been explored before in the

context of salt stress (Leshem et al 2006) In the present study the syntaxin-related KNOLLE-

like protein was significantly up-regulated under salt conditions in the tolerant line Oa-VR and

down-regulated in the sensitive line Oa-D These SNARE family proteins are generally involved

in stress-related signalling pathways in plants (Si et al 2009) and have a critical role in osmotic

stress regulation in Arabidopsis (Leshem et al 2006) A mutation in the TGN-localized t-SNAREndash

SYP61 gene in Arabidopsis causes mislocalisation of SYP61 and confers salt and osmolyte

sensitivity (Oa et al 2011) In tobacco the syntaxin-related protein Nt-Syr1 was shown to have a

crucial role in stress-related signalling pathways both dependent on and independent of ABA

(Leyman et al 2000) Similar findings by Sun et al showed a rapid increased expression of the

R-SNARE family gene in wild soybean Glycine soja exposed to salt using quantitative RT-PCR

and β-glucuronidase activity assays (Sun et al 2013) This new evidence from rice suggests that

they play this role in monocotyledonous species as well as in the dicotyledons listed above Micro-

analysis of intracellular ion distribution in the root cells of transformed rice plants with altered

activity of individual SNARE genes would assist in further linking the salt-tolerance phenotype with

this gene family

The SNARE component syntaxin-121 which drives vesicle fusion (Pant et al 2014) was also

significantly up-regulated in the tolerant genotype Oa-VR and down-regulated in Oa-D Syntaxin

is a component of the SNARE complex located at the target membrane which enables recognition

and fusion of the desired vesicle with the transmembrane (Bennett et al 1992) The Arabidopsis

syntaxin mutant osm1syp61 showed stomatal closure and significantly increased sensitivity to

salinity (Zhu et al 2002) In addition an 8-h treatment of Populus euphratica seedlings with 300

NaCl resulted in the up-regulation of transcripts of syntaxin-line protein (Gu et al 2004) This

study thus suggests a novel mechanism of some snare proteins similar to the ones mentioned

above for the salinity stress regulation in rice wild relatives

45 Conclusion

The aim of the research reported in this chapter was to identify and analyse biochemical pathways

involved in the salinity stress responses in two contrasting wild rice accessions from the Australian

savannah A TMT-labelled proteomics approach was employed to investigate differential protein

abundance patterns and corresponding pathways in response to induced salt stress Despite the

lack of an annotated genome sequence database for the O australiensis species the use of

several bioinformatic tools allowed differences between the two constraining accessions and their

most enriched pathways under salt stress to be revealed

Specific pathways and proteins related to salinity were identified in the salt-tolerant accession Oa-

VR compared to the salt-sensitive accession Oa-D The quantitative proteomics approach taken

provided molecular evidence for exclusive expression of salt-response proteins in the salt-tolerant

accession such as sugar transporters and SNAREs It can be concluded that an increased

abundance of the OsMST6 homologue protein as well as syntaxin 121 in O australiensis is

correlated with increased salinity tolerance in the tested rice relatives

In summary the proteomics analysis conducted allowed a detailed comparison of protein

abundances between two contrasting rice cultivars exposed to salinity The resulting proteome

profiles may provide key proteinspatways that contribute to salt stress tolerance and may serve

as the basis for improving salinity tolerance in rice and other important crops

Chapter 5 Validation of salt-responsive genes

Validation of candidate salt-responsive genes through yeast deletion strains and

quantitative reverse transcription polymerase chain reaction

51 Introduction

511 Proteomics as a powerful tool but with limitations

Although proteomics approaches have been widely used in biology research since the 1990s

variations between biological samples detection limits and unforeseen experimental and

computational challenges can sometimes be the cause of highly inaccurate estimations of

differences in specific proteinpeptide abundance between samples (Aebersold et al 2016)

Quantitative shotgun proteomic experiments based on spectral abundances aim to compile a set

of reliable protein identifications covering the proteome as broadly as possible as well as

assessment of the validity of these identifications by applying statistical restrictions such as protein

false discovery rate (FDR) estimations and p value thresholds False-positive peptide spectrum

matches occur when the highly scored candidate is not the source of the corresponding ion

spectrum Such errors can lead to incorrect conclusions concerning the involvement of specific

proteins in the biological process being studied False readings at the peptide and protein levels

can be difficult to control (Aggarwal et al 2016) and their minimisation requires various

experimental and statistic approaches including FDR targetndashdecoy strategy (Savitski et al 2015)

Mass spectrometric analysis by TMT quantitative proteomics has been routinely employed over

the last two decades (Thompson et al 2003) for large-scale protein identifications from complex

biological mixtures and has evolved to become less descriptive and more quantitative (Neilson et

al 2011) However even contemporary quantitative proteomics using TMT labelling produces

results that should normally be validated using complementary experimental approaches as

described below

512 Validation of proteomics studies

The integral uncertainty of mass spectrometric output and statistical validation of protein

identifications are complex tasks subject to ongoing analytical approaches and debate The

proteomics field has gradually changed so that now quantitative proteomics data can in some

cases be credible without transcriptomic validation such as RT-qPCR (or Northern blotting prior to

RT-PCR) Many projects involve the application of both proteomics and one or more verification

techniques including RNA sequencing (Wang et al 2014) multiple reaction monitoring (Picotti et

al 2015) and the testing of other model species (Fukuda et al 2004)

In addition to the above the study of species with no available nucleotide or protein sequences

rely on reference genomes and cannot be validated without testing the identified proteins in other

biological systems or with additional molecular biology tools On this basis the results for key

proteins in Chapter 4 were subjected to validation in order to establish their potential role in the

salinity tolerance of the wild Australian rice accessions with more confidence

In this chapter I present two independent techniques to address the high sensitivity of proteomics

data and to verify the results presented in Chapter 4 Firstly I employed quantitative reverse

transcription PCR to test the transcriptional activity of the relevant genes Secondly I tested the

phenotype of yeast (Saccharomyces cerevisiae) mutants with deletions of the closest homologues

to the identified rice proteins under high-salt regimes

Thus the experiments described in this chapter were performed with the aim of supporting the

results described in Chapter 4 through two independent approaches

i Quantitative reverse-transcription PCR of target genes

ii Yeast deletion strains to validate the growth phenotype under salt stress

521 Quantitative reverse-transcription PCR (RT-qPCR)

RNA extraction from root tissue

Roots of both Oa-VR and Oa-D growing under 80 mM NaCl and control conditions from the same

plants used for the proteomics experiments (section 421) were used for RNA extraction Roots

were harvested and immediately placed in liquid nitrogen before being stored at -80˚C Three

biological replicates were collected per genotype and treatment giving a total of 12 samples Total

RNA was extracted using the Sigma-Aldrich Spectrumtrade Total RNA Kit (Sigma-Aldrich St Louis

MO USA) using Protocol A with a 6-min incubation at 56˚C for the tissue lysis

Reverse transcriptase and cDNA synthesis

Primer design and screening assay with complementary DNA (cDNA)

Target genes corresponding to each of seven proteins that showed differential levels of protein

expression were chosen and identified in the O sativa genome using the UniProt BLAST tool

These genes were used to design primers for RT-qPCR based on guidelines prescribed previously

(Udvardi et al 2008) The design criteria were amplicon size of 200 base pairs (bp) or smaller

spanning of intronic regions where possible in order to reduce or identify DNA amplification

(through size differentiation) design for gene specificity incorporating 3rsquo untranslated regions

(3rsquoUTR) The Premier3 (v040) platform (httpbioinfouteeprimer3-040) was used to design

primers for the selected genes Three sets of forward and reverse primers derived from these

genes were designed and individually run through BLAST in Phytozome for target specificity and

then checked in an oligo analysis tool for sequence complementarity

(httpswwweurofinsgenomicseu) Primers for genes of interest as well as reference genes (Jain

et al 2006) were synthesised by Integrated DNA Technologies (Australia) A list of all designed

primers and their corresponding genes is given in Table 5-1

A PCR assay was used to test primers (04 μL of each primer at 10 μM stock concentration

forward and reverse) on cDNA using the BioLine SensiFASTTM SYBR No-ROX Kit PCR negatives

(no template DNA) were included to indicate potential genomic contamination Thermocycle

conditions for PCR amplification were 20 μL reactions in a 96-well plate utilising three-step

cycling initial denaturation for one cycle of 95˚C for 2 min then 40 cycles of denaturation at 95˚C

for 5 s annealing at 60ndash64˚C (depending on the primer) for 10 s and extension at 72˚C for 20 s

A Bio Rad T100TM Thermal Cycler (Australia) was used with temperature gradient across the 96-

well plate

Table 5-1 Primer names and locations UniProt accessions O sativa gene name and expected amplicon size for RT-qPCR Three sets of primers

were designed and tested per gene of interest The experiment was conducted using O australiensis root RNA Primer labels highlighted in yellow

successfully amplified PCR products of the expected size in one PCR test while those in green were confirmed in more than one PCR test Upper line

represents the forward and lower line the primer sequences Location of the forward and reverse primers on the same (S) or different (D) exon(s)

Primer label Uniprot Accession Uniprot description Oryza sativa gene product Oryza sativa description Primer sequence Amplicon length (bp) Primers locationACCACTTCGACCGCCACTACT 69 S

ACGCCTAAGCCTGCTGGTTeEF-1a TTTCACTCTTGGTGTGAAGCAGAT 103 D

GACTTCCTTCACGATTTCATCGTAACTACGTCCCTGCCCTTTGTACA 65 SACACTTCACCGGACCATTCAAATCGAAGTTTGCCGAGCTGA 71 DAGACCTATCCCCCATGCTGTAGACTTGCATGTTGCTCGGA 139 DAATGACAGGCTTACGGCCAAAAGTTCTTGCAGTGGCAGGT 101 DTGAAATGCGGGTTGAGTGGAATCGGTGTGGATGGACAGGA 200 DTTTGGGACTCCAGCCTCGTA

CATCGGTGTGGATGGACAGG 127 DATAGACTGGGCCATGGGTTCACCCAAGAAGCTGTTAGGCG 162 STTGATCTGCTCAGAGGAGCCGTTTAGCGACGACGTTCTGC 71 DGCCTCTCGAACACCTTCTCCTTCTCCAACAACCACGGCAA 123 DGTAGTTCGGCGCAATCATCGCGTTTAGCGACGACGTTCTG 190 DCTGGACGGCTTGATTTCCCATGGTGGTGAACAACGGAGG 170 DCACCGACGGGAAGAACTTGAGCGCAAGTGGTCCATGTTC 198 D

AACCCGATGTTGAGCATCCCAACGTGCTCATGCTCATCCT 145 DTGGTGATCATCAGCTGGAACCACTGCAACGTTCTTCGCTG 90 D

ATGGCAGCATGGGACAAGAAGGTTATGCGAAGCTTGCTGG 76 DTCGCGTATATCAAAGGCGGTAGACAAGCATGGTGTCGTGA 175 DCAGGCCAGCGAATGTTCTTCGGTGCACTTTGCTCGTTCTC 127 S

AGGAGGTTGTTCTCGTAGGCGCACTTTGCTCGTTCTCCTC 129 S

GGTTCAGGAGGTTGTTCTCGTAGATCCTCTTCTCCACGGGC 170 SGTTGTAGACGAGGGCGACGCTCCATGAACTCCGTCCTCC 96 DATCTGCGTGTCGGTGATCTTCTCTCCTCGCCTCCATGAAC 150 D

AGCCGAACAGCGAGTAGATGCCGTCCTCCTCGGCTATGAT 94 DAGGATCTCGATCTGCGTGTC

DUF26-like protein (kinase activity) Os04g56430 cysteine-rich receptor-like protein kinase

A0A0D3FF02 Mannitol transporter Os03g10090 transporter family protein

Sugar transport protein MST6 Os07g37320 transporter family protein

A0A0E0KA10 Putative sulphate transporter Os03g09970 sulfate transporter

Salt stress-induced protein Os01g24710 jacalin-like lectin domain containing protein

A0A0E0GUU4 Cupincin Os03g57960 cupin domain containing protein

18S ribosomal RNA Os09g00999 18S ribosomal RNA

A0A0E0MJB0 Major facilitator superfamily antiporter Os12g03860 major facilitator superfamily antiporter

Ubiquitin 5 Os01g0328400 Ubiquitin 5

AK061464 Eukaryotic elongation factor 1-alpha Os03g08010 Eukaryotic elongation factor 1-alpha

Os04g56430_2

Os04g56430_3

Os03g10090_1

Os03g10090_2

Os03g10090_3

AK061988

AK059783

A0A0E0JI75

A0A0D3GSD4

A0A0E0KW83

Os07g37320_2

Os07g37320_3

Os03g09970_1

Os03g09970_2

Os03g09970_3

Os04g56430_1

Os01g24710_2

Os01g24710_3

Os03g57960_1

Os03g57960_2

Os03g57960_3

Os07g37320_1

18S rRNA

Os12g03860_1

Os12g03860_2

Os12g03860_3

Os01g24710_1

Gel electrophoresis of PCR assay amplicons and purified amplicons

Amplified gene products from the PCR trial were visualised using 2 agarose gel

electrophoresis (with 15 μL GelRed) PCR product (6 μL) was loaded with 7 μL water and 2

μL loading dye Gels were run at 90 V for 35ndash45 min before visualising with a UV gel

ChemiDoctrade Imaging System with ImageLab v60 software (Bio Rad Australia)

Quantitative reverse-transcriptase PCR (RT-qPCR)

Following primer screening assays the housekeeping gene eEF-1a and the primer sets

Os12g03860_2 Os01g24710_1 Os03g57960_2 Os07g37320_1 which were successfully

confirmed were utilised for the RT-qPCR assay using the BioLine SensiFASTTM SYBR No-

ROX Kit according to the manufacturerrsquos instructions These genes were initially chosen from

the quantitative proteomics results because their corresponding proteins were significantly

differentially expressed between the salt-treated and control samples (Table 5-2) Each primer

pair was run on separate plates with the individual samples one sample per row using 96-

well (20 μL) white plates Serial dilutions of cDNA (neat 1 in 5 1 in 25 and 1 in 125) were

loaded in triplicate (2 μL cDNA per 20 μL sample volume) PCR thermocycle conditions were

as per the primer assay (annealing temperatures for each primer pair were eEF-1a 580˚C

Os12g03860_2 570˚C Os01g24710_1 581˚C Os03g57960_2 570˚C Os07g37320_1

573˚C) A 20-min melt curve analysis was run with a temperature range of 60ndash95˚C at 30 s

per 1-degree increment Following the melt curve analysis the samples were held at 4˚C

Table 5-2 Summary of all genes analysed in the RT-qPCR experiment and their

respective protein abundances (as determined in Chapter 4)

Oryza sativa gene Uniprot accession Protein abundanceOs12g03860 A0A0E0MJB0 Salt response = 280Os01g24710 A0A0E0JI75 Oa -D_saltOa -D_control = 318 Os03g57960 A0A0E0GUU4 Oa -VR_saltOa -VR_control = 601Os07g37320 A0A0D3GSD4 Salt response = 413

Analysis of qPCR results

For each tested gene relative expression in salt-treated plants in relation to control plants was

calculated with calibration to reference gene eEF-1a using an efficiency-corrected calculation

based on multiple models according to the equation as described before (Pfaffl 2001)

119905119905119904119904119904119904119882119882119888119888 =(119864119864119905119905119905119905119905119905119905119905119905119905119905119905)∆119862119862119901119901 119905119905119905119905119905119905119905119905119905119905119905119905

119872119872119872119872119872119872119872119872 119888119888119888119888119888119888119905119905119905119905119888119888119888119888minus119872119872119872119872119872119872119872119872 119904119904119905119905119904119904119901119901119888119888119905119905

(119864119864119905119905119905119905119903119903119905119905119905119905119905119905119903119903119903119903119905119905)∆119862119862119901119901 119905119905119905119905119903119903119905119905119905119905119905119905119888119888119888119888119905119905119872119872119872119872119872119872119872119872 119888119888119888119888119888119888119905119905119905119905119888119888119888119888minus119872119872119872119872119872119872119872119872 119904119904119905119905119904119904119901119901119888119888119905119905

where E is efficiency of amplification and ΔCt is the change in threshold cycles of amplification

The efficiency of amplification is taken from one cycle in the exponential phase with an

average efficiency range from 16 to 2 (ie ~ doubling of gene product in each cycle) Linear

regression slopes of mean Ct values were utilised against the logarithmic value of cDNA

concentrations using the equation below to calculate the efficiencies (Pfaffl 2001) For each

regression calculation a minimum of three data points was used for regression equations

119864119864 = 10( minus1119904119904119904119904119904119904119904119904119905119905)

Salt-treated samples were assessed using the ratio equation against each of the controls to

give a mean expression ratio change for each gene of interest

522 Validation of salt growth phenotypes using a yeast deletion library

Yeast strains and culture conditions

A yeast deletion library (Giaever et al 2014) was employed to determine the salt-response

growth phenotype resulting from deletion of specific key salt-responsive proteins as identified

in our rice quantitative proteomics experiment This collection comprises more than 21000

mutant strains that carry precise start-to-stop deletions of every one of the sim6000 open reading

frames present in the yeast genome Protein sequences were BLASTed against the yeast

genome using the Saccharomyces Genome Database (SGD) to identify the closest yeast gene

homologue to be tested from the deletion yeast library Eleven deletion strains (Table 5-3) and

the parental strain BY4742 (MATa his3D1 leu2D0 lys2D0 ura3D0 WT) were interrogated to

validate protein hits from the rice TMT-labelling proteomics experiment

(compared to wildtype) in colony growth under salinity Proteins sequences from UniProt

accessions were blasted against the yeast sequence and homologous genes were chosen

from the yeast deletion library

Experimental design

Strains were defrosted and grown on a YPD culture at 30degC for 48 h A few colonies were

picked using a pipette tip suspended in 20 mL YPD solution in a microcentrifuge tube and

grown overnight at 30degC with shaking A 200-microL sample of each the overnight culture was

diluted into a new 20-mL YPD solution and incubated at 30degC for 4ndash5 h to a cell density of

OD600 05ndash07 (OD600 06 = ~2 times 107 cellsmL) to ensure cells were at log phase The

cultures were then serially diluted 10-fold and spotted onto YPD (containing 1 yeast extract

2 peptone 2 D-glucose) and YPG (1 yeast extract 2 peptone 2 glycerol) media with

three different salt concentrations of 300 700 and 1000 mM NaCl in addition to a lsquono-saltrsquo

control YPD and YPG plates with the tested strains were incubated in 30degC as well as in heat

stress conditions at 37degC Plates were imaged on a daily basis for 5 d from 48 h after spotting

the cultures Two consecutive rounds of screenings were made to verify the phenotypes

observed

523 Protein sequence alignment Since this part of the chapter describes the validation of O sativa genes full-length protein

sequences found in the quantitative proteomics experiment (Chapter 4) were aligned to O

sativa homologues with ClustalW (Thompson 1994) This was done using BioEdit Sequence

Alignment Editor software (Hall 1999) with default parameters within Mega6 (Tamura et al

53 Results

While no phenotypic differences were seen between the wild rice accessions Oa-D and Oa-

VR under lsquono saltrsquo control conditions a clear separation between the accessions became

apparent after exposure of the plants to 80thinspmM NaCl for 7 d consistent with our previous

screening (Yichie et al 2018) and as described in section 431

532 RNA extraction

Nucleic acid extracted using Sigma-Aldrich Spectrumtrade Total RNA Kit was used and yielded

sufficient quantities of total RNA for further analyses RNA of each sample was quantified via

the Qubittrade RNA BR (ThermoFisher Scientific Australia) assay which gave an RNA

concentrations of 50ndash350 ngμL

533 Alignment and phylogenetic analysis

Sequences alignments were performed to compare the O sativa MST6 protein (UniProt

Q6Z401) with the original protein accession derived from O barthii found in the mass

spectrometry search (UniProt A0A0D3GSD4) using ClustalW in BioEdit (Fig 5-1) The

alignment shows a very high level of identitysimilarity between the wild relative protein and a

homologue from O sativa strongly suggesting that these proteins have similar roles in the

plant although the amino acid residues that are different might be key to the phenotypic

variation in responses to salt

expressed proteins in the O australiensis accessions UniProt Q6Z401 (O sativa MST6

protein) and UniProt A0A0D3GSD4 (O barthii homologue) using ClustalW in BioEdit Grey-

shaded amino acids are similar and black-shaded amino acids are identical

534 Primer screening assay and amplicon gel electrophoresis

Table 5-1 provides the gene name gene description accession number primer sequences

with their position an indication if primers span introns and the amplicon length A primer

screening assay was conducted to check for amplicons of the expected sizes for each target

and house-keeping gene The primers of genes Os04g56430 and Os03g10090 gave more

than one band or no bands indicating low primer specificity or poor annealing respectively

and hence were excluded from the RT-PCR experiment after testing them at different

temperatures The primers Os12g03860_2 Os01g24710_1 Os01g24710_2 Os01g24710_3

Os03g57960_2 Os07g37320_1 and Os03g09970_2 produced the expected amplicon sizes

as shown in Table 5-1 For the primers that span an intron no genomic DNA (gDNA)

contamination was found (no high-molecular-weight bands were observed) The RT and PCR

negative controls produced no amplicons

Only genes that were successfully confirmed in more than one gel electrophoresis run were

chosen for the RT-PCR experiment Therefore the genes I focussed on were the eEF-1a

house-keeping gene and the four following genes Os12g03860_2 Os01g24710_1

Os03g57960_2 Os07g37320_1

535 RT-qPCR

Real-time PCRs were executed in triplicate for each of the cDNA pools along with a no-

template control for each of the tested gene The melting-curve analysis achieved by the PCR

machine after 40 cycles of amplification and agarose gel electrophoresis (section 533)

showed that all the tested primer sets amplified only a single PCR product of the expected size

from numerous cDNA pools The mean Ct value (average of three biological replicate values)

in a sample for each gene was used to measure the expression stability Although both

Ubiquitin 5 and Eukaryotic elongation factor 1-alpha house-keeping genes were validated in

the gel electrophoresis I chose to use the expression of eEF-1a as a reference gene in this

experiment since it was the most stable and reliable gene for normalization of this real-time

PCR data

The relative quantitative expression of each examined gene within samples was assessed

using Eukaryotic elongation factor 1-alpha (eEF-1a) as the reference gene for calibration

Expression for each of the four genes of interest in salt-treated plants was compared against

controls (no salt) in both Oa-VR and Oa-D The mean neat (undiluted) Ct values for the

reference gene (eEF-1a) for each sample indicated consistent expression across all samples

(Fig 5-2) This in addition to high R-squared values for eEF-1a across samples (Fig 5-3)

made it a stable reference gene for this system Notably a much higher mean Ct value was

found in Oa-VR control vs Oa-VR under salt for almost all genes tested (Fig 5-2)

Figure 5-2 RT-qPCR mean Ct values (with standard errors) for each of the tested genes

for the two O australiensis accessions under 80 mM salt and control conditions Each

mean Ct was derived from three biological replicates Eukaryotic elongation factor 1-alpha

(eEF-1a) was used as the reference gene for each comparison of transcript abundance

n Ct Oa-VR-Salt

Oa-VR-Control

Oa-D-Salt

Oa-D-Control

Figure 5-3 Linear regression of mean neat Ct values vs log10 of RNA template dilutions (starting quantity = 100 ng) for reference gene eEF-1a

across all four genotypesalt treatment samples (a) Oa-VR Control (b) Oa-VR Salt (c) Oa-D Control and (d) Oa-D Salt The high R-squared values

obtained indicate that this gene has a stable expression across samples and could be used as a reference gene in this study

y = -33092x + 26706Rsup2 = 09958

-05 0 05 1 15 2 25

(b)y = -32977x + 29832

Rsup2 = 09761

-05 0 05 1 15

y = -14951x + 24715Rsup2 = 09945

-05 0 05 1 15 2 25

y = -37155x + 28713Rsup2 = 0997

-05 0 05 1 15 2 25

Log10 of RNA template dilutions

Response to salt was measured as a ratio of expression between salt-treated plants and

controls (no added salt) using eEF-1a for calibration For Os01g24710 expression was low

and not responsive to salt for either accession For Os03g57960 the ∆Ct was 13 in the tolerant

accession Oa-VR corresponding to the proteomics results however relative expression was

low due to poor consistency between samples In contrast Os07g37320 and Os12g03860 in

Oa-VR were up-regulated 64- and 142-fold respectively Moreover in Oa-D the expression

of these two genes was suppressed under the same salt treatment compared to the controls

(Fig 5-2)

536 Validation of candidate salt-responsive genes using a yeast deletion library

First salt screening assay

The first salt screening experiment in yeast evaluated eleven strains based on deletion of

respective homologue genes with a putative connection to salt tolerance These strains were

chosen as they contained a deletion in a gene homologous to a protein that showed change

in abundance under salt treatment (Chapter 4) Screening was performed in YPD and YPG

media at 30degC and 37degC Salt treatments of 300 700 and 1000 mM NaCl and a no-salt

treatment (lsquocontrolrsquo) were applied in the YPD medium with a 300 mM NaCl and control in the

YPG medium to test phenotypic difference between the various deletion strains and the

parental wild type BY4742 The strains were grown for 5 d and daily images were taken from

the second day 48 h after inoculating the yeast strains on the different media

Strains did not grow on glycerol as a source of energy (YPG medium) in either lsquono saltrsquo or 300

mM NaCl under 37degC (Fig 5-4) Under 30degC slow growth was detected under control

conditions after 48 h and under 300 mM NaCl after 96 h (day 4) (Fig 5-4) Because strains did

no grow on the higher salt concentration using the YPG medium I focused on YPD to compare

the growth phenotypes of the strains under the different salt treatments For YPD medium 3

d after inoculating the strains (72 h) the phenotypes were found to be the most informative

and easiest to distinguish between strains and growth inhibitions by the salt (Appendix Figure

5-1) On YPD medium colony growth was observed for all strains except YOR332W YFL054C

and YOR036W in both tested temperatures (Fig 5-5) All other strains grew with multiple

colonies under control conditions Growth inhibition was increasingly clear in 300 700 and

1000 mM NaCl for all strains at both 30degC and 37degC (Fig 5-5) While the same colony growth

was observed in both experimental temperatures under the control and lowest salt treatments

a slightly higher level of growth was recorded under 10 M NaCl in 30degC compared to 37degC

(Fig 5-5) Two days after inoculating the strains (48 h) differential growth was visible for some

strains while six strains exhibited the same growth rate and approximately the same number

of colonies as the wild type BY4742 two of the tested yeast deletion strains were more

susceptible to salt treatment compared with WT BY4742 (Fig 5-5) and were chosen for

additional screening

Figure 5-4 Colony growth of wild type BY4742 yeast and the eleven tested strains Cells

at log phase were diluted in a 10 times series (vertical array of four colonies in each panel) and

spotted onto YPG medium with three different NaCl concentrations (in this figure only 300 mM

is presented) and no salt control The plates were incubated at 30degC and 37degC for 5 d Images

were taken on a daily basis from 48 h after inoculating the strains

Figure 5-5 Colony growth of all tested yeast knockout strains and wild type BY4742 after

72 h in YPD medium with three different NaCl concentrations and no salt control Plates

were incubated in 30degC and 37degC for 5 d Three strains (YOR332W YFL054C and YOR360W)

did not grow at all indicating that their specific gene deletions were lethal

Second salt screening assay

A second salt screening assay was conducted to validate the phenotypes observed in the first

screening I focused on the two strains that showed growth inhibition in the first screening and

tested them under the same YPD medium at both 30degC and 37degC for 5 d The strains were

taken from the same source as per the first screening and all other experimental details were

unchanged to ensure the yeast strains were subjected to the same conditions As in the first

experiment YPD medium was found to be more informative specifically at 30degC The same

inhibition of growth was recorded for both strains compared to the wild type however inhibition

was more pronounced for the YLR268 than YLR081W when compared with the WT control

(Fig 5-6 Yichie et al 2019)

YLR268W which have deletions in a gene homologue to the rice OsMST6 gene and a V-

SNARE gene respectively Cells at log phase were diluted in a 10 times series (vertical array of

four colonies in each panel) and spotted onto YPD medium with three different NaCl

concentrations and no salt control Colonies were photographed after 3 d of growth at 30degC

54 Discussion

541 RT-qPCR

This chapter describes the validation of salt-responsive proteins identified in Chapter 4 Using

RT-qPCR I determined the expression profiles of four genes of interest Inconsistency

between the biological replicates resulted in low relative expression levels for Os03g57960

resulted from high efficiency values calculated according to Pfaffl et al models (Pfaffl 2001)

Additionally RT-qPCR analysis of Oa01g24710 resulted in more than one melting curve

indicating multiple products being formed Hence out of the set of four genes two were

suitable for RT-qPCR assays and are discussed here The relative expression of each gene

of interest following salt treatment was measured for both accessions using RT-qPCR with

calculations of amplification efficiency from serial dilutions of a reference gene and the gene

of interest (Pfaffl 2001)

The gene homologous to that encoding O barthii protein (UniProt A0A0D3GSD4) found in

Chapter 4 (saltndashgenotype interaction value 413) Os07g37320 was found to be highly up-

regulated in Oa-VR under salt conditions The O sativa homologue for this gene encodes a

plasma membrane monosaccharide transporter OsMST6 Transcript-level expression analysis

in a previous study showed up-regulation of OsMST6 expression under saline conditions in

both shoots and roots of rice seedlings (Wang et al 2008) The role of OsMST6 in

environmental stress responses and in establishing metabolic sink strength was established

(Wang et al 2008) In addition a monosaccharide transporter in Arabidopsis roots changes

the protein abundance in response to environmental stresses regulated by the expression

pattern of sugar transporters and affects the glucose efflux (Yamada et al 2011)

Monosaccharide transporters have been reported to be involved in other physiological

pathways such as cold stress (Cho et al 2010) programmed cell death (Noslashrholm et al

2006) signal transduction and sugar sensing (Weschke et al 2003) and senescence (Quirino

et al 2001) The up-regulated expression of OsMST6 by salt in Oa-VR and the previous

studies mentioned above imply that this gene may have roles in abiotic stress responses and

by establishing metabolic sink strength

I further investigated the OsMST6 protein utilising a hierarchical protein structure modelling

platform I-TASSER (Zhang 2008) This enabled me to examine a secondary structure-

enhanced Profile-Profile threading Alignment (PPA) and to obtain predictions of the protein

structure (Fig 5-7) In this model a confidence score (C-score) is calculated for estimating the

quality of predicted models for each predicted protein structure according to the significance

of threading template alignments and other parameters (Zhang 2008) A previous study

compared the amino acid sequences of MST proteins from rice and other organisms (Wang et

al 2008) The predicted protein sequence of OsMST6 was compared with previously

characterised OsMST1-5 and 8 from rice plant (O sativa) (Toyofuku et al 2000 Ngampanya

et al 2003) and SopGlcT from spinach (Weber et al 2007) The predicted protein of OsMST6

in that study (Wang et al 2008) contains nearly all conserved amino acid residues on sugar

transport proteins in all tested species similar to the lsquowild ricersquo protein that has notable buried

residues which are highly conserved These motifs and residues are highly conserved among

plant MSTs (Sauer et al 1993) and might hold some clues to function to confer salinity

tolerance in O australiensis Perhaps due to historic periodic salt water inundations in

Australia the Oa-VR accession gained an evolutionary advantage in response to salt stress

In addition the lack of homology for the non-conserved regions may indicate the location of

amino acid substitution (ie exposed residues)

The solvent-exposed residues are different across the two rice species and might be the

reason for the salt stress response between the two Future studies can be focused on

synonymous versus non-synonymous mutation in which the amino acid substitutions would be

explored based on salt tolerance and perhaps in relation to selection from an evolutionary

perspective Additionally since promoters could readily generate variation in the pattern of

gene expression (Doebley et al 1998) it is necessary to sequence the promoters of these

accessions and to look for epigenetic modifications such as DNA methylation and methylation

of histone tails

Exploring proteins with close structural similarities to OsMST6 using the Protein Data Bank

(PDB httpswwwrcsborg ) helped me to find a protein with the closest structural similarity

to OsMST6 with the highest TM-score (Zhang et al 2004) to the predicted I-TASSER model

An A thaliana sugar transport protein 10 (PDB 6H7D) was found to be the most similar to the

OsMST6 protein The precise structure of this transmembrane monosaccharide transporter

explains its high-affinity sugar recognition and suggests a mechanism based on a proton

donoracceptor pair (Paulsen et al 2019) The high-resolution mapping of this Arabidopsis

protein structure illuminates fundamental principles of sugar transport and can potentially

provide clues to the O australiensis sugar transporter mechanism for salt stress response

Figure 5-7 Top four final models predicted by multiple algorithm by I-TASSER for the OsMST6 protein Each predicted model has a different C-

score and number of ligand binding site residues calculated based on the significance of template alignments and the parameters describe the convergence

the structure assembly simulations (Zhang 2008) Blue to red runs from N- to C-terminus using PyMOL platform (httpspymolorg2) with the Spectrum

colour scheme

Another differentially expressed protein that showed an interaction between genotype and salt

was UniProt A0A0E0MJB0 The abundance of this protein was 28-fold higher in salt-treated

Oa-VR than in salt-treated Oa-D (calculated using the same formula described earlier (Pfaffl

2001)) Using UniProtrsquos BLAST tool this protein was identified in O sativa (UniProt Q2QY48)

as a major facilitator superfamily antiporter encoded by the Os12g03860 gene (Yichie et al

2019) A previous antiporter found to confer salt tolerance in Arabidopsis by the over

expression of vacuolar Na+H+ activity (Blumwald et al 1999 Shi et al 2003) In rice the

overexpression of the Na+H+ antiporter gene (OsNHX1) confers the salt tolerance of

transgenic rice cells (Fukuda et al 2004) Additionally the same antiporter Na+H+ originated

from Pennisetum glaucum was introduced to rice and enhanced salt tolerance capabilities of

transgenic rice This study showed the overexpressing PgNHX1 in rice plants resulted with

more extensive and developed root system Additionally the overexpression plants completed

their life cycle by setting flowers and seeds in the presence of 150 mM NaCl (Verma et al

2007) The same approach was used to introduce a Na+H+ antiporter gene from a halophytic

plant Atriplex gmelini to rice The transgenic plants managed to survive under 300 mM NaCl

for 3 d while the wild-type rice plants could not (Ohta et al 2002)

These results suggest that in the tonoplasts the product of the Os12g03860 gene might play

an important role in the compartmentation of Na+ and K+ out of the cytoplasm into the vacuole

The amount of transcript (and as a result the abundance of this antiporter) could be important

factor determining salt tolerance in Oa-VR accession Reduction of sodium uptake and

translocation in shoots are two of the main tactics identified in plants (as described in chapter

1) for the acquisition of salt tolerance (Matsushita et al 1991)

542 First yeast validation salt screening

The second approach used here to validate salt-responsive proteins identified in Chapter 4

was through growth phenotyping of specific yeast knockout mutants Bakerrsquos yeast

(Saccharomyces cerevisiae) is a valuable model organism for the analysis of eukaryotic genes

by analysis and complementation of deletion mutants Yeast can live in a variety of stressful

environments including highly saline solutions and has served as an appropriate model

system for studying stress response mechanisms in plants (Shukla et al 2009) Thus I used

the growth of specific yeast deletion mutants under salt to validate the contribution of specific

proteins identified in the rice proteomics experiment presented in Chapter 4

Because of the essential roles of particular proteins some gene deletions were lethal

nonetheless yeast growth assays could be used to test a valuable subset of the most

prominent salt-responsive proteins found in Chapter 4 To overcome various environmental

conditions plants have evolved specific adaptive mechanisms to display wide variation in their

ability to withstand abiotic stress or a few together known as genetic plasticity (Yamaguchi-

Shinozaki et al 2006 Shao et al 2007) Upon exposure to various abiotic stresses some

plants show a varied range of responses at cellular molecular and whole-plant levels

(Greenway and Munns 1980 Hasegawa and Bressan 2000) The occurrence of numerous

abiotic stresses as compared with single stress consistently proved detrimental to the plants

grown under natural field conditions Therefore a heat stress treatment was added to assess

the growth performance of the tested deletion strains over salt + heat stresses Yeast

bioassays at three different salt concentrations revealed a growth inhibition for two specific

deletion mutants validating the importance of these two genes for salt tolerance as described

While not as prominent as the variation in the resistance of the different strains to salt some

variation was also observed in the resistance of strains to heat stress especially on YPD

medium Some of the tested strains did not exhibit any colony growth in both media for any of

the salt and heat treatments This result might have been due to an error while preparing the

strains for the assay perhaps these strains did not defrost correctly or optical density hadnrsquot

been tested properly and therefore there were insufficient colonies at the log growth phase to

grow on the petri dishes

Two of the tested yeast deletion strains were more susceptible to salt treatment compared with

the WT BY4742 The first strain (SGD systematic name YLR081W) has a deletion in a gene

encoding a monosaccharide transporter protein This gene is the closest homologue of

OsMST6 in O sativa It is a member of the MST gene family known to mediate transport of a

variety of monosaccharides across membrane barriers and has been reported to confer

hypersensitivity to salt in rice as described in Chapter 4 (section 444)

In an earlier study RT-qPCR expression analysis showed up-regulation of OsMST6

expression under saline conditions in both shoots and roots of rice seedlings (Wang et al

2008) In my study abundance of this protein was significantly greater in the salt-tolerant

accession and reduced in the salt-sensitive accession (Chapter 4) The differentially expressed

protein from the proteomics experiment coupled with the growth inhibition of the yeast deletion

mutants under salt treatment implies that the protein product of OsMST6 plays a role in salinity

stress responses in the Oa-VR accession Yet the promoter regulation should be tested to

exclude epigenetic interference This could be done for example via in silico genome-wide

analyses of cis-elements (Hernandez-Garcia et al 2014)

The second yeast strain (SGD systematic name YLR268W) that was susceptible to salt

treatment had a deletion in a V-SNARE gene This gene (Os01g0866300) encodes a vesicle-

associated membrane protein VAMP-like protein YKT62 (UniProt Q5N9F2) Leshem et al

reported that suppression of expression of the VAMP protein AtVAMP7 in Arabidopsis

increased salt tolerance (Leshem et al 2006) Another study reported a contrasting result

with reduced salinity tolerance when novel SNARE (NPSN) genes (OsNPSNs) were cloned

and expressed in yeast cells and tobacco (Leyman et al 2000) This study concluded that the

SNARE gene expression at the PM is vital for its function and is subject to control by parallel

stress‐related signalling pathways promoted by salt stress and wounding (Leyman et al

2000) In rice a semi-quantitative RT-PCR assays showed that the SNARE family-member

gene OsNPSNs were ubiquitously and differentially expressed in roots and other tissues in

response to salt and H2O2 (Bao et al 2008) The SNARE mechanism in the examples above

suggests to be potentially related with a sequestration of sodium via the tonoplast

My results highlight the potential agronomic importance of both OsMST6 and the V-SNARE

gene and provide evidence for genetic and functional dissection of proteins of the same family

in a comparatively simple model system These genes were chosen to be further tested in an

additional yeast salt screening assay

543 Second yeast validation salt screening

In this part of the validation experiments I focussed on the two yeast deletion strains described

above in order to validate the phenotypes found in the first screening In addition I used only

YPD medium without heat stress (using only 30degC) as this specific combination produced the

most well-separated phenotypes between the tested strains as described in the results

Strains were grown and spotted at log phase exactly as described in the first screening and

same growing conditions and medium preparation were used The same overall trend was

recorded for both strains colony growth of YLR081W and YLR268W was inhibited gradually

with an increase in salt concentration compared to the wild type BY4742

The overall results for both yeast assays demonstrate the profound effect of the deletion genes

in each of the strains to confer salinity tolerance in yeast Accordingly both OsNPSNs and V-

SNARE genes appear promising as a prime candidate genes to enhance rice salinity

tolerance However the corresponding proteins found in O australiensis will have to be further

examined to ensure the yeast screening results underly the tolerance found in the rice relatives

for example through complementation experiment

55 Conclusion

In the present study proteomic profiling coupled with transcriptomic analysis provided clues to

understanding salt stress tolerance mechanisms in an O australiensis accession The

abundance of the proteins of interest A0A0D3GSD4 and A0A0E0MJB0 were consistent with

the up-regulation of the corresponding genes Os07g37320 and Os12g03860 in Oa-VR as

shown by the RT-qPCR This provides another piece of evidence about the potential

mechanisms by which Oa-VR accession confers salt stress The expression levels of the other

two tested genes were not consistent with the quantitative proteomics results while

A0A0E0JI75 protein showed significant higher abundance in Oa-VR in salt vs control the

corresponding gene Os01g24710 did not present over expression under salt in the same

accession This might due to a few hypothetical reasons (i) the change of the protein

abundance does not have to be linked to transcript difference (Abreu et al demonstrated that

only 40 of the variation in protein abundance can be explained by the mRNA levels (Abreu

et al 2009)) (ii) although the tested genes were annotated to O sativa genes there is some

degree of likelihood that the tested genes are not similar to the ones in O australiensis and

(iii) usually proteins involved in transcriptional regulation tend to be degraded swiftly and by

contrast metabolic genes tend to be very stable (Schwanhaumlusser et al 2011) Thus regulatory

proteins may have to be synthesised and broken down very rapidly to react to a stimulus which

can affect the protein abundance and the gene expression Using statistical techniques such

as regression analysis it is possible to relate deviations in protein levels to protein (and even

mRNA) sequence that are characteristic as a result of different modes of regulation (Vogel et

al 2010) Finally in this study I evaluated the mRNA data but did not measure the translation

activity mRNA concentration can only partially explain variation in protein concentration (Kapp

et al 2004) Using such strategies can provide estimates of the relative genes exhibited by

multiple regulatory steps and might help to dissect the differences presented in this chapter

The second gene Os03g57960 corresponding to the protein A0A0E0GUU4 presented the

same trend of high levels of expression in Oa-VR under salt compared to control However

the relative expression value was small due to low consistency between biological samples

which affected the efficiency and as a result skewed the analysis for the efficiency-corrected

calculation model (Pfaffl 2001) The discrepancy between samples might be due to the design

of the primers which might not have been sufficiently specific for the tested gene Since the

initial information is amplified exponentially any error is also amplified in the same way and

can therefore skew the resulted values (Tichopad et al 2002) This set of primers needs to

be further tested to assess if they match to any other regions of the samplersquos DNA

The validated monosaccharide transporter in both the RT-qPCR and yeast experiment is likely

be associated with responses to salt This could be part of a mechanism to increase the loading

of sugars into cells that are pumping a lot of sodium and thus have very large respiratory

demands The respiratory demand by ion transport in leaves can dramatically change in

stressed conditions (Yeo 1983) This might trigger sugar transporters such as the one found

in this chapter to supply reduced carbon OsMST6 is possibly connected to the carbon

metabolism regulation via providing respiratory substrates to maintain the energy demands of

transport or maybe even by detecting assimilation abundance changes and transducing these

into reformed patterns of gene expression as proposed earlier for invertases (Kingston-Smith

et al 1999) In addition as seen in this chapter the MST proteins from different rice species

are highly similar which provides some confidence that the O sativa homologue that was used

for the transcriptomic and yeast experiment is highly similar to the MST from O australiensis

Although a yeast strain with a deletion in this gene showed a decreased growth under salt

treatment a further yeast complementation experiment is necessary ensure the rice gene is

the one that regulates this phenotype

Chapter 6 Towards QTL mapping for salt tolerance

Construction of a mapping population to characterise quantitative trait loci (QTLs) for salinity tolerance in Oryza meridionalis

61 Introduction

611 QTL mapping concept and principles

Over the last century the ability to dissect the genetic regulation of phenotypic variation

underlying a trait of interest has been studied widely (Bessey 1906 Tanksley et al 1996

Zamir 2001 Doerge 2002 Wuumlrschum 2012) There have been attempts through various

approaches which are constantly improving and today rely heavily on advanced genome-

sequencing technologies and sophisticated statistical and bioinformatic analysis

The conceptual basis for genetic mapping of complex traits is fairly straightforward At a very

basic level QTL mapping involves finding a link between a genetic marker and a measurable

phenotype either morphological or not (Mauricio 2001) Ever since the pioneering study of

Sax (Sax 1923) considerable efforts have been made to identify the genetic basis of

continuous traits (displaying a range of values) using linkage analysis However many of these

analyses were limited to visible physiological markers (Barton et al 2002)

The prodigious development of molecular and genetic markers as well as currently available

bioinformatic tools allow the construction of detailed genetic maps of both domesticated and

experimental species (Doerge 2002) These genetic maps now provide the foundation for

almost all QTL mapping studies (Mackay 2001 Huang et al 2016)

Two main approaches can be used to genetically dissect complex traits such as salinity

tolerance (i) the traditional and well-studied QTL analysis through a bi-parental or backcross

population and genetic markers whereby progeny are derived from an initial cross of two

genotypes as male and female parents and (ii) the more recent technique of genome-wide

association studies (GWAS) For my research I decided to use the first approach to potentially

map QTLgenes underlying the salinity tolerance trait in a native Australian rice species O

meridionalis My assumption was that a single gene in the wild relative has a profound effect

on salinity tolerance in rice as found before for O sativa (Thomson et al 2010) Therefore I

decided to use a bi-parental population as this is known to be a relatively rapid method to

generate an F2 mapping population which in turn is an ideal genetic stage (segregated

population) for QTL mapping Nevertheless it is possible that to generate the most useful data

from crossing two parental lines backcrossing will need to be conducted to overcome infertility

issues and to remove some of the donor genetic background

612 Bi-parental mapping populations

To allow fine mapping of complex quantitative traits QTL mapping should be designed with a

limited range of genetic variation to minimise the effect of the alien genetic background The

availability of new and abundant markers associated with potential parental materials allows

for the accelerated selection of loci controlling traits that were traditionally difficult to map

phenotypically (Varshney et al 2005) The construction of a bi-parental population can be

accomplished by using two sources originating from homozygous distantly related inbred lines

that exhibit genetic polymorphism influencing the phenotype of interest

Several crossing techniques are used to construct mapping populations In one population

structure lsquorecombinant inbred linesrsquo (RIL) can be created by self-pollinating each one of the

F2 progeny for a few consecutive generations (single-seed descent) In an lsquoF2 designrsquo a cross

between to parental plants generates the F1 progeny followed by selfing In a lsquobackcross

designrsquo the mapping population is produced by crossing the F1 progeny to either or both of

the parents to remove the undesired genetic background of one of the parents

Several combinations of the above techniques have been designed to fully optimise the

shuffling of parental alleles (Mauricio 2001) for instance lsquobackcrossed inbred linesrsquo (BIL)

lsquointrogression linesrsquo (IL) or lsquonear-isogenic linesrsquo (NIL) These facilitate the incorporation of

desired alleles into a highly agriculturally superior genetic background (Tanksley et al 1996)

to be used for ready-to-market breeding programs Many of the QTLs discovered in rice are

specific to O sativa populations since the original starting parental material derived from O

sativa and the discovery of QTLs is limited by the germplasm used Logically a more diverse

set of germplasm resources will enable the identification of a much larger spectrum of

agriculturally relevant loci

In this chapter I describe a collaboration with the International Rice Research Institute (IRRI)

to establish a QTL mapping population for the salinity tolerance trait within O meridionalis For

this purpose a bi-parental mapping population approach was utilised The experimental

procedures described in the chapter have been executed by the lab technician in IRRI under

the supervision of Dr Sung-Ryul Kim with my guidance

621 Bi-parental mapping population construction

To increase the genetic variation specifically for the phenotype of interest two distinct parents

with contrasting physiological response to salinity should be chosen A few O sativa salt-

sensitive varieties have been used in the past as a recipient parent to dissect salt tolerance

traits via bi-parental QTL mapping within O sativa (Edwards et al 1987 Thomson et al

2010) The two main inbred varieties used as a sensitive parent were IR29 (described in

Chapters 2 and 3) and IR24 another salt-sensitive variety developed by IRRI (Ferdose et al

2009) First we chose to cross our salt-resistant wild relative with salt-sensitive IR29 since we

used this control in the previous salt screening experiments (Chapters 2 and 3) and confirmed

independently its reputation for sensitivity to salt To overcome possible genetic incompatibility

IR24 was grown alongside IR29 in case of incompatibility in the F1 generation when IR29 was

the recipient parent Maternal incompatibility is plants is commonly observed and yet entirely

unpredictable (Chen et al 2016) when crossing Oryza species with different chromosome sets

(eg AA with EE) Thus the native Australian O meridionalis accession Om-T (AA genome)

which was previously found to have salinity tolerance characteristics (Chapters 2 and 3 Yichie

et al 2018) was used as a male donor (rather than Oa-VR which contains the EE genome)

for a cross with two O sativa (AA genome) salt-sensitive female lines IR29 and IR24

respectively At 8ndash11 d after pollination embryo rescue (Ballesfin et al 2018) was conducted

(by IRRI staff lead by Dr Sung-Ryul Kim) to obtain interspecific F1 plants

622 Salt screening field trial

At the time of submission of this thesis the salt tolerance screening at IRRI of the mapping

population introduced above had not begun because of the incompatibility issues outlined

below Thus I describe here the F1 population and plan for the screening experiment I have

received University of Sydney funding support (Norman Matheson Student Support Award) to

visit IRRI to assist with these experiments

The population will be evaluated for seedling-stage salinity tolerance with a hydroponic system

under controlled conditions of 2921degC daynight temperature natural lighting and 70 RH in

the IRRI phytotron (Los Bantildeos Philippines) Pre-germinated seeds will be sown in holes on

tray floats with a net suspended on trays filled with Yoshida nutrient (Yoshida et al 1976) as

described in Chapter 4 section 421

Salt treatment will be imposed 14 d after germination by adding NaCl gradually (in three steps)

to the nutrient solution to a final EC of 12 dS mminus1 Both parental genotypes as well as the

entire mapping population will be scored based on visual symptoms using the IRRI SES

system for rice (IRRI 2013) with ratings from 1 (highly tolerant) to 9 (highly sensitive) In

addition Na+ and K+ concentrations in leaves seedling height and chlorophyll content in leaves

will be assessed for each individual 14 d after applying the salt treatment (DAS) Tissue

samples will be collected from each individual plant and DNA will be extracted using the cetyl

trimethylammonium bromide (CTAB) method (Kim et al 2011) to be used for SNP chip array

analysis (as described below)

623 Genotyping using the Illumina Infinium 7K SNP chip array

In order to enrich the mapping analysis and consequently achieve higher resolution mapping

for the targeted QTLs the mapping population will be genotyped using 7098 SNP markers

from the 7K Infinium SNP genotyping platform (Illuminareg) at the Genotyping Services

Laboratory (IRRI Philippines) The 7K SNP chip is the updated version of the well-used 6K

Infinium array (Thomson et al 2017) and allows broad allelic variation to map the desired trait

We will use TASSEL V5241 software as a filtering tool where accessions with call rates

ltthinsp075 SNPs with missing data gtthinsp20 and minor allele frequencythinsplethinsp5 will be removed

(Bradbury et al 2007) Following this filtering the polymorphic information content (PIC)

heterozygosity major allele frequency gene diversity and pairwise linkage disequilibrium will

be calculated using PowerMarker v325 as described previously (Liu et al 2005) Lastly

Principal Component Analysis (PCA) will be carried out using a fixed arrays of SNP (to be

determined) while linkage disequilibrium (LD) decay will be calculated between markers and

loci by pairwise comparisons between the SNP markers using the calculated R2

63 Results

631 Mapping population construction

As explained above we aimed to construct a bi-parental mapping population using the same

male donor Om-T crossed with the salt-sensitive O sativa female parents IR29 With the use

of primer pairs representing an SSR marker RM153 (F CCTCGAGCATCATCATCAGTAGG

R TCCTCTTCTTGCTTGCTTCTTCC) and an insertiondeletion (InDel) marker RTSV-pro (F

CGTTTGCTGTGTTCATGTAG R TCGGTACGAACGAGTAGGAT) we genotyped parental

lines of rice hybrids to distinguish between putative hybrids and inbreds Unfortunately

following two rounds of F1 crosses between Om-T and IR29 all generated seeds were found

to be derived from self-pollination (Fig 6-1) Therefore IRRI made a cross between Om-T and

IR24 as a second attempt to produce viable F1 plants Of the 20 putative F1 plants derived

from the embryo rescue 12 were found to be true hybrids using the same sets of markers used

for the IR29 times Om-T cross (Fig 6-1) Thus IR24 was superior to IR29 as a female parent for

the generation of hybrids with Om-T

Figure 6-1 PCR products amplified using markers RM153 and RTSV-pro-F1R1 were generated for parents and putative F1 plants PCR products

(10 microLwell) were electrophoresed on a 25 agarose gel and visualised with ethidium bromide staining for IR29 times Om-T (in black left panel) and IR24 times

Om-T (in red right panel) For both markers the larger PCR product represents the allele derived from IR29 or IR24 while the smaller amplicon is derived

from Om-T Since no double bands were recorded for the IR29 putative hybrids all ten individuals were found to be derived from self-pollination of the

domesticated O sativa parent Of the 20 tested potential hybrids from the IR24 times Om-T cross 12 generated amplicons from both the wild and domesticated

alleles (blue asterisk) indicating true interspecific hybrids

632 Plant growth and hybrid viability

Physiological differences were seen between the hybrids and the self-pollinated plants at

maturity with a typical vigorous growth characteristic for the hybrid plants vs the self-pollinated

O sativa parent (Fig 6-2a) Some of the true hybrid plants were placed in a darkroom every

evening from 500 pm to 700 am (dark-14hlight-10h) to induce early inflorescence initiation

(Fig 6-2b) To assess the viability of the pollen grains hybrid pollen was tested using iodine

staining which provided an estimate of the potential number of fertile F2 seeds (Fig 6-3) Poor

seed set values were recorded for all hybrid panicles (Fig 6-2c) which would have resulted in

insufficient F2 seeds to generate the mapping population Therefore we conducted a round of

backcrossing to reduce some (maximum half) of the wild genetic background and increase the

domesticated background This might allow us to obtain enough viable pollen grains with a

sufficient BC1F2 seeds to be used for QTL mapping for salinity tolerance In August 2019 we

had 19 BC1F1 seeds generated by the previous cross with the recurrent parent IR24 These

seeds will be sown to produce BC1F2 seeds which will be used to map the salinity tolerance

Figure 6-2 Plants used in production of IR24 x Om-T hybrids (a) Both self-pollinated IR24 (blue pot) and hybrid IR24 times Om-T (green pot) were grown

to full maturity Some hybrid plants (b) were placed in a dark room for a short-day treatment (14 hd) to induce flowering (inflorescences marked with red

arrows) (c) A single F1 panicle exhibiting a long awn purple stigma and empty spikelets resulting from poor seed set

represents an individual hybrid) using iodine staining Anthers were collected during the

spikelet opening period (1000 am to 100 pm) and were placed into 1 iodine solution for

staining of accumulated starch which is the major source of energy for pollen germination and

pollen tube growth Black-stained pollen grains indicate viability while unstained (yellow) pollen

grains reflect poor seed set

63 Discussion and future perspectives

In this chapter I described the workflow and the initial results from the QTL mapping of the

salinity tolerance trait in O meridionalis using the same salt-tolerant accession used for the

earlier salt screenings (Chapters 2 and 3) In the first year of my PhD candidature (2016) I

was fortunate to be invited to IRRI to learn hands-on from some of the most talented and

experienced researchers in rice research As part of this visit I learned the most efficient

practices for salinity screening experiments phenotyping and crossing During my stay in IRRI

(Los Bantildeos Philippines) I managed to establish a collaboration with the well-known salinity

tolerance expert Dr Abdelbagi M Ismail This collaboration has evolved into a joint project run

by principal scientist Dr Sung-Ryul Kim from IRRI Sung-Ryul and his experienced team have

been working on constructing the mapping population from the germplasm I sent them in 2017

The initial plan was to have this mapping population ready by early 2019 so I could travel

again for the phenotyping genotyping and analysis at IRRI before my thesis was due for

submission

Because of the problems described in this chapter (such as germination genetic compatibility

and poor F1 seed setting) we decided not to map the population in the F2 generation as we

are unlikely to have enough F2 individuals (expected number of ~150 plants) to span the

genetic segment(s) that influences salt tolerance The IRRI team has generated F2BC1 seeds

and is currently working to generate the F3BC1 seeds and we are aiming to map this

population as soon as possible

A few fundamental steps need to be taken to unlock the genetic potential of crop wild relatives

Firstly the germplasm should be ideally collected from isolated geographies with endemic

populations in order to identify unique alleles in those plants Second a phenotypic

assessment for the traits of interest must be performed to assess the potential of this genetic

resource as a tool for crop improvement (Tanksley 1997) These steps informed the

experiments in the preceding chapters Revealing the mechanism(s) is an important and

crucial step to address susceptibility to salinity but it is impossible to apply this information

without investigating the inheritance of stress-tolerance genes and the location of QTLs on the

rice chromosomes Therefore following the discovery of differentially expressed proteins

between the tested accessions and salt treatments the ground was laid to study the genetic

regulation and to map this trait for future breeding

The ever-growing number of DNA markers play an important role in advancing us towards the

goal of identifying the genetic factors that underlie various phenotypes The availability of the

rice 7K SNP chip and the state-of-the-art bioinformatic and statistic tools allows us the ability

in a straightforward manner to find stronger associations between polymorphisms at the DNA

level and the measured phenotype of salinity tolerance as previously reported for rice

(Agarwal et al 2016 Gaby et al 2019) The outcome of this study will potentially provide a

novel resource for salinity tolerance to improve rice performance across salt-affected regions

Chapter 7 General discussion and

future directions

71 Conclusions and future perspectives

In this PhD project various approaches were taken to explore how Australian wild Oryza

species can expand our understanding of salinity tolerance in O sativa First two rounds of

glasshouse-based salt screening ranked the members of an Australian wild rice panel for

variation in salt tolerance Second a short-list of the above panel was used in a high-

throughput non-invasive phenotyping facility to validate the previous results and to dissect

components of the salinity tolerance with particular emphasis on phenology Third

quantitative proteomics was applied to reveal mechanisms underlying the variation in salt

tolerance between two contrasting accessions of O australiensis the results of which were

validated by determining levels of gene transcripts Further I evaluated the phenotypic

response to salt in eleven yeast knockout strains which were selected based on genes

homologous to differentially expressed rice genes identified in rice Last steps were taken

towards constructing a mapping population to map QTL and ultimately key stress tolerance

genes within the Australian wild relatives

The background of this research was the need to find novel genetic resources to improve the

responses of rice to salt stress The threat of salinity has become a great concern for many

rice production areas and is likely to increase under the forces of food demand and climate

change There is a need to develop rice varieties that can produce higher yields under salinity

Chapter 2 describes the initial salt screening of a panel of Australian rice native accessions

representing two species O meridionalis and O australiensis The goal was to build on earlier

preliminary screens by making selections from eight accessions with contrasting salt tolerance

these genotypes were then targeted for subsequent experiments The wild Oryza accessions

evaluated for this study were selected from geographically isolated populations in northern

Australia thereby broadening the range of genetic diversity and with it the opportunity to

discover novel salt-tolerance mechanisms However none was chosen specifically because it

had evolved in a salt-affected landscape This screen was conducted alongside O sativa

controls (Pokkali and IR29) which were tolerant and sensitive to salt respectively It revealed

the existence of substantial genetic variation within the Australian Oryza relatives for salinity

tolerance Growth responses were reinforced by a wide range of physiological traits across

different salt treatments

Multiple strands of evidence including growth and tiller development leaf symptoms gas

exchange values and ion concentrations revealed a wide range of responses to salt stress

within the rice relatives and cultivated rice genotypes

The screen verified our initial assumption of natural variation for salinity stress responses within

the Australian wild rice accessions A lsquoshort-listrsquo of five O australiensis and O meridionalis

accessions was selected for contrasting tolerance to salinity during early vegetative growth

The responses under salt treatments of some accessions (particularly Oa-VR) were equal to

and in some cases superior to those of the salt-tolerant cultivar Pokkali (Yeo et al 1990)

these responses included higher biomass accumulation and improved SES scores The low

Na+K+ ratios found in both Oa-VR and Pokkali (ltthinsp05) suggested that active mechanisms are

in play to isolate Na+ even while the external solution was at 80thinspmM NaCl for 30 d

This chapter was the foundation for subsequent chapters targeted to specific questions by

studying a few accessions with contrasting responses to salinity stress

Chapter 3 describes further investigations on specific wild Australian accessions in a non-

destructive system I utilised the high-throughput phenotyping platform at The Plant

Accelerator at Adelaide University enabling me to obtain time-series images of plants treated

with various salt concentrations A more dynamic picture of salinity tolerance was achieved

than the previous destructive measurements described in Chapter 2 Relative growth rates

could be calculated continuously and non-destructively revealing an impact of salt as little as

4 d after commencing the salt treatments (Yichie et al 2018) Water-use efficiency was

substantially greater in Oa-VR than the salt-sensitive Oa-D particularly in the first two weeks

after salt was applied suggesting that the elasticity of photosynthesis observed in salt-

treated Oa-VR plants sustained growth even as stomatal conductance decreased dramatically

(60) as previously reported in studies of indica and aus rice (Al-Tamimi et al 2016) similar

results were found in wheat and barley (Harris et al 2010)

State-of-the-art phenotyping when combined with destructive measurements revealed novel

aspects of physiological tolerance to salt stress For example chlorophyll levels were around

50 lower in IR29 at 40thinspmM NaCl vs IR29 control plants but were unaffected by 40 mM salt

in Oa-VR similar to contrasts in tolerance reported previously (Lutts et al 1995) where 50thinspmM

NaCl lowered chlorophyll levels by up to 70 in salt-sensitive rice varieties The rate at which

shoot growth responded to salt coupled with the internal Na+ and K+ concentrations of young

leaves (Chapter 2) provided insights into possible mechanisms of tolerance Early evidence

as to how this is achieved came from a QTL (Ren et al 2005) now known to span the

OsHKT15 gene found to enhance Na+ exclusion in rice (Hauser et al 2010)

The polygenic nature of salt tolerance as described in this chapter where genes determine ion

import metabolic and compartmentation responses to salt are likely to collectively affect the

physiological tolerance (Munns et al 2008) Consequently based on the overall salt tolerance

responses and rates of shoot development Oa-VR and Oa-D were chosen as complementary

O australiensis genotypes representing contrasting tolerance to salt

Chapter 4 describes quantitative proteomics experiments conducted to understand

mechanisms underlying the salinity tolerance Microsome-enriched protein preparations of

salt-treated and control roots of Oa-VR and Oa-D were quantified by tandem mass tags (TMT)

and triple-stage mass spectrometry (MS) Membrane proteins were substantially enriched in

the microsomal preparation with about 10 of the extracted proteins (363 unique proteins)

categorised as participating in transport this was higher than in previous studies which yielded

around 5 transporters (Meisrimler et al 2017) Further evidence that preparation of the

microsomal fraction was successful was that about 40 of the proteins were found to have at

least one membrane-spanning region similar to a previous study (Chiou et al 2013)

More than 200 differentially expressed proteins were identified between the salt-treated (80

mM NaCl) and control root samples in the two O australiensis accessions (p-value lt005

three replicates) Of all the functional categories ATPases and mitochondrial and SNARE

proteins responded most consistently to salt with an increased abundance in the salt-tolerant

accession (Oa-VR) for most of these proteins and a decrease in the salt-sensitive accession

(Oa-D) This result led me to conclude that trafficking proteins of which the SNAREs are a key

component play a central role in determining salt tolerance in these Australian wild rice

accessions

The proteomics results also showed that some subunits of ATPases were downregulated while

others were over-expressed A previous study (Braun et al 1986) showed that during salt

treatment V-ATPase activity increased to maintain polarisation of the tonoplast thereby

driving Na+H+ antiport-mediated sequestration of Na+ in the vacuole (Maathuis et al 2003)

This energy generation mechanism coupled with the low concentration of Na+ found in Oa-

VR might be a key factor for its superior salt tolerance

Particular interest was directed to proteins whose abundance responded differentially to salt

between Oa-VR and Oa-D ie the relative response to salt between accessions A few

proteins met this criterion with salt increasing abundance in Oa-VR but suppressing it in Oa-

D In general Oa-VR displayed a significantly higher abundance of lsquometabolism processrsquo

proteins in response to salt than the sensitive genotype consistent with the fact that Na+ in the

external soil solution imposes a substantial energy demand on plants (Koqro et al 1993) Of

the most differentially responsive proteins I identified a peroxidase and a sugar transporter

Their mechanism of action remains unclear Oa-VR might utilise this specific monosaccharide

transporter to deliver sugars to root cells for accelerated energy production via activity of

membrane-associated ATPases

Other proteins had marked response in only one accession For example starch synthase

(UniProt A0A0D3GCE6) was significantly and dramatically up-regulated in the salt-sensitive

accession Oa-D (10-fold in salt-treated vs control) while this protein was not detected in Oa-

VR Microscopy and biochemical analyses could be used to investigate whether the increased

abundance of starch synthase is correlated with an increased abundance of starch in the roots

Moreover rice mutants or a gene knockoutdown (eg via CRISPR-Cas9) with impaired starch

synthesis in roots could be used to test whether this gene confers salinity tolerance

Chapter 5 describes validation of the proteomics results via measurements of gene transcripts

and yeast gene knockout experiments Results for mRNA quantification validated the over-

expression in salt-tolerant seedlings of genes encoding a monosaccharide transporter and a

superfamily antiporter (relative expression values of 64- and 142-fold respectively) The

validated monosaccharide gene was BLASTed against the O sativa genome and annotated

as OsMST6 This gene is part of the MST family which is known to mediate transport of a

variety of monosaccharides across membranes and reported to regulate salt tolerance in rice

(Wang et al 2008) The general enrichment of lsquometabolism processrsquo pathways discussed

above in addition to both the differential expression of V-type and F-type ATPase subunits

and the high expression of a sugar transporter underline the connection between

carbohydrate metabolism and salt tolerance in rice This reinforces the fact that salinity stress

triggers many responses in rice including physiological biochemical and morphological

changes (Sarangi et al 2013 Mondal et al 2018)

Using a deletion yeast library I demonstrated growth inhibition of a yeast deletion strain for a

homologue of the MST6 gene from O sativa Although very different salt treatments had to be

used for the rice and yeast salt screenings (up to 120 mM and 1000 mM of NaCl respectively)

due to the contrasting salt tolerance of these organisms the results strongly suggest a role in

salt responses of this gene in both rice and yeast This finding showcased the utility of yeast

deletion libraries in exploring genes of interest in higher eukaryotes such as plants

The second gene validated in the RT-qPCR experiments was the homologue in O sativa of a

major facilitator superfamily antiporter (Os12g03860) Several other antiporters have been

identified to confer salinity tolerance in Arabidopsis (Shi et al 2000) rice (Fukuda et al 2004)

and other species (Niemietz et al 1985 Ye et al 2009) In a previous study in rice V-ATPase

activity increased during salt treatment (Braun et al 1986) thereby ensuring polarisation of

the tonoplast to drive Na+H+ antiport-mediated sequestration of Na+ in the vacuole (Maathuis

et al 2003) My RT-qPCR results verified this superfamily antiporter gene to be highly

expressed under salt in Oa-VR while no relative change in expression was measured for Oa-

D corresponding with the quantitative proteomics results The low Na+K+ ratios in Oa-VR

together with the salt induction of this antiporter gene provide evidence for an additional

mechanism that regulates salinity tolerance in Oa-VR

With the availability of rice genome previous studies have identified abiotic stress QTLs

(Pareek et al 2009) More specifically studies have shown that high-affinity K+ uptake

systems are pivotal for the management of salinity and deficiency symptoms in rice (Suzuki et

al 2016) A major shoot QTL associated with the Na+K+ ratio in seedling-stage rice

named Saltol was found in IR29Pokkali recombinant inbred lines where the tolerant

individuals exhibited a low Na+K+ ratio compared with the sensitive plants (Thomson et al

2010) Within the Saltol QTL region OsHKT5 was identified as encoding for a transporter

that unloads Na+ from the xylem (Ren et al 2005) A similar mechanism has been found in

other species such as Arabidopsis and wheat (Byrt et al 2007 Munns et al 2008) and

reinforces the likelihood that O australiensis accessions control Na+K+ homeostasis under

stress as a defence mechanism for salinity stress as reported earlier in O sativa (Ul Haq et

al 2010)

In future studies the Na+ content in Oa-VR leaves should be checked after silencing (or

knocking out) the gene Os12g03860 This will elucidate the mechanism of action of this

antiporter under salt and non-salinised conditions Alternatively the same gene could be over-

expressed in the salt-sensitive Oa-D and the salinity tolerance trait evaluated (or Os12g03860

could be overexpressed in O sativa) I expect that increased Na+H+ antiporter activity in the

transgenic plants would cause larger amounts of Na+ to be excluded into vacuoles in discrete

cells hence rendering the transgenic rice plants more resilient to salinity

My proteomics results coupled with the RT-qPCR analysis provide evidence that these two

genes have a major role in the Oa-VR response to salt stress I found that specific proteins

that were differently expressed in rice treated with salt exhibited corresponding behaviour in

yeast deletion strains Growth inhibition was presented in a valuable subset of the most

prominent salt-responsive proteins found in Chapter 4 Two deletion strains exhibiting

deletions corresponding to homologues of the proteins of interest highlighted the importance

of these two genes for salt tolerance

Further validation experiments should be conducted to verify the monosaccharide and

antiporter genes in the yeast system Since the O australiensis genome is yet to be published

for this chapter I used homologous genes in O sativa to identify the roles of proteins A

suggested future direction would be to construct longer primer sets and to amplify and

sequence the coding region of key genes from Oa-VR and Oa-D and explore any genetic

variation between genotypes Equally important is to sequence the promoter regions of these

key genes which might be as important as SNPs in the open reading frame in determining salt

tolerance Questions of post-transcriptional control of gene expression are also topics for future

research Assuming the gene sequences were different the Oa-VR gene could be introduced

into the salt-sensitive Oa-D to examine whether this complements the phenotype I attempted

to apply a similar complementation approach using the deletion yeast strains that were

validated in this chapter However due to DNARNA contamination the genes of interest could

not be introduced into the relevant yeast strains following the Gibson assembly method

attempted I aim to run the yeast complementation experiment again utilising the CRISPR-

Cas9 technique but this work could not be included in this thesis because of time constraints

In addition to proteomic and transcriptomic approaches explored in this project it would be

very informative to carry out metabolomic and biochemical studies to help elucidate a

comprehensive network of salt stress response in wild Australian rice thus providing a broader

view of the overall stress response

Chapter 6 describes the ongoing project for mapping a QTLgenes underlying the salinity

tolerance within the Australian wild Oryza species The expected findings of this part of the

project will enable us not only to learn about the mechanisms of salinity tolerance in the

explored accessions but also to lsquozoom inrsquo to explore genomic regions that regulate this trait

The mapping of such a complex trait by means of the QTL mapping approach will be of great

importance for breeders To date there have been no reports on QTLs for salt tolerance in the

Australian rice germplasm so this work in progress could be a novel source for breeding

programs This is especially so because O australiensis is a phylogenetically remote from O

sativa and has evolved under adverse conditions in which gene variants are likely to be

concentrated It would be very interesting to determine whether one or more of the genes

identified earlier in this PhD project are found in the genomic region(s) found in this mapping

population

72 Closing Statement

The research reported in this thesis has revealed valuable variation in salinity tolerance

responses within the Australian Oryza species It has created a foundation for discovering a

genetic source for salinity tolerance in unexplored Oryza species through physiological and

molecular approaches As a consequence a number of proteinsgenes have been identified

with potential as salt-tolerance markers However there is a long way to go before we can fully

understand the molecular mechanisms employed by rice species to cope with salt stress Many

more studies need to be completed to enable the production of rice varieties that can adapt to

climate change and survive under harsh salt (and drought) conditions Considering the global

importance of rice production my hope is that the findings of this project can be used as a

foundation to understand the mechanisms underlying salinity tolerance in rice eventually

leading to development of new salt-tolerant varieties

Chapter 8 Bibliography

Abbasi FM amp Komatsu S (2004) A proteomic approach to analyze salt-responsive proteins in rice leaf sheath Proteomics 4 2072ndash2081

Achard P Cheng H Grauwe L De Decat J Schoutteten H Moritz T Straeten D Van Der Peng J amp Harberd NP (2006) Integration of plant responses to environmentally activated phytohormonal signals Science 311 91ndash94

Aebersold R amp Mann M (2016) Mass-spectrometric exploration of proteome structure and function Nature 537 347ndash355

Agarwal P Parida SK Raghuvanshi S Kapoor S Khurana P Khurana JP amp Tyagi AK (2016) Rice improvement through genome-based functional analysis and molecular breeding in india Rice 9 1ndash17 Rice

Aggarwal S Science TH Yadav AK amp Science TH (2015) False discovery rate estimation in proteomics Pp 119ndash128 in Methods in Molecular Biology

Agrawal GK Rakwal R Yonekura M Kubo A amp Saji H (2002) Proteome analysis of differentially displayed proteins as a tool for investigating ozone stress in rice (Oryza sativa L) seedlings Proteomics 2 947ndash959

Agrawal GK Jwa NS amp Rakwal R (2009) Rice proteomics ending phase I and the beginning of phase II Proteomics 9 935ndash963

Ahsan N Lee DG Lee SH Kang KY Bahk JD Choi MS Lee IJ Renaut J amp Lee BH (2007) A comparative proteomic analysis of tomato leaves in response to waterlogging stress Physioligia Plantarum 131 555ndash570

Al-Tamimi N Brien C Oakey H Berger B Saade S Ho YS Schmoumlckel SM Tester M amp Negraotilde S (2016) Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping Nature Communications 7 p13342

Alam I Lee DG Kim KH Park CH Sharmin SA Lee H Oh KW Yun BW amp Lee BH (2010) Proteome analysis of soybean roots under waterlogging stress at an early vegetative stage Journal of Biosciences 35 49ndash62

Alqahtani M Roy SJ amp Tester M (2019) Increasing salinity tolerance of crops Crop Science 245ndash267

Anbinder I Reuveni M Azari R Paran I Nahon S Shlomo H Chen L Lapidot M amp Levin I (2009) Molecular dissection of tomato leaf curl virus resistance in tomato line TY172 derived from Solanum peruvianum Theoretical and Applied Genetics 119 519ndash530

Apel K amp Heribert H (2004) Reactive oxygen species metabolism oxidative stress and signaling transduction Annual review of plant biology 55 373

Asano T Hakata M Nakamura H Aoki N Komatsu S Ichikawa H Hirochika H amp Ohsugi R (2011) Functional characterisation of OsCPK21 a calcium-dependent protein kinase that confers salt tolerance in rice Plant Molecular Biology 75 179ndash191

Asch F Dingkuhn M Doumlrffling K amp Miezan K (2000) Leaf KNa ratio predicts salinity induced yield loss in irrigated rice Euphytica 113 109ndash118

Aspinwall MJ Varingrhammar A Possell M Tissue DT Drake JE Reich PB Atkin OK Rymer PD Dennison S amp Sluyter SC Van (2019) Range size and growth temperature influence Eucalyptus species responses to an experimental heatwave Global Change Biology 25 1665ndash1684

Assaha DVM Ueda A Saneoka H Al-Yahyai R amp Yaish MW (2017) The role of Na+ and K+ transporters in salt stress adaptation in Glycophytes Frontiers in Physiology 8

Atieno J Li Y Langridge P Dowling K Brien C Berger B Varshney RK amp Sutton T (2017) Exploring genetic variation for salinity tolerance in chickpea using image-based

phenotyping Scientific Reports 7 1ndash11

Atwell BJ Wang H amp Scafaro AP (2014) Could abiotic stress tolerance in wild relatives of rice be used to improve Oryza sativa Plant Science 215 48ndash58

Azhar FM amp McNeilly T (1988) The genetic basis of variation for salt tolerance in Sorghum bicolor (L) moench seedlings Plant Breeding 101 114ndash121

Bai J Qin Y Liu J Wang Y Sa R amp Zhang N (2017) Proteomic response of oat leaves to long-term salinity stress Environmental Science and Pollution Research 24 3387ndash3399

Ballesfin MLE Vinarao RB Sapin J Kim S-R amp Jena KK (2018) Development of an intergeneric hybrid between Oryza sativa L and Leersia perrieri (A Camus) Launert Breeding Science 68 474ndash480

Baniwal SK Bharti K Chan KY Fauth M Ganguli A Kotak S Mishra SK Nover L Port M Scharf KD Tripp J Weber C amp Zielinski D (2004) Heat stress response in plants A complex game with chaperones and more than twenty heat stress transcription factors Journal of Biosciences 29 471ndash487

Bao YM Wang JF Huang J amp Zhang HS (2008) Cloning and characterization of three genes encoding Qb-SNARE proteins in rice Molecular Genetics and Genomics 279 291ndash301

Bardy N amp Pont-lezica R (1998) Free-flow electrophoresis for fractionation of Arabidopsis thaliana membranes Electrophoresis 19 1145ndash1153

Barnawal D Bharti N Pandey SS Pandey A Chanotiya CS amp Kalra A (2017) Plant growth promoting rhizobacteria enhances wheat salt and drought stress tolerance by altering endogenous phytohormone levels and TaCTR1TaDREB2 expression Physiologia plantarum 161 502-514

Barton NH amp Keightley PD (2002) Understanding quantitative genetic variation Nature Reviews Genetics 3 11ndash21

Beachell HM Adair CR Jodon NE Davis LL amp Jones JW (1938) Extent of natural crossing in rice Agronomy Journal 30 743

Bennett MK Calakos N amp Scheller RH (1992) Syntaxin a synaptic protein implicated in docking of synaptic vesicles at presynaptic active zones Science 257 255ndash259

Berger B Parent B amp Tester M (2010) High-throughput shoot imaging to study drought responses 61 3519ndash3528

Berger B Regt B de amp Tester M (2012) High-throughput phenotyping of plant shoots pp 9-20 in High-Throughput Phenotyping in Plants Humana Press NJ

Bessey CE (1906) Crop improvement by utilizing wild species Journal of Heredity 2 112ndash118

Bharti N Yadav D Barnawal D Maji D amp Kalra A (2013) Exiguobacterium oxidotolerans a halotolerant plant growth promoting rhizobacteria improves yield and content of secondary metabolites in Bacopa monnieri (L) Pennell under primary and secondary salt stress World Journal of Microbiology and Biotechnology 29 379ndash387

Biswas S Amin USM Sarker S Rahman MS Amin R Karim R Tuteja N amp Seraj ZI (2018) Introgression generational expression and salinity tolerance conferred by the pea DNA helicase 45 transgene into two commercial rice genotypes BR28 and BR47 Molecular Biotechnology 60 111ndash123

Blumwald E Snedden WA Aharon GS amp Apse MP (1999) Salt tolerance conferred by over expression of a vacuolar Na+H+ antiport in Arabidopsis Science 285 1256ndash1258

Bohler S Sergeant K Lefegravevre I Jolivet Y Hoffmann L Renaut J Dizengremel P amp Hausman JF (2010) Differential impact of chronic ozone exposure on expanding and fully expanded poplar leaves Tree Physiology 30 1415ndash1432

Bonhomme L Monclus R Vincent D Carpin S Lomenech AM Plomion C Brignolas F amp Morabito D (2009) Leaf proteome analysis of eight Populus x euramericana genotypes Genetic variation in drought response and in water-use efficiency involves photosynthesis-related proteins Proteomics 9 4121ndash4142

Bradbury PJ Zhang Z Kroon DE Casstevens TM Ramdoss Y amp Buckler ES (2007) TASSEL Software for association mapping of complex traits in diverse samples Bioinformatics 23 2633ndash2635

Brar DS amp Khush GS (1997) Alien introgression in rice Plant molecular biology 35 35ndash47

Braun Y Hassidim M Lerner HR amp Reinhold L (1986) Studies on H+-translocating ATPases in plants of varying resistance to salinity Plant physiology 81 1050ndash1056

Brien C J (2018) dae Functions useful in the design and ANOVA of experiments Version 30-16

Brinkman DL Jia X Potriquet J Kumar D Dash D Kvaskoff D amp Mulvenna J (2015) Transcriptome and venom proteome of the box jellyfish Chironex fleckeri BMC Genomics 16 407

Brozynska M Copetti D Furtado A Wing RA Crayn D Fox G Ishikawa R amp Henry RJ (2017) Sequencing of Australian wild rice genomes reveals ancestral relationships with domesticated rice Plant Biotechnology Journal 15 765ndash774

Brugnoli E amp Lauteri M (1991) Effects of salinity on stomatal conductance photosynthetic capacity and carbon isotope discrimination of salt-tolerant (Gossypium hirsutum L) and salt-sensitive (Phaseolus vulgaris L) C3 non-halophytes Plant Physiology 95 628ndash635

Brumbarova T Matros A Mock HP amp Bauer P (2008) A proteomic study showing differential regulation of stress redox regulation and peroxidase proteins by iron supply and the transcription factor FER Plant Journal 54 321ndash334

Bu M (2007) The monosaccharide transporter(-like ) gene family in Arabidopsis Febs Letters 581 2318ndash2324

Buckler ES Thornsberry JM amp Kresovich S (2001) Molecular diversity structure and domestication of grasses Genetical research 77 213ndash218

Butler DG Cullis BR Gilmour AR Gogel BJ (2009) Analysis of mixed models for S language environments ASReml-R reference manual DPI Publications

Byrt CS Platten JD Spielmeyer W James RA Lagudah ES Dennis ES Tester M Munns R Dennis ES Tester M Munns R Byrt CS Platten JD Spielmeyer W James RA amp Lagudah ES (2007) HKT15-like cation transporters linked to Na+ exclusion loci in Wheat Nax2 and Kna1 Plant Physiology 143 1918ndash1928

Cairns JE Namuco OS Torres R Simborio FA Courtois B Aquino GA amp Johnson DE (2009) Field crops research investigating early vigour in upland rice (Oryza sativa L ) Part II Identification of QTLs controlling early vigour under greenhouse and field conditions Field Crops Research 113 207ndash217

Campbell MT (2017) Dissecting the genetic basis of salt tolerance in rice (Oryza sativa) The University of Nebraska

Campbell MT Knecht AC Berger B Brien CJ Wang D amp Walia H (2015) Integrating image-based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice Plant Physiology 168 1476ndash1489

Cao H Guo S Xu Y Jiang K Jones AM amp Chong K (2011) Reduced expression of a gene encoding a Golgi localized monosaccharide transporter (OsGMST1) confers hypersensitivity to salt in rice (Oryza sativa) Journal of Experimental Botany 62 4595ndash4604

Carpentier MC Manfroi E Wei FJ Wu HP Lasserre E Llauro C Debladis E Akakpo R Hsing YI amp Panaud O (2019) Retrotranspositional landscape of Asian rice revealed by 3000 genomes Nature Communications 10

Chandra Babu R Safiullah Pathan M Blum A amp Nguyen HT (1999) Comparison of measurement methods of osmotic adjustment in rice cultivars Crop Science 39 150ndash158

Chang WWP Huang L Shen M Webster C Burlingame AL amp Roberts JKM (2000) Patterns of protein synthesis and tolerance of anoxia in root tips of maize seedlings acclimated to a low-oxygen environment and identification of proteins by mass spectrometry Plant Physiology 122 295ndash318

Chapuis R Delluc C Debeuf R Tardieu F amp Welcker C (2012) Resiliences to water deficit in a phenotyping platform and in the field how related are they in maize European Journal of Agronomy 42 59ndash67

Chen C Zhiguo E amp Lin HX (2016) Evolution and molecular control of hybrid incompatibility in plants Frontiers in Plant Science 7 1ndash10

Chen Y Zhou X Chang S Chu Z Wang H Han S amp Wang Y (2017) Calcium-dependent protein kinase 21 phosphorylates 14-3-3 proteins in response to ABA signaling and salt stress in rice Biochemical and Biophysical Research Communications 493 1450ndash1456

Chen Z Newman I Zhou M Mendham N Zhang G amp Shabala S (2005) Screening plants for salt tolerance by measuring K+ flux A case study for barley Plant Cell and Environment 28 1230ndash1246

Cheng C Motohashi R Tsuchimoto S Fukuta Y Ohtsubo H amp Ohtsubo E (2003) Polyphyletic origin of cultivated rice Based on the interspersion pattern of SINEs Molecular Biology and Evolution 20 67ndash75

Cheng M Lowe BA Spencer TM Ye X amp Armstrong CL (2004) Factors influencing Agrobacterium-mediated transformation of monocotyledonous species In Vitro Cellular amp Developmental Biology - Plant 40 31ndash45

Cheng Y Qi Y Zhu Q Chen X Wang N Zhao X Chen H Cui X Xu L amp Zhang W (2009) New changes in the plasma-membrane-associated proteome of rice roots under salt stress Proteomics 9 3100ndash3114

Chiou T-J Tsai Y-C Huang T-K Chen Y-R Han C-L Sun C-M Chen Y-S Lin W-Y Lin S-I Liu T-Y Chen Y-J Chen J-W amp Chen P-M (2013) Identification of downstream components of ubiquitin-conjugating enzyme PHOSPHATE2 by quantitative membrane proteomics in Arabidopsis roots The Plant Cell 25 4044ndash4060

Cho J Il Burla B Lee DW Ryoo N Hong SK Kim HB Eom JS Choi SB Cho MH Bhoo SH Hahn TR Ekkehard Neuhaus H Martinoia E amp Jeon JS (2010) Expression analysis and functional characterization of the monosaccharide transporters OsTMTs involving vacuolar sugar transport in rice (Oryza sativa) New Phytologist 186 657ndash668

Choi JY amp Purugganan MD (2018) Multiple origin but single domestication led to Oryza sativa G3 Genes Genomes Genetics 8 797ndash803

Chunthaburee S Dongsansuk A amp Sanitchon J (2016) Physiological and biochemical parameters for evaluation and clustering of rice cultivars differing in salt tolerance at seedling stage Saudi Journal of Biological Sciences 23 467ndash477 King Saud University

Collard BCY amp Mackill DJ (2008) Marker-assisted selection An approach for precision plant breeding in the twenty-first century Philosophical Transactions of the Royal Society B Biological Sciences 363 557ndash572

Colmer TD Munns R amp Flowers TJ (2005) Improving salt tolerance of wheat and barley Future prospects Australian Journal of Experimental Agriculture 45 1425ndash1443

Colmer TD Flowers TJ amp Munns R (2006) Use of wild relatives to improve salt tolerance in wheat Journal of Experimental Botany 57 1059ndash1078

Cramer GR (2006) Sodium-calcium interactions under salinity stress Salinity Environment - Plants - Molecules 17 205ndash227

Dally AM amp Second G (1990) Chloroplast DNA diversity in wild and cultivated species of rice (Genus Oryza section Oryza ) Cladistic-mutation and genetic-distance analysis Theor Appl Genet 80 209ndash222

Dani V Simon WJ Duranti M amp Croy RRD (2005) Changes in the tobacco leaf apoplast proteome in response to salt stress Proteomics 5 737ndash745

Davenport RJ Muntildeoz-Mayor A Jha D Essah PA Rus A amp Tester M (2007) The Na+ transporter AtHKT11 controls retrieval of Na+ from the xylem in Arabidopsis Plant Cell and Environment 30 497ndash507

Demiral T amp Tuumlrkan I (2005) Comparative lipid peroxidation antioxidant defense systems and proline content in roots of two rice cultivars differing in salt tolerance Environmental and Experimental Botany 53 247ndash257

Derose-wilson L amp Gaut BS (2011) Mapping salinity tolerance during Arabidopsis thaliana germination and seedling growth PLoS One 6 8

Dimroth P (1997) Primary sodium ion translocating enzymes Biochimica et Biophysica Acta 1318 11-51

Dionisio-Sese ML amp Tobita S (2000) Effects of salinity on sodium content and photosynthetic responses of rice seedlings differing in salt tolerance Journal of Plant Physiology 157 54ndash58

Doerge RW (2002) Mapping and analysis of quantitative trait loci in experimental populations Nature Reviews Genetics 3 43ndash52

Downton WJS Grant WJR amp Robinson SP (1985) Photosynthetic and stomatal responses of spinach leaves to salt stress Plant Physiology 78 85ndash88

Dubey R amp Singh AK (1999) Salinity induced sugar accumulation in rice Biologia Plantarium 42 233ndash239

Edwards MD Stuber CW amp Wendel JF (1987) Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize I Numbers Genomic Distribution and Types of Gene Action Genetics 116 113ndash125

Epstein E Rains DW amp Elzam OE (1963) Resolution of dual mechanisms of potassium absorption by barley roots Proceedings of the National Academy of Sciences 49 684ndash692

Faiyue B Al-azzawi MJ amp Flowers TJ (2012) A new screening technique for salinity resistance in rice (Oryza sativa L) seedlings using bypass flow Plant cell 35 1099ndash1108

Feng H Tang Q Cai J Xu B Xu G amp Yu L (2019) Rice OsHAK16 functions in potassium uptake and translocation in shoot maintaining potassium homeostasis and salt tolerance Planta 250 549ndash561

Ferdose J Kawasaki M Taniguchi M amp Miyake H (2009) Differential sensitivity of rice

cultivars to salinity and its relation to ion accumulation and root tip structure Plant Production Science 12 453ndash461

Fernie AR Tadmor Y amp Zamir D (2006) Natural genetic variation for improving crop quality Current opinion in plant biology 9 196ndash202

Fiorani F amp Schurr U (2013) Future Scenarios for Plant Phenotyping Annual Review of Plant Biology 64 267ndash2912

Flowers T Duque E Hajibagheri M McGonigle T amp Yeo A (1985) The effect of salinity on leaf ultrastructure and net photosynthesis of two varieties of rice further evidence for a cellular component of salt‐resistance New Phytologist 100 37-43

Flowers TJ (1977) The mechanism of salt tolerance in halphytes Annual review of plant physiology 28 89ndash121

Flowers TJ (2004) Improving crop salt tolerance Journal of Experimental Botany 55 307ndash319

Ford KL Cassin A amp Bacic A (2011) Quantitative Proteomic Analysis of wheat cultivars with differing drought stress tolerance Frontiers in Plant Science 2 1ndash11

Frank A amp Pevzner P (2005) PepNovo De novo peptide sequencing via probabilistic network modeling 77 964ndash973

Fridman E Pleban T amp Zamir D (2000) A recombination hotspot delimits a wild-species quantitative trait locus for tomato sugar content to 484 bp within an invertase gene Proceedings of the National Academy of Sciences 97 4718ndash4723

Fuumlhrs H Hartwig M Molina LEB Heintz D Van Dorsselaer A Braun HP amp Horst WJ (2008) Early manganese-toxicity response in Vigna unguiculata L - A proteomic and transcriptomic study Proteomics 8 149ndash159

Fukuda A Nakamura A Tagiri A Tanaka H Miyao A Hirochika H amp Tanaka Y (2004) Function intracellular localization and the importance in salt tolerance of a vacuolar Na+H+ antiporter from rice Plant and Cell Physiology 45 146ndash159

Fuller DQ Sato YI Castillo C Qin L Weisskopf AR Kingwell-Banham EJ Song J Ahn SM amp van Etten J (2010) Consilience of genetics and archaeobotany in the entangled history of rice Archaeological and Anthropological Sciences 2 115ndash131

Gaby E Mbanjo N Jones H Greg X Caguiat I Carandang S Ignacio JC Ferrer MC Boyd LA amp Kretzschmar T (2019) Exploring the genetic diversity within traditional Philippine pigmented Rice Rice Rice

GB Gregorio D Senadhira RM (1997) Screening Rice for Salinity Tolerance IRRI discussion paper series No 22

Giacomelli L Rudella A amp Wijk KJ Van (2006) High light response of the thylakoid proteome in arabidopsis wild type and the ascorbate-decient mutant vtc2-2 A Comparative proteomics tudy Plant Physiology 141 685ndash701

Giaever G amp Nislow C (2014) The yeast deletion collection A decade of functional genomics Genetics 197 451ndash465

Gimhani DR Gregorio GB Kottearachchi NS amp Samarasinghe WLG (2016) SNP-based discovery of salinity-tolerant QTLs in a bi-parental population of rice (Oryza sativa) Molecular Genetics and Genomics 291 2081-2099

Golzarian MR Frick RA Rajendran K Berger B Roy S Tester M amp Lun DS (2011) Accurate inference of shoot biomass from high-throughput images of cereal plants 7 2

Greenway H amp Munns R (1980) Mechanisms of salt tolerance in nonhalophytes Annual review of plant biology 31 149ndash90

Grover A Aishwarya V amp Sharma PC (2007) Biased distribution of microsatellite motifs in the rice genome Molecular Genetics and Genomics 277 469ndash480

Gu R Fonseca S Puskaacutes LG Hackler L Zvara Aacute Dudits D amp Pais MS (2004) Transcript identification and profiling during salt stress and recovery of Populus euphratica Tree Physiology 24 265ndash276

Hairmansis A Berger B Tester M amp Roy SJ (2014) Image-based phenotyping for non-destructive screening of different salinity tolerance traits in rice Rice 7 1ndash10

Hajduch M Rakwal R Agrawal GK Yonekura M amp Pretova A (2001) Separation of proteins from metal-stressed rice (Oryza sativa L ) leaves Drastic reductionsfragmentation of ribulose-1 5-bisphosphate carboxylaseoxygenase and induction of stress-related proteins Electrophoresis 22 2824ndash2831

Hake S amp Richardson A (2019) Using wild relatives to improve maize Science 365 640ndash641

Hall TA (1999) BioEdit a user-friendly biological sequence alignment editor and analysis program for Windows 9598NT Nucleic Acids Symposium Series 41 95ndash98

Harberd NP Belfield E amp Yasumura Y (2009) The angiosperm gibberellin-GID1-DELLA growth regulatory mechanism how an ldquoinhibitor of an inhibitorrdquo enables flexible response to fluctuating environments The Plant cell 21 1328ndash39

Harlan JR De Wet JM amp Price EG (1973) Comparative evolution of cereals Evolution 27 311ndash325

Harris BN Sadras VO amp Tester M (2010) A water-centred framework to assess the effects of salinity on the growth and yield of wheat and barley Plant and Soil 336 377ndash389

Hasegawa PM amp Bressan RA (2000) Plant cellular and molecular responses to high salinity Annual review of plant physiology 51 463ndash499

Hashimoto M amp Komatsu S (2007) Proteomic analysis of rice seedlings during cold stress Proteomics 7 1293ndash1302

Hauser F amp Horie T (2010) A conserved primary salt tolerance mechanism mediated by HKT transporters A mechanism for sodium exclusion and maintenance of high K+Na+ ratio in leaves during salinity stress Plant Cell and Environment 33 552ndash565

He Y Yang B He Y Zhan C Cheng Y Zhang J Zhang H Cheng J amp Wang Z (2018) A quantitative trait locus qSE3 promotes seed germination and seedling establishment under salinity stress in rice Plant Journal 97 1089-1104

He Z Zhai W Wen H Tang T Wang Y Lu X Greenberg AJ Hudson RR Wu CI amp Shi S (2011) Two evolutionary histories in the genome of rice The roles of domestication genes PLoS Genetics 7 1ndash10

Heenan D Lewin L amp McCaffery D (1988) Salinity tolerance in rice varieties at different growth stages Australian Journal of Experimental Agriculture 28 343ndash349

Hena A Kamal M amp Cho K (2012) Changes in physiology and protein abundance in salt-stressed wheat chloroplasts Molecular Biology Reports 39 9059ndash9074

Henry RJ Rice N Waters DLE Kasem S Ishikawa R Hao Y Dillon S Crayn D Wing R amp Vaughan D (2010) Australian Oryza utility and conservation Rice 3 235ndash241

Hikosaka K Ishikawa K Borjigidai A Muller O amp Onoda Y (2006) Temperature acclimation of photosynthesis Mechanisms involved in the changes in temperature dependence of photosynthetic rate Journal of Experimental Botany 57 291ndash302

Hoang T Tran T Nguyen T Williams B Wurm P Bellairs S amp Mundree S (2016)

Improvement of salinity stress tolerance in rice challenges and opportunities Agronomy 6 54

Hodges TK amp Mills D (1986) Isolation of the plasma membrane Methods in enzytmologymology 18 41-54

Hoffman GJ Maas E V Prichard TL amp Meyer JL (1983) Salt tolerance of corn in the Sacramento-San Joaquin delta of California Irrigation Science 4 31ndash44

Horie T Karahara I amp Katsuhara M (2012) Salinity tolerance mechanisms in glycophytes An overview with the central focus on rice plants Rice 5 11

Huang F Zhang Z Zhang Y Zhang Z Lin W amp Zhao H (2017) The important functionality of 14-3-3 isoforms in rice roots revealed by affinity chromatography Journal of Proteomics 158 20ndash30

Huang W amp Mackay TFC (2016) The Genetic Architecture of Quantitative Traits Cannot Be Inferred from Variance Component Analysis PLoS Genetics 12 1ndash15

Huang X Kurata N Wei X Wang Z-X Wang A Zhao Q Zhao Y Liu K Lu H Li W Guo Y Lu Y Zhou C Fan D Weng Q Zhu C Huang T Zhang L Wang Y Feng L Furuumi H Kubo T Miyabayashi T Yuan X Xu Q Dong G Zhan Q Li C Fujiyama A Toyoda A Lu T Feng Q Qian Q Li J amp Han B (2012) A map of rice genome variation reveals the origin of cultivated rice Nature 490 497ndash501

Huang XQ Coster H Ganal MW amp Roder MS (2003) Advanced backcross QTL analysis for the identification of quantitative trait loci alleles from wild relatives of wheat (Triticum aestivum L) Theoretical and Applied Genetics 106 1379ndash1389

Hurkman WJ Tao HP amp Tanaka CK (1997) Germin-like polypeptides increase in barley roots during salt stress Plant Physiology 97 366ndash374

Hurry VM Strand A Tobiaeson M Gardestrom P amp Oquist G (1995) Cold hardening of spring and winter wheat and rape results in differential effects on crowth carbon metabolism and carbohydrate content Plant Physiology 109 697ndash706

Imin N Kerim T Rolfe BG amp Weinman JJ (2004) Effect of early cold stress on the maturation of rice anthers Proteomics 4 1873ndash1882

Imin N Kerim T Weinman JJ amp Rolfe BG (2006) Low temperature treatment at the young microspore stage induces protein changes in rice anthers Molecular amp Cellular Proteomics 5 274ndash292

IRRI (2013) Standard Evaluation System (SES) for Rice International Rice Research Institute

Jackson MT (1997) Conservation of rice genetic resources the role of the International Rice Genebank at IRRI Plant Molecular Biology 35 61ndash67

Jacquemin J Bhatia D Singh K amp Wing RA (2013) The international Oryza map alignment project Development of a genus-wide comparative genomics platform to help solve the 9 billion-people question Current Opinion in Plant Biology 16 147ndash156

Jain M Nijhawan A Tyagi AK amp Khurana JP (2006) Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR Biochemical and Biophysical Research Communications 345 646ndash651

James RA Rivelli AR Munns R amp Von Caemmerer S (2002) Factors affecting CO2 assimilation leaf injury and growth in salt-stressed durum wheat Functional Plant Biology 29 1393ndash1403

Jamil A Riaz S Ashraf M amp Foolad MR (2011) Gene expression profiling of plants under salt stress Critical Reviews in Plant Sciences 30 435ndash458

Jayakannan M Bose J Babourina O Rengel Z amp Shabala S (2013) Salicylic acid

improves salinity tolerance in Arabidopsis by restoring membrane potential and preventing salt-induced K+ loss via a GORK channel Journal of Experimental Botany 64 2255ndash2268

Jena KK (2010) The species of the genus Oryza and transfer of useful genes from wild species into cultivated rice O sativa Breeding Science 60 518ndash523

Jiang CF Belfield EJ Cao Y Smith JAC amp Harberd NP (2013) An arabidopsis soil-salinity-tolerance mutation confers ethylene-mediated enhancement of sodiumpotassium homeostasis Plant Cell 25 3535ndash3552

Kapp LD amp Lorsch JR (2004) The molecular mechanics of eukaryotic translation Annual Review of Biochemistry 73 657ndash704

Katerji N Van Hoorn JW Hamdy A amp Mastrorilli M (2000) Salt tolerance classification of crops according to soil salinity and to water stress day index Agricultural Water Management 43 99ndash109

Khatun S amp Flowers TJ (1995) Effects of salinity on seed set in rice Plant Cell amp Environment 18 61ndash67

Khush GS (1997) Origin dispersal cultivation and variation of rice Plant Molecular Biology 35 25ndash34

Khush GS (2005) What it will take to feed 50 billion rice consumers in 2030 Plant Molecular Biology 59 1ndash6

Kieffer P Dommes J Hoffmann L Hausman JF amp Renaut J (2008) Quantitative changes in protein expression of cadmium-exposed poplar plants Proteomics 8 2514ndash2530

Kim S Jeon J amp An G (2011) Development of an Efficient Inverse PCR Method for Isolating Gene Tags from T-DNA Insertional Mutants in Rice Pp 139ndash146 in Plant Reverse Genetics Methods and Protocols

Kingston-Smith A Walker RP amp Pollock C (1999) Invertase in leaves conundrum or control point Journal of Experimental Botany 50 735ndash743

Kobayashi NI Yamaji N Yamamoto H Okubo K Ueno H Costa A Tanoi K Matsumura H Fujii-Kashino M Horiuchi T Nayef M Al Shabala S An G Ma JF amp Horie T (2017) OsHKT15 mediates Na+ exclusion in the vasculature to protect leaf blades and reproductive tissues from salt toxicity in rice Plant Journal 91 657ndash670

Koller A Washburn MP Lange BM Andon NL Deciu C Haynes PA Hays L Schieltz D Ulaszek R Wei J Wolters D amp Yates JR (2002) Proteomic survey of metabolic pathways in rice Proceedings of the National Academy of Sciences 99 11969ndash11974

Komatsu S (2005) Rice Proteome Database A step toward functional analysis of the rice genome Plant Molecular Biology 59 179ndash190

Komatsu S amp Yano H (2006) Update and challenges on proteomics in rice Proteomics 6 4057ndash4068

Koornneef M amp Stam P (2001) Changing paradigms in plant breeding Plant physiology 125 156ndash159

Koqro HW Stelzer R amp Huchzermeyer B (1993) ATPase activities and membrane fine structure of rhizodermal cells from sorghum and spartina roots grown under mild salt stress Botanica Acta 106 110ndash119

Kovach MJ Sweeney MT amp Mccouch SR (2007) New insights into the history of rice domestication Trends in Genetics 23 578ndash587

Krishnamurthy P Ranathunge K Franke R Prakash HS Schreiber L amp Mathew MK (2009) The role of root apoplastic transport barriers in salt tolerance of rice (Oryza sativa L) Planta 230 119ndash134

Krishnamurthy SL Sharma PC Sharma SK Batra V Kumar V amp Rao LVS (2016) Effect of salinity and use of stress indices of morphological and physiological traits at the seedling stage in rice Indian Journal of Experimental Biology 54 843ndash850

Kromdijk J amp Long SP (2016) One crop breeding cycle from starvation How engineering crop photosynthesis for rising CO2 and temperature could be one important route to alleviation Proceedings of the Royal Society B Biological Sciences 283 20152578

Kumar PA amp Bandhu DA (2005) Salt tolerance and salinity effects on plants A review Ecotoxicology and Environmental Safety 60 324ndash349

Lalonde S Wipf D amp Frommer WB (2004) Transport mechanisms for organic forms of carbon and nitrogen between source and sink Annual Review of Plant Biology 55 341ndash372

Lee DG Ahsan N Lee SH Kang KY Lee JJ amp Lee BH (2007) An approach to identify cold-induced low-abundant proteins in rice leaf Comptes Rendus - Biologies 330 215ndash225

Lee DG Ahsan N Lee SH Lee JJ Bahk JD Kang KY amp Lee BH (2009) Chilling stress-induced proteomic changes in rice roots Journal of Plant Physiology 166 1-11

Lee KS Choi WY Ko JC Kim TS amp Gregorio G (2003) Salinity tolerance of japonica and indica rice (Oryza sativa L) at the seedling stage Planta 216 1043ndash1046

De Leon TB Linscombe S amp Subudhi PK (2017) Identification and validation of QTLs for seedling salinity tolerance in introgression lines of a salt tolerant rice landrace ldquoPokkalirdquo PLoS One 12 1ndash30

Leshem Y Melamed-book N Cagnac O Ronen G Nishri Y Solomon M Cohen G amp Levine A (2006) Suppression of Arabidopsis vesicle-SNARE expression inhibited fusion of H2O2-containing vesicles with tonoplast and increased salt tolerance Proceedings of the National Academy of Sciences of the United States of America 103 18008-18013

Leyman B Geelen D amp Blatt MR (2000) Localization and control of expression of Nt-Syr1 a tobacco snare protein Plant Journal 24 369ndash381

Li Q Yang A amp Zhang WH (2017) Comparative studies on tolerance of rice genotypes differing in their tolerance to moderate salt stress BMC Plant Biology 17 141

Liang W Ma X Wan P amp Liu L (2018) Plant salt-tolerance mechanism A review Biochemical and Biophysical Research Communications 495 286ndash291

Liberato CG A JA V Barros Virgilio A C R Machado Nogueira ARA NOacutebrega JA Daniela amp Schiavo (2017) Determination of macro and micronutrients in plants using the Agilent 4200 MP AES Application note Agilent Technologies 1ndash5

Lilley JM amp Ludlow MM (1996) Expression of osmotic adjustment and dehydration tolerance in diverse rice lines Field Crops Research 48 185ndash197

Lilley JM Ludlow MM McCouch SR amp OrsquoToole JCC (1996) Locating QTL for osmotic adjustment and dehydration tolerance in rice Journal of Experimental Botany 47 1427ndash1436

Liu A amp Burke JM (2006) Patterns of nucleotide diversity in wild and cultivated sunflower Genetics 173 321ndash330

Liu C Hsu Y Cheng Y Yen H Wu Y Wang C amp Lai C (2012) Proteomic analysis of salt-responsive ubiquitin-related proteins in rice roots Rapid Communications in Mass Spectrometry 26 1649ndash1660

Liu C Ou S Mao B Tang J Wang W Wang H Cao S Schlaumlppi MR Zhao B Xiao G Wang X amp Chu C (2018) Early selection of bZIP73 facilitated adaptation of japonica rice to cold climates Nature Communications 9 1ndash12

Liu K amp Muse S V (2005) PowerMaker An integrated analysis environment for genetic maker analysis Bioinformatics 21 2128ndash2129

Lohse M Nagel A Herter T May P Schroda M Zrenner R Tohge T Fernie AR Stitt M amp Usadel B (2014) Mercator A fast and simple web server for genome scale functional annotation of plant sequence data Plant Cell and Environment 37 1250ndash1258

Low R Rockel B Kirsch M Ratajczak R Hortensteiner S Martinoia E Luttge U amp Rausch T (2002) Early salt stress effects on the differential expression of vacuolar H+-ATPase genes in roots and leaves of mesembryanthemum crystallinum Plant Physiology 110 259ndash265

Lu X Niu A Cai H Zhao Y Liu J Zhu Y amp Zhang Z (2007) Genetic dissection of seedling and early vigor in a recombinant inbred line population of rice Plant Science 172 212ndash220

Ludewig F amp Sonnewald U (2016) Demand for food as driver for plant sink development Journal of Plant Physiology 203 110ndash115

Lundstroumlm M Leino MW amp Hagenblad J (2017) Evolutionary history of the NAM-B1 gene in wild and domesticated tetraploid wheat BMC Genetics 18 1ndash10

Luo J Ning T Sun Y Zhu J Zhu Y Lin Q amp Yang D (2009) Proteomic analysis of rice endosperm cells in response to expression of HGM-CSF Journal of Proteome Research 8 829ndash837

Lutts S Kinet JM amp Bouharmont J (1995) Changes in plant response to NaCl during development of rice (Oryza sativa L) varieties differing in salinity resistance Journal of Experimental Botany 46 1843ndash1852

Lutts S Kinet JM amp Bouharmont J (1996) NaCl-induced Senescence in leaves of rice (Oryza sativa L) cultivars differing Annals of Botany 78 389ndash398

Lyon C B (1941) Responses of two species of tomatoes and the F1 generation to sodium sulphate in the nutrient medium Botanical Gazette 103 107ndash122

M Akbar TYN (1972) Breeding for saline-resistent varieties of rice Japanese Journal of Breeding 22 227ndash284

Ma B amp Johnson R (2012) De novo sequencing and homology Molecular amp Cellular Proteomics 11 2

Ma NL Che Lah WA Kadir NA Mustaqim M Rahmat Z Ahmad A Lam SD amp Ismail MR (2018) Susceptibility and tolerance of rice crop to salt threat Physiological and metabolic inspections PLoS One 13 1ndash17

Maathuis FJM Filatov V Herzyk P Krijger GC Axelsen KB Chen S Forde BG Michael G Rea PA Williams LE Sanders D amp Amtmann A (2003) Transcriptome analysis of root transporters reveals participation of multiple gene families in the response to cation stress The Plant Journal 35 675ndash692

Mackay TFC (2001) The genetic architecture of quantitative traits Annual Review of Genetics 35 303ndash339

Mackinney G (1941) Absorption of light by chlorophyll The Journal of Biological Chemistry 140 315ndash322

Maggio A Raimondi G Martino A amp De Pascale S (2007) Salt stress response in tomato beyond the salinity tolerance threshold Environmental and Experimental Botany 59

276ndash282

Masson F amp Rossignol M (1995) Basic plasticity of protein expression in tobacco plasma membrane Plant Journal 8 77ndash85

Matsushita N amp Matoh T (1991) Characterization of Na+ exclusion mechanisms of salt‐tolerant reed plants in comparison with salt‐sensitive rice plants Physiologia Plantarum 83 170ndash176

Maurel C Verdoucq L Luu DT amp Santoni V (2008) Plant aquaporins membrane channels with multiple integrated functions Annual review of plant biology 59 595ndash624

Mauricio R (2001) Mapping quantitative trait loci in plants uses and caveats for evolutionary biology Nature reviews Genetics 2 370ndash381

McLean J Hardy B amp Hettel G (2013) Rice Almanac P in IRRI Los Bantildeos Philippines 298

Meisrimler C-N Wienkoop S amp Luumlthje S (2017) Proteomic profiling of the microsomal root fraction discrimination of pisum sativum L cultivars and identification of putative root growth markers Proteomes 5 8

Meloni DA Oli MA amp Martinez CA (2003) Photosynthesis and activity of superoxide dismutase peroxidase and glutathione reductase in cotton under salt stress Environmental and Experimental Botany 49 69ndash76

Michelson I Zamir D amp Czosnek H (1994) accumulation and translocation of TYLCV in a Lycopersicon esculentum breeding line containing the L chilense TYLCV Tolerance Gene Ty-1 Phytopathology 84 928ndash933

Mikio T Miyuki M amp Hitoshi N (1994) Physiological response to salinity in rice plant III A possible mechanism for Na+ exclusion in rice root under NaCl-stress conditions Japanese Journal of Crop Science 63 326ndash332

Mirzaei M Soltani N Sarhadi E Pascovici D Keighley T Salekdeh GH Haynes PA amp Atwell BJ (2012) Shotgun proteomic analysis of long-distance drought signaling in rice roots Journal of proteome research 11 348ndash358

Mirzaei M Pascovici D Wu JX Chick J Wu Y Cooke B amp Molloy MP (2017) TMT one‐stop shop from reliable sample preparation to computational analysis platform Methods in Molecular Biology 1549 45ndash66

Mishra A amp Tanna B (2017) Halophytes potential resources for salt stress tolerance genes and promoters Frontiers in plant science 8 1ndash10

Mishra P Jain A Takabe T Tanaka Y Negi M Singh N Jain N Mishra V Maniraj R Krishnamurthy SL Sreevathsa R Singh NK amp Rai V (2019) Heterologous expression of serine hydroxymethyltransferase-3 from rice confers tolerance to salinity stress in E Coli and arabidopsis Frontiers in Plant Science 10 1ndash17

Mitra SK Clouse SD amp Goshe MB (2009) Chapter 20 enrichment and preparation of plasma membrane proteins from arabidopsis thaliana for global proteomic analysis using liquid chromatography ndash tandem mass spectrometry Pp 341ndash355 in Proteomics

Mohanty S Wassmann R Nelson A Moya P amp Jagadish SVK (2013) The important of rice for food and nutritional security Pp 1ndash5 in Rice and Climate Change Significance for Food Security and Vulnerability IRRI

Molina J Sikora M Garud N Flowers JM Rubinstein S Reynolds A Huang P Jackson S Schaal BA Bustamante CD Boyko AR amp Purugganan MD (2011) Molecular evidence for a single evolutionary origin of domesticated rice Proceedings of the National Academy of Sciences of the United States of America 108 8351ndash6

Moslashller IS Gilliham M Jha D Mayo GM Roy SJ Coates JC Haseloff J amp Tester

M (2009) Shoot Na+ exclusion and increased salinity tolerance engineered by cell type-specific alteration of Na+ transport in Arabidopsis The Plant cell 21 2163ndash2178

Mondal TK Panda AK Rawal HC amp Sharma TR (2018a) Discovery of microRNA-target modules of African rice (Oryza glaberrima) under salinity stress Scientific Reports 8 1ndash11

Mondal TK Rawal HC Chowrasia S Varshney D Panda AK Mazumdar A Kaur H Gaikwad K Sharma TR amp Singh NK (2018b) Draft genome sequence of first monocot-halophytic species Oryza coarctata reveals stress-specific genes Scientific Reports 8 1ndash13

Moradi F amp Ismail AM (2007) Responses of photosynthesis chlorophyll fluorescence and ROS-scavenging systems to salt stress during seedling and reproductive stages in rice Annals of Botany 99 1161ndash1173

Muir JF Pretty J Robinson S Thomas SM amp Toulmin C (2010) Food security The challenge of feeding 9 billion people Science 327 812-818

Mulkidjanian AY Galperin MY Makarova KS Wolf YI amp Koonin EV (2008) Evolutionary primacy of sodium bioenergetics Biology Direct 3 1ndash19

Munns R (2011) Plant adaptations to salt and water stress differences and commonalities Advances in Botanical Research 57 1ndash32

Munns R amp Termaat A (1986) Whole-plant responses to salinity Australian Journal of Plant Physiology 13 143ndash160

Munns R amp Tester M (2008) Mechanisms of salinity tolerance Annual review of plant biology 59 651ndash81

Munns R Tonnet L M Shennan C amp Anne Gardner P (1988) Effect of high external NaCl concentration on ion transport within the shoot of Lupinus albus II Ions in phloem sap Plant Cell amp Environment 11 291ndash300

Munns R James RA amp Lauchli A (2006) Approaches to increasing the salt tolerance of wheat and other cereals Journal of Experimental Botany 57 1025ndash1043

Munns R James RA Gilliham M Flowers TJ amp Colmer TD (2016) Tissue tolerance an essential but elusive trait for salt-tolerant crops Functional Plant Biology 43 1103ndash1113

Murchie EH amp Horton P (1997) Acclimation of photosynthesis to irradiance and spectral quality in British plant species Chlorophyll content photosynthetic capacity and habitat preference Plant Cell and Environment 20 438ndash448

Nadeem SM Ahmad M Zahir ZA Javaid A amp Ashraf M (2014) The role of mycorrhizae and plant growth promoting rhizobacteria (PGPR) in improving crop productivity under stressful environments Biotechnology Advances 32 429ndash448

Ndimba BK Chivasa S Simon WJ amp Slabas AR (2005) Identification of Arabidopsis salt and osmotic stress responsive proteins using two-dimensional difference gel electrophoresis and mass spectrometry Proteomics 5 4185ndash4196

Neilson EH Edwards AM Blomstedt CK Berger B Moslashller BL amp Gleadow RM (2015) Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time Journal of Experimental Botany 66 1817ndash1832

Neilson KA Gammulla CG Mirzaei M Imin N amp Haynes PA (2010) Proteomic analysis of temperature stress in plants Proteomics 10 828ndash845

Neilson KA Mariani M amp Haynes PA (2011) Quantitative proteomic analysis of cold-responsive proteins in rice Proteomics 11 1696ndash1706

Ngampanya B Sobolewska A Takeda T Toyofuku K Narangajavana J Ikeda A amp Yamaguchi J (2003) Characterization of Rice Functional Monosaccharide Transporter OsMST5 Bioscience Biotechnology and Biochemistry 67 556ndash562

Nicolas M Munns R Samarakoon A amp Gifford R (1993) Elevated CO2 Improves the Growth of Wheat Under Salinity Functional Plant Biology 20 349

Niemietz C amp Willenbrink J (1985) The function of tonoplast ATPase in intact vacuoles of red beet is governed by direct and indirect ion effects Planta 20 545ndash549

Niknam SR amp McComb J (2000) Salt tolerance screening of selected Australian woody species- A review Forest Ecology and Management 139 1ndash19

Nishikawa T Vaughan DA amp Kadowaki K (2005) Phylogenetic analysis of Oryza species based on simple sequence repeats and their flanking nucleotide sequences from the mitochondrial and chloroplast genomes The Plant Genome 110 696ndash705

Nohzadeh M Sahar HR Mehran H Manzar H amp Salekdeh G (2007) Proteomics reveals new salt responsive proteins associated with rice plasma membrane Bioscience Biotechnology and Biochemistry 71 2144ndash2154

Noslashrholm MHH Nour-Eldin HH Brodersen P Mundy J amp Halkier BA (2006) Expression of the Arabidopsis high-affinity hexose transporter STP13 correlates with programmed cell death FEBS Letters 580 2381ndash2387

Oa AW Kim S amp Bassham DC (2011) TNO1 Is Involved in salt tolerance and vacuolar Plant Physiology 156 514ndash526

Oda Y Kobayashi NI Tanoi K Ma JF Itou Y Katsuhara M Itou T amp Horie T (2018) T-DNA tagging-based gain-of-function of OsHKT14 reinforces Na exclusion from leaves and stems but triggers Na toxicity in roots of rice under salt stress International Journal of Molecular Sciences 19 1ndash14

Ohta M Hayashi Y Nakashima A Hamada A Tanaka A Nakamura T amp Hayakawa T (2002) Introduction of a Na+H+ antiporter gene from the halophyte Atriplex gmelini confers salt tolerance to rice FEBS Lett 532 279ndash282

Palmisano G Lendal SE Engholm-Keller K Leth-Larsen R Parker BL amp Larsen MR (2010) Selective enrichment of sialic acid-containing glycopeptides using titanium dioxide chromatography with analysis by HILIC and mass spectrometry Nature Protocols 5 1974ndash1982

Pant SR Matsye PD McNeece BT Sharma K Krishnavajhala A Lawrence GW amp Klink VP (2014) Syntaxin 31 functions in Glycine max resistance to the plant parasitic nematode Heterodera glycines Plant Molecular Biology 85 107ndash121

Pappin DJC Creasy DM Cottrell JS amp Perkins DN (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data Electrophoresis 20 3551ndash67

Park HJ Kim W-Y amp Yun D-J (2016) A new insight of salt stress signaling in plant Molecules and Cells 39 447ndash459

Paulsen PA Custoacutedio TF amp Pedersen BP (2019) Crystal structure of the plant symporter STP10 illuminates sugar uptake mechanism in monosaccharide transporter superfamily Nature Communications 10 407

Peleg Z amp Blumwald E (2011) Hormone balance and abiotic stress tolerance in crop plants Current Opinion in Plant Biology 14 290ndash295

Pfaffl MW (2001) A new mathematical model for relative quantification in real-time RT-PCR Pp 63ndash82 in Nucleic Acids Res

Picotti P amp Aebersold R (2015) Selected reaction monitoringndash based proteomics workflows

potential pitfalls and future directions Nature 9 555

Piegu B Guyot R Picault N Roulin A Saniyal A Kim H Collura K Brar DS Jackson S Wing RA amp Panaud O (2006) Doubling genome size without polyploidizationthinsp Dynamics of retrotransposition-driven genomic expansions in Oryza australiensis a wild relative of rice Proteome Science 16 1262ndash1269

Pires IS Negratildeo S Oliveira MM amp Purugganan MD (2015) Comprehensive phenotypic analysis of rice (Oryza sativa) response to salinity stress Physiologia Plantarum 155 43ndash54

Platten JD Egdane JA amp Ismail AM (2013) Salinity tolerance Na+ exclusion and allele mining of HKT15 in Oryza sativa and O glaberrima many sources many genes one mechanism BMC Plant Biology 13 32

Prusty MR Kim S-R Vinarao R Entila F Egdane J Diaz MGQ amp Jena KK (2018) Newly identified wild rice accessions conferring high salt tolerance might use a tissue tolerance mechanism in leaf Frontiers in Plant Science 9 1ndash15

Qadir M Quilleacuterou E Nangia V Murtaza G Singh M Thomas RJ Drechsel P amp Noble AD (2014) Economics of salt-induced land degradation and restoration Natural Resources Forum 38 282ndash295

Qihui Z Xiaoming Z Jingchu L Brandon SG amp Song G (2007) Analysis of nucleotide variation of Oryza sativa and its wild relatives severe bottleneck during domestication of rice Molecular Biology and Evolution 24 875ndash888

Quirino BF Reiter WD amp Amasino RD (2001) One of two tandem Arabidopsis genes homologous to monosaccharide transporters is senescence-associated Plant Molecular Biology 46 447ndash457

Rabello AR Guimaratildees CM Rangel PHN Felipe R Seixas D Souza E De Brasileiro ACM Spehar CR Ferreira ME amp Mehta Acirc (2008) Identification of drought-responsive genes in roots of upland rice (Oryza sativa L ) BMC genomics 9 485

Radanielson AM Gaydon DS Li T Angeles O amp Roth CH (2018) Modeling salinity effect on rice growth and grain yield with ORYZA v3 and APSIM-Oryza European Journal of Agronomy 100 44ndash55

Rahman ML Jiang W Chu SH Qiao Y Ham TH Woo MO Lee J Khanam MS Chin JH Jeung JU Brar DS Jena KK amp Koh HJ (2009) High-resolution mapping of two rice brown planthopper resistance genes Bph20(t) and Bph21(t) originating from Oryza minuta Theoretical and Applied Genetics 119 1237ndash1246

Rajendran K Tester M amp Roy SJ (2009) Quantifying the three main components of salinity tolerance in cereals Plant Cell and Environment 32 237ndash249

Ram T Majumder ND Mishra B Ansari MM amp Padmavathi G (2007) Introgression of broad-spectrum blast resistance gene(s) into cultivated rice (Oryza sativa ssp indica) from wild rice O rufipogon Current Science 92 225ndash230

Rebolledo MC Dingkuhn M Courtois B Gibon Y amp Cruz DF (2015) Phenotypic and genetic dissection of component traits for early vigour in rice using plant growth modelling sugar content analyses and association mapping Journal of Experimental Botany 66 5555ndash5566

Ren D Rao Y Wu L Xu Q Li Z Yu H Zhang Y Leng Y Hu J Zhu L Gao Z Dong G Zhang G Guo L Zeng D amp Qian Q (2016) The pleiotropic ABNORMAL FLOWER AND DWARF1 affects plant height floral development and grain yield in rice Journal of Integrative Plant Biology 58 529ndash539

Ren Z Gao J Li L Cai X Huang W Chao D Zhu M Wang Z Luan S amp Lin H

(2005) A rice quantitative trait locus for salt tolerance encodes a sodium transporter Nature Genetics 37 1141ndash1147

Rengasamy P (2006) World salinization with emphasis on Australia Journal of Experimental Botany 57 1017ndash1023

Reuveni M Bennett AB Bressan RA amp Hasegawa PM (1990) Enhanced H+ transport capacity and ATP hydrolysis activity of the tonoplast H-ATPase after NaCI adaptation Plant Physiology 94 524ndash530

Richardson SG amp McCree KJ (1985) Carbon Balance and water relations of sorghum exposed to salt and water stress Plant Physiology 79 1015ndash1020

Rick CM (1974) High soluble-solids content in large-fruited tomato lines derived from a wild green-fruited species Hilgardia 42 493ndash510

Roy S amp Chakraborty U (2018) Role of sodium ion transporters and osmotic adjustments in stress alleviation of Cynodon dactylon under NaCl treatment a parallel investigation with rice Protoplasma 255 175ndash191

Roy SJ Negratildeo S amp Tester M (2014) Salt resistant crop plants Current Opinion in Biotechnology 26 115ndash124

Ruppert C amp Lemker T (1999) Structure and Function of the A1 A0-ATPases from methanogenic archaea Journal ofBioenergetics and Biomembranes 31 15ndash27

Sabouri H amp Sabouri A (2008) New evidence of QTLs attributed to salinity tolerance in rice African Journal of Biotechnology 7 4376ndash4383

Salekdeh GH Siopongco J Wade LJ Ghareyazie B amp Bennett J (2002) A proteomic approach to analyzing drought- and salt-responsiveness in rice Field Crops Research 76 199ndash219

Sang T amp Ge S (2007) The puzzle of rice domestication Journal of Integrative Plant Biology 49 760ndash768

Saranga Y Zamir D Marani amp Rudich J (1991) Breeding tomatoes for salt tolerance field evaluation of Lycopersicon germplasm for yield and dry-matter production Journal of the American Society for Horticultural Science 116 1067ndash1071

Saranga Y Cahaner A Zamir D Marani A amp Rudich J (1992) Breeding tomatoes for salt tolerance inheritance of salt tolerance and related traits in interspecific populations Theoretical and Applied Genetics 84 390ndash396

Sarangi SK Town C Misra RC amp Pradhan S (2013) Performance of Rice Germplasm (Oryza sativa L) under Coastal Saline Performance of Rice Germplasm (Oryza sativa L) under Coastal Saline Conditions Journal of the Indian Society of Coastal Agricultural Research 31 1ndash7

Sauer N amp Stadler R (1993) A sink-specific H+monosaccharide co- transporter from Nicotiana tabacum cloning and heterologous expression in bakerrsquos yeast The Plant Journal 4 601ndash610

Savitski MM Wilhelm M Hahne H Kuster B amp Bantscheff M (2015) A scalable approach for protein false discovery rate estimation in large proteomic data sets Molecular amp Cellular Proteomics 14 2394ndash2404

Sax K (1923) The association of size differences with Genetics 8 552ndash560

Scafaro AP Atwell BJ Muylaert S Van Reusel B Alguacil Ruiz G Van Rie J amp Galleacute A (2018) A thermotolerant variant of Rubisco activase from a wild relative improves growth and seed yield in rice under heat stress Frontiers in Plant Science 9 1663

Schwanhaumlusser B Busse D Li N Dittmar G Schuchhardt J Wolff J Chen W amp

Selbach M (2011) Genome-wide parallel quantification of mRNA and protein levels and turnover in mammalian cells Nature 437 337ndash342

Senadheera P Singh RK amp Maathuis FJM (2009) Differentially expressed membrane transporters in rice roots may contribute to cultivar dependent salt tolerance Journal of Experimental Botany 60 2553ndash2563

Serraj R amp Sinclair TR (2002) Osmolyte accumulation Can it really help increase crop yield under drought conditions Plant Cell and Environment 25 333ndash341

Shalata A amp Tal M (1998) The effect of salt stress on lipid peroxidation and antioxidants in the leaf of the cultivated tomato and its wild salt-tolerant relative Lycopersicon pennellii Physioligia Plantarum 104 169ndash174

Shao HB Guo QJ Chu LY Zhao XN Su ZL Hu YC amp Cheng JF (2007) Understanding molecular mechanism of higher plant plasticity under abiotic stress Colloids and Surfaces B Biointerfaces 54 37ndash45

Shen Y Shen L Shen Z Jing W Ge H Zhao J amp Zhang W (2015) The potassium transporter OsHAK21 functions in the maintenance of ion homeostasis and tolerance to salt stress in rice Plant Cell and Environment 38 2766ndash2779

Shereen A Mumtaz S Raza S Khan M amp Solangi S (2005) Salinity effects on seedling growth and yield components of different inbred rice lines Pakistan Journal of Botany 37 131ndash139

Shi H Ishitani M Cheolsoo K amp Jian-Kang Z (2000) The Arabidopsis thaliana salt tolerance gene SOS1 encodes a putative NaH antiporter Proceedings of the National Academy of Sciences 97 6896ndash6901

Shi H Lee B ha Wu SJ amp Zhu JK (2003) Overexpression of a plasma membrane Na+H+ antiporter gene improves salt tolerance in Arabidopsis thaliana Nature Biotechnology 21 81ndash85

Shoeb F Yadav JS Bajaj S amp Rajam M V (2001) Polyamines as biomarkers for plant regeneration capacity Improvement of regeneration by modulation of polyamine metabolism in different genotypes of indica rice Plant Science 160 1229ndash1235

Shukla RK Tripathi V Jain D Yadav RK amp Chattopadhyay D (2009) CAP2 enhances germination of transgenic tobacco seeds at high temperature and promotes heat stress tolerance in yeast FEBS Journal 276 5252ndash5262

Shylaraj KS amp Sasidharan NK (2005) VTL 5thinsp A high yielding salinity tolerant rice variety for the coastal saline ecosystems of Kerala Journal of Tropical Agriculture 43 25ndash28

Si Y Zhang C amp Meng S (2009) Gene expression changes in response to drought stress in Citrullus colocynthis Plant Cell Reports 28 997ndash1009

Siddiqui ZS Cho JI Park SH Kwon TR Ahn BO Lee GS Jeong MJ Kim KW Lee SK PSC (2014) Phenotyping of rice in salt stress environment using high-throughput infrared imaging Acta Bot Croat 73 149ndash158

Sirault XRR James RA amp Furbank RT (2009) A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography Functional Plant Biology 970ndash977

Skylas DJ Cordwell SJ Hains PG Larsen MR Basseal DJ Walsh BJ Blumenthal C Rathmell W Copeland L amp Wrigley CW (2006) Heat shock of wheat during grain filling proteins associated with heat-tolerance Journal of Cereal Science 35 175ndash188

Smajgl A Toan TQ Nhan DK Ward J Trung NH Tri LQ Tri VPD amp Vu PT (2015) Responding to rising sea levels in the Mekong Delta Nature climate change 4 167ndash74

Sobhanian H Razavizadeh R Nanjo Y Ehsanpour A Jazii F Motamed N amp Komatsu S (2010) Proteome analysis of soybean leaves hypocotyls and roots under salt stress Proteome Science 8 19

De Sousa Abreu R Penalva LO Marcotte EM amp Vogel C (2009) Global signatures of protein and mRNA expression levels Molecular BioSystems 5 1512ndash1526

Sperotto RA Ricachenevsky FK Duarte GL Bo T Lopes VKL Sperb ER Grusak MA amp Palma J (2009) Identification of up-regulated genes in flag leaves during rice grain filling and characterization of OsNAC5 a new ABA-dependent transcription factor Planta 230 985ndash1002

Sreedhar R amp Tiku PK (2016) Cupincin a unique protease purified from rice (Oryza sativa L) bran is a new member of the Cupin superfamily PLoS ONE 11 4

Stein JC Yu Y Copetti D Zwickl DJ Zhang L Zhang C Chougule K Gao D Iwata A Goicoechea JL Wei S Wang J Liao Y Wang M Jacquemin J Becker C Kudrna D Zhang J Londono CEM Song X Lee S Sanchez P Zuccolo A Ammiraju JSS Talag J Danowitz A Rivera LF Gschwend AR Noutsos C Wu CC Kao SM Zeng JW Wei FJ Zhao Q Feng Q El Baidouri M Carpentier MC Lasserre E Cooke R Rosa Farias D Da Da Maia LC Dos Santos RS Nyberg KG McNally KL Mauleon R Alexandrov N Schmutz J Flowers D Fan C Weigel D Jena KK Wicker T Chen M Han B Henry R Hsing YIC Kurata N De Oliveira AC Panaud O Jackson SA Machado CA Sanderson MJ Long M Ware D amp Wing RA (2018) Genomes of 13 domesticated and wild rice relatives highlight genetic conservation turnover and innovation across the genus Oryza Nature Genetics 50 285ndash296

Sun X Ji W amp Ding X (2013) GsVAMP72 a novel Glycine soja R-SNARE protein is involved in regulating plant salt tolerance and ABA sensitivity Plant Cell Tissue and Organ Culture 113 199ndash215

Sunarpi Horie T Motoda J Kubo M Yang H Yoda K Horie R Chan WY Leung HY Hattori K Konomi M Osumi M Yamagami M Schroeder JI amp Uozumi N (2005) Enhanced salt tolerance mediated by AtHKT1 transporter-induced Na+ unloading from xylem vessels to xylem parenchyma cells Plant Journal 44 928ndash938

Suzanne K Redfern NA and JSB (2012) Building resilience for adaptation to climate change in the agriculture sector Proceedings of a Joint FAOOECD Workshop 23ndash24

Suzuki K Costa A Nakayama H Katsuhara M Shinmyo A amp Horie T (2016) OsHKT221-mediated Na+ influx over K+ uptake in roots potentially increases toxic Na+ accumulation in a salt-tolerant landrace of rice Nona Bokra upon salinity stress Journal of Plant Research 129 67ndash77

Tamura K Stecher G Peterson D Filipski A amp Kumar S (2013) MEGA6 Molecular evolutionary genetics analysis version 60 Molecular Biology and Evolution 30 2725ndash2729

Tanaka N Fujita M Handa H Murayama S Uemura M Kawamura Y Mitsui T Mikami S Tozawa Y Yoshinaga T amp Komatsu S (2004) Proteomics of the rice cell Systematic identification of the protein populations in subcellular compartments Molecular Genetics and Genomics 271 566ndash576

Tang Y Liu K Zhang J Li X Xu K Zhang Y Qi J Yu D Wang J amp Li C (2017) JcDREB2 a physic nut AP2ERF gene alters plant growth and salinity stress responses in transgenic rice Frontiers in Plant Science 8 1ndash12

Tanksley SD (1997) Seed banks and molecular maps Unlocking genetic potential from the wild Science 277 1063ndash1066

Tanksley SD amp Nelson JC (1996) Advanced backcross QTL analysis a method for the simultaneous discovery and transfer of valuable QTLs from unadapted germplasm into

elite breeding lines Theoretical and applied genetics 92 191ndash203

Tester M amp Davenport R (2003) Na+ tolerance and Na+ transport in higher plants Annals of Botany 91 503ndash527

Thi L Huyen N Cuc LM Ham LH amp Khanh TD (2013) Introgression the saltol QTL into Q5DB the elite variety of Vietnam using marker- assisted - selection ( MAS ) American Journal of BioScience 1 80ndash84

Thomashow MF (1999) Plant cold acclimation Freezing tolerance genes and regulatory mechanisms Annual Review of Plant Physiology and Plant Molecular Biology 50 571ndash599

Thompson A Kuhn K Kienle S Schwarz J Neumann T amp Hamon C (2003) Tandem Mass Tagsthinsp A Novel Quantification Strategy for Comparative Analysis of Complex Protein Mixtures by MS MS Analytical Chemistry 75 1895ndash1904

Thompson JD Higgins DG amp Gibson TJ (1994) CLUSTALW improving the sensitivity of progressive multiple sequence alignment through sequence weighting position-specific gap penalties and weight matrix choice Nucleic Acids Research 22 4673ndash4680

Thomson MJ de Ocampo M Egdane J Rahman M a Sajise AG Adorada DL Tumimbang-Raiz E Blumwald E Seraj ZI Singh RK Gregorio GB amp Ismail AM (2010) Characterizing the saltol quantitative trait locus for salinity tolerance in Rice Rice 3 148ndash160

Thomson MJ Singh N Dwiyanti MS Wang DR Wright MH Perez FA DeClerck G Chin JH Malitic-Layaoen GA Juanillas VM Dilla-Ermita CJ Mauleon R Kretzschmar T amp McCouch SR (2017) Large-scale deployment of a rice 6 K SNP array for genetics and breeding applications Rice 10 Rice

Tichopad A Dzidic A amp Pfaffl MW (2002) Improving quantitative real-time RT-PCR reproducibility by boosting primer-linked amplification efficiency Biotechnology Letters 24 2053ndash2056

Tiwari S Krishnamurthy SL Kumar V Singh B Rao AR SV AM Rai V Singh AK amp Singh N (2016) Mapping QTLs for salt tolerance in rice (Oryza sativa L) by bulked segregant analysis of recombinant inbred lines using 50K SNP chip PLoS One 11 1ndash19

Toyofuku K Kasahara M amp Yamaguchi J (2000) Characterization and expression of monosaccharide transporters (OsMSTs) in rice Plant and Cell Physiology 41 940ndash947

Trivers RL Willard DE Williams GC Burley N Sheldon BC Andersson S Griffith SC Sendecka J Ewen JG Cassey P Fawcett TW Kuijper B Pen I Weissing FJ Komdeur J Cunningham E Russell A Lope F De Gil D Graves J Hazon N Wells A Petrie M Williams A West S a Pryke SR Southern HN Owens IPF Burke T Aparicio JM Parkin DT Montgomerie R Price T Briscoe D Brooks R Bonduriansky R amp Merrill R (2009) The domestication process and domestication rate in rice spikelet bases from the lower yangtze Science 323 1607ndash1610

Tuberosa R Graner A FE (2014) Non-invasive phenotyping methodologies enable the accurate characterization of growth and performance of shoots and roots Pp 173ndash206 in Genomics of Plant Genetic Resources Springer N

Tuteja N (2007) Abscisic acid and abiotic stress signaling Plant Signaling and Behavior 2 135ndash138

Udvardi MK Czechowski T amp Scheible WR (2008) Eleven golden rules of quantitative RT-PCR The Plant cell 20 1736ndash1737

Ul Haq T Gorham J Akhtar J Akhtar N amp Steele KA (2010) Dynamic quantitative trait

loci for salt stress components on chromosome 1 of rice Functional Plant Biology 37 634ndash645

Varshney RK Graner A amp Sorrells ME (2005) Genomics-assisted breeding for crop improvement Trends in Plant Science 10 621ndash630

Verma D Singla-Pareek SL Rajagopal D Reddy MK amp Sopory SK (2007) Functional validation of a novel isoform of Na+H+ antiporter from Pennisetum glaucum for enhancing salinity tolerance in rice Journal of Biosciences 32 621ndash628

Vogel C De Sousa Abreu R Ko D Le SY Shapiro BA Burns SC Sandhu D Boutz DR Marcotte EM amp Penalva LO (2010) Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line Molecular Systems Biology 6 1ndash9

Walter A Liebisch F amp Hund A (2015) Plant phenotyping from bean weighing to image analysis Plant Methods 11 1ndash11

Wan Q Hongbo S Zhaolong X Jia L Dayong Z amp Yihong H (2017) Salinity tolerance mechanism of osmotin and osmotin-like proteins A promising candidate for enhancing plant salt tolerance Current Genomics 18 553ndash556

Wang J Zuo K Wu W Song J Sun X Lin J Li X amp Tang K (2003) Molecular cloning and characterization of a new Na+H+ antiporter gene from Brassica napus DNA Sequence 14 351ndash358

Wang S Cao M Ma X Chen W Zhao J Sun C Tan L amp Liu F (2017) Integrated RNA sequencing and QTL mapping to identify candidate genes from Oryza rufipogon associated with salt tolerance at the seedling stage Frontiers in Plant Science 8 1ndash11

Wang W-S Zhao X-Q Li M Huang L-Y Xu J-L Zhang F Cui Y-R Fu B-Y amp Li Z-K (2016) Complex molecular mechanisms underlying seedling salt tolerance in rice revealed by comparative transcriptome and metabolomic profiling Journal of Experimental Botany 67 405ndash419

Wang W Vinocur B amp Altman A (2003b) Plant responses to drought salinity and extreme temperatures towards genetic engineering for stress tolerance Planta 218 1ndash14

Wang W Mauleon R Hu Z Chebotarov D Tai S Wu Z Li M Zheng T Fuentes RR Zhang F Mansueto L Copetti D Sanciangco M Palis KC Xu J Sun C Fu B Zhang H Gao Y Zhao X Shen F Cui X Yu H Li Z Chen M Detras J Zhou Y Zhang X Zhao Y Kudrna D Wang C Li R Jia B Lu J He X Dong Z Xu J Li Y Wang M Shi J Li J Zhang D Lee S Hu W Poliakov A Dubchak I Ulat VJ Borja FN Mendoza JR Ali J Gao Q Niu Y Yue Z Naredo MEB Talag J Wang X Li J Fang X Yin Y Glaszmann JC Zhang J Li J Hamilton RS Wing RA Ruan J Zhang G Wei C Alexandrov N McNally KL Li Z amp Leung H (2018) Genomic variation in 3010 diverse accessions of Asian cultivated rice Nature 557 43ndash49

Wang X Liu Q amp Zhang B (2014) Leveraging the complementary nature of RNA-Seq and shotgun proteomics data Proteomics 14 2676ndash2687

Wang Y Xiao Y Zhang Y Chai C Wei G Wei X Xu H Wang M Ouwerkerk PBF amp Zhu Z (2008) Molecular cloning functional characterization and expression analysis of a novel monosaccharide transporter gene OsMST6 from rice (Oryza sativa L ) Planta 228 525ndash535

Ward JM Maumlser P amp Schroeder JI (2009) Plant ion channels gene families physiology and functional genomics analyses Annual review of physiology 71 59ndash82

Weber A Servaites JC Geiger DR Kofler H Hille D Groner F Hebbeker U amp Flugge U-I (2007) Identification purification and molecular cloning of a putative plastidic glucose translocator The Plant Cell 12 787

Weschke W Panitz R Gubatz S Wang Q Radchuk R Weber H amp Wobus U (2003) The role of invertases and hexose transporters in controlling sugar ratios in maternal and filial tissues of barley caryopses during early development Plant Journal 33 395ndash411

Wessel D amp Fluumlgge UI (1984) A method for the quantitative recovery of protein in dilute 157 solution in the presence of detergents and lipids Analytical biochemistry 138 141ndash143

Wing RA Ammiraju JSS Luo M Kim HR Yu Y Kudrna D Goicoechea JL Wang W Nelson W Rao K Brar D Mackill DJ Han B Soderlund C Stein L SanMiguel P amp Jackson S (2005) The Oryza map alignment project the golden path to unlocking the genetic potential of wild rice species Plant Molecular Biology 59 53ndash62

Wise RR Olson AJ Schrader SM amp Sharkey TD (2004) Electron transport is the functional limitation of photosynthesis in field-grown Pima cotton plants at high temperature Plant Cell and Environment 27 717ndash724

Wisniewski J Brewin NJ amp Bornemann S (2007) A germin-like protein with superoxide dismutase activity in pea nodules with high protein sequence identity to a putative rhicadhesin receptor Journal of Experimental Botany 58 1161ndash1171

Wormit A Trentmann O Feifer I Lohr C Tjaden J Meyer S Schmidt U Martinoia E amp Neuhaus HE (2006) Molecular identification and physiological characterization of a novel monosaccharide transporter from Arabidopsis involved in vacuolar sugar transport The Plant cell 18 3476ndash3490

Wright SI Bi IV Schroeder SG Yamasaki M Doebley JF McMullen MD amp Gaut BS (2005) The effects of artificial selection on the maize genome Science 308 1310ndash1314

Wu S Zhu Z Fu L Niu B amp Li W (2011) WebMGA A customizable web server for fast metagenomic sequence analysis BMC Genomics 12

Wu Y Mirzaei M Pascovici D Haynes PA amp Atwell BJ (2019) Proteomes of leaf‐growing zones in rice genotypes with contrasting drought tolerance Proteomics 1800310 1800310

Wuumlrschum T (2012) Mapping QTL for agronomic traits in breeding populations Theoretical and Applied Genetics 125 201ndash210

Xu X Liu X Ge S Jensen JJDJJDJ Hu F Li X Dong Y Gutenkunst RN Fang L Huang L Li J He W Zhang G Zheng X Zhang F Li Y Yu C Kristiansen K Zhang X Wang JJ Wright M Mccouch S Nielsen R amp Wang W (2012) Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes Nature biotechnology 30 105ndash11

Yadav R Flowers TJ amp Yeo a R (1996) The involvement of the transpirational bypass flow in sodium uptake by high- and low-sodium-transporting lines of rice developed through intravarietal selection Plant Cell and Environment 19 329ndash336

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Yamada K Kanai M Osakabe Y Ohiraki H Shinozaki K amp Yamaguchi-Shinozaki K (2011) Monosaccharide absorption activity of Arabidopsis roots depends on expression profiles of transporter genes under high salinity conditions Journal of Biological Chemistry 286 43577ndash43586

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Yan S Tang Z Su W amp Sun W (2005) Proteomic analysis of salt stress-responsive proteins in rice root Proteomics 5 235ndash244

Yang Q Wang Y Zhang J Shi W Qian C amp Peng X (2007) Identification of aluminum-responsive proteins in rice roots by a proteomic approach Cysteine synthase as a key player in Al response Proteomics 7 737ndash749

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Zhu JK (2001) Plant salt tolerance Trends in Plant Science 6 66ndash71

Appendix

The figures and tables listed below are numbered according to the chapter in which

they are cited

ORIGINAL ARTICLE Open Access

Salinity tolerance in Australian wild Oryzaspecies varies widely and matches thatobserved in O sativaYoav Yichie1 Chris Brien23 Bettina Berger23 Thomas H Roberts1 and Brian J Atwell4

Abstract

Background Soil salinity is widespread in rice-producing areas globally restricting both vegetative growth and grainyield Attempts to improve the salt tolerance of Asian rice Oryza sativamdashthe most salt sensitive of the major cerealcropsmdashhave met with limited success due to the complexity of the trait and finite variation in salt responses amongO sativa lines Naturally occurring variation among the more than 20 wild species of the Oryza genus has greatpotential to provide breeders with novel genes to improve resistance to salt Here through two distinct screeningexperiments we investigated variation in salinity tolerance among accessions of two wild rice species endemic toAustralia O meridionalis and O australiensis with O sativa cultivars Pokkali and IR29 providing salt-tolerant and sensitivecontrols respectively

Results Rice plants were grown on soil supplemented with field-relevant concentrations of NaCl (0 40 80 and 100mM) for 30 d a period sufficient to reveal differences in growth and physiological traits Two complementary screeningapproaches were used destructive phenotyping and high-throughput image-based phenotyping All genotypesdisplayed clear responses to salt treatment In the first experiment both salt-tolerant Pokkali and an O australiensisaccession (Oa-VR) showed the least reduction in biomass accumulation SES score and chlorophyll content in responseto salinity Average shoot Na+K+ values of these plants were the lowest among the genotypes tested In the secondexperiment plant responses to different levels of salt stress were quantified over time based on projected shoot areacalculated from visible red-green-blue (RGB) and fluorescence images Pokkali grew significantly faster than the othergenotypes Pokkali and Oa-VR plants displayed the same absolute growth rate under 80 and 100mM while Oa-D grewsignificantly slower with the same treatments Oa-VR showed substantially less inhibition of growth in response tosalinity when compared with Oa-D Senescence was seen in Oa-D after 30 d treatment with 40mM NaCl while theputatively salt-tolerant Oa-VR had only minor leaf damage even at higher salt treatments with less than a 40increase in relative senescence at 100mM NaCl compared to 120 for Oa-VR

Conclusion The combination of our two screening experiments uncovered striking levels of salt tolerance diversityamong the Australian wild rice accessions tested and enabled analysis of their growth responses to a range of saltlevels Our results validate image-based phenotyping as a valuable tool for quantitative measurement of plantresponses to abiotic stresses They also highlight the potential of exotic germplasm to provide new genetic variationfor salinity tolerance in rice

Keywords Oryza sativa Oryza australiensis Oryza meridionalis Salt Australian native rice

Correspondence yoavyichiesydneyeduau1Sydney Institute of Agriculture University of Sydney Sydney AustraliaFull list of author information is available at the end of the article

copy The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 40International License (httpcreativecommonsorglicensesby40) which permits unrestricted use distribution andreproduction in any medium provided you give appropriate credit to the original author(s) and the source provide a link tothe Creative Commons license and indicate if changes were made

Yichie et al Rice (2018) 1166 httpsdoiorg101186s12284-018-0257-7

IntroductionSalinity drought and heat are major abiotic stresses lim-iting the productivity of crop plants Accumulation oftoxic levels of salt as well as osmotic stress constitute amajor threat to rice production worldwide particularlyin coastal rice-growing regions Modern rice hybrids aresome of the most salt-sensitive genotypes (Grattan et al2002 Munns et al 2008 Qadir et al 2014) with yieldreductions evident above 30mM NaCl (Ismail and Horie2017) and survival of salt-sensitive genotypes compro-mised at 70 mM NaCl (Yeo et al 1990) Rice is particu-larly vulnerable to salinity during the early seedling andreproductive stages (Zeng et al 2002) The impact ofsalinity will be further exacerbated by factors such asmarine inundation (Takagi et al 2015) This has vastimplications for food security because rice is the staplefor much of Asia (Khush 2005) and throughout pantrop-ical countriesThe basis of salt tolerance is polygenic determined by

a complex network of interactions involving signallingstress-induced gene expression and membrane trans-porters (Wang et al 2003) This complexity has compli-cated the search for physiological salt tolerance in ricebecause genotypes with tolerance in one trait are oftenintolerant in another (Yeo et al 1990) Moreover differ-ent developmental phases are characterised by distinctsalt-tolerance mechanisms (Munns and Tester 2008)requiring breeding for genotypes with a suite of mor-phological physiological and metabolic responsesAttempts to improve the salt tolerance of O sativa havemet with limited success due to these complexities aswell as the interaction with nutritional factors hetero-geneity of field sites and other environmental factorssuch as heat and periodic drought (Flowers 2004 Yeo etal 1990) Notwithstanding the improvement of salt tol-erance of rice at the seedling stage is a major breedinggoal in many Asian countries where seedlings mustoften establish in soils already contaminated by saltWhile other crops might be better suited to salt-affectedsoils few are suitable alternatives to rice because of itsunique ability to grow when floodedEven though O sativa represents less than 20 of the

genetic diversity that exists in the 27 Oryza species (Zhuet al 2007 Stein et al 2018) there is still substantial vari-ability in the tolerance to NaCl within this species (Gre-gorio et al 1993 Lutts et al 1995 Munns et al 2016) InO sativa transport of Na+ to the shoot is a major deter-minant of salt tolerance (Yeo et al 1987 Yadav et al 1996Ochiai et al 2002) The activity of a vacuolar antiporterwas found to increase salt tolerance (Fukuda et al 2004)More recently a novel quantitative trait locus (QTL)named Saltol was found to encode a trans-membrane pro-tein OsHKT15 which regulates K+Na+ homeostasisunder salt stress increasing tolerance to salt (Ren et al

2005 Thomson et al 2010) Additional studies have iden-tified other QTL and mutations for salt tolerance withinO sativa (Lang et al 2001 Yao et al 2005 Sabouri et al2008 Islam et al 2011 Takagi et al 2015) but the mecha-nisms of the proteins encoded in these loci are yet to berevealedThe diversity of wild rice relatives would suggest that a

novel salt-tolerance mechanism for rice breedingprograms should come from the examination of Oryzaspecies from natural populations of which four are indi-genous to Australia O meridionalis O officinalis O rufi-pogon and O australiensis (Henry et al 2010 Atwell et al2014) While the best evidence thus far for the ability ofOryza species to contribute stress-tolerance genes is thecase of resistance to brown leaf hopper (Khush 1997 Rah-man et al 2009) abiotic factors have been powerful select-ive forces on these species in northern Australiaencouraging our search for tolerance to physical con-straints on growth For example O meridionalis and Oaustraliensis have superior heat tolerance compared withO sativa (Scafaro et al 2010) with the wild allelic form ofthe Rubisco activase gene responsible for this trait in Oaustraliensis (Scafaro et al 2016)Although the Australian endemic rices are poorly

characterised trials demonstrate the potential of usingwild rice species introgressions to enhance the growth ofO sativa (Ballini et al 2007) A recent study showedthat Australia may be a centre of origin and segregationof the AA genome of Oryza and underlined the widegenetic diversity within the Oryza species that share thisgenome (Brozynska et al 2016) Further diversity couldbe expected in the phylogenetic outlier O australiensiswhich is the sole species with an EE genome (Jacqueminet al 2013) The discovery of many domesticated alleleswithin the wild species reinforces the hypothesis thatwild relatives are a key asset for crop improvement (Bro-zynska et al 2016)Over recent years several studies in cereals and legumes

have utilised high-throughput phenotyping technologyunder controlled environments to gain a better understand-ing of the genetic architecture and the physiologicalprocesses associated with salinity stress (Hairmansis et al2014 Campbell et al 2015 2017 Atieno et al 2017) How-ever this approach had not been applied to crop wildrelatives In a large-scale non-destructive phenotyping facil-ity (lsquoThe Plant Acceleratorrsquo) we assembled shoot images ofO sativa O meridionalis and O australiensis exposed to arange of salt treatments for five weeks during the earlyvegetative stage We sought to examine developmentallyspecific salinity responses growth dynamics and the com-plex relationship between different traits under salt stress inAustralian wild rices pre-selected for inherent tolerance tosalinity Comparisons were made between these genotypesand O sativa genotypes Pokkali (salt-tolerant) and IR29

Yichie et al Rice (2018) 1166 Page 2 of 14

(salt-sensitive) The broader context of this work was togain insights into abiotic stress tolerance of exotic Austra-lian genotypes with the aim of identifying key genes insubsequent research

Material and methodsPlant material growth conditions and salt treatmentsExperiment 1Five wild accessions chosen from two Australian en-demic wild rice species O meridionalis and O austra-liensis were tested along with two cultivated varieties ofO sativa Pokkali and IR29 The wild accessions wereselected from a wide range of sites including transientlysaline waterways in the north and northwest ofAustralia Approximately 30 genotypes were screenedfor symptoms and survival in preliminary experiments(unpublished data) exhibiting a wide spectrum of toler-ance to 25ndash100 mM NaCl over a four-week treatmentThe initial testing led to a narrower selection of geno-

types screened at Macquarie University SydneyAustralia (lat 337deg S long 1511deg E) in spring 2016Seeds were de-hulled and surface-sterilised by successiveimmersion in water (30 min) 4 commercial bleach (30min) and at least five rinses with diH2O Seedlings werethen germinated in petri dishes in the dark at 28 degC (Osativa) and 36 degC (wild rice) and grown for a further 5 dat 28 degC After 8 d two to four seedlings per genotypewere sown in a 15-L polyvinyl chloride (PVC) pot (withdrainage holes) containing 13 L of locally sourcedclay-loam slow-release fertiliser (Nutricote StandardBlue Yates 004) and placed in the greenhouse Seed-lings were thinned leaving one uniformly sized andhealthy seedling in each pot 15 d after transplanting(DAT)Salt treatments were applied to the top of the pots

gradually in three stages from 25 DAT (25 up to 40 andup to 80mM daily increments) The final NaCl concen-trations for the first screening were 0 40 and 80 mMNaClmdasha total electrolyte concentration resulting in anelectrical conductivity (EC) of 00 05 45 and 87 dSmminus 1 respectively Plants were watered once a day with~ 50 mL per pot of their respective salt concentration(including 04 g Lminus 1 of Aquasol Soluble Fertiliser Yates)A square aluminum tray was placed under each set oftreatment pots and the drainage was collected every 3 dPlants were exposed to salt treatments for 30 d in a con-trolled greenhouse with 30 degC22 degC daynighttemperature and relative humidity of 57 (plusmn 9 SD)during the day and 77 (plusmn 2 SD) at nightA completely randomised design was used with a

minimum of five replicates (pots) for each plantgenotype-treatment combination The locations of thetrays and of each pot within trays were changed ran-domly every 3 d to subject each one of the plants to the

same conditions and to prevent neighbour effects A fewIR29 plants dehydrated two weeks after exposure to salt(80 mM NaCl treatment) and were removed from thestatistical analysis

Experiment 2Seven lines of rice including two cultivated O sativacontrolsmdashPokkali a positive control (salt tolerant) andIR29 a negative control (salt sensitive)mdashwere investi-gated at the four salt concentrations described abovewith an additional salt treatment of 100 mM (EC = 105dS mminus 1) This experiment was performed in the SouthEast Smarthouse at The Plant Accelerator (AustralianPlant Phenomics Facility University of Adelaide Adel-aide Australia lat 349deg S long 1386deg E) in the summerof 2017 The same greenhouse conditions and treat-ments were applied as in Experiment 1 The seedlingswere sown and thinned following the same protocol asused in Experiment 1 in 25-L pots with 20ndash22 L of UCDavis-mix (25 g Lminus 1 Mini Osmocotereg 16ndash3-9 + te) andthe surface was covered with white gravel (particle size~ 2ndash5 mm) to minimise evaporation from the pot and toreduce algal growth For the first 7 DAT each pot waswatered daily with ~ 100 mL from the top The potswere placed on top of square containers (93 mm diam-eter 50 mm height) to prevent water from spilling ontothe conveyor system and to allow the drainage water tobe collectedSalt treatments were applied gradually in four steps

from 22 DAT to the square container (25 up to 40 upto 80 and up to 100 mM daily increments) The holes inthe pots allowed for the infiltration of salt solution intothe soil through capillary action The water level wasmaintained constant by weighing each plant and water-ing to a target volume of 600 mL Daily imaging andwatering were continued for 30 d after salt treatmentuntil 30 d after salting (DAS) The same post-harvestparameters were measured as in Experiment 1Image-based high-throughput phenotyping was

performed on rice genotypes selected from the widergroup tested in initial screening experiment (spring2016)A split-unit design was performed concurrently where

12 lanes times 14 positions (5ndash12 15ndash20) with six replicatesto assign the factorial set of treatments were occupiedEach replicate occupied two consecutive lanes andincluded all 28 rice line-treatment combinations Eachreplicate comprised seven main units each consisting offour carts arranged in a grid of two lanes times two posi-tions Thus the 42 main units formed a grid of 6 reps times7 main positions The plant lines were assigned to mainunits using a 7 times 6 Youden square The four salttreatments were assigned to the four carts within eachmain unit using a resolved incomplete block design for

four treatments in blocks of size 2 The design was ran-domised using dae (Brien 2018) a package for the Rstatistical computing environment (R Core Team 2018)

Phenotyping of physiological traitsGas exchange valuesPlants were phenotyped throughout the experiment forgrowth parameters Gas exchange parameters such asphotosynthesis stomatal conductance and transpirationwere measured on DAS 29 and DAS 30 (for the first andsecond experiments respectively) with an infrared opengas exchange system (LI-6400 LICOR Inc Lincoln NEUSA) All gas measurements were completed on thesame day between 1000 am and 1230 pm and weremade on the youngest fully-expanded leaf (YFL) of eachrice plant

Growth and yield componentsPlants were characterised for phenotypic responses tosalinity stress on 30 d after salt application (DAS) theplants were harvested and the following post-harvestparameters were determined Shoot fresh weight (SFW)was measured for each plant immediately after harvestas well as number of tillers Plant shoots were dried at65 degC in a ventilated oven for 48 h to constant weightand shoot dry weight (SDW) was measured

Leaf chlorophyll determinationThe YFL was collected from each plant on the day ofharvest (DAS30) leaves were flash-frozen in liquid nitro-gen after being washed with diH2O Chlorophyll was ex-tracted using 95 ethanol and total chlorophyll wasdetermined (Mackinney 1941) Chlorophyll concentra-tions at each salt level were normalised against control(non-salinised) levels

Ion assayThe YFL of each plant was collected as described aboveSamples were washed thoroughly and dried at 70 degCEach sample was weighed and extracted with 10ml 01N acetic acid for every 10 mg of dried tissue Sampleswere placed in a water bath at 90 degC for 3 h Sampleswere diluted 10 times after the extracted tissues werecooled at room temperature Sodium and potassiumconcentrations were measured using an Agilent 4200Microwave Plasma Atomic Emission Spectrometer (Agi-lent Technologies Melbourne Australia)

Salinity tolerance estimationSalinity tolerance (ST) was determined by the percentageratio of mean shoot dry weight (80 mM NaCl) dividedby mean shoot dry weight (no salt) [SDW (salt treat-ment)) (SDW (control)) times 100] Each plant was evalu-ated for seedling stage salinity tolerance based on visual

symptoms using the International Rice Research Insti-tute (IRRI) standard evaluation system (SES) scores(IRRI 2013)

RGBfluorescence image capture and image analysisTwo types of non-destructive imaging systems were uti-lised to address our questions RGB (red-green-blue)vis-ible spectrum and fluorescence (FLUO) Standard RGBimages had a resolution of 8M pixels while fluorescenceimages had a resolution of 5M pixels (Berger et al2012) However in our experiment some plants attaineda physical height exceeding that of the field of view ofthe RGB camera (the RGB camera was closer to theplants than the fluorescence camera) Thus we chose touse the projected shoot area (PSA) based on RGB im-ages at the beginning of the experiment (DAS 4ndash19) andPSA based on fluorescence at the end (DAS 20 on-wards) For the RGB images PSA is the sum of the areasas measured (in kilopixels) from two side views at an an-gular separation of 90 degrees and a view from abovefor the fluorescent images PSA is the sum of the areasas measured (in kilopixels) from two side views at anangular separation of 90 degreesConsequently a hybrid PSA trait was calculated using

the RGB images for DAS 4ndash19 and the FLUO images forDAS 20 onwards The PSA data from the FLUO imageswere transformed using the linear relationship betweenPSA from the RGB images and PSA from the FLUOimages (for DAS 20) The conversion was made on theraw observations and then the new data were preparedfor each plant as described below Water levels weremonitored and adjusted daily by the Scanalyzer 3Dweighing and watering system (LemnaTec GmbH Aa-chen Germany) with pot weight before and after water-ing being recordedTo screen for osmotic tolerance plant growth rate

after the addition of NaCl was determined using the hy-brid PSA trait from DAS 2 to 30 where DAS 0 corre-sponded to the commencement of the salt treatments togenerate the PSA of the plant The results of thehigh-throughput screening focused on PSA and the ab-solute growth rate (AGR) and relative growth rate (RGR)derived for these plants The traits were obtained as de-scribed (Al-Tamimi et al 2016) The PSA AGR and PSARGR were calculated from the PSA values by determin-ing the difference between consecutive PSA and ln(PSA)values respectively and dividing by the time differenceSimilarly the daily water loss from each pot wasobtained by subtracting the weight before watering inthe current imaging day from the weight after wateringon the previous imaging day The PSA water use index(WUI) was calculated daily by dividing the PSA AGR bythe water use On the one occasion that water use valueswere negative due to leakage from a storm values were

replaced with blank values to avoid affecting thesmoothed spline curve fitting

Data preparation and statistical analysisFirst experimentStatistical significance of phenotypic traits was deter-mined by Analysis of Variance (ANOVA) with TukeyHSD multiple comparison with significant values of P le005 and P le 001 Pairwise comparisons were conductedusing LSD-Test and Tukey adjustments to producep-values for the significant differences of specific pairsusing the R package ggplot2 (Wickham 2009) A linearregression model was used to calculate the SalinityTolerance (ST) against sodium and potassium concen-trations and the corresponding r coefficients

Second experimentData from the Smarthouse were first analysed using ima-geData (Brien 2018) to determine subjectively the de-gree of smoothing required to produce growth curvesusing PSA values this approach removed noise in thedata while accurately capturing the underlying growthtrajectories PSA AGR and the PSA RGR were derivedby fitting natural cubic smoothing splines to the data foreach plant with different settings of the smoothing par-ameter degrees of freedom (df) (Al-Tamimi et al 2016)A df value of five was chosen as it gave the most satis-factory results over all three traits The water use ratewas also smoothed by fitting a spline using df = 5 Afterexamination of the plots for the smoothed traits sPSAsPSA AGR and sPSA RGR we decided to investigategrowth for six DAS endpoints (DAS 4 9 14 19 23 and28) and thus the response of the rice plants to salt treat-ment was separated into five corresponding intervalsCorrelation analysis was performed on the biomass-re-

lated metrics (smoothed PSA 28 and 30 DAS) and manualmeasurements of SFW and SDW Both SDW and SFW dis-played a strong positive correlation with PSA with thehighest correlation between smoothed PSA and SDW (r2 =0966 P = 0001 n = 168) (Additional file 1 Figure S1) usingthe squared Pearson correlation coefficient A similarstrong positive correlation was found (r2 = 096 P = 0001n = 72) in a previous study that measured the correlationbetween PSA and total plant area using a leaf area meter(LI-3100C LI-COR) (Campbell et al 2015) This validatesour experimental set-up as suitable to monitor plantgrowth and physiological responses to salt treatments andindicates that PSA is an accurate and sensitive metric forassessing plant biomass accumulation in response tosalinityTo produce phenotypic means adjusted for the spatial

variation in the Smarthouse a mixed-model analysis wasperformed for each trait using the R package ASReml-R(Butler et al 2009) and asremlPlus (Brien 2018) both

packages for the R statistical computing environment (RCore Team 2018) The maximal mixed model used wasdescribed previously (Al-Tamimi et al 2016)Residual variances were tested using REML ratio tests

with α = 005 to test whether the differences were signifi-cant for both salinities and lines for just one of them ornot at all In order to reflect the results of these testsand to check that the assumptions underlying the ana-lysis were met the model was modified toresidual-versus-fitted value plots and normal probabilityplots of the residuals inspected Wald F-tests were con-ducted to check whether an interaction (between linesand salinity) was significant for its main effects Thepredicted means and standard errors were obtained forthe selected model for salinity and lines effects To com-pare a pair of predicted means the p-value for an ap-proximate t-test was calculate from the predicted meansand their standard errors However for cases in whichthe variances were unequal these were computed foreach prediction using the average variance of the pair-wise differences over all pairwise differences in whichthe prediction was involved and are only approximate

ResultsFirst screening (experiment 1)After 30 d of growth in non-salinised (control) condi-tions O sativa O meridionalis and O australiensisshoot dry biomass ranged from 115 (IR29) to 22 g (Pok-kali) with the exception of Oa-KR for which dry biomassreached 34 g by the end of the experiment Average chloro-phyll concentrations ranged from 167 to 394mg gminus 1

(SDW) while mean net photosynthetic rates ranged from149 to 199 μmolmminus 2 sminus 1 (Additional file 2 Table S1)Relative to the non-salinised control plants clear differ-

ences in phenotype became apparent after exposure to 40and 80mM NaCl Visual symptoms across all six geno-types were assessed by SES showing salt-induced injurywhen expressed relative to control plants (for which SES= 10 ie no loss of leaf function) In the oldest leaves ofIR29 SES reached 54 at 40mM and 83 at 80mM NaClreflecting loss of function in all but the most recently ex-panded leaves (Fig 1a) In the most salt-tolerant genotype(Oa-VR) SES was 18 at 40mM and 24 at 80mM NaClChlorophyll concentrations followed an identical pattern(Fig 1b) where in the salt-sensitive genotype (IR29) therewas a 34 reduction at 40mM and a 72 reduction at 80mM NaCl while in Oa-VR there was no change in chloro-phyll concentration at 40mM and a 19 reduction at 80mM NaClSeedling fresh and dry biomass were measured 30 DAS

Because of inherent variation in the growth rate of the wildspecies biomass of plants treated with 40 and 80mM NaClare shown relative to control plants (Fig 1c - dry weightsAdditional file 2 Table S1) There was no growth penalty

in the two most tolerant wild rice genotypes (Oa-VR andOa-CH) at 40mM NaCl with both being considerablymore tolerant than the salt-tolerant O sativa genotypePokkali The most salt-sensitive wild rice line (Oa-D) wasas susceptible to salt as IR29 at 40mM NaCl These dataare consistent with visual symptoms indicating thatOa-VR was the most salt-tolerant wild Oryza accessionand Oa-D the least tolerant NaK ratio calculated at 40and 80mM NaCl (Fig 1d) revealed the lowest NaK ratiosin Oa-VR and Pokkali while the other wild rice genotypesand IR29 had progressively higher ratios reaching an aver-age of 241 for Oa-CHSodium and potassium ion concentrations were mea-

sured in the youngest fully expanded leaves where tissuesremained hydrated even in the salt-sensitive genotypes asshown by the narrow range of variation in K+

concentrations (Fig 2) The relationships between ion con-centrations and leaf biomass (as a percentage of controls)illustrate the strong negative relationship between Na+ con-centration and salinity tolerance confirming that the exclu-sion of Na+ conferred physiological tolerance (Fig 2) Thethree most salt-sensitive genotypes had 300ndash500 μmol Na+

gminus 1 (SDW) while the most salt-tolerant genotypes had upto three times less Na+ A negative relationship betweenphysiological tolerance (ST) and Na+ concentrations in theyoungest fully expanded leaves was clear when all geno-types were compared (Fig 2) A weak positive relationshipwas recorded between K+ concentrations in shoots and sal-inity tolerance Notably Na+ concentrations in Oa-VR andPokkali were lowest of all six genotypes (114 and 83 μmolgminus 1 (SDW) respectively) and when expressed on a tissuewater basis (using the SFWSDW ratio of 36 and 34

Fig 1 a Standard Evaluation System (SES) scores [1-9] b Normalized chlorophyll content (as a ratio of the control) c Normalized biomass growthby SDW (as a ratio of the control) and d Shoot Na+K+ ratio of the four wild Oryza accessions and O sativa controls IR29 (salt sensitive) andPokkali (salt tolerant) Trait means (plusmn standard errors) are shown for each genotype under 40 and 80 mM NaCl (EC = 87 dS m-1) at the seedlingstage For a b and c asterisks indicate significant differences from the non-salinised control for the same genotype based on Studentlsquos t test (Plt 005 P lt 001) For d asterisks indicate significant differences between 40 and 80 mM based on Studentlsquos t test (P lt 005 P lt 001)because the ratios (as used for a to c) were so low in non-salinised controls as to be negligible whereas the increase in ratio from 40 to 80 mMwas highly relevant salt tolerance differences between genotypes

respectively) Na+ concentrations were 34 and 44 μmol gminus 1

(FW) respectively ie much lower than those in the soil so-lution in which they grew Oa-VR accumulated 215 μmolK+ gminus 1 (SDW) 20 more (P lt 005) than the levels foundin IR29 and Oa-D (171 and 168 μmol gminus 1 (SDW)respectively)Depending upon the genotype ion toxicity symptoms

were first visible in leaves 7ndash15 DAS Initiallysalt-induced symptoms were always restricted to theolder leaves but increased progressively in severity andextent until only the most recently emerged leaves wereunaffected (data not shown)Measurements at 80 mM NaCl established that the

negative effects of salt were consistent across three vege-tative traitsmdashplant height SDW and number of tillers(Additional file 3 Table S2) Furthermore damage mea-sured by SES scores correlated negatively with thesetraits as well as photosynthetic rates (P = 001)

Plant accelerator (experiment 2)There were no visual leaf symptoms or wilting in anygenotype 4 d after salt was applied Pokkali grew signifi-cantly faster (162 kpixels dminus 1) than other lines over thefirst 9 d (P lt 005) while IR29 grew slowest in all treat-ments (Fig 3 Additional file 4 Figure S2) The two wildrice species had the same relative growth rate at thisearliest stage of salt treatment (P gt 005) while Pokkaliand IR29 grew significantly faster and slower respect-ively (Additional file 5 Figure S3) Importantly the aver-age growth rates of the control plants during DAS 0 to 4and 4 to 9 were significantly greater (P lt 005) than anyof the salt treatments (Fig 3 Additional file 4 FigureS2) RGR in Pokkali declined steadily throughout theexperiment even in salt-treated plants (Additional file 4Figure S2 Additional file 5 Figure S3) indicating thatplants did not grow exponentially at any stage of the salt

treatment On the other hand periods of exponentialgrowth were observed in the other three genotypes withexponential growth notably sustained in Oa-VR for thefirst 15 d of salt treatment (Additional file 5 Figure S3)After 23 DAS RGR was lower (Pokkali Oa-VR andOa-D) or the same (IR29) in control plants when com-pared with salt-treated plants which grew at 10 perday These time-dependent shifts in the response of thegenotypes to salinity were analysed using p-values forprediction mean differences within each interval identi-fied in Fig 3 While differential effects of salinity acrossgenotypes were not seen in the absolute growth rateuntil plants had been exposed to salt for at least 19 dsalinity times genotype interactions were seen strongly inRGR from the beginning of the experiment This isreflected in Additional file 5 Figure S3 where thechanges in RGR in Pokkali plants reflected the vigorouscanopy growth early self-shading and distinctive rapidcanopy development rate compared with the other threegenotypes testedThere was a wide range of growth responses at each

salt level in the seven genotypes imaged (Additional file6 Figure S4) with IR29 notably the slowest growinggenotype Individual performances of the two O sativastandard lines and two of the most contrasting O aus-traliensis accessions are represented at all four salt levelsin Fig 3 The reduction in shoot growth as measured byPSA was most pronounced at 80 and 100 mM NaClwith smaller reductions at 40 mM NaCl (Fig 3) By 12DAS non-salinised plants of all four genotypes weregrowing significantly faster than all salt-treated plantsImportantly Pokkali Oa-VR and Oa-D grew substan-tially faster than IR29 at 12 DAS non-salinised controlplants grew at 251 138 135 and 59 kilopixels dminus 1 (asmeasured by PSA) in the four genotypes respectivelyPokkali Oa-VR and Oa-D treated with 100 mM NaCl

Fig 2 Linear regression of Salinity Tolerance (ST) against a leaf Na+ concentrations [μmol Na+ g-1 (SDW)] (R2 = 075) and b leaf K+ concentrations[μmol Na+ g-1 (SDW)] (R2 = 069) ST was calculated as the percentage ratio of mean shoot dry weight (salt treatment 80 mM of NaCl) divided bymean shoot dry weight (control no salt) [SDW (salt treatment))(SDW (control)) x 100]

were reduced to 78ndash88 of the controls while no effectof 100 mM NaCl could be detected in IR29 plants Des-pite the reputation of IR29 as a salt-sensitive genotypeits inherently slow growth made responses to NaCl diffi-cult to detect in the early stages of vegetative develop-ment (Additional file 5 Figure S3) The divergence inAGR between plants grown at 80 and 100 mM NaCl wasnotable with Pokkali and Oa-VR plants growing at thesame rate in these two highest salt treatments whileOa-D plants grew significantly slower at 100 mM than at80 mM NaCl (Fig 3) Importantly Oa-VR showed sub-stantially less inhibition of growth in response to salinitywhen compared with Oa-D supporting the observationfrom the first experiment that Oa-VR is the most salttolerant of the wild rice accessions tested (Fig 3) Themost severe reduction in PSA across all genotypes testedin the Plant Accelerator was an O meridionalis genotype(Om-T) where there was a 27 reduction after DAS9and a further reduction of almost 20 by DAS18 in 100mM NaCl

Shoot images generated in the Plant Acceleratorgenerated an estimate of relative leaf senescence usingfluorescence optics even though these values differ fromvisual analyses by SES which showed that non-salinisedleaves had not begun to senesce However the relativeeffects of NaCl on canopy development and the reportedchanges in senescence in salinised plants (Fig 4) providean accurate assessment of the impact of salt on Oa-VRand Oa-D (Hairmansis et al 2014) Necrosis of olderleaves was seen in the salt-sensitive genotype Oa-D after30 d treatment with 40mM NaCl while the putativelysalt-tolerant Oa-VR had minor leaf damage even at 80to 100 mM NaCl (Fig 4) Oa-VR exhibited less than a40 increase in relative senescence at 100 mM NaClcompared with the control while an increase of morethan 120 was recorded for Oa-D (Fig 4) Furthermorethe impact of 100mM NaCl on chlorophyll content wassmaller in Oa-VR than in Oa-D (Fig 4)Compared with controls WUI was impaired immedi-

ately after salt was applied (Fig 5) While WUI

Fig 3 Absolute growth rates of Pokkali Oa-VR Oa-D and IR29 from 0 to 30 DAS including non-salinised controls Smoothed AGR values werederived from projected shoot area (PSA) values to which splines had been fitted Thin lines represent individual plants Bold lines represent thegrand average of the six replicates plants for each treatment The vertical broken lines represent the tested intervals

continued to increase in Oa-VR throughout the experi-ment at all salt levels (in Oa-D at 80 and 100 mM NaCl)it accelerated only after 14 d of salt treatment Controlplants used water more efficiently than salt-treatedplants up until 18 DAS and 24 DAS in Oa-VR andOa-D respectively At 100 mM NaCl Oa-VR used watersubstantially more efficiently than Oa-D with WUI 25higher at 100mM NaCl by the end of the experiment inOa-VRBoth Pokkali and Oa-VR had a 36 lower fresh bio-

mass under the higher salt treatment (100 mM NaCl)compared with non-salinised controls while higher re-ductions were recorded for IR29 and Oa-D (49 and 53respectively Additional file 7 Table S3)

DiscussionComplementary approaches were taken to assess the sal-inity tolerance of linesaccessions of three rice speciesO sativa O australiensis and O meridionalis In a pre-liminary screening prior to these experiments a surveyof a wide range of wild Oryza accessions alongside Pok-kali and IR29 produced a lsquoshort-listrsquo of five accessionschosen from O australiensis and O meridionalis thatwere selected for contrasting tolerance and sensitivity tosalinity during early vegetative growth The wild Oryzaaccessions chosen for this study evolved in geographic-ally isolated populations thereby broadening the rangeof genetic diversity and with it the opportunity to dis-cover novel salt tolerance mechanisms (Menguer et al2017) However the preliminary goal was to find

contrasting salt tolerance within the same species inorder to facilitate subsequent experiments involvingmapping populations and comparative proteomics Inthis paper we report on one destructive experimentwith salt levels maintained at a steady state of 40 and 80mM NaCl and the second non-destructive experimentwhere soil was saturated initially with saline solutionthen followed by daily fresh water applications to replaceevaporation and transpiration The use of a series of im-ages of plants in the Plant Accelerator gave a more dy-namic picture of salinity tolerance than could beachieved by destructive measurements as in the first ex-periment Ion concentrations in the YFL and phenotypicobservations from the first experiment were seminal todeveloping a salt tolerance rankingMultiple strands of evidence from our data including

biomass leaf visual symptoms gas exchange and ionconcentrations confirm the wide range of tolerances tosalt in the genotypes of wild and cultivated rice selectedfor these experiments For example chlorophyll levelswere almost 50 lower in IR29 at 40 mM NaCl but wereunaffected in Oa-VR similar to contrasts in tolerancereported previously (Lutts et al 1996) where 50 mMNaCl lowered chlorophyll levels by up to 70 The cri-teria reported in Fig 1 support the long-established viewthat Pokkali is highly tolerant to salt (Yeo et al 1990)but make a case that the wild O australiensis species(Oa-VR) has at least the same level of salt tolerance Inthe first experiment salt tolerance in Oa-VR was evidentafter 25 d of 80 mM NaCl where shoot biomass was

Fig 4 a Phenotypic changes in response to the different salt treatments 30 days after salting for the salt-tolerant Oa-VR and the salt-sensitive(Oa-D) b Chlorophyll concentration and average relative senescence under non-salinised (0 mM) and salinised (100 mM NaCl) treatments forboth tested genotypes

reduced by 58 in Pokkali compared with controlswhile the reduction in biomass in Oa-VR was marginallyless (50) Moreover symptoms of leaf damage inOa-VR due to NaCl were significantly less pronouncedthan those seen in PokkaliThe additional level of salt tolerance found in Oa-VR

offers a potential tool for crop improvement especiallyin that Oa-VR is from a wild Oryza population with theunique EE genome (Jacquemin et al 2013) and is thusphylogenetically remote from O sativa this enhancesthe possibility of identifying novel mechanisms of salttolerance unique to O australiensis By contrast IR29 isreputedly highly salt-sensitive (Martinez-Atienza et al2006 Islam et al 2011) Surprisingly for the mostsalt-sensitive of the wild rice genotypes (Oa-D andOa-KR) in very moderate salinity (40 mM NaCl) bio-mass and ion concentrations were more stronglyaffected by salt than leaf symptoms possibly indicatinggenotypic variation in tissue tolerance to NaCl as

reported earlier (Yeo et al 1990) In reverse the veryslow absolute growth rates of IR29 appeared paradoxic-ally to result in a small effect of salt on relative growthrates (Fig 3) but much larger effects on senescence (Fig1a) This suggests that a range of performance criteria isessential to distinguish the intrinsic differences in salttolerances in screening experiments This underlines thepolygenic nature of salt tolerance where genes deter-mining ion import compartmentation and metabolicresponses to salt are likely to play a collective role inphysiological tolerance (Munns et al 2008) Thereforebased on the overall indicators of salt tolerance and ratesof shoot development Oa-VR and Oa-D were chosen ascomplementary O australiensis genotypes for imageanalysis (Fig 4) representing contrasting tolerance tosalt in otherwise indistinguishable O australiensis acces-sions While the salt-tolerant genotype (Oa-VR) is fromthe Northern Territory and the salt-sensitive accession isfrom the Kimberley region of Western Australia there is

Fig 5 Relationship between growth and water use during salt treatment Smoothed PSA Water Use Index is shown for the selected genotypesunder salt treatments and non-salinised control conditions The values were obtained by dividing the total increase in sPSA for each interval bythe total water loss in the same interval Thin lines represent individual plants Bold lines represent the grand average of the six replicates foreach treatment Vertical broken lines represent the tested intervals

no obvious basis for predicting their respective toler-ances to salinity without a fine-scale investigation of thecollection sites and the seasonal fluctuations in soilwater content and soil chemistryThe rate at which shoot growth responded to salt (Ex-

periment 2) as well as the internal Na+ and K+ concen-trations of young leaves (Experiment 1) provide insightsinto possible mechanisms of tolerance In rice only partof the Na+ load reaching the leaves is taken up symplas-tically by the roots (Krishnamurthy et al 2009) enteringthe transpiration stream and further regulated under thecontrol of a suite of transporters The low Na+K+ ratiosfound in both Oa-VR and Pokkali (lt 05) suggest that ac-tive mechanisms are in play to exclude Na+ even whenthe external solution was fixed at 80 mM NaCl for 30 dEarly clues as to how this is achieved came from a QTL(Ren et al 2005) now known to contain the OsHKT15gene which enhances Na+ exclusion in rice (Hauser etal 2010) Davenport et al (2007) and others have estab-lished that the HKT1 transporters in Arabidopsis re-trieve Na+ from the xylem In general high-affinity K+

uptake systems have now been shown to be pivotal forthe management of salinity and deficiency symptoms inrice (Suzuki et al 2016) as well as other species such asArabidopsis and wheat (Byrt et al 2007 Munns et al2008 Hauser et al 2010) Further candidates such as theSOS1 transporter might also play a key part in the re-moval of Na+ from the xylem stream (Shi et al 2002)The complexity of the rice HKT transporters identifiedin O sativa (Garciadeblaacutes et al 2003) has not yet beenexplored in a wider range of Oryza genetic backgroundsThe levels of tolerance reported for O australiensisshould stimulate an analysis of the expression of genesregulating Na+ and K+ transport and the functionalproperties of these transporters which may have evolvedin lineages of geographically isolated communities fromthe Australian savannahSodium exclusion appeared to operate effectively in

Pokkali and Oa-VR but failed in other wild rice acces-sions where Na+K+ exceeded 20 in the most severecases at 80 mM NaCl An earlier study reported leafNa+K+ ratios of 44 in 21 indica rice lines after 48 d ofabout 35 mM NaCl (Asch et al 2000) reinforcing theview that Oa-VR is tolerant to salt Supporting thisclaim Na+ concentrations in Pokkali and Oa-VR calcu-lated on a tissue-water basis were half those in the exter-nal solution when the roots were in an 80mM solutionThese contrasting degrees of Na+ exclusion and the con-sequences for plant performance are illustrated by thestrong relationship between ST and the accumulation ofNa+ (Fig 2) Based on the observation that diminishedapoplastic uptake of Na+ in the roots of Pokkali (Krish-namurthy et al 2011) enhances Na+ exclusion the de-gree of bypass flow in Oa-VR and the other genotypes in

the current study is a priority for identifying the mech-anism of salt tolerance The consequences of Na+ loadsin leaves for shoot physiology (SES chlorophyll contentphotosynthesis and tiller development) was apparent forthe wild Oryza species as well as the two O sativastandard genotypes with strong correlations betweenion levels and leaf damageIn the second experiment relative growth rates could

be observed continuously and non-destructively reveal-ing an impact of salt even in the first 4 DAS (Additionalfile 5 Figure S3) A binary impact of salt on plants isexerted through osmotic stress and ion toxicity (Green-way and Munns 1980) The long-term impact of salt inthis 30-d salt treatment was primarily due to toxic ef-fects of Na+ rather than osmotic stress which wouldhave been most apparent in the earliest stages of thetreatment period when tissue ion levels were lowest andosmotic adjustment was not yet established (Munns etal 2016) The more salt-sensitive genotypes appeared tohave less capacity to exclude salt causing leaf Na+ andK+ concentrations to rise above parity and cause toxicityand metabolic impairmentWater use efficiency was substantially greater in

Oa-VR than Oa-D particularly in the first two weeksafter salt was applied suggesting that the resilience ofphotosynthesis observed in salt-treated Oa-VR plantssustained growth (PSA) even as stomatal conductancefell by 60 WUI values for Oa-D plants at 100 mMNaCl were notably lower than those at 40 and 80mMNaCl reflecting the progressively higher impact of NaClon hydraulics in this sensitive genotype as concentra-tions increased from 40 to 100 mM NaCl This trend oflow WUI in salt-treated plants is consistent with previ-ous studies of indica and aus rice (Al-Tamimi et al2016) as well as barley and wheat (Harris et al 2010)The effects of salt are dynamic depending both upon

relative growth rates and ion delivery and rootshoot ra-tios (Munns et al 2016) Non-destructive measurementsof growth showed that the relationship between controland salt-treated plants varied substantially over thetime-course of treatment in all genotypes This waspartly due to the different developmental programs ofeach genotype with Pokkali characterised by vigorousearly growth and an early transition to flowering innon-saline conditions when vegetative growth arrestedthe transition to flowering was delayed in salt-treatedplants Such developmental effects are likely to be a fac-tor in the impact of salinity on yield (Khatun et al1995) Among the wild rices we have observed strongcontrasts in photoperiod sensitivity between accessionsresulting in large differences in duration of vegetativegrowth We speculate that this would affect thetime-course of NaCl accumulation and its impact onbiomass and grain yield

Under paddy and rainfed conditions salt levels in theroot medium are unlikely to remain constant as they didin the treatment regime applied in the first experimentThis variation in salt load was better represented in thePlant Accelerator (Experiment 2) where soil was salinisedand then transpired water replaced with fresh water to thesoil surface daily We contend that these contrasting re-gimes of salt application mimicked both steady-state andtransient salinisation including the salt loads imposed onrice paddies following spasmodic tidal surges The rankingof salt-tolerance for both the O sativa lsquostandardrsquo genotypesand the four wild rice relatives was broadly maintainedunder the two experimental regimes we employedIn this study we explored the naturally occurring vari-

ation in salt tolerance among some of ricersquos wild relativesin comparisons to selected O sativa cultivars Despitethe substantial genetic distance between O australiensis(taxon E) and Oryza sativa (taxon A) several studieshave managed to leap this species barrier allowing thesetwo species to be crossed (Morinaga et al 1960 Nezu etal 1960) Another study reported a rapid phenotype re-covery of the recurrent parent after only two backcrosses(Multani et al 1994) Using this backcrossing approachO australiensis accessions have been used in breedingprograms as a source of tolerance to biotic stresses in-cluding bacterial blight resistance (Brar and Khush1997) brown planthopper resistance (Jena et al 2006)and blast resistance (Jeung et al 2007 Suh et al 2009)Our study highlights the potential use of the Australianwild-species alleles in breeding programs to exploit vari-ations in abiotic stress generally and salinity tolerance inparticular However harnessing alleles from wild rela-tives of rice that confer salt tolerance and applying themto modern cultivars remains a long-term objective untilmechanisms of tolerance become clearer

Additional files

Additional file 1 FigureS1 Relationships between Projected ShootArea (kpixels) 28 and 30 days after salting with Fresh Weight and DryWeight based on 168 individual plants using the fluorescence imagesSquared Pearson correlation coefficients are given on the right (152 kb)

Additional file 2 Table S1 Shoot dry weight shoot fresh weightchlorophyll concentration and photosynthetic rate for the four wild Oryzaaccessions and O sativa controls (15 kb)

Additional file 3 Table S2 Linear correlation (r values) betweenvarious physiological characteristics measured for the four wild Oryzaaccessions and O sativa controls combined at seedling stage grownunder 80 mM NaCl for 30 d = Significant at 5 level of probability and = Significant at 1 level of probability (17 kb)

Additional file 4 Figure 2 Smoothed Projected Shoot Area (describedby kpixels) of Absolute Growth Rates over six intervals within 0ndash28 daysafter salting X-axis represents the salt levels and the error bars representplusmn12 Confidence Interval (85 kb)

Additional file 5 Figure S3 Smoothed Projected Shoot Area(described by kpixels) of Relative Growth Rates over the four salt

treatments within 0ndash25 days after salting Error bars represent plusmn12Confidence Interval (81 kb)

Additional file 6 Figure S4 Absolute growth rates of all testedgenotypes from 0 to 30 DAS including non-salinised controls SmoothedAGR values were derived from projected shoot area (PSA) values to whichsplines had been fitted Thin lines represent individual plants Bold linesrepresent the grand average of the six replicates plants for each treat-ment The vertical broken lines represent the tested intervals (357 kb)

Additional file 7 Table S3 Photosynthetic rate stomatal conductancenumber of tillers and shoot fresh weight of the four wild Oryzaaccessions and O sativa controls The first three traits were evaluated on29 DAS while shoot fresh weight was measured on the termination ofthe experiment on 30 DAS Two measurements were excluded from thestomatal conductance analysis as they gave large negative values (minus 30and minus 50) Reduction values were rounded to the nearest integer (32 kb)

AbbreviationsAGT Absolute Growth Rate ANOVA Analysis of Variance DAS Days AfterSalting DAT Days After Transplanting DF Degrees of Freedom EC ElectricalConductivity FLUO Fluorescence IRRI International Rice Research InstitutePSA Projected Shoot Area PVC Polyvinyl Chloride QTL Quantitative TraitLocus RGB Red-Green-Blue RGR Relative Growth Rate SDW Shoot DryWeight SES Standard Evaluation System SFW Shoot Fresh WeightsPSA Smoothed Projected Shoot Area ST Salinity Tolerance WUI Water UseIndex YFL Youngest Fully Expanded Leaf

AcknowledgementsThe authors acknowledge the financial support of the AustralianGovernment National Collaborative Research Infrastructure Strategy(Australian Plant Phenomics Facility) The authors also acknowledge the useof the facilities and scientific and technical assistance of the Australian PlantPhenomics Facility which is supported by NCRIS The authors would like tothank all staff from the Plant Accelerator at the University of Adelaide forsupport during the experiments We also thank AProf Stuart Roy forconstructive comments on the manuscript

FundingThe research reported in this publication was supported by funding fromThe Australian Plant Phenomics Facility YY was supported by anInternational Postgraduate Research Scholarship

Availability of data and materialsThe datasets used andor analysed during the current study are availablefrom the corresponding author on reasonable request

Authorsrsquo contributionsYY designed and executed the first experiment YY also phenotyped theplants (for both experiments) performed the data analyses for the firstexperiment and wrote the manuscript CB designed the second experimentperformed the spatial correction and conceived of and developed thestatistical analyses for the phenotypic data of the second experiment BBassisted with the phenotypic analyses and revised the manuscript THR andBJA contributed to the original concept of the project and supervised thestudy BJA conceived the project and its components and provided thegenetic material All authors read and contributed to the manuscript

Ethics approval and consent to participateNot applicable

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Publisherrsquos NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations

Author details1Sydney Institute of Agriculture University of Sydney Sydney Australia2School of Agriculture Food and Wine University of Adelaide AdelaideAustralia 3Australian Plant Phenomics Facility The Plant Accelerator WaiteResearch Institute University of Adelaide Adelaide Australia 4Department ofBiological Sciences Macquarie University Sydney Australia

Received 8 August 2018 Accepted 3 December 2018

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high-throughput non-invasive phenotyping Nat Commun 713342Asch F Dingkuhn M Doumlrffling K Miezan K (2000) Leaf K Na ratio predicts

salinity induced yield loss in irrigated rice Euphytica 113109ndash118Atieno J Li Y Langridge P (2017) Exploring genetic variation for salinity tolerance

in chickpea using image-based phenotyping Sci Rep 71ndash11Atwell BJ Wang H Scafaro AP (2014) Could abiotic stress tolerance in wild

relatives of rice be used to improve Oryza sativa Plant Sci 215ndash21648ndash58Ballini E Berruyer R Morel JB (2007) Modern elite rice varieties of the ldquogreen

revolutionrdquo have retained a large introgression from wild rice around thePi33 rice blast resistance locus New Phytol 175340ndash350

Berger B Bas De Regt MT (2012) High-throughput phenotyping in plants shootsMethods Mol Biol 9189ndash20

Brar DS Khush GS (1997) Alien introgression in rice Plant Mol Biol 3535ndash47Brien C J (2018) dae Functions useful in the design and ANOVA of experiments

Version 30-16Brozynska M Copetti D Furtado A (2016) Sequencing of Australian wild rice

genomes reveals ancestral relationships with domesticated rice Plant BiotechJ 151ndash10

Butler DG Cullis BR Gilmour AR Gogel BJ (2009) Analysis of Mixed Models for Slanguage environments ASReml-R reference manual Brisbane DPIPublications

Byrt CS Platten JD Spielmeyer W (2007) HKT15-like cation transporters linked toNa+ exclusion loci in wheat Nax2 and Kna1 Plant Physiol 1431918ndash1928

Campbell MT Du Q Liu K (2017) A comprehensive image-based phenomicanalysis reveals the complex genetic architecture of shoot growth dynamicsin rice Plant Genome 102

Campbell MT Knecht AC Berger B (2015) Integrating image-based phenomicsand association analysis to dissect the genetic architecture of temporalsalinity responses in rice Plant Physiol 1681476ndash1489

Davenport RJ Muntildeoz-Mayor A Jha D (2007) The Na+ transporter AtHKT11controls retrieval of Na+ from the xylem in Arabidopsis Plant CellEnviron 30497ndash507

Flowers TJ (2004) Improving crop salt tolerance J Exp Bot 55307ndash319Fukuda A Nakamura A Tagiri A (2004) Function intracellular localization and the

importance in salt tolerance of a vacuolar Na+H+ antiporter from rice PlantCell Physiol 45146ndash159

Garciadeblaacutes B Senn ME Bantildeuelos MA Rodriacuteguez-Navarro A (2003) Sodiumtransport and HKT transporters the rice model Plant J 34788ndash801

Grattan SR Shannon MC Roberts SR (2002) Rice is more sensitive to salinity thanpreviously thought Calif Agric 56189ndash195

Greenway H Munns R (1980) Mechanisms of salt tolerance in nonhalophytesAnnu Rev Plant Biol 31149ndash190

Gregorio GB Senadhira D (1993) Genetic analysis of salinity tolerance in rice(Oryza sativa L) Theor Appl Genet 86333ndash338

Hairmansis A Berger B Tester M Roy SJ (2014) Image-based phenotyping for non-destructive screening of different salinity tolerance traits in rice Rice 71ndash10

Harris BN Sadras VO Tester M (2010) A water-centred framework to assess theeffects of salinity on the growth and yield of wheat and barley Plant Soil336377ndash389

Hauser F Horie T (2010) A conserved primary salt tolerance mechanismmediated by HKT transporters a mechanism for sodium exclusion andmaintenance of high K+Na+ ratio in leaves during salinity stress Plant CellEnviron 33552ndash565

Henry RJ Rice N Waters DLE (2010) Australian Oryza utility and conservationRice 3235ndash241

IRRI (2013) Standard Evaluation System (SES) for Rice International Rice ResearchInstitute Manila p 38

Islam MR Salam MA Hassan L Collard BCY Singh RK Gregorio GB (2011) QTLmapping for salinity tolerance in rice Physiol Mol Biol Plants 23137ndash146

Ismail AM Horie T (2017) Molecular breeding approaches for improving salttolerance Annu Rev Plant Biol 681ndash30

Jacquemin J Bhatia D Singh K Wing RA (2013) The international Oryza mapalignment project development of a genus-wide comparative genomicsplatform to help solve the 9 billion-people question Curr Opin PlantBiol 16147ndash156

Jena KK Jeung JU Lee JH (2006) High-resolution mapping of a new brownplanthopper (BPH) resistance gene Bph18(t) and marker-assisted selectionfor BPH resistance in rice (Oryza sativa L) Theor Appl Genet 112288ndash297

Jeung JU Kim BR Cho YC (2007) A novel gene Pi40(t) linked to the DNAmarkers derived from NBS-LRR motifs confers broad spectrum of blastresistance in rice Theor Appl Genet 1151163ndash1177

Khatun S Flowers TJ (1995) Effects of salinity on seed set in rice Plant CellEnviron 1861ndash67

Khush GS (1997) Origin dispersal cultivation and variation of rice Plant Mol Biol3525ndash34

Khush GS (2005) What it will take to feed 50 billion rice consumers in 2030 PlantMol Biol 59(1)ndash6

Krishnamurthy P Ranathunge K Franke R (2009) The role of root apoplastictransport barriers in salt tolerance of rice (Oryza sativa L) Planta 230119ndash134

Krishnamurthy P Ranathunge K Nayak S (2011) Root apoplastic barriers blockNa+ transport to shoots in rice (Oryza sativa L) J Exp Bot 624215ndash4228

Lang N Li Z Buu B (2001) Microsatellite markers linked to salt tolerance in riceOmonrice 99ndash21

Lutts S Kinet JM Bouharmont J (1995) Changes in plant response to NaCl duringdevelopment of rice (Oryza sativa L) varieties differing in salinity resistance JExp Bot 461843ndash1852

Lutts S Kinet JM Bouharmont J (1996) NaCl-induced senescence in leaves of rice(Oryza sativa L) cultivars differing in salinity resistance Ann Bot 78389ndash398

Mackinney G (1941) Absorption of light by chlorophyll solutions J Biol Chem140315ndash322

Martinez-Atienza J Jiang X Garciadeblas B (2006) Conservation of the salt overlysensitive pathway in rice Plant Physiol 1431001ndash1012

Menguer PK Sperotto RA Ricachenevsky FK (2017) A walk on the wild side Oryzaspecies as source for rice abiotic stress tolerance Genet Mol Biol 40238ndash252

Morinaga T Kuriyama H (1960) Interspecific hybrids and genomic constitution ofvarious species in the genus Oryza Agric Hortic 351245ndash1247

Multani DS Jena KK Brar DS de los Reyes BG Angeles ER Khush GS (1994)Development of monosomic alien addition lines and introgression of genesfrom Oryza australiensis Domin to cultivated rice O sativa L Theor ApplGenet 88102ndash109

Munns R James RA Gilliham M (2016) Tissue tolerance an essential but elusivetrait for salt-tolerant crops Funct Plant Biol 431103ndash1113

Munns R Tester M (2008) Mechanisms of salinity tolerance Annu Rev Plant Biol59651ndash681

Nezu M Katayama TC Kihara H (1960) Genetic study of the genus Oryza ICrossability and chromosomal affinity among 17 species Seiken Jiho 111ndash11

Ochiai K Matoh T (2002) Characterization of the Na+ delivery from roots toshoots in rice under saline stress excessive salt enhances apoplastictransport in rice plants Soil Sci Plant Nutr 48371ndash378

Qadir M Quilleacuterou E Nangia V (2014) Economics of salt-induced landdegradation and restoration Nat Resour Forum 38282ndash295

R Core Team (2018) R A language and environment for statistical computingVienna Austria R Foundation for Statistical Computing

Rahman ML Jiang W Chu SH (2009) High-resolution mapping of two rice brownplanthopper resistance genes Bph20(t) and Bph21(t) originating from Oryzaminuta Theor Appl Genet 1191237ndash1246

Ren Z-H Gao J-P Li L (2005) A rice quantitative trait locus for salt toleranceencodes a sodium transporter Nat Genet 371141ndash1146

Sabouri H Sabouri A (2008) New evidence of QTLs attributed to salinity tolerancein African J Biotechnol 74376ndash4383

Scafaro AP Galleacute A Van Rie J (2016) Heat tolerance in a wild Oryza species isattributed to maintenance of rubisco activation by a thermally stable rubiscoactivase ortholog New Phytol 211899ndash911

Scafaro AP Haynes PA Atwell BJ (2010) Physiological and molecular changes inOryza meridionalis ng a heat-tolerant species of wild rice J Exp Bot 61191ndash202

Shi H Quintero FJ Pardo JM Zhu JK (2002) The putative plasma membrane Na+H+

antiporter SOS1 controls long-distance Na+ transport in plants Plant Cell 14465ndash477Stein JC Yu Y Copetti D (2018) Genomes of 13 domesticated and wild rice

relatives highlight genetic conservation turnover and innovation across thegenus Oryza Nat Genet 50285ndash296

Suh JP Roh JH Cho YC (2009) The pi40 gene for durable resistance to rice blastand molecular analysis of pi40-advanced backcross breeding linesPhytopathology 99243ndash250

Suzuki K Costa A Nakayama H (2016) OsHKT221-mediated Na+ influx over K+

uptake in roots potentially increases toxic Na+ accumulation in a salt-tolerantlandrace of rice Nona Bokra upon salinity stress J Plant Res 12967ndash77

Takagi H Tamiru M Abe A (2015) MutMap accelerates breeding of a salt-tolerantrice cultivar Nat Biotechnol 33445ndash449

Thomson MJ de Ocampo M Egdane J (2010) Characterizing the Saltolquantitative trait locus for salinity tolerance in rice Rice 3148ndash160

Wang W Vinocur B Altman A (2003) Plant responses to drought salinity andextreme temperatures towards genetic engineering for stress tolerancePlanta 2181ndash14

Wickham H (2009) ggplot2 Create Elegant Data Visualisations Using theGrammar of Graphics R package version 221

Yadav R Flowers TJ Yeo A (1996) The involvement of the transpirational bypassflow in sodium uptake by high- and low-sodium-transporting lines of ricedeveloped through intravarietal selection Plant Cell Environ 19329ndash336

Yao MZ Wang JF Chen HY Zha HQ Zhang HS (2005) Inheritance and QTLmapping of salt tolerance in rice Rice Sci 1225ndash32

Yeo AR Yeo ME Flowers SA Flowers TJ (1990) Screening of rice (Oryza sativa L)genotypes for physiological characters contributing to salinity resistance andtheir relationship to overall performance Theor Appl Genet 79377ndash384

Yeo AR Yeo ME Flowers TJ (1987) The contribution of an apoplastic pathway tosodium uptake by rice roots in saline conditions J Exp Bot 381141ndash1153

Zeng L Shannon MC Grieve CM (2002) Evaluation of salt tolerance in ricegenotypes by multiple agronomic parameters Euphytica235ndash245

Zhu Q Zheng X Luo J (2007) Multilocus analysis of nucleotide variation of Oryzasativa and its wild relatives severe bottleneck during domestication of riceMol Biol Evol 24875ndash888

RESEARCH ARTICLEwwwproteomics-journalcom

Salt-Treated Roots of Oryza australiensis Seedlings areEnriched with Proteins Involved in Energetics and Transport

Yoav Yichie Mafruha T Hasan Peri A Tobias Dana Pascovici Hugh D GooldSteven C Van Sluyter Thomas H Roberts and Brian J Atwell

Salinity is a major constraint on rice productivity worldwide Howevermechanisms of salt tolerance in wild rice relatives are unknown Rootmicrosomal proteins are extracted from two Oryza australiensis accessionscontrasting in salt tolerance Whole roots of 2-week-old seedlings are treatedwith 80 mM NaCl for 30 days to induce salt stress Proteins are quantified bytandem mass tags (TMT) and triple-stage Mass Spectrometry More than 200differentially expressed proteins between the salt-treated and control samplesin the two accessions (p-value lt005) are found Gene Ontology (GO) analysisshows that proteins categorized as ldquometabolic processrdquo ldquotransportrdquo andldquotransmembrane transporterrdquo are highly responsive to salt treatment Inparticular mitochondrial ATPases and SNARE proteins are more abundant inroots of the salt-tolerant accession and responded strongly when roots areexposed to salinity mRNA quantification validated the elevated proteinabundances of a monosaccharide transporter and an antiporter observed inthe salt-tolerant genotype The importance of the upregulatedmonosaccharide transporter and a VAMP-like protein by measuring salinityresponses of two yeast knockout mutants for genes homologous to thoseencoding these proteins in rice are confirmed Potential new mechanisms ofsalt tolerance in rice with implications for breeding of elite cultivars are alsodiscussed

1 Introduction

Rice (Oryza sativa L) is one of the most important staple foodcrops globally providing a primary source of carbohydrates formore than half of the worldrsquos population[1] Demand for rice isexpected to increase tomore than 800million tons in 2035[2] Riceis the leading source of calories in many developing countries

Y Yichie Dr M T Hasan Dr P A Tobias T H RobertsSydney Institute of AgricultureUniversity of SydneySydney AustraliaE-mail yoavyichiesydneyeduauDr D PascoviciAustralian Proteome Analysis FacilityDepartment of Molecular SciencesMacquarie UniversitySydney Australia

The ORCID identification number(s) for the author(s) of this articlecan be found under httpsdoiorg101002pmic201900175

DOI 101002pmic201900175

but substantial areas of otherwise high-yielding environments are subject tosalinization where toxic salt levels arefurther exacerbated by rising sea levelstidal surges and poorly regulated irriga-tion systems[3]

The polygenic nature of salt tolerancein plants has made it difficult to en-act effective countermeasures throughbreeding[4] The risks associated withsalinity are further amplified by globalpopulation growth requiring amore pro-found knowledge of the genetic vari-ation in salt tolerance and traits thatmight be used to improve toleranceSome genetic variation in salt toler-

ance has been reported among cultivatedrice varieties[5ndash7] Indeed several breed-ing programmes have used O sativa cul-tivars such as Pokkali and Nona Bokraas salt-tolerant parent donors incorpo-rating Saltol and other salt tolerancegenes[38] However the allelic variationrequired to breed stress-tolerant cropsmust now be expanded by introgressinggenes from wild relatives[910] because of

the relatively small proportion of the total genetic diversity inthe genus Oryza found in O sativa[11] Salinity tolerance of otherkey crop species such as durum wheat (Triticum durum)[12] andtomato (Solanum lycopersicum)[9] has been improved using natu-ral allelic variationEndemic Australian rice species have been identified as a

source of tolerance to abiotic and biotic stress in cultivated

Dr H D GooldNSW Department of Primary IndustriesMacquarie UniversitySydney AustraliaDr H D GooldDepartment of Molecular SciencesMacquarie UniversitySydney AustraliaDr S C Van Sluyter Prof B J AtwellDepartment of Biological SciencesMacquarie UniversitySydney Australia

Proteomics 2019 19 1900175 copy 2019 WILEY-VCH Verlag GmbH amp Co KGaA Weinheim1900175 (1 of 12)

wwwadvancedsciencenewscom wwwproteomics-journalcom

rice[1314] Tissue tolerance to Na+ in seven pantropical wild ricespecies was reported recently implying the presence of keytolerance genes in the Oryza CC and DD genomes[10] Mem-brane transporters are a vital part of the control of influx ef-flux and partitioning of Na+ and Clminus For example withinthe Saltol QTL region OsHKT8 was identified to encode fora transporter that unloads Na+ from the xylem[15] Howevercare must be taken to acknowledge the many other potentialsources of tolerance such as the development of passage cells inrootsSeveral studies have investigated the molecular responses to

salt stress in rice using qualitative proteomics technologies[61617]

including root samples from O sativa[18] A quantitative riceplasma membrane study identified several important mecha-nisms of plant adaptation to salinity stress[19] Some of thesemechanisms are involved in the regulation of plasma mem-brane pumps and channels amelioration of oxidative stress sig-nal transduction and ldquomembrane and protein structurerdquo To ourknowledge this approach has not been applied to wild Oryzaspecies the accessions we identified recently[20] now make thisa priorityIn this study we used Tandem Mass Tags (TMT) to quantify

salinity-induced differences in the root membrane protein com-plement between two Australian Oryza australiensis accessionswhich we had established as salt-tolerant and susceptible[20]

Oryza australiensis is widely distributed across northern Aus-traliarsquos savannah and is well-adapted to erratic water supply sus-tained heat and spasmodic inundation from coastal and inlandwaterways By adopting the TMT approach we aimed to providea deeper understanding of salt-tolerance mechanisms that maynot have evolved in O sativa with the goal of providing molec-ular markers for the development of rice cultivars with greaterresilience to soil salinity

2 Experimental Section

21 Growth and Salinity Treatments

Following initial screening of a wide range of rice species andaccessions for growth responses to 25 and 75 mM NaCl in a hy-droponic solution two accessions of O australiensis were chosenfor this study Oa-VR and Oa-D which were salinity tolerant andsensitive respectively[20] Seeds were germinated on Petri dishesat 28 degC and at the two- to three-leaf stage transferred to dark-walled containers in Yoshida hydroponic solution[21] Plants weregrown in a temperature-controlled glasshouse with a 14-h pho-toperiod and daynight temperatures of 2822 degC with light in-tensity exceeding 700 micromolmminus2 sminus1 After 1 week in hydroponicsplants were exposed to salt solution (details below) or left as salt-free controls (ldquocontrolrdquo)Fifteen plants of each genotype were grown in each treatment

contributing five plants to each biological triplicate Fifteen daysafter germination (DAG) salt treatment was imposed graduallyin daily increments to concentrations of 25 40 and finally 80mMby adding NaCl to a final electrical conductivity (EC) of 10 dSmminus1[21] Hydroponic solutions were replaced at every 5 days and apH of 5 wasmaintained daily by adding 1 NNaOHorHCl Plantswere grown on a foam tray with netted holes to allow only the

Significance Statement

Expressionof genes in roots plays an important role in re-sponsesof rice to salinity because exclusionmechanismsarean important defense against salt toxicityQuantitative pro-teomics ofmembrane-enriched root preparationsoffers thepossibility of discoveringnewpathways of salt tolerance By ap-plying this approach toOryza australiensis a distant relative ofO sativa we contrast proteomic profiles atmoderate salt levelsin sensitive and tolerant accessions identified fromgenotypesendemic to theAustralian savannahWe found116proteinswere significantlymore abundant in the salt-tolerant than thesensitive accession after salt treatmentwhile 88proteinswererelatively less abundant in the tolerant accession After analysisof themost enrichedpathwaysmitochondrial ATPases andSNAREproteinswere found tobeparticularly responsive tosalt whichwe speculate play an indirect role in ion transportWe validated the salinity tolerancephenotypeof someof thedifferentially expressed root proteins via bothRT-qPCRandtestingof yeast strainswith deletions in homologuesof thegenes encoding thoseproteinsOur findingsprovide valuableinsights into pathways anda few individual proteins that con-tribute to salt tolerance inOaustraliensis andmay serve as thebasis for improving salinity tolerance in elite rice varieties andother important crops

roots to contact the solution The foam trays were covered withfoil to keep the roots in the dark thus preventing algal growthAir pumps were used to maintain vigorous aeration in the hydro-ponic solution

22 Preparation of Root Microsomal Protein Fractions

Thirty days after salt application (DAS) the entire root systemswere harvested and washed thoroughly with deionized waterProteins were extracted by grinding the washed roots with a mor-tar and pestle in 2mL ice-cold extraction buffer per gram of tissueas described[22] but with the addition of 1 mM sodium sulfiteHomogenates were filtered and centrifuged[22] and the pelletswere discarded Supernatants were centrifuged again at 87000 timesg for 35 min The pellets were washed with the same extractionbuffer (without BSA) and centrifuged as above The microsomalprotein and ultracentrifugation steps were repeated three timesso that transmembrane proteins were concentrated in the finalpelletPellets were dissolved with sonication in 100 microL 8 M urea 2SDS 02MN-methylmorpholine 01M acetic acid 10mM tris(2-carboxyethyl)phosphine (TCEP) then incubated at room temper-ature for 1 h to reduce disulphide bonds Cysteines were alkylatedby incubating with 4 microL 25 2-vinylpyridine in methanol for 1h at room temperature Alkylation was quenched with 2 microL of2-mercaptoethanolAlkylated proteins were extracted by acetate solvent pro-

tein extraction (ASPEX) according to Aspinwall et al[23] exceptthat the volumes of solvents and ammonium acetate solutionwere doubled The volumes of 11 ethanoldiethyl ether 01 M

triethylamine 01 M acetic acid 1 water 1 DMSO were keptat 15 mLThe ASPEX-extracted pellets were redissolved in 100 microL

8 M urea 2 SDS 02 M N-methylmorpholine 01 Macetic acid and protein concentrations determined by BCAassay (Thermo Scientific Rockford IL) Protein aliquots(50 microg) were then ASPEX extracted without the inclusion ofapomyoglobin[23]

23 Lys-Ctrypsin Digestion and TMT Reaction

Partially air-dried pellets were digested in Rapigest containingLys-C and trypsin as described[23] at pH 84 except that 04Rapigest was used instead of 03 Also instead of stoppingovernight digests by acidification with TFA digests were labeledwith TMT 10-plex reagents (Thermo Scientific) directly beforeacidifying the samplesA master mix of the 12 samples was created by pooling 4 microL

of each sample and labeled with the 126 channel All other chan-nels were randomly assigned to the samples in two sets of sixTMT channels The TMT reagent was dissolved in dry ACN andreactions were carried out according to the manufacturerrsquos in-structions After a 1-h incubation at room temperature reactionswere quenched with 2 microL 5 hydroxylamine for 15 minThe six channels per TMT set and the master mix were com-

bined and incubated with 250 microL of 05 TFA at 37 degC for 45minto hydrolyze the Rapigest The pooled samples were evaporatedto approximately 250 microL with a centrifugal evaporator (Eppen-dorf Hamburg Germany) and 250 microL of 01 TFA was addedfollowed by centrifugation at 15000 times g for 5 minSupernatants were desalted by solid-phase extraction using

Oasis HLB SPE cartridges (Waters Milford MA) as described[24]

Samples were dried to completion overnight in a centrifugalevaporator and reconstituted in water for hydrophilic interac-tion liquid chromatography (HILIC) fractionation Aliquots of25 microL of peptide for the total proteome analysis were fraction-ated as described previously[25] dividing each sample into sevenfractions

24 NanoLCndashMS3 Analysis Using an Orbitrap Fusion TribridtradeMass Spectrometer

Each TMT-labeled HILIC fraction was resuspended in 6 microLof MS Loading Buffer (3 (vv) ACN 01 (vv) formic acid)and analyzed by nanoLCndashMSMSMS using a Dionex Ultimate3000 HPLC system coupled to a Thermo Scientific OrbitrapFusion Tribrid Mass Spectrometer Peptides were injected ontoa reversed-phase column (75 microm id times 40 cm) packed in-housewith C18AQmaterial of particle size 19 microm (DrMaisch Ammer-buch Germany) and eluted with 2ndash30 ACN containing 01(vv) formic acid for 140 min at a flow rate of 250 nL minminus1 at55 degC The MS1 scans were acquired over the range of 350ndash1400 mz (120000 resolution 4e5 AGC 50 ms maximuminjection time) followed by MS2 and MS3 data-dependentacquisitions of the 20 most intense ions with higher collisiondissociation (HCD-MS3) (60000 resolution 1e5 AGC 300 msinjection time 2 mz isolation window)

25 Protein Identification

Raw data files of mass spectra generated using the Xcalibur soft-ware were processed using Proteome Discoverer 22 (ThermoScientific) with local Sequest HT andMascot servers[26] Since thesamples were derived fromO australiensis for which the genomehas not been sequenced a combined Oryza database was assem-bled as the search database Available Oryza species identifiersfrom UniProt were chosen consisting of O barthii O glaber-rima O nivara O punctata O rufipogon O sativa sp indica Osativa sp japonica and O meridionalis (downloaded from httpwwwuniprotcom in August 2018) The database was concate-nated (90 identity threshold) using CD-HIT software[27] givinga total of 133 465 sequences common contaminant protein se-quences were from GPM DB (httpswwwthegpmorgcrap)Search parameters includedMS andMSMS tolerances ofplusmn2 Daand plusmn02 Da and up to two missed trypsin cleavage sites Fixedmodifications were set for carbamidomethylation of cysteine andTMT tags on lysine residues and peptide N-termini Variablemodifications were set for oxidation of methionine and deamina-tion of asparagine and glutamine residues Proteins results werefiltered to 1 FDR quantified by summing reporter ion countsacross all peptide identifications and the summed signal intensi-ties were normalized to the channel that contributed the highestoverall signal

26 Analysis of Differentially Expressed Proteins (DEPs)and Functional Annotation

The TMTPrepPro scripts implemented in the R programminglanguage[28] were used for the subsequent analysis they wereaccessed through a graphical user interface provided via a localGenePattern server The scripts were used to identify DEPs and tocarry out overall multivariate analyses on the resulting datasetsFour quantitative comparisons were made of the DEPs be-

tween the two genotypes and treatments

(a) Oa-VR salt versus Oa-VR control

(b) Oa-D salt versus Oa-D control

(c) Oa-VR salt versus Oa-D salt

(d) (Oa-VR salt versus Oa-VR control)(Oa-D salt versus Oa-Dcontrol) that is the salt times genotype interaction

Student t-tests for each of the above comparisons and an Anal-ysis of Variance (ANOVA) were performed on log-transformedratios Proteins were deemed to be differentially expressed ifthey met the criteria of p-value lt005 and fold change gt15 orlt067 The quantified proteins were classified by parallel se-quence searches against reference databases to compile the re-sults and compute the most likely functional categories (BINs)for each query using MapMan[29] Bioinformatics analysis wasperformed using Mercator and MapMan[2930] to categorize theproteins into their biological processesSequential BLASTP searches with an E-value cut-off of 1eminus10

was used to map the sequences to corresponding identifiers inthe UniProt O sativa database Gene Ontology (GO) informa-tion was extracted from the UniProt database andmatched to theidentified proteins This GO information was used to categorize

the biological processes associated with DEPs using the PloGOtool[31] as described before[32] These proteins were categorizedinto a selected number of biological processes of interest usingthe PloGO tool which were further assessed for ldquoenrichmentrdquo inresponse to salt by means of Fisherrsquos exact test and in terms oftheir overall salt response by GO category using the same PloGOtool Proteins were then classified into pathways based on biolog-ical process information available on the KEGG database[29]

27 Primer Design

Primers were designed against the OsMST6 gene encoding aplasma membrane monosaccharide transporter from O sativa(Os07g37320) which was homologous to the correspondingO australiensis protein (UniProt A0A0D3GSD4) while theOs12g03860 gene was used for UniProt A0A0E0MJB0 Primer3software version 040 (httpbioinfouteeprimer3-040) wasutilized ensuring at least one primer spanned an intron Forwardand reverse primers Os07g37320 (F TGGTGGTGAACAACG-GAGG R CACCGACGGGAAGAACTTGA) Os12g03860 (FAGACTTGCATGTTGCTCGGA R AATGACAGGCTTACGGC-CAA) and a reference gene Eukaryotic elongation factor 1-alpha(F TTTCACTCTTGGTGTGAAGCAGAT R GACTTCCTTCAC-GATTTCATCGTAA) were BLASTed against theO sativa genomewithin Phytozome (v121) for target specificity Both primers setswere synthesized by Integrated DNA Technologies Ltd (NSWAustralia) and tested on complementary DNA (cDNA) using theBioLine SensiFAST SYBR No-ROX Kit according to the manu-facturerrsquos instructions Resulting amplicons were visualized us-ing 2 agarose gel electrophoresis and bands were validated withthe expected amplicon sizes

28 RNA Extraction and Quantitative Reverse-Transcription PCR(RT-qPCR) Analysis of Rice Gene Expression

Harvested roots (section 22) were immediately placed in liquidnitrogen before being stored at minus80 ˚C Three biological repli-cates were collected per genotype and treatment giving a total of12 samples Total RNA was extracted using the SigmandashAldrichSpectrumtrade Total RNA Kit (Sigma-Aldrich St Louis MO) usingProtocol A with incubation at 56 ˚C for 6 min for the tissuelysis cDNA was synthesized using the SensiFAST cDNA Syn-thesis Kit (BioLine NSW Australia) as per the manufacturerrsquosinstructions Primer pairs were run separately on 96-well plates(20 microL BioLine SensiFAST SYBR No-ROX Kit) with salt-treatedand control cDNA Serial dilutions were loaded in triplicate[33]

and PCR thermocycling was performed using the BioRad C1000Touch thermocycler as per the previously confirmed assay Rel-ative gene expression in salt-treated plants versus control plantswas calculated for each gene with calibration to the referencegene using efficiency-corrected calculation models based onreplicate samples[34]

29 Validation of Candidate Salt-Responsive Genes Using a YeastDeletion Library

The Saccharomyces cerevisiae deletion library containing gt21000haploid gene deletion mutants and the parental strain BY4742

(MATa his3D1 leu2D0 lys2D0 ura3D0 wild type [WT]) were in-terrogated to validate protein hits from the rice TMT-labeled pro-teomics experiment[35] Rice gene sequences for some of themoststrongly salt-affected proteins were BLASTed against the yeastgenome using the Saccharomyces Genome Database (SGD) toidentify the closest yeast gene homologuesThe corresponding yeast deletion strains identified from the

deletion yeast library[35] were used to assess colony growth versusWT when these lines were exposed to salinity NaCl was added at300mM 700mM and 10 M to the YPD solid medium (1 yeastextract 2 peptone 2d-glucose) at 30 degC These salt concentra-tions were much higher than those used for the rice experimentsbecause yeast is highly salt tolerant[36] For control images strainswere also grown in the absence of exogenous NaCl

3 Results

31 Growth and Phenotype of O australiensis Accessions underSalt Stress

Root microsomal fractions were extracted at 30 days after ex-posure to NaCl Salt-stress symptoms in both accessions wereapparent Growth was markedly more affected in Oa-D than inOa-VR after the salt treatment as previously reported[20] Further-more leaf necrosis was seen only in Oa-D All seedlings grewvigorously in the absence of salt with green and healthy leavesand a visibly larger root system than in the presence of salt

Only peptides with p-values below the Mascot significancethreshold filter of 005 were included in the search result A to-tal of 2680 and 2473 proteins were quantified (FDR lt1) inthe Oa-VR and Oa-D accessions respectively (Table 1A) TheUniProt taxonomy tool was used to sort these hits from individualrice species in a combined rice database comprising sequencesfrom several accessions as described in the section 2 The high-est number of matches was the 1090 annotated proteins fromO punctata while O sativa and O barthii generated 670 and625 hits respectively (Table 1B) The functional MapMan cat-egories of the reference data coverage of quantified proteinswere combined and the numbers of proteins protein domainsand family profiles classified in the 35 main MapMan categories(Figure 1) Of all the quantified proteins 10were categorized astransporters 8 as signaling proteins and 4 as stress proteins(Figure 1A) About 40 of the quantified proteins had at least onetransmembrane region (Figure 1B) of which more than 200 (6of the total proteins identified) had ten or more transmembranedomains

33 Statistically Significant Differentially Expressed Proteins

Sample replicates (control and salt) were plotted to evaluatethe consistency of the TMT experiment Only minor deviationswere observed between replicates and principal component anal-ysis showed that biological replicates were clustered All tested

Table 1 (A) Summary of proteins identified and quantified bymultiple pep-tides forO australiensis accessionsOa-VR andOa-D using the TMT quan-tification method (FDR lt1) (B) Number of proteins identified for Oa-VR and Oa-D accessions from the combined Oryza database (consistingOryza barthii Oryza glaberrima Oryza nivara Oryza punctata Oryza rufi-pogon Oryza sativa sp indica Oryza sativa sp Japonica and Oryza merid-ionalis) and the corresponding genome of eachOryza species The numberof hits corresponding to each taxon was determined using the UniProt tax-onomy tool

Oryzaaustraliensisaccession

Totalredundantpeptides

Uniquepeptides

Totalredundantproteins

Proteinsquantifiedby multiplepeptides

Oa-VR 57 498 43 788 11 046 2680

Oa-D 52 925 40 113 9986 2473

Oryzaspecies

Numberof hits

Genome

O barthii 625 AA

O glaberrima 192 AA

O meridionalis 547 AA

O punctata 1090 BB

O rufipogon 231 AA

O sativa 670 AA

genotype and treatment combinations had similar log ratio dis-tributions (Figure S1A-S1C Supporting Information) To de-termine whether a protein was significantly up- or downregu-lated between the two treatments or genotypes we imposed twocriteria (i) the absolute fold-change values which had to be gt15or lt067 for up- and downregulated proteins respectively and(ii) the p-value which had to be lt005 according to a t-test per-formed between the three biological replicates (salt vs control)

The TMT overall multirun hits resulted in a multivariateoverview of the data which could be represented as four unsu-pervised cluster patterns (Table S1 and Figure S2 SupportingInformation) Accordingly 190 proteins were upregulated inboth sensitive and tolerant accessions under salt treatment while197 proteins were downregulated in both genotypes under thesame salt treatment (Figure S2 Supporting Information)A total of 268 proteins increased by at least the 15-fold cut-

off in at least one of the tested comparisons (Experimental Sec-tion) This increase was significant for 260 proteins as foundusing an ANOVA test with three replicates at p lt005 (Ta-ble S1 Supporting Information) The largest change in proteinabundance was a 645-fold increase in an uncharacterized pro-tein (UniProt A0A0D3H139) in the sensitive accession (Oa-D) treated with salt compared with the same accession grownwithout salt (Table S1 Supporting Information) The five high-est fold changes that were induced by salt were observed in bothaccessions

34 SaltndashGenotype Interaction

In salt-treated plants 116 proteins were significantly upreg-ulated and 88 proteins were significantly downregulated inOa-VR relative to Oa-D (Table 2) while 1132 responded to asimilar degree in the two genotypes When the data from bothaccessions were combined the numbers of up- and downreg-ulated salt-responsive proteins identified were almost equalwith 1341 up and 1339 down in Oa-VR and 1279 up and 1194down in Oa-D (data not shown) compared with the respectivecontrols However the proportion of individual proteins withsignificantly downregulated expression in response to salt was48 for Oa-VR (the salt-tolerant genotype) which was lowerthan the 55 observed for Oa-D (Table 2)Proteins comprising the functional processes of lipid trans-

porter activity transporter activity and transmembrane trans-porter activity were significantly upregulated (p lt001) in Oa-D

Figure 1 (A) An overview of the percentages of identified proteins categorized in the MapMan BINs of all quantified proteins The quantified proteinswere classified by a parallel sequence search against reference databases to compile the results and compute the most likely MapMan BINs for eachquery (B) Quantified proteins were analyzed for transmembrane (TM) domains using TMHMM ldquo0 TMrdquo represents proteins with no transmembranedomain ldquo1 TMrdquo for one transmembrane domain and so on Protein modification and metabolism including synthesis degradation and localizationProteins involved in cell divisioncycleorganizationvesicle transport Miscellaneous proteins including peroxidases and other enzymes notdesignated to specific groups

Table 2 Overall numbers of significantly up- and downregulated (foldchange gt15 or lt067 respectively) proteins in multiple two-sample com-parisons within accessions in response to salt and between accessionswith salt treatment (p-value lt005)

Significant changes(Student t-testp lt005)

Oa-VR_Saltvs Control

Oa-D_Saltvs Control

Oa-VR_Saltvs Oa-D_Salt

Upregulated 104 (52) 128 (45) 116 (57)

Downregulated 96 (48) 154 (55) 88 (43)

Percentage values in brackets represent the proportion number of proteins that wereupdownregulated in each comparison

compared with Oa-VR (Figure 3) All eight proteins involved inlipid transporter activity that were found in the tolerant genotypewere downregulated significantly under salt treatment (Figure 3and Table S2 Supporting Information)

35 Functional Annotation and Pathway Analysis

The identified proteins were classified into several biological pro-cesses and molecular functions of interest When all identifiedproteins from both genotypes were combined the categories con-taining themost upregulated proteins were those associated with

ldquometabolic processrdquo ldquoprotein metabolic processrdquo ldquotransportrdquoand ldquotransmembrane transporter activityrdquo (Figure 2) The firsttwo of these categories were highly enriched in terms of proteinnumbers among the proteins upregulated in the salt-treated Oa-VR compared with the salt-treatedOa-D (Fisher exact test p-valuelt10minus5) the ldquotransmembrane transporter activityrdquo category wasenriched among the proteins upregulated in the salt-treatedOa-Daccession (Figure S3 and Table S3 Supporting Information) Thetransport category was represented by nine subcategories andlog-fold changes were calculated for both genotypes (Figure 3)Several transport categories including ldquotransporter activityrdquo andldquotransmembrane transporter activityrdquo had increased numbers ofproteins when Oa-D plants were salt treated (Table S2 Support-ing Information) consistent with the relative enrichment of pro-teins as a proportion of the numbers of proteins identified witheach of these categoriesThe KEGG pathway mapper was used to assign the identified

proteins to pathways Of the 363 hits for transport proteinsquantified oxidative phosphorylation and SNARE interactionsin vacuolar transport were the pathways with the most proteinsaffected by salt treatment as well as being highly enrichedrelative to other transport proteins in terms of protein numbers(Fisher exact test p-value lt10minus10) Under salt treatment sevenkey subunits (of a total of 12) of vacuolar-type H+-ATPase weredifferentially expressed in the tolerant genotype Additionally

Figure 2 Qualitative comparison of differentially expressed proteins of Oa-VR and Oa-D showing total numbers of up- and downregulated proteinsunder salt and control treatments Up- and downregulated proteins were categorized into several biological process and molecular function categoriesof interest Upregulated proteins are plotted to the right and downregulated proteins are plotted to the left of the central y-axis Values in bracketsrepresent the proportion of each group out of the entire set of proteins

Figure 3 Boxplot representing the subset of transport-related Gene Ontology categories used to assess salt-response protein abundance across the twoaccessions Individual up- and downregulation (log fold changes) in the nine transport subgroups were determined for the salt-sensitive (white) andsalt-tolerant (grey) accessions ofO australiensis Fold change values were calculated as a ratio between the response to salt and the control plants Eachbox indicates the 25 and 75 percentiles the bold line across the box depicts the median and the dots represent the outlier proteins The significance ofdifferent values comparing each set of accessions under the same transporter group are denoted by asterisks (p lt005 p lt001 by Student t-test)

13 proteins were differentially expressed in the SNARE inter-actions in the vacuolar transport pathway Of these five andeight proteins were upregulated in Oa-VR and Oa-D respec-tively and six and three proteins were downregulated in Oa-VRand Oa-D respectively under salt treatment In addition totalprotein abundance for each category was summed for the tol-erant and sensitive accessions which revealed that the tolerantaccession had a higher abundance of proteins in the categoryldquometabolic processrdquo under salt treatment (Figure S3 SupportingInformation)

36 Validation of Os07g37320 and Os12g03860 Expression UsingRT-qPCR

A set of six genes derived from six DEPs were chosen for theinvestigation of the expression levels under salt stress for thetested accessions RT-qPCR results indicated that expression lev-els of four of the chosen genes were not consistent across bio-logical samples or that more than one melt curve was presentindicating multiple products being formed Hence out of thisset two genes were suitable for RT-qPCR assays and are dis-cussed here The relative expression of each gene of interest fol-lowing salt treatment was measured for both accessions usingRT-qPCR with calculations of amplification efficiency from se-rial dilutions of a reference gene and the gene of interest[34]

OsMST6 (Os07g37320) expression was upregulated by salt treat-ment in salt-tolerant Oa-VR (delta cycle threshold [ΔCt] = 649

and relative expression change = 64) and downregulated (ΔCt= minus506 with no relative expression change using the Pfafflet al equation[34]) in salt-sensitive Oa-D The expression ofOs12g03860 gene was upregulated under salt treatment in thesalt-tolerant Oa-VR ([ΔCt] = 763 and relative expression change= 146) and downregulated (ΔCt = minus346 with no relative expres-sion change) under salt conditions in the salt-sensitive accessionOa-D

37 Validating Effects of Key Salt-Tolerance Genes on GrowthPhenotype Using a Yeast Deletion Library

A yeast (S cerevisiae) deletion library was used to determinethe salt-response growth phenotype resulting from deletion ofspecific key salt-responsive proteins as identified in our riceexperiment[35] Protein sequences were BLASTed against theyeast genome to find homologous genes and correspondingstrains from the deletion yeast library[35] Eleven strains were cho-sen initially based on deletion of respective homologous genesand screened under YPD medium at 30 degC For three strains nogrowth of the colonies was observed while for six strains thesame growth rate was observed as found for the WT BY4742 un-der the chosen salt concentrations (Figure S4A and S4B Sup-porting Information) Two of the tested yeast deletion strainswere more susceptible to salt treatment compared with the WTBY4742 (Figure S4B Supporting Information) and were chosenfor additional screening

Figure 4 Colony growth of BY4742 yeast WT and the two deletion strainsYLR081W and YLR268W Cells at log phase were serially diluted tenfold(vertical array of four colonies in each panel) and spotted onto YPDmedium with three different NaCl concentrations and a ldquono-saltrdquo controlColonies were photographed after 3 days of growth at 30 degC YLR081W hasa deletion in a gene homologue to the riceOsMST6 gene and YLR268W toa V-SNARE gene

The first of these strains YLR081W had a deletion in therice homologue gene identified as UniProt A0A0D3GSD4 Thisgene was chosen because its rice homologue changed by 413-fold under the saltndashgenotype interaction comparison (Oa-VR saltvsOa-VR control)(Oa-D salt vsOa-D control) (Table S1 Support-ing Information) in the proteomics experiment This hit (UniProtA0A0D3GSD4) was identified in the O barthii database asan uncharacterized protein however using UniProtrsquos BLASTtool (httpswwwuniprotorgblast) it was annotated to themonosaccharide transporter gene OsMST6 The second yeaststrain YLR268 lacked a specific V-SNAREgene corresponding tothe rice homologue with the UniProt Q5N9F2 Proteomic datashowed that the rice homologue was differentially expressed inrice roots under mildly saline conditions and was identified aspart of the SNARE interaction complex in the vacuolar transportpathwayA second yeast screening was performed and showed that the

inhibition of growth wasmore pronounced for the YLR268 strainthan the YLR081W strain when compared with the WT controlstrain (Figure 4)

4 Discussion

41 Genome Relationships Between O australiensis and theMore Comprehensively Studied Oryza Species

This research aimed to reveal novel mechanisms of salt tolerancein rice by identifying proteins that enable a salt-tolerant O aus-traliensis accession (Oa-VR) to survive in up to 100 mM NaClwhile a second accession (Oa-D) suffers severe damage at theselevels[20] We posit that salt tolerance in Oa-VR resides largely inroot characteristics and is probably centred on ion exclusion asobserved for O sativa[37]

Oryza australiensis is the sole Oryza species with an EEgenome[38] which is substantially larger than the AA genomeof O sativa and the BB genome of O punctata[39] Dramaticstructural genomic changes in the lineage of O australiensis [38]

combined with stringent natural selection due to environmentalstresses make O australiensis a strong candidate for the discov-ery of novel stress tolerance mechanisms Annotations from thisstudy suggest that O australiensismay be more closely related toO punctata (BB genome) for which there were over 60 moreprotein hits than for the five sequenced Oryza species whichare all AA genome species This is consistent with a previousstudy that showed that the EE genome (O australiensis) is geneti-cally closer to the BB genome (O punctata) than the AA genome(such as O sativa and O meridionalis)[39] and underscores thestrategy of searching among wild germplasm for tolerancegenes

42 Role of Root Proteins in Salt Tolerance

Expression levels of orthologous genes compared across 22Oryza species contribute to salt tolerance[10] but we have nocomparable information on proteomic profiles when roots aresalinized Here proteins involved in energy metabolism wereheavily enriched by salt stress with large numbers of proteinscategorized functionally as relating to primary metabolism aspreviously reported[40]

External salt loads interrupt water absorption through osmoticimbalance and induce toxicity as ions accumulate[41] Thereforethe set of adaptive responses in salt-tolerant plants should ex-tend beyondmodified ion transport capacity (eg Na+ exclusion)to scavenge ROS synthesize osmolytes to minimize metabolicdamage and hydraulic changes in membrane propertiesMembrane proteins use energy to regulate cellular

H+ transport membrane potential and thereby Na+

compartmentation[42] and are especially critical in rice whichhas limited tissue tolerance to salt[7] Membrane proteins aretargeted to various cell compartments including the endomem-brane system plasma membranes interfacing the apoplast andvacuolar (tonoplast) membranes[43] In our experiment rootswere prepared after 30 days of salt treatment to ensure rootmembranes were in a steady state with respect to transportproteinsA core mechanism for tolerance to toxic ions such as Na+

is their compartmentation into vacuoles thereby reducing theirmetabolic impact[42] Generally membrane transport plays a cru-cial role in salinity tolerance across a huge range of nonhalophyte

species such as Arabidopsis[44] wheat[45] barley[46] rapeseed[47]

and maize[48] with transporters being critical to the exclusion ofNa+ in rice[4950] Building on our previous study[20] which con-trasted salt tolerance in several wild rice accessions we aimedto identify key proteins that respond differentially to 80 mMNaClSemipurified membrane-enriched (ldquomicrosomalrdquo) fractions

from whole roots were examined to facilitate the enrichment oftransport proteins while acknowledging apoplastic bypass as acontributor to salt sensitivity in rice Functional annotation re-vealed a large number of proteins not directly associated withmembrane transport as discussed below

43 Effectiveness of the Membrane-Enriched Purification

Estimating the purity of a microsomal extraction can be compli-cated since membrane proteomes are dynamic[51] and may varywithin the same organ according to development protein translo-cation and changes in the environment For example the roothomogenate that gave rise to our preparation contained amixtureof mature and developing tissues an unavoidable consequenceof the highly branched fine root system of riceMembrane-specific enzyme markers can be used to evalu-

ate the presence of different membrane fractions in extracts[22]

but cannot be used to quantify contributions arising from eachfraction Hence we evaluated the membrane-enriched fractionby parallel sequence searches against reference databases us-ing Mercator enabling extracted proteins to be given functionalannotations using GO terms This approach provided evidencethat membrane proteins were enriched with about 10 of theextracted proteins (363 unique proteins) categorized as partici-pating in transport In previous studies a microsomal-enrichedfraction from pea roots (Pisum sativum) yielded around 5transporters[52] and a highly purified Arabidopsis plasma mem-brane preparation fromgreen tissue (leaves and petioles) resultedin 17 transporters[53] In the only comparable report on ricemembranes 7 of total proteins extracted from roots were trans-port proteins[54]

To further assess the effectiveness of our microsomal en-richment we predicted the number of transmembrane he-lices in our extracted root proteins using the TMHMMtransmembrane (TM) platform (httpwwwcbsdtudkservicesTMHMM) About 40 of the proteins were found to have atleast one membrane-spanning region similar to the 35 foundfor a membrane-enriched extraction from Arabidopsis roots[55]

The microsomal study referred to above which focused on pearoots[52] reported only 20 of proteins with a transmembraneregionWe conclude that preparation of our microsomal fraction was

successful in terms of membrane protein enrichment

44 Protein Clusters that Respond Collectively to Salt

441 ATPases and Mitochondrial Proteins

Proteins associated with transport phenomena within oxidativephosphorylation were some of the most strongly enriched in

the root microsomal fractions Subunits of both V- and F-typeATPases which are highly related enzymes involved in energytransduction[56] were differentially expressed under salt stress insalt-tolerant and -sensitive accessions In the halophyte Mesem-bryanthemum crystallinum the activity of some ATPase subunitsdecreased while others increased in abundance under salinitystress[5657] Similarly our findings indicate complex regulation ofthe expression of ATPase subunits as a fundamental part of theresponse to salinityThe tolerant accession Oa-VR displayed a higher abundance

of ldquometabolism processrdquo proteins in response to salt than thesensitive genotype In Dunaliella a salt-tolerant green alga up-regulation of ldquometabolic processrdquo pathways was reported withsome of these proteins common to plants[58] Sodium in the ex-ternal soil solution imposes a substantial energy demand onplants for example plasma-membrane associated ATPase activ-ity increased five-fold in sorghum to ldquomanagerdquo growth in 40 mMNaCl[59] Sodium that enters root cells is ideally effluxed viaplasma membrane-associated Na+H+ antiporters which con-sumes substantial amounts of energy[60] Indeed it has beendemonstrated that approximately sevenmoles of ATP are neededto transport one mole of NaCl across a membrane[61]

442 SNARE Proteins

Membrane vesicle traffic is facilitated by the SNARE (solu-ble N-ethylmaleimide-sensitive factor attachment protein recep-tor) superfamily of proteins[62] which fuse vesicles with targetmembranes[63] SNAREs comprise proteins that are located onthe plasma membrane early and late endosome trans-Golgi net-work (TGN) and the endoplasmic reticulum (ER)Among the 363 proteins identified as transporters KEGG

pathway analysis identified 13 SNARE interaction proteins in thevacuolar transport pathway as the third most abundant pathwayto be affected by salt treatment The TGN regulates both secre-tory and vacuolar transport pathways and TGN SYP4 proteinsplay critical roles in salinity stress tolerance in plants by regu-lating vacuolar transport pathways[64] Here the syntaxin-relatedKNOLLE-like protein was significantly upregulated under saltconditions in the tolerant line Oa-VR and downregulated in Oa-D These KNOLLE-like proteins are generally involved in stress-related signaling pathways and play an important role in osmoticstress tolerance in Arabidopsis[63] tobacco [65] and wild soybeanGlycine soja[66] They participate in the compartmentalization ofions once they have entered a living cell our new evidence fromrice suggests that they play this role inmonocotyledonous speciesas well as in the dicotyledons listed aboveSyntaxin is a component of the SNARE complex located

at the target membrane it enables recognition and fusion ofthe desired vesicle with the transmembrane[62] Known saltstress-related proteins such as SOS1 might be candidates forthe cargos of the SNARE complex and could interact with a regu-latory subunit of a potassium channel to regulate gating and K+

influx[67]

A second SNARE component called syntaxin-121 which drivesvesicle fusion[68] was also significantly upregulated inOa-VR anddownregulated in Oa-D Syntaxin is a plasma membrane pro-tein reported in other biological systems such as yeast[69] Some

studies have shown that the syntaxin homologue PEN1SYP121in Arabidopsis mediates a resistance reaction to suppress activityof the powdery mildew fungus Blumeria graminis f sp hordei [70]

but a direct link with abiotic stress has not been made until thepresent study

45 Validation of Salt-Tolerance Genes Using RT-qPCR and aYeast Deletion Library

In general the majority of DEPs responded to salt to a simi-lar degree in both genotypes There were relatively few DEPsthat showed an interaction between genotype and salt One wasUniProt A0A0D3GSD4 (BLASTed to O sativa OsMST6) thatincreased 414-fold more in salt-treated Oa-VR than in salt-treatedOa-D (calculated using the formula [Oa-VR salt vsOa-VRcontrol][Oa-D salt vs Oa-D control])OsMST6 is a member of the MST family in O sativa and

known to mediate transport of a variety of monosaccharidesacross membranes[71] MSTs have been reported to confer hy-persensitivity to salt in rice[71] and Arabidopsis[72] There are afew techniques to validate protein expression such as RT-qPCRgene silencing knockdownsouts and homologous expression inother species In this study the expression of theMST gene in thetolerant versus sensitive accessions was further tested using RT-qPCR resulting in verification of the proteomics results Whilethis transcript was heavily upregulated in Oa-VR with salt stressit appears to be downregulated in the salt sensitive Oa-D underthe same treatmentTranscript-level expression analysis in a previous study showed

upregulation of OsMST6 expression under saline conditions inboth shoots and roots of rice seedlings[71] A role ofOsMST6 in en-vironmental stress responses and in establishing metabolic sinkstrength was established[71] In our study abundance of this pro-tein was significantly greater in the salt-tolerant accession andreduced in the salt-sensitive accession (saltndashgenotype interactionvalue 413)In addition to the expression levels of OsMST6 we tested the

yeast growth phenotypes of a yeast strain (YLR081W) with a sin-gle deletion in a gene that encodes amonosaccharide transportera homologue of OsMST6 from rice Yeast bioassays at threesalt concentrations revealed a growth inhibition for the dele-tion strain compared with the WT The differential abundanceof the MST protein and transcript from our RT-qPCR experi-ment coupled with the growth inhibition of the yeast deletionmutants under salt treatment implies that the protein productof OsMST6 plays an important role in salinity stress responsesinOa-VR as described in a simple model (Figure S5 SupportingInformation)Another DEP that showed an interaction between genotype and

salt was UniProt A0A0E0MJB0 The abundance of this proteinwas 28-fold higher in salt-treated Oa-VR than in salt-treatedOa-D (calculated using the same formula as given in section45) Using UniProtrsquos BLAST tool we identified this protein inO sativa (UniProt Q2QY48) as a major facilitator superfamilyantiporter encoded by the Os12g03860 gene To date manyantiporters were identified to confer salinity tolerance in variousplant such as Arabidopsis[73] rice[74] and other species[7576]

During salt treatment V-ATPase activity increased[77] to ensure

tonoplast energisation to drive Na+H+ antiport-mediated se-questration of Na+ in the vacuole[78] In our study utilizingRT-qPCR we verified this superfamily antiporter gene to behighly expressed under salt in Oa-VR while no relative changein expression was measured for salt-sensitive Oa-D corre-sponding with our quantitative proteomics results This genedeletion is lethal in yeast and thus could not be tested via aknockoutWhile our results clearly indicate upregulated expression for

both OsMST6 and the Os12g03860 gene in salt-tolerant Oa-VRthe calculations relative to the reference gene in salt-sensitiveOa-D did not indicate downregulation but rather ldquono changerdquo de-spite negative ΔCt results Calculations based on amplificationefficiencies (E values) in both the reference and target genes arehighly sensitive to small differences in E values thereby explain-ing this relative expression outputDespite the lethality of the gene deletion for the homologue

of Os12g03860 an additional nonlethal gene was tested throughyeast growth phenotypes as described for the YLR081W strainThe second yeast strain (YLR268W) susceptible to salt treatment(compared to WT) had a deletion in a V-SNARE gene Thisgene (Os01g0866300) encodes a vesicle-associated membraneprotein VAMP-like protein YKT62 (UniProt O sativa Q5N9F2corresponding to UniProt O punctata A0A0E0JRG1) Leshemet al[63] reported that suppression of expression of the VAMPprotein AtVAMP7 in Arabidopsis increased salt tolerance A ricestudy reported a contrasting result with reduced salinity tolerancewhen novel SNARE (NPSN) genes (OsNPSNs) were expressed inyeast cells[79] Another study reported that theOsSNAP32 SNAREgenewas found to be involved in the response to biotic and abioticstresses in various tissues including roots[80] To our knowledgeour study is the first to strongly link V-SNARE protein to stresstoleranceOverall our proteome profiling provided key pathways and

proteins that contribute to salt stress tolerance in anO australien-sis accession We found remarkable proteomic contrasts betweenthe accessions as well as between the salt-treated and controlplants These data coupled with our RT-qPCR and yeast pheno-typing results constitute substantial progress toward elucidationof the mechanisms underlying salinity tolerance within the Aus-tralian Oryza and may serve as the basis for improving salinitytolerance in rice and other important cropsThe mass spectrometry proteomics data have been deposited

to the ProteomeXchange Consortium via the PRIDE[81] partnerrepository with the dataset identifier PXD013701

Supporting InformationSupporting Information is available from the Wiley Online Library or fromthe author

AcknowledgmentsThe authors acknowledge Associate Professor Ben Crossett andDr AngelaConnolly from The Mass Spectrometry Core Facility at the University ofSydney for their valuable assistance with MS3 analysis YY acknowledgessupport from The University of Sydney in the form of the InternationalPostgraduate Research Scholarship

Conflict of InterestThe authors declare no conflict of interest

Keywordsmembrane proteins Oryza australiensis plant proteomics rice salttolerance

Received May 14 2019Revised August 5 2019

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875[12] P A Kumar D A Bandhu Ecotoxicol Environ Saf 2005 60 324[13] R J Henry N Rice D L E Waters S Kasem R Ishikawa Y Hao S

Dillon D Crayn R Wing D Vaughan Rice 2010 3 235[14] B J Atwell H Wang A P Scafaro Plant Sci 2014 215-216 48[15] Z Ren J Gao L Li X Cai W Huang D Chao M Zhu Z Wang S

Luan H Lin Nat Genet 2005 37 1141[16] Q Wan S Hongbo X Zhaolong L Jia Z Dayong H Yihong Curr

Genomics 2017 18 553[17] P Achard H Cheng L De Grauwe J Decat H Schoutteten T

Moritz D Van Der Straeten J Peng N P Harberd Science 2006311 91 PMID16400150

[18] S Yan Z Tang W Su W Sun Proteomics 2005 5 235[19] M Nohzadeh H R Sahar H Mehran H Manzar G Salekdeh

Biosci Biotechnol Biochem 2007 71 2144[20] Y Yichie C Brien B Berger T H Roberts B J Atwell Rice 2018 11

66 PMID30578452[21] S Yoshida D A Forno J H Cock K A Gomez Laboratory Manual

for Physiological Studies of Rice IRRI Los Bantildeos Philippines 197661

[22] Y Cheng Y Qi Q Zhu X Chen N Wang X Zhao H Chen X CuiL Xu W Zhang Proteomics 2009 9 3100

[23] M J Aspinwall A Varingrhammar M Possell D T Tissue J E DrakeP B Reich O K Atkin P D Rymer S Dennison S C Van SluyterGlobal Change Biol 2019 25 1665

[24] X S Yue A B Hummon J Proteome Res 2013 12 4176[25] G Palmisano S E Lendal K Engholm-Keller R Leth-Larsen B L

Parker M R Larsen Nat Protoc 2010 5 1974

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[27] S Wu Z Zhu L Fu B Niu W Li BMC Genomics 2011 12 444PMID21899761

[28] M Mirzaei D Pascovici J X Wu J Chick Y Wu B Cooke M PMolloyMethods Mol Biol 2017 1549 45 PMID27975283

[29] T Zhang M Jiang L Chen B Niu Y Cai Biomed Res Int 2013 32401

[30] M Lohse A Nagel T Herter P May M Schroda R Zrenner T To-hge A R Fernie M Stitt B Usadel Plant Cell Environ 2014 371250

[31] D Pascovici T Keighley M Mirzaei P A Haynes B Cooke Pro-teomics 2012 12 406

[32] Y Wu M Mirzaei D Pascovici P A Haynes B J Atwell Proteomics2019 19 1800310

[33] P A Tobias N Christie S Naidoo D I Guest C Kuumllheim Tree Phys-iol 2017 37 565

[34] M W Pfaffl Nucleic Acids Res 2001 29 45e[35] G Giaever C Nislow Genetics 2014 197 451 PMID24939991[36] A Blomberg Yeast 1997 13 529 PMID9178504[37] S Roy U Chakraborty Protoplasma 2018 255 175 PMID28710664[38] B Piegu R Guyot N Picault A Roulin A Saniyal H Kim K Collura

D S Brar S Jackson R A Wing O Panaud Proteome Sci 2006 161262

[39] T Nishikawa D A Vaughan K Kadowaki Plant Genome 2005 110696

[40] M H Nam S Mi Huh K Mi Kim W J Park J B Seo K Cho D YKim B G Kim I S Yoon Proteome Sci 2012 10 25

[41] J K Zhu Trends Plant Sci 2001 6 66[42] E Blumwald Curr Opin Cell Biol 2000 12 431[43] H Shi F J Quintero J M Pardo J K Zhu Plant Cell 2002 14 465[44] F E Tracy M Gilliham A N Dodd A A R Webb M Tester Plant

Cell Environ 2008 31 1063[45] C S Byrt J D Platten W Spielmeyer R A James E S Lagudah E

S Dennis M Tester R Munns E S Dennis M Tester R Munns CS Byrt J D Platten W Spielmeyer R A James E S Lagudah PlantPhysiol 2007 143 1918

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Mol Breed 2007 19 215[50] Z -H Ren J -P Gao L Li X Cai W Huang D -Y Chao M Zhu Z

-Y Wang S Luan H Lin Nat Genet 2005 37 1141[51] F Masson M Rossignol Plant J 1995 8 77[52] C -N Meisrimler S Wienkoop S Luumlthje Proteomes 2017 5 8[53] E Alexandersson G Saalbach C Larsson P Kjellbom Plant Cell

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2017 158 20[55] T J Chiou Y C Tsai T K Huang Y R Chen C L Han C M Sun Y

S Chen W Y Lin S I Lin TY Liu Y J Chen J W Chen P M ChenPlant Cell 2013 25 4044

[56] A Y Mulkidjanian M Y Galperin K S Makarova Y I Wolf E VKoonin Biol Direct 2008 3 13

[57] R Low B Rockel M Kirsch R Ratajczak S Hortensteiner EMartinoia U Luttge T Rausch Plant Physiol 2002 110 259

[58] J Patterson P Kulkarni M Smith N Deller Plant Physiol 2004 1362806

[59] H W Koqro R Stelzer B Huchzermeyer Botanica Acta 1993 106110

[60] M Tester R Davenport Ann Bot 2003 91 503[61] J A Raven New Phytol 1985 101 25[62] Y A Chen R H Scheller H H Medical Nature 2001 2 98

[63] Y Leshem N Melamed-book O Cagnac G Ronen Y Nishri MSolomon G Cohen A Levine Proc Natl Acad Sci USA 2006 10318008

[64] T Uemura T Ueda A Nakano Plant Signaling Behav 2012 7 1118[65] B Leyman D Geelen M R Blatt Plant J 2000 24 369[66] X Sun W Ji X Ding Plant Cell Tissue Organ Cult 2013 113 199[67] S Sokolovski P Campanoni A Honsbein M Paneque Z Chen M

R Blatt R Pratelli I Johansson C Grefen Plant Cell 2009 21 2859[68] S R Pant P D Matsye B T McNeece K Sharma A Krishnavajhala

G W Lawrence V P Klink Plant Mol Biol 2014 85 107[69] M Edamatsu Y Y Toyoshima Biochem Biophys Res Commun 2003

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Christensen P Schulze-Lefert N C Collins S C Somerville AFreialdenhoven J-L Qiu M Stein Nature 2003 425 973 PMID14586469

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[72] S Reuscher M Akiyama T Yasuda H Makino K Aoki D ShibataK Shiratake Plant Cell Physiol 2014 55 1123

[73] H Shi M Ishitani K Cheolsoo Z Jian-Kang Proc Natl Acad SciUSA 2000 97 6896

[74] A Fukuda A Nakamura A Tagiri H Tanaka A Miyao H HirochikaY Tanaka Plant Cell Physiol 2004 45 146

[75] C Niemietz J Willenbrink Planta 1985 166 545 PMID24241621[76] C Ye H Zhang J Chen X Xia W Yin Physiol Plant 2009 137 166[77] Y Braun M Hassidim H R Lerner L Reinhold Plant Physiol 1986

81 1050[78] F J M Maathuis V Filatov P Herzyk G C Krijger K B Axelsen S

Chen B G Forde G Michael P A Rea L E Williams D SandersA Amtmann Plant J 2003 35 675

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[81] Y Perez-Riverol A Csordas J Bai M Bernal-Llinares S Hewapathi-rana D J Kundu A Inuganti J Griss G Mayer M Eisenacher EPeacuterez J Uszkoreit J Pfeuffer T Sachsenberg S Yilmaz S Tiwary JCox E Audain M Walzer A F Jarnuczak T Ternent A Brazma JA Vizcaiacuteno Nucleic Acids Res 2019 47 D442

Appendix Table 2-1 Operating parameters as used for determination and analysis of the

inorganic ions from rice leaves

Appendix Table 2-2 summary of dead leaf percentage for each genotype and treatment

was calculated as the weight of dead leaf as a percentage of total leaf weight from the

main tiller

Linetreatment 0 mM 25 mM 50 mM 75 mM 120 mMIR29 0 8 63 93 100

Nipponbare 0 11 29 53 96Oa -VR 0 4 11 17 46Oa -CH 0 11 33 31 85Oa -D 0 45 56 65 94Oa -KR 0 8 48 54 92Om -HS 0 4 5 46 83Om -CY 0 14 72 95 100Oa -T3 0 30 35 69 81300183 0 5 21 45 94Pokalli 0 3 22 54 92

Parameter ValuePump speed (rpm) 15

Sample uptake delay (s) 15Stabilisation time (s) 15

Read time (s) 15Replicates 3

Rinse time (s) 30Sample pump tubing Orangegreen SolvaflexWaste pump tubing Blueblue Solvaflex

Background correction AutoGas source 4107 Nitrogen generator

Appendix Figure 2-1 Relationship between net photosynthesis rates of surviving green

leaf tissue and percent dead leaf of the main tiller A linear regression line y = minus102(x) +

182 with R2 = 04 correlation coefficient was found for all genotypes grown under all salt

treatments

0 02 04 06 08 1 12

tic ra

Dead Leaves []

Appendix Table 2-3 Phenotypic measurements of all tested accessions 4 and 29 d after applying the salt treatments (DAS) Different letters

indicate significant differences between means from the non-salinised treatment (0 mM NaCl) per accession based on Studentrsquos t test (Plt005) The

reduction values were calculated between DAS4 and 29 in each combination of salt treatment and accession

DAS4 DAS29 DAS4 DAS29 DAS4 DAS29Genotype Treatment Reduction Reduction Reduction

mM NaCl IR29 0 081 A 028 A 66 2325 A 915 A 61 2335 A 1629 A 3023

40 051 B 034 A 33 1673 B 1232 A 26 1467 B 941 B 358780 037 C 017 B 55 1285 C 653 B 49 1582 B 134 B 1527

Oa -VR 0 074 A 043 A 41 1424 A 1239 A 13 2467 A 2364 A 41340 052 AB 013 B 76 904 B 493 B 45 1939 AB 1013 B 477680 032 B 013 B 59 89 B 499 B 44 1475 B 974 B 3394

Oa -CH 0 065 A 031 A 53 1721 A 91 A 47 2796 A 1817 A 350040 034 B 011 B 68 1117 B 44 B 61 1839 B 797 B 566580 031 B 013 B 56 1005 B 515 B 49 1687 B 207 C 8774

Oa -D 0 069 A 032 A 53 1924 A 1003 A 48 2172 A 172 A 208140 034 B 018 B 49 117 B 646 B 45 1794 A 1423 A 206580 035 B 011 B 70 1205 B 419 B 65 1625 A 983 A 3951

Oa -KR 0 062 A 031 A 50 1656 A 975 A 41 2908 A 1803 A 380140 041 B 018 B 57 138 B 683 B 50 1999 B 1195 A 402180 035 B 017 B 52 117 C 645 B 45 144 C 24 B 8333

Pokkali 0 046 A 021 54 1396 A 757 46 2474 A 1491 A 397040 021 B 017 23 84 B 656 22 1419 B 1298 AB 85280 035 B 019 47 12 B 716 40 1523 B 1087 B 2862

Stomatal Conductance Transpiration Rate mol m-2 s-1 mmol (H2O) m-2 s-1

Net Photosynthetic Rateμmol (CO2) m-2 s-1

Appendix Figure 2-2 Linear regressions of salinity-induced injury against ion accumulation (Na+ in red K+ in blue) in rice leaves The visual SES

injury scores were correlated with (a) leaf Na+ concentrations [μmol Na+ g-1 (SDW)] (R2 = 033) and (b) leaf K+ concentrations [μmol K+ g-1 (SDW)] (R2 =

025) Leaf rolling scores were correlated against (c) leaf Na+ concentrations (R2 = 033) and (d) leaf K+ concentrations (R2 = 026)

Appendix Figure 4-1 Standard calibration curve for the BCA assay showing absorbances plotted against the BSA standard concentrations

y = 0001439x + 0085718Rsup2 = 0994227

0 100 200 300 400 500

Protein concentration ugmL

Appendix Figure 4-2 Mass spectrometry spectra example (a) BSA calibration of the Thermo Scientific Orbitrap Fusion Tribridtrade Mass Spectrometer

(Thermo Scientific CA USA) (b) Averaged mass spectra of the peptide YICDNQDTISSK (mz 72232 M2H2+) as identified from extracted ion

chromatograms in the LC-MS analysis of a tryptic BSA digest was picked randomly to assess the quality and sensitivity of the machine before loading the

experimental samples

Appendix Figure 4-3 Gradient profile of a test sample (rice root microsomal test sample extraction) for retention times of 9 (red) 60 (blue) and

90 (pink) min One microgram of sample was injected for the blue and the pink gradients while 01 microg was used for the red gradient

Appendix Figure 4-4 Example of a mass spectrum showing the signals obtained for the first TMT set (fraction 1 of Oa-VR) The image shows the

product ion scan spectrum of the 4-foldndashcharged ion signal after collision-induced dissociation Resulting product ions were assigned to the amino acid

sequence respective to the mass-to-charge ratio

Appendix Figure 4-5 Protein patterns for the most abundant proteins (label above each

plot represents the protein accession name) from the Oryza database

plot represents the protein accession name) from the Salt-tolerant species database

plot represents the protein accession name) from the Grasses database

plot represents the protein accession name) from the Arabidopsis database

Appendix Table 4-1 Raw data results from TMT derived from Oryza database

httpscloudstoraarneteduauplussQV2P3SBxDkNtnJf

Appendix Table 4-2 Raw data results from TMT derived from Grasses database

httpscloudstoraarneteduauplussxaDnR0PShopEbGm

Appendix Table 4-3 Raw data results from TMT derived from Salt-tolerants database

httpscloudstoraarneteduauplussp3Mq0lSUPYZZ5lD

Appendix Table 4-4 Raw data results from TMT derived from Arabidopsis database

httpscloudstoraarneteduaupluss83XLPh0DFYnAXri

Appendix Figure 5-1 Colony growth of all tested yeast strains and the wild type BY4742

under salt at 30degC Cells at log phase were serially diluted 10-fold (vertical array of four

colonies in each panel) and spotted onto YPD medium containing 700 NaCl Colonies were

photographed after 48 h and then every 24 h

Salinity tolerance of wild rice accessions from northern Australia_YYichie PhD Thesispdf


Dedication

Acknowledgments

Abbreviations

Journal articles

Journal articles

Presentations awards and visits


Abstract

Abstract

Table of Contents

Table of Contents

List of Figures

List of Tables


11 Introduction





12 Background

121 Origin of rice


















Arabidopsis

Cereals

Rice



Salinity

Submergence

Drought

Chilling

Heat

16 Conclusion



21 Introduction




223 Salinity tolerance (ST) leaf rolling (LR) and standard evaluation system (SES) scale





228 Data analysis


231 First salt screening to establish a core collection of salt-tolerant accessions


Results

Discussion

233 Conclusion


Chapter 3 High-throughput image-based phenotyping

31 Introduction


321 Plant materials


323 Phenotyping

Plant water use




Plant height

Centre of mass







33 Results

34 Discussion

35 Conclusion


41 Introduction














4210 Analysis of differently expressed proteins between the accessions and salt treatments


43 Results





44 Discussion





445 Up-regulation of protein clusters involved in energy metabolism vesicle trafficking and membrane phagosomes under salt stress

Metabolic process


45 Conclusion


51 Introduction











Experimental design

523 Protein sequence alignment

53 Results


532 RNA extraction



535 RT-qPCR




54 Discussion

541 RT-qPCR



55 Conclusion


61 Introduction






63 Results



Chapter 7 General discussion and future directions




Appendix

paper combined 2020pdf

Yichie2018

Abstract

Background

Results

Conclusion

Introduction

Material and methods

Plant material growth conditions and salt treatments

Experiment 1

Experiment 2

Phenotyping of physiological traits

Gas exchange values

Growth and yield components

Leaf chlorophyll determination

Ion assay

Salinity tolerance estimation

RGBfluorescence image capture and image analysis

Data preparation and statistical analysis

First experiment

Second experiment

Results

First screening (experiment 1)

Plant accelerator (experiment 2)

Discussion

Additional files

Abbreviations

Acknowledgements

Funding

Availability of data and materials

Authorsrsquo contributions

Ethics approval and consent to participate

Consent for publication

Competing interests

Publisherrsquos Note

Author details

References

yichie2019

Salinity tolerance of wild rice accessions from northern Australia_YYichie PhD Thesis


This is to certify that to the best of my knowledge the content of this thesis is my own work

This thesis has not been submitted for any degree or other purposes

I certify that the intellectual content of this thesis is the product of my own work and that all

the assistance received in preparing this thesis and sources have been acknowledged

Yoav Yichie

3th February 2020

Dedication

The Climb the Fall

Luke Thompson

missed

Acknowledgments

thesis

Hansen

after rice plants

forward at IRRI

Abbreviations

ABA Abscisic acid

ACN Acetonitrile

DTT Dithiothreitol

FLUO Fluorescence

LR Leaf rolling

PM Plasma membrane

RGB Red-green-blue

TMT Tandem mass tag

WUI Water use index

Journal articles

Chapters 2 and 3)

Sydney Australia

Australia

Awards

2016 - August 2019)

(2017)

Sydney (2018)

Research visits

Abstract

11 Introduction 2

12 Background 6

16 Conclusion 26

21 Introduction 30

233 Conclusion 60

31 Introduction 64

323 Phenotyping 68

33 Results 74

34 Discussion 83

35 Conclusion 86

41 Introduction 89

43 Results 102

44 Discussion 112

45 Conclusion 120

51 Introduction 123

53 Results 130

535 RT-qPCR 132

54 Discussion 139

541 RT-qPCR 139

55 Conclusion 146

61 Introduction 150

63 Results 154

Appendix 193

List of Figures

11 Introduction

12 Background

121 Origin of rice

Choi et al 2018)

0 50 100 150 200 250

ChinaIndia

IndonesiaBangladesh

VietnamThailand

MyanmarPhilippines

NigeriaBrazil

JapanCambodia

MaliMalaysia

KoreaGuinea

Australia

the future

and Indonesia

varieties

et al 2016)

a dominant pattern

(Wang et al 2003b)

et al 2008)

Arabidopsis

Cereals

al 2017)

Salinity

Submergence

Drought

Chilling

(wwwirriorg)

16 Conclusion

important crops

library (Chapter 5)

(Chapter 6)

tolerance

21 Introduction

plant breeding

treatment

otherwise mentioned

119878119878119878119878119878119878 (119904119904119904119904119904119904119904119904 119904119904119905119905119905119905119904119904119904119904119905119905119905119905119905119905119904119904)119878119878119878119878119878119878 (119888119888119888119888119905119905119904119904119905119905119888119888119904119904)

119909119909 100

119878119878119905119905119904119904119863119863 119871119871119905119905119904119904119871119871 119878119878119905119905119882119882119882119882ℎ119904119904119879119879119888119888119904119904119904119904119904119904 119871119871119905119905119904119904119871119871 119878119878119905119905119882119882119882119882ℎ119904119904

119909119909 100

119864119864119904119904119905119905119905119905119905119905119905119905119904119904 119905119905119905119905119888119888119904119904119882119882 =

119905119905119904119904119905119905119905119905119905119905119905119905119904119904 119905119905119905119905119904119904119863119863 [119901119901119901119901119905119905] lowast 001119871119871 lowast 10

119905119905119888119888119904119904119905119905119888119888119898119898119904119904119904119904119905119905 119905119905119904119904119904119904119904119904 119905119905119882119882119905119905119905119905119888119888119904119904 lowast 119904119904119904119904119905119905119901119901119904119904119905119905 119908119908119905119905119882119882119882119882ℎ119904119904 [119882119882]

228 Data analysis

t test

IR29 8 2 75 32 7 79 20 5 75Nipponbare 11 2 82 32 7 78 75 5 93

Oa -VR 9 3 67 31 16 48 66 25 62Oa -CH 5 3 40 37 9 76 60 14 77Oa -D 6 2 67 30 9 70 106 38 64

tolerance

Results

stress (Fig 2-4)

compared with Na+

4 0 mM

8 0 Mm

O a -V R

4 0 mM

8 0 Mm

O a -C H

4 0 mM

8 0 Mm

O a -D

F re s h W e ig h t

D ry W e ig h t

4 0 mM

8 0 Mm

O a -K R

4 0 mM

8 0 Mm

P o k k a li

4 0 mM

8 0 Mm

IR 2 9

Discussion

et al 2010)

et al 2002)

233 Conclusion

populations

wild germplasm

based phenotyping

the journal article

31 Introduction

and development

al 2016)

stress respectively

321 Plant materials

323 Phenotyping

Plant water use

Plant height

Centre of mass

et al 2018)

119858119858 = 119831119831119831119831 + 119833119833119833119833 + 119838119838

33 Results

(Yichie et al 2018)

34 Discussion

35 Conclusion

41 Introduction

in the wild type

pathway mapping

digestion

al 2019)

searched

meridionalis

treatments

43 Results

Database accession

Unique peptides

Proteins quantified

Oryza Oa-VR 57498 43788 11046 2680

Oa-D 52925 40113 9986 2473

Grasses Oa-VR 22125 14901 5068 1873

Oa-D 19646 13626 4515 1683

Salt-tolerant

Oa-VR 23296 16477 5857 1338

Oa-D 20828 14809 5109 1187

Oa-D 3136 2411 807 446

4-6a and b)

(b) (a)

44 Discussion

enrichment

O australiensis

identified

Metabolic process

this gene family

45 Conclusion

51 Introduction

described below

well plate

Os04g56430_2

Os04g56430_3

Os03g10090_1

Os03g10090_2

Os03g10090_3

AK061988

AK059783

A0A0E0JI75

A0A0D3GSD4

A0A0E0KW83

Os07g37320_2

Os07g37320_3

Os03g09970_1

Os03g09970_2

Os03g09970_3

Os04g56430_1

Os01g24710_2

Os01g24710_3

Os03g57960_1

Os03g57960_2

Os03g57960_3

Os07g37320_1

18S rRNA

Os12g03860_1

Os12g03860_2

Os12g03860_3

Os01g24710_1

119905119905119904119904119904119904119882119882119888119888 =(119864119864119905119905119905119905119905119905119905119905119905119905119905119905)∆119862119862119901119901 119905119905119905119905119905119905119905119905119905119905119905119905

119872119872119872119872119872119872119872119872 119888119888119888119888119888119888119905119905119905119905119888119888119888119888minus119872119872119872119872119872119872119872119872 119904119904119905119905119904119904119901119901119888119888119905119905

(119864119864119905119905119905119905119903119903119905119905119905119905119905119905119903119903119903119903119905119905)∆119862119862119901119901 119905119905119905119905119903119903119905119905119905119905119905119905119888119888119888119888119905119905119872119872119872119872119872119872119872119872 119888119888119888119888119888119888119905119905119905119905119888119888119888119888minus119872119872119872119872119872119872119872119872 119904119904119905119905119904119904119901119901119888119888119905119905

119864119864 = 10( minus1119904119904119904119904119904119904119904119904119905119905)

Experimental design

observed

53 Results

532 RNA extraction

Os03g57960_2 Os07g37320_1

535 RT-qPCR

PCR data

n Ct Oa-VR-Salt

Oa-VR-Control

Oa-D-Salt

Oa-D-Control

y = -33092x + 26706Rsup2 = 09958

-05 0 05 1 15 2 25

(b)y = -32977x + 29832

Rsup2 = 09761

-05 0 05 1 15

y = -14951x + 24715Rsup2 = 09945

-05 0 05 1 15 2 25

y = -37155x + 28713Rsup2 = 0997

-05 0 05 1 15 2 25

(Fig 5-2)

54 Discussion

541 RT-qPCR

of histone tails

colour scheme

55 Conclusion

61 Introduction

63 Results

submission

future directions

accessions

al 2010)

population

276ndash282

Appendix

they are cited

Abstract

Additional files

1 Introduction

DOI 101002pmic201900175

27 Primer Design

3 Results

Uniquepeptides

Oa-VR 57 498 43 788 11 046 2680

Oa-D 52 925 40 113 9986 2473

Oryzaspecies

Numberof hits

Genome

O barthii 625 AA

O glaberrima 192 AA

O punctata 1090 BB

O rufipogon 231 AA

O sativa 670 AA

Oa-D_Saltvs Control

Upregulated 104 (52) 128 (45) 116 (57)

Downregulated 96 (48) 154 (55) 88 (43)

4 Discussion

442 SNARE Proteins

influx[67]

main tiller

treatments

0 02 04 06 08 1 12

tic ra

Dead Leaves []

mM NaCl IR29 0 081 A 028 A 66 2325 A 915 A 61 2335 A 1629 A 3023

40 051 B 034 A 33 1673 B 1232 A 26 1467 B 941 B 358780 037 C 017 B 55 1285 C 653 B 49 1582 B 134 B 1527

y = 0001439x + 0085718Rsup2 = 0994227

0 100 200 300 400 500


Dedication

Acknowledgments

Abbreviations

Journal articles

Journal articles



Abstract

Abstract

Table of Contents

Table of Contents

List of Figures

List of Tables


11 Introduction





12 Background

121 Origin of rice


















Arabidopsis

Cereals

Rice



Salinity

Submergence

Drought

Chilling

Heat

16 Conclusion



21 Introduction









228 Data analysis




Results

Discussion

233 Conclusion



31 Introduction


321 Plant materials


323 Phenotyping

Plant water use




Plant height

Centre of mass







33 Results

34 Discussion

35 Conclusion


41 Introduction
















43 Results





44 Discussion






Metabolic process


45 Conclusion


51 Introduction











Experimental design


53 Results


532 RNA extraction



535 RT-qPCR




54 Discussion

541 RT-qPCR



55 Conclusion


61 Introduction






63 Results







Appendix


Yichie2018

Abstract

Background

Results

Conclusion

Introduction



Experiment 1

Experiment 2


Gas exchange values



Ion assay




First experiment

Second experiment

Results



Discussion

Additional files

Abbreviations

Acknowledgements

Funding





Competing interests


Author details

References

yichie2019



Dedication

The Climb the Fall

Luke Thompson

missed

Acknowledgments

thesis

Hansen

after rice plants

forward at IRRI

Abbreviations

ABA Abscisic acid

ACN Acetonitrile

DTT Dithiothreitol

FLUO Fluorescence

LR Leaf rolling

PM Plasma membrane

RGB Red-green-blue

TMT Tandem mass tag

WUI Water use index

Journal articles

Chapters 2 and 3)

Sydney Australia

Australia

Awards

2016 - August 2019)

(2017)

Sydney (2018)

Research visits

Abstract

11 Introduction 2

12 Background 6

16 Conclusion 26

21 Introduction 30

233 Conclusion 60

31 Introduction 64

323 Phenotyping 68

33 Results 74

34 Discussion 83

35 Conclusion 86

41 Introduction 89

43 Results 102

44 Discussion 112

45 Conclusion 120

51 Introduction 123

53 Results 130

535 RT-qPCR 132

54 Discussion 139

541 RT-qPCR 139

55 Conclusion 146

61 Introduction 150

63 Results 154

Appendix 193

List of Figures

11 Introduction

12 Background

121 Origin of rice

Choi et al 2018)

0 50 100 150 200 250

ChinaIndia

IndonesiaBangladesh

VietnamThailand

MyanmarPhilippines

NigeriaBrazil

JapanCambodia

MaliMalaysia

KoreaGuinea

Australia

the future

and Indonesia

varieties

et al 2016)

a dominant pattern

(Wang et al 2003b)

et al 2008)

Arabidopsis

Cereals

al 2017)

Salinity

Submergence

Drought

Chilling

(wwwirriorg)

16 Conclusion

important crops

library (Chapter 5)

(Chapter 6)

tolerance

21 Introduction

plant breeding

treatment

otherwise mentioned

119878119878119878119878119878119878 (119904119904119904119904119904119904119904119904 119904119904119905119905119905119905119904119904119904119904119905119905119905119905119905119905119904119904)119878119878119878119878119878119878 (119888119888119888119888119905119905119904119904119905119905119888119888119904119904)

119909119909 100

119878119878119905119905119904119904119863119863 119871119871119905119905119904119904119871119871 119878119878119905119905119882119882119882119882ℎ119904119904119879119879119888119888119904119904119904119904119904119904 119871119871119905119905119904119904119871119871 119878119878119905119905119882119882119882119882ℎ119904119904

119909119909 100

119864119864119904119904119905119905119905119905119905119905119905119905119904119904 119905119905119905119905119888119888119904119904119882119882 =

119905119905119904119904119905119905119905119905119905119905119905119905119904119904 119905119905119905119905119904119904119863119863 [119901119901119901119901119905119905] lowast 001119871119871 lowast 10

119905119905119888119888119904119904119905119905119888119888119898119898119904119904119904119904119905119905 119905119905119904119904119904119904119904119904 119905119905119882119882119905119905119905119905119888119888119904119904 lowast 119904119904119904119904119905119905119901119901119904119904119905119905 119908119908119905119905119882119882119882119882ℎ119904119904 [119882119882]

228 Data analysis

t test

IR29 8 2 75 32 7 79 20 5 75Nipponbare 11 2 82 32 7 78 75 5 93

Oa -VR 9 3 67 31 16 48 66 25 62Oa -CH 5 3 40 37 9 76 60 14 77Oa -D 6 2 67 30 9 70 106 38 64

tolerance

Results

stress (Fig 2-4)

compared with Na+

4 0 mM

8 0 Mm

O a -V R

4 0 mM

8 0 Mm

O a -C H

4 0 mM

8 0 Mm

O a -D

F re s h W e ig h t

D ry W e ig h t

4 0 mM

8 0 Mm

O a -K R

4 0 mM

8 0 Mm

P o k k a li

4 0 mM

8 0 Mm

IR 2 9

Discussion

et al 2010)

et al 2002)

233 Conclusion

populations

wild germplasm

based phenotyping

the journal article

31 Introduction

and development

al 2016)

stress respectively

321 Plant materials

323 Phenotyping

Plant water use

Plant height

Centre of mass

et al 2018)

119858119858 = 119831119831119831119831 + 119833119833119833119833 + 119838119838

33 Results

(Yichie et al 2018)

34 Discussion

35 Conclusion

41 Introduction

in the wild type

pathway mapping

digestion

al 2019)

searched

meridionalis

treatments

43 Results

Database accession

Unique peptides

Proteins quantified

Oryza Oa-VR 57498 43788 11046 2680

Oa-D 52925 40113 9986 2473

Grasses Oa-VR 22125 14901 5068 1873

Oa-D 19646 13626 4515 1683

Salt-tolerant

Oa-VR 23296 16477 5857 1338

Oa-D 20828 14809 5109 1187

Oa-D 3136 2411 807 446

4-6a and b)

(b) (a)

44 Discussion

enrichment

O australiensis

identified

Metabolic process

this gene family

45 Conclusion

51 Introduction

described below

well plate

Os04g56430_2

Os04g56430_3

Os03g10090_1

Os03g10090_2

Os03g10090_3

AK061988

AK059783

A0A0E0JI75

A0A0D3GSD4

A0A0E0KW83

Os07g37320_2

Os07g37320_3

Os03g09970_1

Os03g09970_2

Os03g09970_3

Os04g56430_1

Os01g24710_2

Os01g24710_3

Os03g57960_1

Os03g57960_2

Os03g57960_3

Os07g37320_1

18S rRNA

Os12g03860_1

Os12g03860_2

Os12g03860_3

Os01g24710_1

119905119905119904119904119904119904119882119882119888119888 =(119864119864119905119905119905119905119905119905119905119905119905119905119905119905)∆119862119862119901119901 119905119905119905119905119905119905119905119905119905119905119905119905

119872119872119872119872119872119872119872119872 119888119888119888119888119888119888119905119905119905119905119888119888119888119888minus119872119872119872119872119872119872119872119872 119904119904119905119905119904119904119901119901119888119888119905119905

(119864119864119905119905119905119905119903119903119905119905119905119905119905119905119903119903119903119903119905119905)∆119862119862119901119901 119905119905119905119905119903119903119905119905119905119905119905119905119888119888119888119888119905119905119872119872119872119872119872119872119872119872 119888119888119888119888119888119888119905119905119905119905119888119888119888119888minus119872119872119872119872119872119872119872119872 119904119904119905119905119904119904119901119901119888119888119905119905

119864119864 = 10( minus1119904119904119904119904119904119904119904119904119905119905)

Experimental design

observed

53 Results

532 RNA extraction

Os03g57960_2 Os07g37320_1

535 RT-qPCR

PCR data

n Ct Oa-VR-Salt

Oa-VR-Control

Oa-D-Salt

Oa-D-Control

y = -33092x + 26706Rsup2 = 09958

-05 0 05 1 15 2 25

(b)y = -32977x + 29832

Rsup2 = 09761

-05 0 05 1 15

y = -14951x + 24715Rsup2 = 09945

-05 0 05 1 15 2 25

y = -37155x + 28713Rsup2 = 0997

-05 0 05 1 15 2 25

(Fig 5-2)

54 Discussion

541 RT-qPCR

of histone tails

colour scheme

55 Conclusion

61 Introduction

63 Results

submission

future directions

accessions

al 2010)

population

276ndash282

Appendix

they are cited

Abstract

Additional files

1 Introduction

DOI 101002pmic201900175

27 Primer Design

3 Results

Uniquepeptides

Oa-VR 57 498 43 788 11 046 2680

Oa-D 52 925 40 113 9986 2473

Oryzaspecies

Numberof hits

Genome

O barthii 625 AA

O glaberrima 192 AA

O punctata 1090 BB

O rufipogon 231 AA

O sativa 670 AA

Oa-D_Saltvs Control

Upregulated 104 (52) 128 (45) 116 (57)

Downregulated 96 (48) 154 (55) 88 (43)

4 Discussion

442 SNARE Proteins

influx[67]

main tiller

treatments

0 02 04 06 08 1 12

tic ra

Dead Leaves []

mM NaCl IR29 0 081 A 028 A 66 2325 A 915 A 61 2335 A 1629 A 3023

40 051 B 034 A 33 1673 B 1232 A 26 1467 B 941 B 358780 037 C 017 B 55 1285 C 653 B 49 1582 B 134 B 1527

y = 0001439x + 0085718Rsup2 = 0994227

0 100 200 300 400 500


Dedication

Acknowledgments

Abbreviations

Journal articles

Journal articles



Abstract

Abstract

Table of Contents

Table of Contents

List of Figures

List of Tables


11 Introduction





12 Background

121 Origin of rice


















Arabidopsis

Cereals

Rice



Salinity

Submergence

Drought

Chilling

Heat

16 Conclusion



21 Introduction









228 Data analysis




Results

Discussion

233 Conclusion



31 Introduction


321 Plant materials


323 Phenotyping

Plant water use




Plant height

Centre of mass







33 Results

34 Discussion

35 Conclusion


41 Introduction
















43 Results





44 Discussion






Metabolic process


45 Conclusion


51 Introduction











Experimental design


53 Results


532 RNA extraction



535 RT-qPCR




54 Discussion

541 RT-qPCR



55 Conclusion


61 Introduction






63 Results







Appendix


Yichie2018

Abstract

Background

Results

Conclusion

Introduction



Experiment 1

Experiment 2


Gas exchange values



Ion assay




First experiment

Second experiment

Results



Discussion

Additional files

Abbreviations

Acknowledgements

Funding





Competing interests


Author details

References

yichie2019



Acknowledgments

thesis

Hansen

after rice plants

forward at IRRI

Abbreviations

ABA Abscisic acid

ACN Acetonitrile

DTT Dithiothreitol

FLUO Fluorescence

LR Leaf rolling

PM Plasma membrane

RGB Red-green-blue

TMT Tandem mass tag

WUI Water use index

Journal articles

Chapters 2 and 3)

Sydney Australia

Australia

Awards

2016 - August 2019)

(2017)

Sydney (2018)

Research visits

Abstract

11 Introduction 2

12 Background 6

16 Conclusion 26

21 Introduction 30

233 Conclusion 60

31 Introduction 64

323 Phenotyping 68

33 Results 74

34 Discussion 83

35 Conclusion 86

41 Introduction 89

43 Results 102

44 Discussion 112

45 Conclusion 120

51 Introduction 123

53 Results 130

535 RT-qPCR 132

54 Discussion 139

541 RT-qPCR 139

55 Conclusion 146

61 Introduction 150

63 Results 154

Appendix 193

List of Figures

11 Introduction

12 Background

121 Origin of rice

Choi et al 2018)

0 50 100 150 200 250

ChinaIndia

IndonesiaBangladesh

VietnamThailand

MyanmarPhilippines

NigeriaBrazil

JapanCambodia

MaliMalaysia

KoreaGuinea

Australia

the future

and Indonesia

varieties

et al 2016)

a dominant pattern

(Wang et al 2003b)

et al 2008)

Arabidopsis

Cereals

al 2017)

Salinity

Submergence

Drought

Chilling

(wwwirriorg)

16 Conclusion

important crops

library (Chapter 5)

(Chapter 6)

tolerance

21 Introduction

plant breeding

treatment

otherwise mentioned

119878119878119878119878119878119878 (119904119904119904119904119904119904119904119904 119904119904119905119905119905119905119904119904119904119904119905119905119905119905119905119905119904119904)119878119878119878119878119878119878 (119888119888119888119888119905119905119904119904119905119905119888119888119904119904)

119909119909 100

119878119878119905119905119904119904119863119863 119871119871119905119905119904119904119871119871 119878119878119905119905119882119882119882119882ℎ119904119904119879119879119888119888119904119904119904119904119904119904 119871119871119905119905119904119904119871119871 119878119878119905119905119882119882119882119882ℎ119904119904

119909119909 100

119864119864119904119904119905119905119905119905119905119905119905119905119904119904 119905119905119905119905119888119888119904119904119882119882 =

119905119905119904119904119905119905119905119905119905119905119905119905119904119904 119905119905119905119905119904119904119863119863 [119901119901119901119901119905119905] lowast 001119871119871 lowast 10

119905119905119888119888119904119904119905119905119888119888119898119898119904119904119904119904119905119905 119905119905119904119904119904119904119904119904 119905119905119882119882119905119905119905119905119888119888119904119904 lowast 119904119904119904119904119905119905119901119901119904119904119905119905 119908119908119905119905119882119882119882119882ℎ119904119904 [119882119882]

228 Data analysis

t test

IR29 8 2 75 32 7 79 20 5 75Nipponbare 11 2 82 32 7 78 75 5 93

Oa -VR 9 3 67 31 16 48 66 25 62Oa -CH 5 3 40 37 9 76 60 14 77Oa -D 6 2 67 30 9 70 106 38 64

tolerance

Results

stress (Fig 2-4)

compared with Na+

4 0 mM

8 0 Mm

O a -V R

4 0 mM

8 0 Mm

O a -C H

4 0 mM

8 0 Mm

O a -D

F re s h W e ig h t

D ry W e ig h t

4 0 mM

8 0 Mm

O a -K R

4 0 mM

8 0 Mm

P o k k a li

4 0 mM

8 0 Mm

IR 2 9

Discussion

et al 2010)

et al 2002)

233 Conclusion

populations

wild germplasm

based phenotyping

the journal article

31 Introduction

and development

al 2016)

stress respectively

321 Plant materials

323 Phenotyping

Plant water use

Plant height

Centre of mass

et al 2018)

119858119858 = 119831119831119831119831 + 119833119833119833119833 + 119838119838

33 Results

(Yichie et al 2018)

34 Discussion

35 Conclusion

41 Introduction

in the wild type

pathway mapping

digestion

al 2019)

searched

meridionalis

treatments

43 Results

Database accession

Unique peptides

Proteins quantified

Oryza Oa-VR 57498 43788 11046 2680

Oa-D 52925 40113 9986 2473

Grasses Oa-VR 22125 14901 5068 1873

Oa-D 19646 13626 4515 1683

Salt-tolerant

Oa-VR 23296 16477 5857 1338

Oa-D 20828 14809 5109 1187

Oa-D 3136 2411 807 446

4-6a and b)

(b) (a)

44 Discussion

enrichment

O australiensis

identified

Metabolic process

this gene family

45 Conclusion

51 Introduction

described below

well plate

Os04g56430_2

Os04g56430_3

Os03g10090_1

Os03g10090_2

Os03g10090_3

AK061988

AK059783

A0A0E0JI75

A0A0D3GSD4

A0A0E0KW83

Os07g37320_2

Os07g37320_3

Os03g09970_1

Os03g09970_2

Os03g09970_3

Os04g56430_1

Os01g24710_2

Os01g24710_3

Os03g57960_1

Os03g57960_2

Os03g57960_3

Os07g37320_1

18S rRNA

Os12g03860_1

Os12g03860_2

Os12g03860_3

Os01g24710_1

119905119905119904119904119904119904119882119882119888119888 =(119864119864119905119905119905119905119905119905119905119905119905119905119905119905)∆119862119862119901119901 119905119905119905119905119905119905119905119905119905119905119905119905

119872119872119872119872119872119872119872119872 119888119888119888119888119888119888119905119905119905119905119888119888119888119888minus119872119872119872119872119872119872119872119872 119904119904119905119905119904119904119901119901119888119888119905119905

(119864119864119905119905119905119905119903119903119905119905119905119905119905119905119903119903119903119903119905119905)∆119862119862119901119901 119905119905119905119905119903119903119905119905119905119905119905119905119888119888119888119888119905119905119872119872119872119872119872119872119872119872 119888119888119888119888119888119888119905119905119905119905119888119888119888119888minus119872119872119872119872119872119872119872119872 119904119904119905119905119904119904119901119901119888119888119905119905

119864119864 = 10( minus1119904119904119904119904119904119904119904119904119905119905)

Experimental design

observed

53 Results

532 RNA extraction

Os03g57960_2 Os07g37320_1

535 RT-qPCR

PCR data

n Ct Oa-VR-Salt

Oa-VR-Control

Oa-D-Salt

Oa-D-Control

y = -33092x + 26706Rsup2 = 09958

-05 0 05 1 15 2 25

(b)y = -32977x + 29832

Rsup2 = 09761

-05 0 05 1 15

y = -14951x + 24715Rsup2 = 09945

-05 0 05 1 15 2 25

y = -37155x + 28713Rsup2 = 0997

-05 0 05 1 15 2 25

(Fig 5-2)

54 Discussion

541 RT-qPCR

of histone tails

colour scheme

55 Conclusion

61 Introduction

63 Results

submission

future directions

accessions

al 2010)

population

276ndash282

Appendix

they are cited

Abstract

Additional files

1 Introduction

DOI 101002pmic201900175

27 Primer Design

3 Results

Uniquepeptides

Oa-VR 57 498 43 788 11 046 2680

Oa-D 52 925 40 113 9986 2473

Oryzaspecies

Numberof hits

Genome

O barthii 625 AA

O glaberrima 192 AA

O punctata 1090 BB

O rufipogon 231 AA

O sativa 670 AA

Oa-D_Saltvs Control

Upregulated 104 (52) 128 (45) 116 (57)

Downregulated 96 (48) 154 (55) 88 (43)

4 Discussion

442 SNARE Proteins

influx[67]

main tiller

treatments

0 02 04 06 08 1 12

tic ra

Dead Leaves []

mM NaCl IR29 0 081 A 028 A 66 2325 A 915 A 61 2335 A 1629 A 3023

40 051 B 034 A 33 1673 B 1232 A 26 1467 B 941 B 358780 037 C 017 B 55 1285 C 653 B 49 1582 B 134 B 1527

y = 0001439x + 0085718Rsup2 = 0994227

0 100 200 300 400 500


Dedication

Acknowledgments

Abbreviations

Journal articles

Journal articles



Abstract

Abstract

Table of Contents

Table of Contents

List of Figures

List of Tables


11 Introduction





12 Background

121 Origin of rice


















Arabidopsis

Cereals

Rice



Salinity

Submergence

Drought

Chilling

Heat

16 Conclusion



21 Introduction









228 Data analysis




Results

Discussion

233 Conclusion



31 Introduction


321 Plant materials


323 Phenotyping

Plant water use




Plant height

Centre of mass







33 Results

34 Discussion

35 Conclusion


41 Introduction
















43 Results





44 Discussion






Metabolic process


45 Conclusion


51 Introduction











Experimental design


53 Results


532 RNA extraction



535 RT-qPCR




54 Discussion

541 RT-qPCR



55 Conclusion


61 Introduction






63 Results







Appendix


Yichie2018

Abstract

Background

Results

Conclusion

Introduction



Experiment 1

Experiment 2


Gas exchange values



Ion assay




First experiment

Second experiment

Results



Discussion

Additional files

Abbreviations

Acknowledgements

Funding





Competing interests


Author details

References

yichie2019



Documents

Salinity tolerance of wild rice accessions from northern