Genome wide identification of NBS-LRR genes in Brassica …360384/s4255… · · 2017-01-18caused by the fungal pathogen Leptosphaeria maculans, is one of the most devastating diseases

Genome wide identification of NBS-LRR genes in Brassica and

their association with disease resistance in Brassica napus

Salman F. Alamery

BSC (Biochemistry)

MSC (Molecular Biology and Biotechnology)

A thesis submitted for the degree of Doctor of Philosophy at

The University of Queensland in 2015

School of Agriculture and Food Sciences

i

Abstract

Brassica napus (canola/rapeseed/oilseed rape) is an important commercial oilseed crop in Australia

with an annual production of approximately 1.6 million tons of oil. Canola is an important source of

edible vegetable oil and has a broad range of industrial purposes. Blackleg disease (stem canker)

caused by the fungal pathogen Leptosphaeria maculans, is one of the most devastating diseases in

B. napus. This disease causes significant yield losses with an annual average loss of 15 to 48 %,

although losses can reach up to 80% worldwide, mainly in Europe, Australia and Canada.

In order to develop an effective strategy to control the blackleg disease, there is a need to identify

blackleg resistance genes in Brassica species and understand the genetic interaction between plant

resistance genes and the pathogen avirulence genes. Thus, identification of Nucleotide Binding Site-

Leucine Rich Repeat (NBS-LRR) resistance genes is one of the most important objectives of

understanding resistance. NBS-LRR resistance genes have been extensively studied because they

represent the largest class of disease resistance genes and play a critical role in defending plants

from pathogens.

The objective of this study was to perform comprehensive analysis on identification and

characterization of NBS-LRR genes in the B. napus genome and to study the synteny and

conservation of NBS-LRR genes between Brassica species. In this study, a total of 641, 249 and

443 NBS-LRR encoding genes in B. napus, B. rapa and B. oleracea, respectively, were identified.

The comparative analysis between B. napus and its progenitor species indicated that NBS-LRR

genes exhibited similar gene structure, genomic location, arrangement in clusters and syntenic

relationships. The results provide evidence that there was a selective advantage to maintaining

similar features of NBS-LRR genes in B. napus to both B. rapa and B. oleracea following

polyploidization. More than 60% of NBS LRR genes from the progenitor species were conserved.

The differences in NBS-LRR gene conservation could be attributed to gene losses or selection

pressure to offer species-specific or cultivars-specific resistance.

This study found that the NBS-LRR resistance genes are physically clustered and individual genes

involved in clusters were more polymorphic and subject to evolutionary process than singleton

genes. These clusters, which have been described in many other species, provide a reservoir of

genetic variation influenced by tandem duplication and selection pressure. In addition, there was a

significant correlation and co-localization between the number of NBS-LRR genes within the

disease QTL intervals and the number of genes involved in gene clusters or duplication. This

ii

correlation provides evidence that NBS-LRR are distributed and clustered throughout the genome

and tends to be linked and associated with disease QTL intervals.

Genetic studies have identified the gene for gene interactions between avirulence (Avr) genes in L.

maculans and their corresponding Rlm (Resistance to Leptosphaeria maculans) genes in B. napus.

In addition, genetic mapping studies have shown that there are five major resistance genes on

chromosome A7: Rlm1, Rlm3, Rlm4, Rlm7, and Rlm9. At present, none of the genetically mapped

Rlm genes on chromosome A7 have been sequenced and validated in B. napus.

A total of 12 NBS-LRR and 18 LRR-containing resistance genes were on B. napus chromosome A7

located within the Rlm QTL region of interest. The comparative analysis of these resistance genes

between Brassica species confirmed the gene synteny and conservation. However, there was

considerable variation; either gene presence/absence or substantial differences in the protein

sequence. The comparative analysis allowed making an initial prediction and prioritization for

targeting these identified genes for further characterization and validation. In this study, a candidate

gene approach, combined with comparative analysis, was exploited for identification of Rlm9

candidate genes in B. napus. The candidate gene approach identified six NBS-LRR and eight LRR-

containing genes associated with the Rlm9 QTL region. The NBS-LRR genes were selected for

further analysis as highest priority candidate genes.

These results provide the first in-depth molecular characterization of NBS-LRR genes in B. napus

providing potential candidate gene for disease resistance trait in B. napus. More importantly, this

work has significantly increased our understanding about blackleg resistance in B. napus and major

disease resistance genes have been identified.

iii

Declaration by author

This thesis is composed of my original work, and contains no material previously published or

written by another person except where due reference has been made in the text. I have clearly

stated the contribution by others to jointly-authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical

assistance, survey design, data analysis, significant technical procedures, professional editorial

advice, and any other original research work used or reported in my thesis. The content of my thesis

is the result of work I have carried out since the commencement of my research higher degree

candidature and does not include a substantial part of work that has been submitted to qualify for

the award of any other degree or diploma in any university or other tertiary institution. I have

clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and,

subject to the policy and procedures of The University of Queensland, the thesis be made available

for research and study in accordance with the Copyright Act 1968 unless a period of embargo has

been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright

holder(s) of that material. Where appropriate I have obtained copyright permission from the

copyright holder to reproduce material in this thesis.

iv

Publications during candidature

Peer reviewed journal publications

Raman, H., Dalton-Morgan, J., Diffey, S., Raman, R., Alamery, S., Edwards, D. & Batley, J. 2014.

SNP markers-based map construction and genome-wide linkage analysis in Brassica

napus. Plant Biotechnology Journal, 12, 851-860.

Dalton-Morgan, J., Hayward, A., Alamery, S., Tollenaere, R., Mason, A., Campbell, E., Patel, D.,

Lorenc, M., Yi, B., Long, Y., Meng, J., Raman, R., Raman, H., Lawley, C., Edwards, D. &

Batley, J. 2014. A high-throughput SNP array in the amphidiploid species Brassica

napus shows diversity in resistance genes. Functional & Integrative Genomics, 1-13.

Chalhoub, B., Denoeud, F., Liu, S., Parkin, I. A. P., Tang, H., Wang, X., Chiquet, J., Belcram, H.,

Tong, C., Samans, B., Corréa, M., Da Silva, C., Just, J., Falentin, C., Koh, C. S., Le

Clainche, I., Bernard, M., Bento, P., Noel, B., Labadie, K., Alberti, A., Charles, M., Arnaud,

D., Guo, H., Daviaud, C., Alamery, S., Jabbari, K., Zhao, M., Edger, P. P., Chelaifa, H.,

Tack, D., Lassalle, G., Mestiri, I., Schnel, N., Le Paslier, M.-C., Fan, G., Renault, V., Bayer,

P. E., Golicz, A. A., Manoli, S., Lee, T.-H., Thi, V. H. D., Chalabi, S., Hu, Q., Fan, C.,

Tollenaere, R., Lu, Y., Battail, C., Shen, J., Sidebottom, C. H. D., Wang, X., Canaguier, A.,

Chauveau, A., Bérard, A., Deniot, G., Guan, M., Liu, Z., Sun, F., Lim, Y. P., Lyons, E.,

Town, C. D., Bancroft, I., Wang, X., Meng, J., Ma, J., Pires, J. C., King, G. J., Brunel, D.,

Delourme, R., Renard, M., Aury, J.-M., Adams, K. L., Batley, J., Snowdon, R. J., Tost, J.,

Edwards, D., Zhou, Y., Hua, W., Sharpe, A. G., Paterson, A. H., Guan, C. & Wincker, P.

2014. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed

genome. Science, 345, 950-953.

Salman Alamery, Reece Tollenaere, Philipp E. Bayer, Boulos Chalhoub, David Edwards and

Jacqueline Batley (2015) Genome wide identification and characterization of NBS-LRR

resistance genes in Brassica napus, Plant Biotechnology journal (submitted).

Salman Alamery, David Edwards and Jacqueline Batley (2015) Association and localization of

NBS-LRR genes with disease resistance QTL in Brassica napus, international Journal of

Genomics (submitted).

v

Publications included in this thesis












2014. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed

genome. Science, 345, 950-953 (accepted). Included in Chapter 3

Contributor Statement of contribution

Salman Alamery (Candidate) NBS-LRR gene analysis, identification and

comparative analysis 40%

Jacqueline Batley NBS-LRR gene analysis, group leader 10%

Reece Tollenaere NBS-LRR gene analysis, identification and

comparative analysis 10%

Philipp E. Bayer

NBS-LRR gene analysis, bioinformatics 40% Chuchuan Fan

Yong Pyo Lim

Sahana Manoli

vi

Salman Alamery, Reece Tollenaere, Philipp E. Bayer, Boulos Chalhoub, David Edwards and

Jacqueline Batley (2015) Genome wide identification and characterization of NBS-LRR

resistance genes in Brassica napus, Plant Biotechnology journal (submitted). Included as Chapter

2 and 3


Salman Alamery (Candidate) Designed experiments (60%)

Conducted experiments (100%)

Sequence data analysis (60%)

Wrote the paper (100%)

Jacqueline Batley Designed experiments (40%)

Edited paper (50%)

David Edwards Edited paper (30%)

Boulos Chalhoub Edited paper (20%)

Philipp E. Bayer Sequence data analysis (20%)

Reece Tollenaere Sequence data analysis (20%)

Salman Alamery, David Edwards and Jacqueline Batley (2015) Association and localization of

NBS-LRR genes with disease resistance QTL in Brassica napus, International Journal of

Genomics (submitted). Included as Chapter 4


Salman Alamery (Candidate) Designed experiments (60%)

Conducted experiments (100%)

Wrote the paper (100%)

Jacqueline Batley Designed experiments (40%)

Edited paper (50%)

David Edwards Edited paper (50%)

vii

Contributions by others to the thesis

Prof Jacqueline Batley contributed to the conception and supervision of the research and assisted

with editing of writing. Illumina read mapping of Skipton and Ag-Spectrum reads and running of

the MAST/MEME pipeline was performed by Prof Edwards’ bioinformatics group.

Statement of parts of the thesis submitted to qualify for the award of another degree

None

viii

Acknowledgements

I am pleased to dedicate this thesis to all people who have helped and supported me during my PhD

study.

First of all, I would like to acknowledge and extend my deep gratitude to my principal advisor, Prof

Jacqueline Batley for supervision and providing me with the opportunity to conduct my PhD

research. She has been constantly supportive and encouraging throughout my PhD study. I have

learned a lot from her expertise and without her, this thesis wouldn’t have been completed. I greatly

appreciated her advices, friendship and the time taken to read my papers and thesis. I look forward

to further collaboration with in the future.

I also wish to thank my co-advisor, Prof David Edwards and his bioinformatics group at the

University of Queensland for assisting with bioinformatics analysis.

I would also like to extend my gratitude to all the members of the Batley group and the staff and

students at CILR at the University of Queensland, who I have been lucky enough to share a lab with

them. In particular, I would like to thank Reece Tollenaere for his friendship, helpful discussions.

I would like to thank A/Prof Elizabeth Aitken and Dr Brett Ferguson for their contributions to the

university assessment process and constructive advice during candidature reviews.

I would like to acknowledge King Saud University, Saudi Arabia, for a PhD Scholarship and

financial support during my study. Acknowledge is also made to the University of Queensland,

School of Agricultural and Food Sciences for study courses and research facilities to achieve my

PhD degree.

Above all, I would like to thank my wife, Alya and my daughters, Eman and Lean for their support,

great patience, love and encouragement at all times.

ix

Keywords

Brassica, Leptosphaeria maculans, blackleg disease, comparative genomics, NBS-LRR resistance

gene, gene cluster, candidate genes, disease resistance QTL

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 060702 Plant Cell and Molecular Biology, 40%

ANZSRC code: 060408 Genomics, 50%

ANZSRC code: 060704 Plant Pathology, 10%

Fields of Research (FoR) Classification

FoR code: 0607, Plant Biology, 80%

FoR code: 0601, Biochemistry and Cell Biology, 20%

x

Table of Contents

Abstract ............................................................................................................................................ i

Declaration by author ................................................................................................................... iii

Acknowledgements ...................................................................................................................... viii

Chapter 1 : Literature review ........................................................................................................... 2

1.1 Introduction ........................................................................................................................... 2

1.2 Brassica napus and related species ....................................................................................... 2

1.3 Brassica genome sequencing: an overview ........................................................................... 3

1.4 Identifying and characterizing the structure of NBS-LRR genes in Brassica ...................... 4

1.5 Genetics of disease resistance in Brassica ............................................................................ 6

1.6 The fungal pathogen Leptosphaeria maculans: Biology and blackleg disease ..................... 8

1.7 Molecular interaction between Brassica and L. maculans .................................................... 9

1.8 Genetic mapping of blackleg resistance genes in Brassica species .................................... 12

1.9 Introgression of blackleg resistance genes into the B. napus genome: attempts and

challenges ....................................................................................................................................... 17

1.10 Genomic approaches for identification of candidate resistance genes ................................ 19

1.10.1 Comparative analysis based candidate gene identification .......................................... 20

1.10.2 Sequence based candidate gene identification ............................................................. 21

1.10.3 SNP genotyping and association with candidate genes ............................................... 22

1.11 Research aims and significance ........................................................................................... 26

Chapter 2 : Genome wide identification and characterization of NBS-LRR resistance genes in

Brassica napus .................................................................................................................................. 30

2.1 Abstract ............................................................................................................................... 30

2.2 Introduction ......................................................................................................................... 31

2.3 Methods ............................................................................................................................... 33

2.3.1 Brassica genome and gene prediction ......................................................................... 33

2.3.2 Identification of NBS-LRR genes in B. napus by MEME/ MAST analysis................ 33

2.3.3 Identification of NBS-LRR genes in B. napus by CNLs and TNLs for validation ..... 33

2.3.4 Correlation between the MAST output and CNL/TNL BLAST results ...................... 34

2.3.5 Manual annotation check and characterization of candidate NBS-LRR genes ........... 34

2.3.6 Multiple alignment and phylogenetic analysis............................................................. 34

2.3.7 NBS-LRR genes cluster and duplication analyses ....................................................... 35

2.4 Results ................................................................................................................................. 36

2.4.1 Genome wide identification of B. napus NBS-LRR genes .......................................... 36

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2.4.2 Genomic distribution and organisation of NBS-LRR encoding genes in the B. napus

genome ………………………………………………………………………………………..40

2.4.3 NBS-LRR gene clustering ........................................................................................... 44

2.4.4 Alignment and phylogenetic analysis .......................................................................... 45

2.4.5 NBS-LRR gene duplication ......................................................................................... 49

2.5 Discussion ........................................................................................................................... 53

2.5.1 Genome wide identification of B. napus NBS-LRR genes .......................................... 53

2.5.2 Alignment and phylogenetic analysis .......................................................................... 55

2.5.3 NBS-LRR gene clustering ........................................................................................... 56

2.5.4 NBS-LRR gene duplication ......................................................................................... 57

Chapter 3 : Comparative and conservation analysis of NBS-LRR genes in Brassica ............... 61

3.1 Abstract ............................................................................................................................... 61

3.2 Introduction ......................................................................................................................... 62

3.3 Methods ............................................................................................................................... 64

3.3.1 Brassica reference genomes ......................................................................................... 64

3.3.2 Identification of NBS-LRR genes in B. rapa and B. oleracea .................................... 64

3.3.3 Reciprocal Best BLAST (RBB) of NBS-LRR for comparative analysis between B.

napus, B. rapa and B. oleracea................................................................................................... 64

3.4 Results ................................................................................................................................. 65

3.4.1 Comparison of the distribution of B. napus NBS-LRR genes to its related diploid

species B. rapa and B. oleracea .................................................................................................. 65

3.4.2 Conservation analysis of B. napus NBS-LRR genes to its related diploid species B.

rapa and B. oleracea ................................................................................................................... 75

3.4.3 Comparative analysis of chromosome A7 and C6 in B. napus .................................... 76

3.5 Discussion ........................................................................................................................... 79


progenitor species B. rapa and B. oleracea ................................................................................ 79

3.5.2 Conservation analysis of B. napus NBS-LRR genes to its related diploid species B.

rapa and B. oleracea ................................................................................................................... 80

3.5.3 Comparative analysis of chromosomes A7 and C6 in B. napus .................................. 82

Chapter 4 : Association and localization of NBS-LRR genes with disease resistance QTL in

Brassica napus .................................................................................................................................. 84

4.1 Abstract ............................................................................................................................... 84

4.2 Introduction ......................................................................................................................... 85

4.3 Methods ............................................................................................................................... 88

4.3.1 Brassica reference genome sequences ......................................................................... 88

xii

4.3.2 Identification of QTL intervals in B. napus by marker homology BLAST search ...... 88

4.4 Results ................................................................................................................................. 89

4.4.1 Identification and localization of QTL intervals in B. napus ....................................... 89

4.4.2 Co-localization and association of NBS-LRR genes and QTL intervals ..................... 99

4.5 Discussion ......................................................................................................................... 105

4.5.1 Identification and localization of QTL intervals in B. napus ..................................... 105

4.5.2 Co-localization and association of NBS-LRR genes and QTL intervals ................... 107

Chapter 5 : Comparative analysis enabled the identification of candidate Rlm9 blackleg

resistance genes in Brassica napus ................................................................................................ 110

5.1 Abstract ............................................................................................................................. 110

5.2 Introduction ....................................................................................................................... 111

5.3 Methods ............................................................................................................................. 113

5.3.1 Brassica genome and gene prediction ....................................................................... 113

5.3.2 Identification of NBS-LRR and LRR- containing genes in B. napus ........................ 113

5.3.3 Comparative analysis of NBS-LRR and LRR-containing gene on the A7 and C6

chromosome of B. napus .......................................................................................................... 113

5.3.4 Genetic mapping of the Rlm9 QTL ............................................................................ 113

5.3.5 SNP genotyping of B. napus cultivars ....................................................................... 114

5.3.6 Extraction of genomic DNA ...................................................................................... 116

5.3.7 PCR amplification and sequencing of Rlm9 candidate genes .................................... 116

5.3.8 DNA Sequencing and Sequence Analysis ................................................................. 118

5.4 Results ............................................................................................................................... 119

5.4.1 Identification and characterization of NBS LRR and LRR-containing genes on B.

napus chromosome A7 ............................................................................................................. 119

5.4.2 Comparative analysis of NBS-LRR and LRR-containing genes on chromosome A7 of

B. napus ………………………………………………………………………………………122

5.4.3 Haplotype analysis of Rlm9 and mapping potential SNPs in B. napus...................... 127

5.4.4 The identification of candidate Rlm9 blackleg resistance genes in B. napus ............ 130

5.4.4.1 Candidate gene BnDRG 13..................................................................................... 132



5.4.4.4 Candidate gene BnDRG19...................................................................................... 133

5.4.4.5 Candidate gene BnDRG20...................................................................................... 133


5.4.5 Amplification and sequencing of Rlm9 candidate genes ........................................... 134

5.5 Discussion ......................................................................................................................... 145

xiii

5.5.1 Identification and characterization of NBS-LRR and LRR-containing genes on B.

napus chromosome A07 ........................................................................................................... 145

5.5.2 Comparative analysis of NBS-LRR and LRR-containing genes on chromosome A7

………………………………………………………………………………………145

5.5.3 Haplotype analysis of Rlm9 and mapping potential SNPs on B. napus ..................... 147

5.5.4 The physical location and identification of candidate Rlm9 blackleg resistance gene in

B. napus ………………………………………………………………………………………148

5.5.5 Amplification and sequencing Rlm9 candidate genes ................................................ 149

Chapter 6 : General discussion and future directions ................................................................ 153

6.1 Genome wide identification of NBS-LRR resistance genes in Brassica .......................... 153

6.2 Identification of candidate blackleg resistance genes in B. napus .................................... 155

6.3 Future directions ................................................................................................................ 158

Bibliography................................................................................................................................ 160

xiv

List of Figures

Figure ‎1.1: The genomic relationships between the six cultivated Brassica species indicating the

genome composition (U, 1935). ........................................................................................................... 3

Figure ‎1.2: The domain structure of NBS-LRR proteins in plants. Taken from (McHale et al.,

2006). ................................................................................................................................................... 5

Figure ‎1.3: Blackleg infection symptoms on B. napus caused by L. maculans .................................. 9

Figure ‎1.4: The mode of activation the plant immune responses by PAMP-triggered immunity

(PTI) and effector-triggered immunity (ETI). .................................................................................... 10

Figure ‎1.5: The infection outcomes between Brassica R genes and L. maculans Avr genes

according to the gene for gene interaction.. ....................................................................................... 11

Figure ‎1.6: Integration the partial genetic map of Rlm4 QTL on chromosome A7 of B. napus

against the physical map of B. rapa. .................................................................................................. 17

Figure ‎1.7: Sequence based identification of Rlm4 candidate gene using NGS data.. ..................... 22

Figure ‎1.8: The principles of whole genome genotyping using the Illumina infinium assay. .......... 25

Figure ‎1.9: Schematic representation of genomics based identification of candidate resistance

gene(s) used in this study. .................................................................................................................. 28

Figure ‎2.1: Example of representation of motif patterns in NBS-LRR genes in B. napus.. ............. 39

Figure ‎2.2: Physical locations of NBS-LRR genes on the chromosome of the A genome of B.

napus.. ................................................................................................................................................ 42

Figure ‎2.3: Physical locations of NBS-LRR genes on the chromosome of the C genome of B.

napus.. ................................................................................................................................................ 43

Figure ‎2.4: A phylogenetic tree of 176 CNL encoding genes of B. napus for NBS domains based

on the neighbour-joining method using MEGA 6.0 software.. .......................................................... 47

Figure ‎2.5: A phylogenetic tree of 366 TNL encoding genes of B. napus for NBS domains based on

the neighbour-joining method using MEGA 6.0 software. ................................................................ 48

Figure ‎2.6: Inter-genomic and intra-genomic duplication relationship of NBS-LRR -genes between

the two sub-genomes of B. napus: the A and C genomes.. ................................................................ 50

Figure ‎3.1: The distribution of NBS-LRR genes in the A genome of B. napus and B. rapa

(Chalhoub et al., 2014). ...................................................................................................................... 69

Figure ‎3.2: The distribution of NBS-LRR genes in the C genome of B. napus and B. oleracea

(Chalhoub et al., 2014). ...................................................................................................................... 69

Figure ‎3.3: The proportion of TNL and CNL genes to the total number of NBS-LRR genes in B.

napus, B. rapa and B. oleracea. ......................................................................................................... 70

Figure ‎3.4: Comparative organization of NBS-LRR genes between the An genome of B. napus and

Ar genome of B. rapa (chromosomes A1 to A5).). ........................................................................... 71


Ar genome of B. rapa (chromosomes A6 to A10).. ........................................................................... 72

Figure ‎3.6: Comparative organization of NBS-LRR genes between the Cn genome of B. napus and

Co genome of B. oleracea (chromosomes C1 to C5).. ...................................................................... 73


Co genome of B. oleracea (chromosomes C6 to C9).. ...................................................................... 74

Figure ‎3.8: Comparative chromosomal map of NBS-LRR genes on chromosomes A7 and C6

between B. napus (Bn), B. rapa (Br) and B. oleracea (Bo). .............................................................. 77

xv

Figure ‎3.9: A phylogenetic tree of TNL and CNL genes located on chromosomes A7 and C6 in B.

napus and the diploid species B. rapa and B. oleracea based on a neighbour-joining method using

MEGA 6.0 software. .......................................................................................................................... 78

Figure ‎4.1: The location of disease resistance loci QTL in the chromosomal map of B. napus. ..... 98

Figure ‎4.2: The correlation between the number of NBS-LRR genes within the 2Mbp flanking

regions of QTL and the number of NBS-LRR genes involved in gene clusters .............................. 103


regions of QTL and the number of duplicated NBS-LRR genes. .................................................... 104

Figure ‎5.1: Distribution of NBS-LRR and LRR-containing genes on chromosome A7 of B. napus.

.......................................................................................................................................................... 121


between B. napus (Bn), B. rapa (Br) and B. oleracea (Bo). ............................................................ 125

Figure ‎5.3: Comparative chromosomal map of LRR-containing genes on chromosomes A7 and C6

between B. napus (Bn), B. rapa (Br) and B. oleracea (Bo). s ......................................................... 126

Figure ‎5.4: Mapping based identification of the Rlm9 candidate gene using marker physical

mapping, NBS LRR genome wide identification and SNP haplotypes.. ......................................... 131

Figure ‎5.5: Comparison of deduced amino acid sequences of BnDRG 13 in B. napus Darmor A7 to

its homologous genes in B. napus Tapidor and B. rapa. ................................................................. 137


its homologous genes in B. napus Tapidor A7 and B. rapa............................................................. 138


its homologous genes in B. napus Darmor C6 and B. rapa. ............................................................ 139


its homologous genes in B. napus Darmor C6, B. napus Tapidor A7 and B. rapa. ........................ 140


its homologous genes in B. napus Darmor C6 and B. rapa. ............................................................ 142

Figure ‎5.10: Comparison of deduced amino acid sequences of BnDRG 23 in B. napus Darmor A7

to its homologous genes in B. napus Tapidor A7. ........................................................................... 143

Figure ‎5.11: Assembly of B. napus Skipton and Ag-Spectrum sequence short reads to B. napus

Darmor reference genome within the Rlm9 candidate resistance genes: BnDRG 12, BnDRG 13 ,

BnDRG 18 and BnDRG 19............................................................................................................... 144

xvi

List of Tables

Table 1.1: Resistance genes to L. maculans that have been identified in Brassica species based on

genetics and mapping studies. ............................................................................................................ 15

Table ‎2.1: The total number of predicted NBS-LRR genes identified in the B. napus genome. The

comparison between methods used: MEME / MAST and CNL and TNL BLAST .......................... 37

Table ‎2.2: NBS-LRR specific motifs sequence identified with MEME/MAST. .............................. 38

Table ‎2.3: The distribution and organisation of candidate NBS-LRR genes in B. napus ................. 41

Table ‎2.4: The number of NBS-LRR genes classified into different classes and their subfamilies

and domain compositions................................................................................................................... 44

Table ‎2.5: Conserved and consensus sequence of NBS domain motifs found in the NBS-LRR genes

identified in B. napus ......................................................................................................................... 46

Table ‎2.6: The correlation between B. napus NBS-LRR intra-genomic and inter-genomic

duplications and conserved blocks found between B. napus and Arabidopsis .................................. 52

Table ‎3.1: The total number of predicted NBS-LRR genes identified in the three Brassica genomes.

The table shows comparison between the methods used: MEME / MAST and CNL and TNL

BLAST ............................................................................................................................................... 65

Table ‎3.2: The number of candidate NBS-LRR genes in B. napus. The total numbers of genes in

each chromosome with their classification into TNL or CNL as well as the reciprocal best BLAST

results are presented ........................................................................................................................... 66

Table ‎3.3: The number of candidate NBS-LRR genes in B. rapa and B. oleracea. The total numbers

of genes in each chromosome with their classification into TNL or CNL as well as the reciprocal

best BLAST results are presented. ..................................................................................................... 67

Table 3.4: Comparative analysis of synteny of NBS-LRR genes in B. napus to its progenitor species

............................................................................................................................................................ 68

Table ‎3.5: Comparative analysis of the number of NBS-LRR genes in the three Brassica species

and the reciprocal best BLAST hits ................................................................................................... 75

Table ‎4.1: Marker homology search of clubroot resistance QTL flanking or linked markers for

identification of QTL intervals in B. napus ....................................................................................... 92

Table ‎4.2: Marker homology search of downy mildew resistance QTL flanking or linked markers

for identification of QTL intervals in B. napus .................................................................................. 94

Table ‎4.3: Marker homology search of blackleg resistance QTL flanking or linked markers for

identification of QTL intervals in B. napus ....................................................................................... 96

Table ‎4.4: Correlation between the number of NBS-LRR resistance genes and disease resistance

QTL intervals in chromosomes of B. napus .................................................................................... 100

Table ‎5.1: List of B. napus cultivars genotyped with the SNP genotyping assay........................... 115

Table ‎5.2: List of the B. napus cultivars and their Rlm complement used for the PCR amplification

.......................................................................................................................................................... 117

Table ‎5.3: List of primer pairs used for long range PCR amplification of Rlm9 candidate genes . 117

Table ‎5.4: List of characterized NBS-LRR and LRR-containing genes on chromosome A7 of B.

napus cv. Darmor. Candidate Rlm9 genes located within the Rlm9 QTL are highlighted .............. 120

Table ‎5.5: Comparative analysis of the number of NBS-LRR and LRR-containing genes on

chromosomes A7 and C6 of the three Brassica species: B. napus, B. rapa and B. oleracea .......... 122

Table ‎5.6: The potential SNPs on chromosome A7 with a good correlation to the Rlm9 gene and

association with disease and susceptibility in B. napus cultivars. ................................................... 128

Table ‎5.7: Mapping and annotation of the potential SNPs identified in B. napus cv. Darmor ....... 129

xvii

Table ‎5.8: Comparative analysis of NBS-LRR Rlm9 candidate genes between B. napus cv. Darmor,

B. napus cv. Tapidor and B. rapa. The sequence identity is based on protein sequence alignment 135

Table ‎5.9: The coverage of Skipton and Ag-Spectrum sequence short reads of candidate Rlm9

genes on B. napus. The identity is based on gene sequence alignment ........................................... 136

xviii

List of Abbreviations

Avr gene Avirulence gene

AvrLm Avirulence to Leptosphaeria maculans

BnDRG Brassica napus Disease Resistance Gene

CC Coiled-Coil domain

CNL CC-NBS-LRR

CNV Copy Number Variation

LRR-RLKs Leucine Rich Repeat -Receptor-Like Kinase

LRR-RLPs Leucine Rich Repeat -Receptor-Like Proteins

MAST Motif Alignment Search Tool

Mbp Millions Base Pairs

MEME Multiple Em for Motif Elicitation

NBS-LRR Nucleotide Binding Site- Leucine Rich Repeat protein

NGS Next-Generation Sequencing

QTL Quantitative Trait Loci

R gene Resistance gene

RBB Reciprocal Best BLAST

RGA Resistance Gene Analogues

Rlm Resistance to Leptosphaeria maculans

SCAR Sequence-Characterized Amplified Region

SNP Single Nucleotide Polymorphism

SSR Simple Sequence Repeat Marker

SV Structural Variation

TIR Toll/ Interleukin-1 Receptor domain

TNL TIR-NBS-LRR

WGD Whole Genome Duplication

1

Chapter 1

Literature Review

2

Chapter 1 : Literature review

1.1 Introduction

Brassica napus (canola/rapeseed/oilseed rape) is an important commercial oilseed crop in Australia

with an annual production of approximately 3 million tons of oil (AOF, 2014). Canola is an

important source of edible vegetable oil and has a broad range of industrial purposes. However,

blackleg disease (stem canker) caused by the fungal pathogen Leptosphaeria maculans, is one of

the most devastating diseases in B. napus. This disease causes significant yield losses with an

annual average losses of 15 to 48% although losses can reach up to 80% worldwide (Marcroft and

Bluett, 2008). An effective strategy to control blackleg disease is to develop resistant B. napus

varieties via interspecific hybridization or genetic transformation. This can be facilitated by the

identification of blackleg resistance genes in B. napus and application of these genes in the breeding

programs. The recent completion of the B. napus, B. rapa and B. oleracea genome sequences

provides invaluable genomics resources to accelerate this research. Furthermore, it allows the study

of the conservation of these genes between Brassica species. This literature review provides insight

about the genome wide NBS-LRR comparison and scope for identification of candidate resistance

genes associated with disease resistance QTL in Brassica. It also highlights significant progress that

has recently been made in mapping and identification of resistance genes in B. napus against L.

maculans.

1.2 Brassica napus and related species

Brassica is one of the most important genera in the Brassicaceae family due to its agricultural and

economic importance. Six of the important Brassica species are: B. juncea, B. napus, B. nigra, B.

oleracea, B. rapa and B. carinata. The genetic relationships among these different diploid and

amphidiploid Brassica species are described according to their genome composition (termed “A” ,

“B” and “C”) by U’s triangle (Figure 1.1) (U, 1935).

3

Figure ‎1.1: The genomic relationships between the six cultivated Brassica species indicating the

genome composition (U, 1935).

Brassicas are important sources of fresh and preserved vegetables and condiments. For instance, B.

oleracea and B. rapa represent many of the vegetables in our daily diet such as cauliflower,

broccoli and cabbage (all B. oleracea), Chinese cabbage (B. rapa) and various mustards (B. nigra)

(Paterson et al., 2001).

B. napus originated from interspecific hybridisation between the diploids B. rapa (A genome) and

B. oleracea (C genome) resulting in an amphidiploid genome (AACC, n=19). B. napus is cultivated

worldwide as the most productive Brassica oilseed species and is grown primarily for its seed

which yield approximately 40% oil making it the second important oilseed crop in the world after

soybean (Snowdon et al., 2007). Total oilseed production in 2014/15 was estimated to be 530

million metric tons, with rapeseed contributing 71.8 million metric tons (USDA, 2014). Canola oil

is used for cooking, in margarine and other edible products in the food processing industry as

healthy edible oil.

1.3 Brassica genome sequencing: an overview

Sequencing of Brassica genomes has been the main focus of Brassica researchers worldwide

because Brassicas are an excellent model species for studying the evolution of polyploid crop

plants. Brassica species contain many triplicated genomic segments and subsequent rearrangements

4

such as inversions, insertions, deletions, and substitutions (Jiang et al., 2011). Genome sequencing

projects for Brassica species, especially B. rapa and B. oleracea, were initiated after the

establishment of the multinational Brassica genome project in 2002 (http://www.brassica.info)

(Hong et al., 2008, Wang et al., 2011).

The rapid development of second-generation sequencing technology and advanced bioinformatics

programs has resulted in the completion of genome sequences of B. napus (Chalhoub et al., 2014),

B. rapa (Wang et al., 2011) and B. oleracea (Liu et al., 2014, Parkin et al., 2014). These Brassica

genome projects also aimed to produce reference genomes for genetic and genomic studies

(Hayward et al., 2011). Illumina whole genome sequencing has been adopted for Brassica species

resulting in the generation of large datasets of short read sequence information for different B.

napus cultivars (Imelfort and Edwards, 2009). Illumina sequencing technology (HiSeq2000)

provides high throughput sequence information generating hundreds of millions of paired short read

sequences (100 - 150 bp) in a single run. If there is a reference genome available, these short reads

can be physically mapped to the reference genome and used to search for sequence variations in

candidate genes underlying QTL regions. Bioinformatics tools such as genome browsers provide a

convenient way to visualise the short reads against a reference genome to identify sequence

coverage, SNPs, coding regions and other annotations (Batley and Edwards, 2009).

1.4 Identifying and characterizing the structure of NBS-LRR genes in Brassica

Plants have developed sophisticated defence mechanisms to recognise and respond to a wide range

of pathogens. Resistance (R) genes are involved in direct or indirect interaction with avirulence

(Avr) genes in order to trigger a defence response. Thus, understanding the molecular structure and

function of R genes has been crucial for plant resistance research. Over the last few decades, a vast

number of R genes have been cloned from a wide range of plant species. These R genes are diverse

in terms of their structure, function and evolution, but they can be grouped into five different

classes, based on structural similarities of their predicted protein products (Staskawicz et al., 1995,

Liu et al., 2007). The largest class includes proteins with putative nucleotide binding site (NBS) and

leucine-rich repeats (LRR). These NBS-LRR genes can be subdivided into two distinct types based

on the structure of their N-terminal domain either a coiled-coil (CC) motif or a Toll/ Interleukin-1

Receptor (TIR) domain (Figure 1.2) (Meyers et al., 2003). The NBS region is thought to be

important for ATP binding activity and comprises of a P-loop, Kinase 2a, Kinase 3 and GLPL

motifs. The LRRs may be the main determinant in recognition specificity of the avirulence gene

product and as components of a signal transduction pathway (Ellis et al., 2000b).

http://www.brassica.info/

5

Figure ‎1.2: The domain structure of NBS-LRR proteins in plants. Taken from (McHale et al.,

2006).

Genome wide analysis of NBS-LRR genes in many plant species including rice (Monosi et al.,

2004) sorghum (Paterson et al., 2009), Arabidopsis (Meyers et al., 2003, Tan et al., 2007) and

papaya (Porter et al., 2009) showed that they are widely distributed throughout the genome with

approximately 0.6–1.8% of genes encoding NBS-LRRs at a density of 0.3–1.6 genes per megabase.

A study of NBS-LRR genes in the B. rapa genome (550Mbp) predicted a lower number of NBS-

encoding genes than in other sequenced crops (Mun et al., 2009). However, at the time of the study

the B. rapa genome had not been fully sequenced. Now this is completed (Wang et al., 2011), a

comprehensive assessment of NBS-LRR genes can be undertaken. Theoretically, the number of

NBS-LRR genes in the B. rapa genome should be higher than in Arabidopsis because the B. rapa

genome has undergone genome triplication since divergence from the common ancestor of

Arabidopsis. Another significant finding was that almost 50% of NBS family members were

detected as tandem arrays within homogenous clusters suggesting tandem duplication in

combination with polyploidy played an important role in the expansion of NBS-LRR genes in the

Brassica genome (Fourmann et al., 2001, Vicente and King, 2001, Mun et al., 2009). Overall, B.

rapa can be used as a source to identify NBS-LRR genes for common pathogens of Brassica crops

(Mun et al., 2009).

A more recent study (Yu et al., 2014) has identified 206, 176 and 157 NBS-LRR genes in B. rapa,

B. oleracea and Arabidopsis, respectively. They found that the number of NBS-LRR genes in these

three species was very close despite the genome size and complexity. This is surprising as B. rapa

and B. oleracea genomes would be expected to contain higher numbers of NBS-LRR genes than in

6

Arabidopsis because the B. rapa and B. oleracea genomes have undergone extensive genome

triplication events.

Resistance genes can occur as a single gene in allelic series or as tightly linked genes (within a gene

cluster) conferring different resistance specificities (Leister, 2004). Thus, race-specific resistance

might have evolved and be present in clusters resulting from tandem duplications of paralogous

sequences (Meyers et al., 2005, McDowell and Simon, 2006, Kaur et al., 2009). Indeed, previous

studies revealed that R genes are often present as tightly linked genes with high homology and are

prone to gene duplication and recombination, and thus evolve more rapidly than the rest of genome

(Grant et al., 1998). For this reason, functional polymorphism at R loci could maintain multiple

alleles or linked genes with different recognition capabilities that would recognize novel pathogen

variants (Grant et al., 1998).

The molecular basis of the resistance responses to pathogens in plants depends on the specificities

of the interactions between the Avr and R gene. The genetic analysis of plant NBS-LRR genes has

shown that they are highly related in sequence and present as multiple alleles of a simple locus or

several closely related resistance genes. Multiple resistance gene specificities can be encoded by

different allelic variants of resistance genes by which each allele can provide resistance to different

pathogen types (Ellis et al., 2000a). An example of allelic forms at the NBS-LRR locus is RPP

(recognition of peronospora parasitica) in Arabidopsis (McDowell et al., 1998) and several alleles

of the L gene in flax encode different flax rust resistance specificities (Ellis et al., 1999).

1.5 Genetics of disease resistance in Brassica

There are two types of disease resistance in Brassica species: qualitative and quantitative. The exact

type of resistance is controlled by different genetic interactions and determines resistance during

specific stages of plant growth: seedling and adult stage resistance (Ferreira et al., 1995b, Ansan-

Melayah et al., 1998, Pilet et al., 1998).

Seedling resistance is qualitative, single-gene race specific and expressed during the cotyledon

stage (Delourme et al., 2006). This resistance typically depends on the presence of a resistance (R)

gene in the plant and a corresponding avirulence (Avr) gene in the pathogen, where if the Avr gene

does not correspond to the R gene in the plant, the plant is susceptible to disease. This is a very

effective resistance and operates through R gene activity when a pathogen infects the cotyledons of

the seedling, subsequently preventing infection spread to the whole plant (Johnson and Lewis,

1994). By contrast, adult resistance is a partial resistance, known as quantitative resistance, and is

controlled by multiple genes. This is race non-specific resistance. It was suggested that quantitative

7

resistance genes work together in a complex interaction with many pathogen Avr genes. Adult plant

infection is the most damaging in terms of quality and yield losses (Zhu et al., 1993, Delourme et

al., 2008).

In spite of the fact that seedling and adult resistance are under separate genetic control: monogenic

and polygenic, respectively, and they are differentially expressed in the plant (Ferreira et al.,

1995a), the genes involved at both stages might be closely linked in quantitative trait loci (QTL)

(Salisbury et al., 1995, Delourme et al., 2006). For instance, two closely linked but distinct loci

mediating resistance at the seedling and adult plant stage of B. napus breeding lines were mapped to

chromosome A7 within 5-10 cM of each other (Ferreira et al., 1995b).

As with many crops, Brassicas are susceptible to many serious diseases including fungi, bacteria

and viruses which cause a major impact on canola production worldwide. In the three major

cultivated Brassica species, B. napus B. rapa, and B. oleracea, clubroot (caused by

Plasmodiophora brassicae), downy mildew (caused by Hyaloperonospora Parasitica) and blackleg

(caused by Leptosphaeria maculans) diseases have become an increasing problem causing heavy

yield losses to Brassica crops world-wide and have been a major focus in the Brassica disease

resistance research (Delourme et al., 2011).

Clubroot disease occurs worldwide to all cruciferous vegetable and oil crops, including Brassica

species. Different sources of resistance to clubroot have been found in B. oleracea, B. rapa and B.

napus (Hirai, 2006, Suwabe et al., 2006, Diederichsen et al., 2009, Piao et al., 2009, Verma et al.,

2014). These different studies suggested that the interaction between Plasmodiophora brassicae and

Brassica are classified as race-specific resistance. To date, two major resistance genes: Crr1a and

CRa, which confer resistance to clubroot in B. rapa, have been identified and cloned. They both

encode a TIR-NBS-LRR protein (Ueno et al., 2012, Hatakeyama et al., 2013).

The downy mildew disease causes damage to production of Brassica species worldwide, including

Australia. While it causes severe destruction on young seedlings, the disease still causes yield and

quality reduction at adult-plant stages. For instance, in Australia, outbreaks of downy mildew

disease at the early seedling stage have caused losses of canola production (Ge et al., 2008). Several

major qualitative resistance loci to downy mildew have been identified in B. rapa and B. oleracea

(Farinhó et al., 2007, Yu et al., 2009, Kim et al., 2011, Carlier et al., 2012). In addition, multiple

sources of resistance have been reported in B. napus (Nashaat et al., 1997, Ge et al., 2008). They

showed that the resistance is more likely to be controlled by a major resistance gene.

8

1.6 The fungal pathogen Leptosphaeria maculans: Biology and blackleg disease

Leptosphaeria maculans is the causal agent of blackleg disease (also termed stem canker or phoma

disease) of Brassica crops. L. maculans has a broad host range within the Brassicaceae infecting

numerous cruciferous species including Raphanus sativus (radish), R. raphanistrum (wild radish),

Sinapis alba (white mustard) and cultivated Brassica crops; such as B. napus, B. rapa, B. juncea

and B. oleracea (Johnson and Lewis, 1994, Williams and Fitt, 1999). Moreover, the model plant

Arabidopsis, also a member of the Brassicaceae, is a host for L. maculans (Rouxel and Balesdent,

2005).

Blackleg is the most serious fungal disease of Brassicas worldwide, and can lead to drastic losses of

up to 80% of canola production (Fitt et al., 2006). Blackleg disease is primarily of economic

importance in the main canola growing areas of Europe, Australia and North America (West et al.,

2001). For instance, the value of Canola production in Australia is around AUD $500 million

annually (Wang et al., 2009) with an average 15% yield loss occurring due to L. maculans infection.

Infection symptoms occur at various stages of crop development causing cotyledon and leaf lesions

prominent during the vegetative phase of the plant, progressing to canker development in the

susceptible cultivars (Figure 1.3) (Delourme et al., 2008). This latter stage results from the fungus

invading cells in the stem cortex, resulting in a blackened canker; hence the name “blackleg” and

causing lodging of the plants (Guo and Fernando, 2005, Fernando et al., 2007). The severity of

blackleg has increased in recent years due to intensification of cultivation and production, rapid

evolution of the pathogen population and lack of sustainable management strategies. Thus, there is

an urgent need to establish effective management of blackleg.

9

Figure ‎1.3: Blackleg infection symptoms on B. napus caused by L. maculans. (A) blackleg lesions

on leaves (source: Canola Council of Canada) (B) blackleg lesions from multiple infections

(Courtesy C. Bradley, American Phytopathological Society) (C) blackleg stem lesion (source:

Canola Council of Canada) (D) interior of stem infected with blackleg(source: Canola Council of

Canada) (E) interior of stem infected with different levels of blackleg severity (source: Canola

Council of Canada) (F) black root form of blackleg as compared to healthy root (source: DEPI,

Victoria).

L. maculans is a haploid fungus, with a small genome size of about 45 Mbp, predicted to encode

10,000-13,000 genes within 16 chromosomes (Rouxel et al., 2011). The Leptosphaeria Genome

Consortium was established in 2004 by Genoscope (CEA) (http://www.genoscope. cns.fr) and the

genome was completed and published in 2011. The genome sequence has been annotated,

assembled and publically released on NCBI (Howlett, 2004, Rouxel et al., 2011).

1.7 Molecular interaction between Brassica and L. maculans

Traditionally, the gene for gene hypothesis is used to explain genetic interactions between the host

plants and their pathogens. This concept proposes that for each resistance gene in the host there is a

specific gene corresponding to avirulence in the pathogen (Dangl and Jones, 2001). Basically, the

gene for gene interaction suggests direct or indirect recognition of pathogen Avr-encoded effectors

by the protein product encoded by the corresponding R gene. Often R genes encode nucleotide

binding site- Leucine rich repeat (NBS-LRR) proteins leading to the induction of a signalling

cascade and subsequent downstream defence responses (Bent, 1996).

http://www.genoscope/

10

Plants operate a defence response against pathogens at two levels: pattern-triggered immunity (PTI)

and effector-triggered immunity (ETI) (Dodds and Rathjen, 2010) (Figure 1.4). PTI involves the

recognition of pathogen associated molecular patterns (PAMPs) and trigger low levels of defence

activation. The pathogen is able to suppress PTI by effector proteins delivered into the plant.

However, PTI results in initiation of ETI. The ETI is gene for gene resistance in which the

interaction is between disease resistance proteins and specific effectors (Avr proteins). This is

mediated largely by nucleotide binding-site-leucine rich repeat (NBS-LRR) proteins. ETI triggers a

stronger resistance response and often causes localized cell death described as a hypersensitive

response (HR) and prevents further infection (Collier and Moffett, 2009, Tsuda and Katagiri, 2010).

Figure ‎1.4: The mode of activation of the plant immune responses by PAMP-triggered immunity (PTI) and

effector-triggered immunity (ETI). Adopted from (Alcázar and Parker, 2011).

In the Brassica–L. maculans pathosystem, a typical gene-for-gene interaction has been reported,

where the outcome of the infection (resistance or susceptibility) depends on the presence of an R

gene in the plant and one corresponding (Avr ) gene in the pathogen (Figure 1.5) (Ansan-Melayah

et al., 1998, Balesdent et al., 2001, Balesdent et al., 2002). A set of differential interactions between

Brassica species and L. maculans were utilized at the seedling stage using a cotyledon inoculation

test (Williams and Delwiche, 1979). This determined the presence of the Avr gene required for race

specific resistance in various Brassica species and cultivars with known R gene complements based

on genetic mapping (Balesdent et al., 2002).

11

Figure ‎1.5: The infection outcomes between Brassica R genes and L. maculans Avr genes

according to the gene for gene interaction. Only when the R gene is corresponding to the Avr gene,

is the plant resistant against the pathogen.

Genetic studies have identified the gene for gene interactions between Avr genes in L. maculans and

their corresponding Rlm (Resistance to Leptosphaeria maculans) genes in B. napus. For example,

Rlm1/AvrLm1 and Rlm2/ AvrLm2 interactions were found in the B. napus cultivars, Quinta and

Glacier, respectively (Ansan-Melayah et al., 1998).

Effector-triggered immunity (ETI), a pathogen race-specific resistance, is a well-studied example of

host-resistance and has been observed in most plant species, including B. napus (Jones & Dangl,

2006; Poland et al., 2009). The existence of ETI between B. napus and L. maculans has been

described between the Rlm1 and LepR 3 genes and AvrLm1 gene (Raman et al., 2012a, Larkan et

al., 2013) and between the Rlm 2 gene and AvrLm2 gene (Larkan et al., 2014).

Genetic mapping of avirulence genes revealed four unlinked genomic regions of L. maculans

associated with host specificity: the AvrLm1–AvrLm2–AvrLm6 cluster, the AvrLm3–AvrLm4–

AvrLm7 cluster, AvrLm5, AvrLm8 and AvrLm11 (Balesdent et al., 2002, Fernando et al., 2007,

Balesdent et al., 2013). This cluster of Avr genes in L. maculans has been described as the first

example of Avr gene clustering in fungi. It was suggested that there might be a relationship between

Avr gene clustering in L. maculans and a counterpart clustering of R genes in B. napus (Delourme et

al., 2004).

12

To date, several avirulence genes in L. maculans have been cloned: AvrLm1 (Gout et al., 2006),

AvrLm2 (Ghanbarnia et al., 2015), AvrLm6 (Fudal et al., 2007) and AvrLm4-7 (Parlange et al.,

2009) confers avirulence towards two different resistance genes, Rlm4 and Rlm7. AvrLm11

(Balesdent et al., 2013) and AvrLmJ1 (Van de Wouw et al., 2014).

The availability of genome sequences has led to the identification of candidate resistance genes and

provides the opportunity to validate the interaction between R genes and Avr genes using sequence

information, genetic transformation, phenotyping and gene expression analysis. However,

Agrobacterium -mediated transient expression (Agroinfiltration) is an alternative and quick

approach for validating a candidate R gene (Vaghchhipawala et al., 2011, Ma et al., 2012). It is a

rapid and simple technique to study gene function and host-pathogen interaction and protein-protein

interaction (Bendahmane et al., 2000, Wroblewski et al., 2005, Dodds et al., 2006). It is based on

infiltration of Agrobacterium tumefaciens cultures into intact plant leaves (tobacco) to co-express a

candidate R gene with its corresponding Avr gene. This triggers a defence response that results in

localized cell death at the site of infection termed a hypersensitive response (HR) indicating that

these are functional R-Avr gene interaction. In this study, the validation can be done if both R and

Avr gene sequences are known. For instance, candidate blackleg resistance genes such as Rlm4 can

be validated due to the presence of the cloned AvrLm4 gene. Whereas, candidate Rlm9 genes cannot

be validated as AvrLm9 has not been cloned or sequenced.

1.8 Genetic mapping of blackleg resistance genes in Brassica species

All the blackleg resistance genes identified to date have been found on the A genome of B. napus

with none found on the C genome (Ananga et al., 2006, Leflon et al., 2007). This is supported by

the absence of Rlm1, Rlm2 or Rlm4 in the diploid C genome species, B. oleracea when screened

against L. maculans isolates harbouring AvrLm1, AvrLm2 and AvrLm4 alleles (Rouxel et al.,

2003b).

To date, ten race specific Rlm genes have been genetically mapped and identified in B. napus. By

screening B. napus cultivars with a differential set of L. maculans isolates, Rlm1 was identified in

the cultivar Quinta (Ansan-Melayah et al., 1998), LEM1, LmR1 and cRLMm, are present in the

cultivars Major, Shiralee and Maluka, respectively, Rlm2 and Rlm3 in the cultivar Glacier

(Balesdent et al., 2002), Rlm4 in the cultivars Jet Neuf (Balesdent et al., 2001) and Skipton (Raman

et al., 2012), Rlm7 in non-commercial lines (Balesdent et al., 2002), and Rlm9 in the cultivar

Darmor (Delourme et al., 2004).

13

Genetic mapping studies have showed that all resistance genes in B. napus are organised in clusters

in two genomic regions: the Rlm2 resistance gene on chromosome A10 is associated with adult

resistance (Pilet et al., 2001) and five specific resistance genes: Rlm1, Rlm3, Rlm4, Rlm7, and Rlm9

are on chromosome A7 (Delourme et al., 2004) (Table 1.1).

Rlm1 was suggested to be distinct from Rlm3 because they both occur in one cultivar and they

genetically map to different positions. In addition, Rlm1 and Rlm4 are linked, not allelic and can be

present in the same cultivar. Rlm3 and Rlm4 are found in many rapeseed cultivars and are rarely

present together in a single cultivar (Delourme et al., 2006). Indeed, the existence of Rlm1, Rlm3,

Rlm4, Rlm7 and Rlm9 as a cluster of tightly linked genes has never been observed. Thus, it is

impossible to judge if these genes are a cluster of tightly linked genes, or a single gene with

different alleles, or a combination of both (Delourme et al., 2004).

Rlm4 provides effective resistance against isolates with the avirulence gene AvrLm4 (Rouxel et al.,

2003b, Raman et al., 2012b) and is present in the French cultivars Major and Jet Neuf, as well as

Australian cultivars including Maluka, Dunkeld and Skipton. However, the cultivar Westar is

highly susceptible to blackleg (lack of any Rlm4 genes) and shows a reciprocal translocation break

point close to the Rlm4 locus in A7, making fine mapping extremely difficult (Rimmer, 2006).

Interestingly, an AvrLm4-7 locus in L. maculans has dual interaction specificity to resistance genes

Rlm4 and Rlm7 in B. napus, yet it is unclear if Rlm4 and Rlm7 represent allelic forms of the same

resistance gene. It was suggested that deletion of AvrLm4-7 may be the major event leading to

acquisition of virulence towards Rlm7 resistance whilst mutation of a single nucleotide is sufficient

to avoid Rlm4- mediated recognition of AvrLm4-7 (Parlange et al., 2009).

The genes LEM1, LmR1, cRLMm and cRLMrb present in different B. napus cultivars were also

mapped onto chromosome A7 (Table 1.1) (Mayerhofer et al., 1997, Rimmer, 2006). LEM1 was

found to confer seedling resistance to an isolate containing Avr1-2-4-7 (Ferreira et al., 1995a) and to

be located within an extensive intra-chromosomal tandem duplication region (Mayerhofer et al.,

2005). However, LmR1, cRLMm and cRLMrb are likely to be identical to Rlm4, and are present in

the cultivars Major and Maluka (Rouxel et al., 2003b).

Four dominant race specific resistance genes were also identified in the A genome of B. rapa: Rlm8

(Balesdent et al., 2002), LepR1 a single dominant gene mapped on chromosome A2, LepR2 which

maps to chromosome A10 (Yu et al., 2005) and LepR3 mapped to chromosome A10, 15–20 cM

from LepR2 (Li and Cowling, 2003). It is also proposed that LepR3 is not identical to LepR2 (Yu et

al., 2008) and LepR3 possibly corresponds to Rlm1 (Van De Wouw et al., 2009). Another two

14

resistance genes BLMR1 and BLMR2 have been identified. The former may provide cotyledonary

stage resistance whereas the latter has a role in preventing infection development (Long et al.,

2011). Interestingly, LepR3 was located between BLMR1 and BLMR2 and represents the resistance

combination of BLMR1 and BLMR2 (Table 1.1) (Yu et al., 2008, Long et al., 2011). LepR3 was

first blackleg resistance gene in Brassica to be cloned in B. napus lines with introgressions from B.

rapa ssp. Sylvestris (Larkan et al., 2013). It belongs to a receptor-like protein (RLP) family.

The LepR4 resistance gene was mapped to chromosome A6 and two different alleles LepR4a and

LepR4b were mapped to the same position. LepR4 was found as a recessive gene conferring a wide

spectrum of resistance to the fungus isolates (Yu et al., 2012). In addition, the B. rapa genome

might harbour genes previously identified in B. napus such as Rlm1, Rlm2, Rlm4 and Rlm7 as

previous studies have (Leflon et al., 2007) suggested that these genes are orthologous and are

located in the same position in B. rapa and B. napus (Rana et al., 2004, Delourme et al., 2006).

The B genome Brassica species B. nigra contains two resistance genes: Lm1 and Rlm10 (Table 1.1)

(Chèvre et al., 1996, Wretblad et al., 2003). Plants containing Lm1 have improved resistance to L.

maculans in the cotyledon and adult stage when it is overexpressed in B. napus (Wretblad et al.,

2003). Significantly, the Lm1 gene belongs to the serine/theronine kinase family (Howlett, 2004). It

is expected that B. nigra carries a number of different resistance genes in the B genome (Zhu et al.,

1993, Chèvre et al., 1996), which are yet to be reported. Zhu et al. (1993) reported that the

resistance in B. nigra is polygenic, controlled by a small number of genes located on chromosome

B3. The Rlm10 gene introgression location into B. napus is thought to be on A7 (Chèvre et al.,

1997, Dixelius, 1999).

In the amphidiploid AABB species B. juncea, resistance to L. maculans was suggested to be

mediated by two genes called Rlm5 and Rlm6 (Table 1.1) (Rimmer and van den Berg, 1992, Keri et

al., 1997, Balesdent et al., 2002, Leflon et al., 2007). Additionally, the lm2 gene identified in B.

napus hybrids, derived from B. juncea, was highly effective against a wide range of L. maculans

isolates at the cotyledon stage (Saal et al., 2004). Sequence-characterized amplified regions (SCAR)

markers were developed based on amplification of resistance gene analogues (RGA) in which they

are isolated by PCR with degenerate primers designed from the highly conserved motifs of

resistance genes. The SCAR marker was strongly associated to the resistance locus lm2 in B. napus,

B. rapa and B. oleracea. Sequence analysis of this gene revealed significant homology to two

putative R genes on a resistance gene cluster on chromosome 5 of Arabidopsis (Saal and Struss,

2005).

15

Table 1.1: Resistance genes to L. maculans that have been identified in Brassica species based on

genetics and mapping studies.

Species Resistance gene

Corresponding avirulence gene

Gene location in B. napus

Comments

B. napus

LEM1 Avr1-2-4-7 A7 May be identical to Rlm4

LmR1 AvrLm4 A7 May be identical to Rlm4

cRLMm AvrLm4 A7 May be identical to Rlm4

cRLMb AvrLm4 A7 May be identical to Rlm4

Rlm1 Avrlm1 A7 Distinct from Rlm3 and Rlm4

Rlm2 Avrlm2 A10 Associated with adult resistance

Rlm3 Avrlm3 A7 Linked , not allelic to Rlm1.

Rlm4 AvrLm4 A7 Linked, not allelic to Rlm1. rarely present together with Rlm3

Rlm7 AvrLm7 A7 This might be allelic variant of Rlm4

Rlm9 AvrLm9 A7 Rlm3, Rlm4, Rlm7 and Rlm9 as cluster of tightly linked genes

B. rapa

Rlm8 AvrLm8 -- --

LepR1 -- A2 Introgressed into B. napus from B. rapa

LepR2 -- A10 Introgressed into B. napus from B. rapa

LepR3 -- A10

Mapped close to LepR2, not identical to LepR2 LepR3 is possibly corresponding to Rlm1 Introgressed into B. napus from B. rapa

LepR4 A6 A recessive gene, two alleles

BLMR1 -- A10 LepR3 was located in between BLMR1 and BLMR2

BLMR2 -- A10 --

B. nigra Lm1 -- A3

Cotyledon and adult resistance

Rlm10 -- A7 --

B. juncea

Rlm5 AvrLm5 A8 --

Rlm6 AvrLm6 A8 May be identical to r j lm2

r j lm2 -- --

Identified in B. napus and B. juncea hybrids effective to different L. maculans isolates at cotyledon stage

16

Arabidopsis was recently found to be resistant to a wide range of L. maculans isolates. It is believed

that a dominant resistance (R) gene encoding a nucleotide binding site - leucine-rich repeats (NBS-

LRR) is required to confer resistance. To date, three genes have been identified as Arabidopsis

thaliana Resistance to Leptosphaeria maculans named AtRlm1, AtRlm2 and AtRlm3 (Staal et al.,

2006, Staal et al., 2008). Two TIR-NBS- LRR genes: AtRlm1 and AtRlm2 are present in the

different genotypes Col and Ler and are mapped on chromosomes 1 and 4, respectively. AtRLM1

was found to share a similarity to a homologous region on chromosome 4 that corresponds to

AtRLM2 indicating that they are closely related and may have evolved through gene duplication

(Staal et al., 2006). AtRLM3 encodes an NBS-LRR and is another candidate that appears to act as a

critical downstream component of AtRlm1 (Meyers et al., 2003, Staal et al., 2006, Staal and

Dixelius, 2008, Staal et al., 2008). Since it has been shown that blackleg resistance genes in B.

napus (LepR1, LmR1, CLmR1, Rlm1, Rlm3, Rlm7 and Rlm9) are mapped to genomic loci that

correspond to the chromosome segment on Arabidopsis chromosome 1 harbouring AtRlm1

(Mayerhofer et al., 2005), it could be hypothesized that L. maculans resistance genes are related to

the NBS-LRR protein family. Also of importance is to study the level of sequence conservation in

blackleg resistance genes in Brassica species and Arabidopsis since little is known about sequence

information of resistance genes identified so far.

According to the most recent study (Raman et al., 2012b), simple sequence repeat (SSR) markers

have been linked to a Rlm4 blackleg resistance QTL region in a segregating population derived

from the B. napus cultivars: Skipton and Ag-Spectrum. This region has been physically mapped to

scaffold 3 on chromosome A7 of the sequenced B. rapa genome. Therefore, it could be

hypothesized Rlm4 and other resistance genes mapped to B. napus chromosome A7 are present on

intervals homologous to the B. rapa chromosome A7 regions with considerable sequence variations

due to gene duplication and recombination events (Figure 1.6).

Taken together, although many studies have identified numerous blackleg disease resistance QTL

and qualitative genes, it is impossible to compare or even use homology searches between these

studies because of different marker systems being used, along with differences in the cultivars used,

blackleg isolates and inoculum concentrations present at each location. Thus, the use of map-based

cloning to identify a gene underlying the QTL region is relatively difficult through map based

cloning because the region is still large and often not tightly linked to the resistance gene(s). This is

often further complicated by the complexity of the genomic region due to duplication and

rearrangement events. As a consequence, it is difficult to determine if these genes are truly different

genes or allelic variants.

17

Figure ‎1.6: Integration the partial genetic map of Rlm4 QTL on chromosome A7 of B. napus

against the physical map of B. rapa. This is by using 12 linked SSR markers (Raman et al., 2012b).

1.9 Introgression of blackleg resistance genes into the B. napus genome: attempts and

challenges

Attempts have been made to transfer blackleg resistance genes in B. napus breeding programs

through interspecific hybridization (Rimmer and van den Berg, 1992, Chèvre et al., 1996). A

resistance gene from B. juncea (later described as Rlm6 by (Chèvre et al., 1997, Chèvre et al., 2008)

as well as the gene, rjLM2 (Saal et al., 2004) were introduced into B. napus. The resistance was

effective at the seedling stage in spring and winter type genetic backgrounds of B. napus against

various L. maculans isolates. However, subsequent transfer from the B genome has been

unsuccessful, presumably due to a low level of homology between the two genomes or lack of

introgression of the B genome genes into B. napus (Salisbury et al., 1995).

The cultivar Surpass 400 was developed as a blackleg resistant cultivar by crossing B. napus and B.

rapa (Crouch et al., 1994). The resistance obtained was assumed to be as a result of introgresion of

the genes LepR1, LepR2 and LepR3 from B. rapa (Yu et al., 2005, Yu et al., 2008). Li and Cowling

(2003) reported a complete resistance to blackleg in ‘Surpass 400’ when tested against Australian

isolates at the time of its release in 2001. However, there are evidences of resistance breakdown in

blackleg resistant varieties in France (Rouxel et al., 2003b, Brun et al., 2010) and Australia

18

(Sprague et al., 2006). The breakdown of the Rlm1 resistance in France occurred within three years

of release due to L. maculans population changes from avirulence (AvrLm1) to virulence

(avrLm1)(Rouxel et al., 2011). In 2001, the cultivar surpass 400 was released commercially and

showed a highly resistant response to blackleg in the field. However, this resistance become

similarly ineffective after only three years due to a rapid increase in the local pathogen populations

of isolates virulent on LepR3 (Li and Cowling, 2003, Rouxel et al., 2003b). There is also evidence

of sequential breakdown of major resistances genes Rlm9, Rlm2 and Rlm4 in France, as well as

Rlm4 in Australia after widespread use of cultivars containing these genes (Rouxel and Balesdent,

2005).

Breeding for B. napus blackleg resistance has faced challenges with respect to the stability and

durability of resistance genes. The loss of resistance stability and rapid breakdown of race specific

genes is most likely associated with a major shift in populations of L. maculans towards altered Avr

composition (Balesdent et al., 2001, Fitt et al., 2006, Sprague et al., 2006).

Crop rotation, of cultivars containing different resistance genes, could be a suitable approach to

maximize the durability and stability of the resistance and minimize the selection pressure on

avirulence isolates to overcome the resistance genes. The rotation is aimed to decrease the incidence

of blackleg through reduced exposure to inoculum and not imposing a selection pressure on the

fungus to rapidly evolve towards virulence.

The breakdown of resistance seen in France in 2000 (Rouxel et al., 2003a) and Australia in 2003

(Sprague et al., 2006) was a result of rapid change of the frequency of virulence alleles of

avirulence genes. The frequency of virulence alleles of avirulence genes changed significantly

depending on the resistance gene present in the cultivar. Hence, rotation provides a way to reduce

the change of the frequency of virulent isolates towards a particular resistance gene upon exposure

to difference complements of resistance genes in the canola cultivars. For example, when a cultivar

with Rlm1 is grown, the frequency of virulence towards Rlm1 will be selected for and increase in

number. However, if a cultivar with Rlm4 is grown the following year, the frequency of virulence

will be shifted towards Rlm4. In this case, rotation of cultivars with different resistance genes

should reduce the selection pressure on fungus isolate to evolve (Marcroft et al., 2012b).

It is recommended that the cultivars containing a different combination of resistance genes be

rotated every four years, in order to minimize selection pressure on the fungus and increase

durability of cultivars (Marcroft et al., 2004). However, it was found that not all resistance genes

can be rotated with each other. For instance, cultivars with Rlm1 resistance should not be rotated

19

with cultivars with Rlm6 resistance (Marcroft et al., 2012b). This is because the selection towards

AvrLm1 in the pathogen also results in increase the frequency of virulence of AvrLm6 as these two

genes are tightly linked in the pathogen genome.

Thus, identification of these resistance genes and understanding of the genetic interaction between

resistance gene and avirulence genes is required for development of specific resistance gene

rotation.

1.10 Genomic approaches for identification of candidate resistance genes

Candidate resistance genes are putatively genes that are essential components of plant immune

systems and can be broadly classified as those potential genes involved in the initial recognition or

interaction with pathogen avirulence gene to trigger a defence response. Quantitative trait locus

(QTL) mapping is frequently used to identify genomic regions associated with a phenotypic trait of

interest. The association of candidate resistance genes or major resistance genes and QTL has been

widely noted (Gebhardt and Valkonen, 2001, Quint et al., 2003, Wisser et al., 2005). The nucleotide

binding site–leucine rich repeat (NBS-LRR) class of R genes has been found to be potential

candidate resistance genes co-localized with disease resistance QTL such as in barley, potato and

apple (Ramalingam et al., 2003, Calenge et al., 2005, Bakker et al., 2011). However, although

numerous disease resistance QTL have been identified, isolating and cloning a gene underlying the

QTL/gene mapped region is relatively difficult through map based cloning because the region is

still large and contains hundreds of genes that often not tightly linked to the resistance gene(s). This

is often further complicated by the complexity of the genomic region due to duplication and

rearrangement events.

An alternative approach, the candidate genes approach was exploited in this project to analyse the

disease resistance QTL using a homology search. One of the major steps in the candidate gene

approach is the physical identification and characterization of QTL region using genomics analysis.

The physical gene mapping determines the gene location and its relative distance to the QTL region

and other adjacent genes on the chromosome. This allows narrowing and prioritizing the number of

associated candidate resistance genes for further sequencing and functional studies. Thus, candidate

resistance gene identification becomes much faster and less expensive for rapid cloning and

sequencing of the gene/s responsible for plant-pathogen interactions.

20

1.10.1 Comparative analysis based candidate gene identification

Genome comparative analysis is a powerful tool for genetic studies to investigate the resistance

gene organisation, conservation and evolution of related species. It allows the study of conserved

genomic segments with gene content, synteny, collinearity and conservation between related

species at the micro-level in selected chromosomal regions such as QTL region or at the macro-

level in the whole genome. Determining orthologous and syntenic genes within genomic regions

among closely related species is important to identify structural or functional similarities/

differences. This also enables the confirmation of potential inversion, insertion, gene

presence/absence and gene sequence homology (Lyons et al., 2008, Tang et al., 2008).

The availability of a reference genome sequence allows the identification of position of the QTL in

the chromosome and prediction of the full complement of genes that encode the resistance gene.

When a QTL of the species under study is located in a syntenic region on its related species, the

resistance genes are likely to be found in a syntenic relationship and show high or divergent

sequence conservation (Paterson et al., 2000, Cheng et al., 2012a).

Several studies have shown aspects of genome evolution and organization between Brassica

genomes and the genome of A. thaliana (Parkin et al., 2005, Cheung et al., 2009, Trick et al., 2009).

The close relationship of the genus Brassica to A. thaliana was exploited in identifying the

candidate gene for a major flowering time QTL in B. nigra (Osterberg et al., 2002) and seed weight

in Brassica napus (Cai et al., 2012). In addition, this strategy has been used to identify blackleg

resistance genes in B. napus (Mayerhofer et al., 2005, Fopa Fomeju et al., 2014) and clubroot

resistance gene in B. rapa (Suwabe et al., 2006, Suwabe et al., 2012).

In the comparative analysis strategy, candidate resistance genes are likely to be structurally and

functionally conserved between related species providing insight into the evolution of these genes.

Therefore, the comparative analysis of the resistance gene sequences not only revealed the level of

conservation but also identified potential target genes showing or associated with disease resistance

QTL.

Candidate genes can be further studied via analysis of gene expression. The level of R genes

expression is regulated to ensure correct resistance responses. They are expressed constitutively at a

very low level which changes slightly following pathogen infection (Graham et al., 2000, Joshi and

Nayak, 2011). However, structurally and functionally conserved R genes are likely to show changes

in expression pattern contributing to the R gene diversity and resistance specificities. These related

R genes with different recognition specificities can be found within or between plant species as

21

single or a multiple alleles recognizing a particular pathogen race. The gene duplication followed by

sequence divergence in polyploid species such as B. napus is a primary mechanism for altering

expression patterns and causing phenotypic variations (Hanada et al., 2009, Wang et al., 2012).

Differential expression levels of orthologous or paralogous NBS-LRR genes reflect the expression

divergence and contribute to functional diversification (Blanc and Wolfe, 2004).

1.10.2 Sequence based candidate gene identification

Next-generation sequencing (NGS) technologies have advanced rapidly in the past few years,

providing the ability to sequence reference genomes as well as re-sequence cultivars of interest

(Duran et al., 2010, Malory et al., 2011). The combination of resistance genes profiling with next-

generation sequencing offers enormous advantages for genetic studies. Re-sequencing is used to

identify genetic variation between individuals, which can provide molecular genetic markers and

insights into gene function (Imelfort et al., 2009). Thus, the increasing use of next-generation

sequencing technologies has impact on disease gene discovery by speeding up the identification of

potentially candidate genes by their probability of being shown disease-relevant mutations.

These NGS strategies produce millions of sequencing reads in a single run, producing large

amounts of short-sequencing reads that are aligned/mapped to a reference genome sequence. This

way, the sequence reads were anchored to comparable sites in the target sequences, which allow the

alignment of the reads directly without the need of a prior assembly step (Batley and Edwards,

2009). Once this has been achieved, it is possible to determine read coverage and variation and

identify and characterise polymorphisms for candidate genes between individuals. Thus, the NGS

reads that mapped to the gene regions of interest can be used to assess complete sequence

divergence between the contrasting genotypes.

The approach was recently utilized to identify a candidate Rlm4 resistance gene. By taking

advantage of the B. rapa reference genome sequence (A genome) and next generation sequence

data (short reads) for B. napus cultivars, including the cultivars Skipton and Ag-Spectrum which

differed in resistance to Rlm4, the putative Rlm4 blackleg resistance genes can be identified among

candidate NBS-LRR genes located within the physically mapped Rlm4 QTL region on chromosome

A7. Preliminary data suggests that duplication and clustering of tightly linked genes in the QTL

region containing R genes on A7 indicate that the cloning of Rlm4 may also identify additional

blackleg resistance genes (Tollenaere et al., 2012) (Figure 1.7).

22

Figure ‎1.7: Sequence based identification of Rlm4 candidate gene using NGS data. Illumina short

reads: Skipton (in red arrows) and Ag-Spectrum (green arrows). Bold line shaded by grey

represents known sequence from Illumina reads (there is sequence coverage) compared with the

reference genome. Whereas, black and blue represent sequence obtained from PCR amplification

and sequencing.

1.10.3 SNP genotyping and association with candidate genes

A single nucleotide polymorphism (SNP) is a single base pair change in genomic DNA and the

most abundant type of DNA sequence variation in plant genomes. They are found in high density

across plant species. SNP variation between different alleles in contrasting genotypes has a direct

association with disease resistance and susceptibility (Heffner et al., 2009). In the model plant

Arabidopsis, more than 37,000 SNPs have been identified between the ecotypes Columbia (Col)

and Landsberg erecta (Ler) providing essential elements for a genotyping assay (Jander et al.,

2002). SNPs are invaluable genetic markers for developing genetic maps and genotyping

populations for QTL mapping and association mapping of important agricultural traits. In cases

where SNPs in genic regions have a significant change in amino acid causing the altered phenotype,

23

these SNPs are known as perfect markers. In B. napus, existing genomic resources for SNP

discovery and the ability to associate SNPs variation with particular traits creates an efficient

approach for gene identification (Westermeier et al., 2009, Edwards and Batley, 2010).

Genotyping is the process of identifying polymorphism between individuals in a genome or

genomic region. SNP genotyping has become extremely important to study the distribution of SNPs

and the relationship between SNPs and phenotypic variation in a populations (Syvanen, 2005). SNP

genotyping currently has many applications in plant genomics: identification of candidate resistance

genes, haplotype determination, quantitative trait loci (QTL) mapping, association mapping and

comparative genomics. SNP genotyping can be further used for the positional cloning of the

candidate gene underlying QTL and as a diagnostic marker (Kaur et al., 2012).

Genome wide association of SNPs and their correlation to a segregating population would

significantly identify regions that are associated with a particular phenotype gene (Rafalski, 2002).

The identification of SNPs for specific candidate genes might provide a direct correlation of allele

function with specific trait variation. Thus, SNP genotyping technologies provide an effective

approach for fine genetic mapping narrowing QTL region and its association with disease and

susceptibility. They are now routinely used to identify loci that are associated with many complex

traits (McCarthy et al., 2008).

The identification of candidate genes for flowering time in Brassica using EST-based SNP markers

has been possible (Li et al., 2009). There are many successful examples of identification of closely

linked SNP markers underlying QTL region to enhance resolution within the target locus and

narrow the number of candidate genes. For example, in rice, a number of SNPs had been

functionally associated with variation for the yield (Yu et al., 2011a). In soybean, SNP genotyping

improved narrowing the QTL for the aphid resistance gene, Rag1 with two linked SNP markers

and additional candidate genes were identified (Kim et al., 2010).

SNP genotyping involves selecting very large numbers of SNP markers, precisely located on a

genome, for detection of alleles and their association with a phenotype. Then, SNPs within the QTL

of interest are physically mapped to the reference genome and the genotypic data is compared

across different species, cultivars or segregating lines. Ultimately, a group of SNPs located within

the functional gene or at a small physical distance from the gene will be associated and identified.

This strategy provides a good solution to the problems associated with positional cloning and

physical mapping.

24

High-throughput genotyping assays (Infinium assay ) developed by Illumina have proven successful

and efficient for many crops (Chagné et al., 2007, Kaur et al., 2012) and could serve as the platform

of choice for SNP validation as well as for genotyping large populations (Durstewitz et al., 2010,

Hu et al., 2012)

The Infinium assay is a whole genome SNP genotyping assay which is capable of multiplexing

from 3,000 up to 1 million SNPs across a large number of individuals. It enables large-scale

analysis spanning the entire genome offering an ideal method to narrow down candidate

polymorphic SNPs for the whole genome. The Infinium assay develops BeadChips with customized

SNP content enabling virtually unlimited multiplexing in SNP genotyping. These BeadChips are

commercially available with a variable number of fixed or custom SNPs. Illumina BeadChips can

process up to 24 samples simultaneously, with four able to be processed at once, providing high

genome coverage, array efficiency and genotype call accuracy. Each SNP locus is assayed and

analysed independently for each sample yielding highly intensity genotype calls (Illumina,

www.illumina.com).

The Infinium assay consists of four steps (Figure 1.8), a whole-genome amplification and

fragmentation step, hybridisation to immobilised SNP-specific primers on BeadChips, followed by

single base extension with labelled nucleotides. The primers hybridise adjacent to the SNP and are

extended with a single fluorescently labelled dideoxynucleotide corresponding to the SNP allele.

The intensities of the bead’s fluorescence are detected by the iScan Reader (Illumina) to generate

the genotype calls (Illumina, www.illumina.com).

Allelic discrimination occurs through single-base primer extension reactions using a two-colour

assay. Data consists of two intensity values (X, Y) for each SNP, with intensity for each one of the

fluorescent dyes associated with the two alleles of the SNP. After normalization, the alleles

measured by the X colour are called the A alleles, whereas the alleles measured by the Y colour are

called the B alleles. Then, clustering and GeneCall (call rate) algorithms are used to determine the

genotype call depending on the clustering of tested samples at each SNP locus (Illumina,

www.illumina.com).

http://www.illumina.com/



25

Figure ‎1.8: The principles of whole genome genotyping using the Illumina infinium assay.

modified from (Gunderson et al., 2006).

The availability of the Brassica A genome sequence (Wang et al., 2011) and NGS has made it

possible to develop high density SNP arrays the Illumina Infinium™ platform for Brassica

(Appleby et al., 2009). B. napus 6K Infinium™ chip comprised of 5306 of SNPs marker was

developed and was applied to genotype B. napus cultivars and mapping populations. The results

showed that the SNPs assay was successful with > 94% of these producing a reproducible,

polymorphic SNP alleles (Dalton-Morgan et al., 2014). The 6K chip was also used to genotype a

doubled haploid population derived from a cross between B. napus Skipton and Ag-Spectrum for

Rlm4 blackleg resistance association (Raman et al., 2014). The QTL analysis revealed the location

of Rlm4 locus was consistent with previous studies (Raman et al., 2012b, Tollenaere et al., 2012). A

number of SNP markers were identified linked to the Rlm4 locus. In this project, a 60K chip was

used to study the association to Rlm9 blackleg resistance in B. napus Darmor.

26

1.11 Research aims and significance

In order to understand disease resistance in Brassicas, the identification and characterization of

NBS-LRR genes in Brassica is important to provide comprehensive analysis into the resistance

genetics and genomic structure of NBS-LRR in Brassica species and disease resistance gene

conservation and evolution. Thus, the identification of NBS-LRR genes further leads to

identification and validation of potential sources of resistance genes involved in blackleg disease

resistance or other diseases in Brassica. In this project, the utilization and integration of the

information of genomics resources such as availability of Brassica genome sequences, NGS data,

SNP genotyping and QTL genetic maps are the foundation for identification of a candidate NBS-

LRR gene linked to disease traits allowing rapid cloning of functional resistance genes (Figure 1.9).

My primary motivation for the present study was to address the need for genome wide NBS-LRR

gene identification and characterization to identify candidate resistance genes within disease

resistance QTL interval. In particular, the identification of candidate Rlm9 blackleg resistance genes

in B. napus because B. napus cv. Darmor, which contains the Rlm9 resistance gene, was used as the

reference for B. napus genome sequencing.

The genetic studies have mapped all the resistance genes for the devastating pathogen

Leptosphaeria maculans to the A genome with none mapped to the C genome in Brassica species.

Thus, the blackleg resistance genes should be retained and conserved in the A genome of B. napus

and B. rapa, whereas, they are probably absent or highly divergent in the C genome of B. napus and

B. oleracea. By characterizing and comparing these NBS-LRR genes in these species, it would be

possible to identify candidate blackleg resistance genes and assess their genetic diversity between

Brassica species.

The primary objectives are:

1- A comprehensive study of NBS-LRR genes can be undertaken to provide new insights into

the genetic diversity of the R genes in Brassica species and to understand the genomic

architecture of this gene family. This involves identification and characterization of

candidate NBS-LRR genes and determines their distribution, domain structure, gene

clustering and duplication. Thus, the advances in Brassica genome sequencing enable

identification of large number of disease resistance genes and their characterization and

evolutionary relationships.

2- Comparative analysis of NBS-LRR genes between B. napus compared to B. rapa and B.

oleracea. The identification of candidate genes in Brassica species and studying the genome

27

organization and genetic diversity through comparative genomics will help to understand

NBS-LRR conservation and evolution. The better understanding of the syntenic structure of

NBS-LRR genes in ancestral genomes is required to study the genomic rearrangements such

as duplication and translocation within the B. napus genome that have occurred during

evolution. Previously, mapping and comparative studies have demonstrated that Brassica

species had undergone genome duplications and rearrangements. It would be interesting to

find how NBS LRR genes have been affected by the genome duplication and rearrangement

events in Brassica.

3- Study the correlation or association between a given diseases QTL regions and the candidate

NBS-LRR genes. This would allow identification of the physical location of QTL regions

into genome chromosomal maps and association of the QTL intervals with the genome wide

identification of disease resistance NBS LRR genes.

4- To identify candidate gene(s) for blackleg resistance in B. napus using all available

genomics resources such as QTL mapping, comparative studies and SNP genotyping. It

should be possible to tighten the QTL region and further narrow the list of candidate genes.

Then, the potential candidate resistance genes are to be identified and further subject to

sequence comparison studies.

This project is the first to conduct comprehensive analysis of NBS- LRR genes in the B. napus

genome and present comparative analysis of NBS-LRR genes between B. napus and its progenitor

species: B. rapa and B. oleracea. It will also enable identification of a large number of resistance

genes in Brassica species. In addition, the project will enrich the Brassica database with resistance

genes for several disease resistance traits, in particular, blackleg disease. The identification of

blackleg resistance genes in Brassica will provide some understanding of the key molecular

components of disease and enhance development and breeding of resistant varieties of B. napus.

28

Figure ‎1.9: Schematic representation of genomics based identification of candidate resistance gene(s) used in this study.

29

Chapter 2

Genome wide identification and

characterization of NBS-LRR

resistance genes in Brassica napus

30

Chapter 2 : Genome wide identification and characterization of NBS-LRR

resistance genes in Brassica napus

*This chapter contributed towards a paper being submitted

2.1 Abstract

Plant disease resistance genes play a critical role in providing resistance against pathogens. The

largest family of resistance genes are the nucleotide binding site (NBS) and leucine rich repeat

(LRR) genes. They are classified into two major subfamilies, TIR-NBS-LRR (TNL) proteins and

CC-NBS-LRR (CNL) proteins. The availability of the genome sequence of Brassica napus provides

an important resource to study the NBS-LRR structure and genomic organization.

This chapter presents a comprehensive overview of the genome wide NBS-LRR identification and

gene diversity in B. napus. A total of 641 NBS-LRR genes were identified in B. napus comprising

of a ratio of 1:2 of TNL to CNL genes. Further domain structure analysis revealed that 60% of the

NBS LRR genes are typical resistance gene with all three domains and the remaining are partially

deleted or truncated. Fifty nine percent of the NBS-LRR genes were found to be physically

clustered and individual genes involved in clusters were more polymorphic and subject to

evolutionary selection pressure. Fifty percent of the total NBS-LRR genes in B. napus were

identified as duplicates, suggesting a high level of genomic duplication and rearrangement.

This chapter provides a valuable resource for identification and association of candidate NBS-LRR

genes linked to disease resistance QTL allowing rapid cloning of functional NBS-LRR genes and

understanding the functional diversity.

31

2.2 Introduction

Plant disease resistance genes (R genes) are important components of the genetic resistance defence

mechanisms in plants. R genes are involved in a direct or indirect interaction with avirulence (Avr)

genes in order to trigger a defence response. Thus, understanding the molecular structure and

function of R genes has been crucial for plant resistance research. Genome sequencing efforts of

plant species have facilitated genome wide analysis of NBS-LRR genes in many plant species. For

examples, 438 genes in potato (Jupe et al., 2012), 535 genes in rice (Zhou et al., 2004), 333 genes in

Medicago truncatula (Ameline-Torregrosa et al., 2008), 402 genes in Populus trichocarpa (Kohler

et al., 2008), 221 genes in sorghum (Paterson et al., 2009), 167 genes in Arabidopsis (Yu et al.,

2014) and 355 genes in cotton (Wei et al., 2013). These studies showed that the NBS-LRR class of

genes is abundant and widely distributed throughout the genome. Moreover, genetic and genomics

studies demonstrated that the majority of NSB-LRR genes are present in gene clusters in plant

genomes (Hulbert et al., 2001). The clustered arrangement of these genes may be a critical attribute

of the generation of novel resistance specificities via gene duplication or recombination (Meyers et

al., 2003).

Sequence analyses revealed that NBS domains share a high degree of homology and have a number

of conserved motifs (Wan et al., 2012). To date, eight conserved motifs have been identified in the

NBS domains of NBS LRR classes including P-loop, kinase-2, kinase-3a, GLPL, RNBS-A-TIR,

RNBS-D-TIR, RNBS-A-non-TIR and RNBS-D-non-TIR (Wan et al., 2013). The conserved motifs

of NBS domains assist in cloning NBS-LRR genes via PCR amplification, alignment for

phylogenetic analyses and classification of NBS-LRR genes (Meyers et al., 2003).

The NBS-LRR proteins contain three domains: a NBS domain, a C-terminal LRR domain and an

N-terminal domain of either Toll Interleukin-1 receptor (TIR) or a coiled coil (CC). The NBS-LRR

genes can be subdivided into two distinct types based on the structure of their N-terminal domain:

either a coiled-coil (CC) motif or a Toll Interleukin-1 Receptor (TIR) domain (Meyers et al., 2003).

These form the two major subfamilies of plant NBS-LRR proteins: TIR-NBS-LRR proteins (TNLs)

and CC-NBS-LRR proteins (CNLs). The TNL group of genes has been observed only in dicot plant

species (Meyers et al., 1999, Goff et al., 2002). Whereas, CNLs (sometimes called non-TNL) are

found in both dicot and monocot plant species. Both families are involved in defence mechanisms

against pathogens in different signalling pathways. They are distinct in their NBS conserved

sequence motifs and therefore are found in separate clusters in phylogenetic analyses (McHale et

al., 2006).

32

A comprehensive study of NBS-LRR genes was undertaken to provide new insights into the genetic

diversity of the resistance genes in Brassica species and to understand the genomic architecture of

this gene family. This study is the first to conduct genome wide identification of NBS-LRR genes in

the B. napus genome (Chalhoub et al., 2014).

The main objective of this chapter is to identify NBS-LRR genes, characterize the functional

domain and motifs, and determine the distribution of NBS-LRR genes on the B. napus

chromosomes. It also aims to study the conservation, gene clustering and duplication of the NBS-

LRR genes. As a result, this will provide a valuable resource for identification of candidate NBS

LRR genes linked to disease traits allowing rapid cloning of functional NBS LRR genes.

33

2.3 Methods

2.3.1 Brassica genome and gene prediction

The genome sequence and gene annotation of B. napus cv. Darmor was used as the reference

genome for genomic studies on B. napus (Chalhoub et al., 2014).

2.3.2 Identification of NBS-LRR genes in B. napus by MEME/ MAST analysis

The MAST/MEME (Motif Alignment Search Tool/Multiple Em for Motif Elicitation) suite of

software was used to identify predicted genes that contain motif homology to known disease

resistance genes (Bailey et al., 2009). NBS-LRR “positive” and non NBS-LRR “negative” sequence

training sets which were consensus of 20 amino acid motifs derived from MEME analysis (Jupe et

al., 2012) were used as queries in a MAST search against the predicted genes of the B. napus

genome. Predicted genes were considered to be candidate CNL or TNL if the reported MAST E-

value were ≤ E-24

.

2.3.3 Identification of NBS-LRR genes in B. napus by CNLs and TNLs for validation

To further validate the results from the MAST output, consensus sequences of plant CNLs and

TNLs (Cannon et al., 2002, Cannon et al., 2004) were obtained from a previous study (Ameline-

Torregrosa et al., 2008). Candidate genes containing NBS domains were identified using tBLASTn

and BLASTp (maximum E-value 1E-5) (Altschul et al., 1997) performed using the consensus

sequences below against the B. napus cv. Darmor genome. Candidate NBS-LRR proteins were

provisionally assigned to either the CNL or TNL groups on the basis of similarity.

Consensus of CNLs used for BLAST search was as follows:

erpsestiVGletmleklwnrLledndvgivgiyGMGGVGKTTLatqifNdfdvkgehFdrviWVvVSkefnvekiqqdIl

ekLglgdeewlekteeekaaeienLfqlLegKkfLLvLDDvWekevdLdkigvpfPdrenGsKvlfTTRsesvavcgdmgv

dxmevecLtpeeAWeLFqkkvfentlksdpeieelaKevvkkCgGLPLAlkVlGgllacKrtvqEWkraievlssslaaefsg

messilpvLklSYdnLppelKsCFLYcalFPEDykIekekLieyWiaEGfideseggetaedvGyeylgeLVrrsLleegdk

tdnetsrketVkMHDvvREmALwiaseegfkeviiVraGvglreipnvkswntvrRmSlmnneieelldspenpklrsLltlllq

snsh.

Consensus of TNLs used for BLAST search was as follows:

RDFddlVGiEaHlekmksLLcLdsdeVrMVGIwGPaGIGKTTIARALfsqLSssFqlsaFmenlrgsyStrpaglD

eYsmKLhLQeqfLSkILnqkDikIhHLGvieERLkdqKVLIiLDDVDdleQLdALAketqWFGpGSRIIVT

TeDkqLLkaHgInhIYeVgfPSkeeALqIFCrsAFgQnsPpdGFeeLAreVtkLaGnLPLGLrVlGSsLRGkske

eWedmLpRLrtsLDgkIekvLrvsYDgLhekDqaLFLhIACfFNgekvdyVkalLadsnLDVrqGLkvLadKSLI

hisplgdgtieMHnLLqqLGReIVrkQsidePgKRqFLvDaeeIcdVLtdnTGtgsVlGIslDtseieeelnIsekAFeg

MrNLqFLriykksfrddgk.

34

2.3.4 Correlation between the MAST output and CNL/TNL BLAST results

The NBS-LRR candidate genes identified from the MAST output were compared with CNL and

TNL BLAST results to validate the NBS LRR genes and to classify them according to the BLAST

similarity to either the CNL or TNL groups. Furthermore, any candidate NBS-LRR that did not

correlate between the two approaches was subject to further search against NCBI non-redundant

nucleotide database.

2.3.5 Manual annotation check and characterization of candidate NBS-LRR genes

The annotation of all identified NBS-LRR gene were manually checked using gene prediction

programs to obtain information on complete open reading frames (ORFs). Every individual gene

sequence was manually annotated and the annotation compared between all gene prediction

programs. The prediction programs used were FGENSH (http://www.softberry.com), Genscan

(http://genes.mit.edu/GENSCAN.html) and AUGUSTUS (http://bioinf.uni-

greifswald.de/augustus/).

All predicted NBS-LRR genes were surveyed to further determine their domain structure and

whether they contained TIR, CC, NBS, and/or LRR motifs. The predicted genes were searched for

similarity to known proteins using BLASTp (Altschul et al., 1997) with a threshold of E-value < -

10 against the NCBI non-redundant (nr) protein database. The structural information on protein

domains was used to classify the NBS-LRR genes into subfamilies.

2.3.6 Multiple alignment and phylogenetic analysis

Alignment and phylogenetic analyses were performed with all NBS-LRR proteins. The NBS region

was defined as the region extending from the P-loop to the MHDV motif, which contains about 300

amino acids, using the corresponding conserved motifs from B. rapa (Mun et al., 2009).

To extract the NBS domain, CNL and TNL consensus sequences were aligned with NBS-LRR

genes using alignment in Geneious Pro v6.1.2 (Kearse et al., 2012) and then the NBS domain

manually extracted from the P loop motif to the MHDV motif or in case there is a missing motif,

the NBS domain extracted to get other internal motifs. In addition, a search comparison in NCBI

non-redundant (nr) protein database was used to extract the NBS domain and also to determine the

type and length of NBS motifs within the NBS domain.

http://www.softberry.com/

http://genes.mit.edu/GENSCAN.html

http://bioinf.uni-greifswald.de/augustus/

http://bioinf.uni-greifswald.de/augustus/

35

Genes with ≤ 50% of total NBS domain length, such as genes with partial NBS domains with length

less than 150 aa or genes lacking NBS domains such as TIR genes, TIR-LRR genes and linker LRR

genes were excluded from phylogenetic analysis.

The NBS sequences were then aligned using CLUSTAL W (Thompson et al., 1994). A

phylogenetic tree was constructed using the neighbour-joining method (Saitou and Nei, 1987) with

bootstrap multiple alignment resampling set at 1000. These functions were performed using

Molecular Evolutionary Genetics Analysis (MEGA) software version 6.0 (Tamura et al., 2013).

2.3.7 NBS-LRR genes cluster and duplication analyses

NBS-LRR gene clusters were determined by their physical position on each chromosome according

to criteria previously published and widely used (Holub, 2001, Richly et al., 2002, Meyers et al.,

2003). The parameter to define a cluster was three or more NBS-LRR genes that occurred within a

maximum of eight non-NBS genes. Furthermore, the distance between neighbouring NBS-LRRs

was required to be ≤ 200 kb.

Gene duplication was defined in accordance with the criteria previously published and widely used

(Zhou et al., 2004): (1) the alignment covered more than 70% of the longer gene, and (2) the

aligned region had an identity >70%. A block of duplications was defined if more than one gene in

a gene cluster was involved in the duplication. Homologous or paralogous genes were confirmed by

the BLASTp comparison of all the predicted NBS-LRR proteins against each other with E-value of

E-20. This stringent E-value of E-20 was used to ensure the correct definition of singleton genes as

those having only one copy in the genome.

36

2.4 Results

2.4.1 Genome wide identification of B. napus NBS-LRR genes

The genome wide identification of NBS-LRR resistance genes has become an essential component

for better understanding of the genomics and evolution of R genes and resistance genetics. This

study is the first to perform comprehensive analysis on identification and characterization of NBS-

LRR genes in the B. napus genome taking advantages of the recent sequence completion of the

genome. Two methods were used to identify candidate NBS-LRR genes: MEME/MAST analysis

and CNL and TNL consensus sequences. MEME was used in combination with a positive sequence

set of characterised NBS-LRR protein sequences, from diverse plant species, and a negative

sequence set, containing diverse nucleotide binding protein sequences, to create a list of 20

sequence motifs putatively characteristic of NBS-LRR proteins which were then used as queries in

a MAST search against the predicted genes of the B. napus genome. Subsequently, predicted genes

were considered to be candidate CC or TIR NBS LRRs if the reported MAST E-value were ≤ E-24

.

In addition, candidate genes containing NBS domains were identified based on a BLASTp and

tBLASTn search of CNL and TNL consensus sequences as a query at a cut-off value of E -5 to

ensure that there were no other related genes missing from the gene prediction.

The initial classification of candidate NBS-LRR genes into CNLs or TNLs were mostly based on

CNL/TNL consensus BLAST results, as well as taking into account the presence of the TIR domain

motifs among motifs composition in the MAST output. However, the MEME/MAST analysis was

found to be highly dependent on the gene prediction. If the gene prediction is very accurate, an

improved output is obtained. For instance, the MAST E-value could drop down below the cut off

due to the gene annotation splitting one gene into multiple small genes. Furthermore, manual

checking of gene annotation revealed some inaccuracies and there were some genes with predicted

amino acid sequence that was still not complete due to sequence errors leading to insertion of false

introns or false start or stop codons. These were mainly the genes in the MAST output with E-value

close to the cut off E-24. Therefore, in our analysis, less stringent criteria was applied in order to

avoid underestimation of the total number of NBS-LRR genes in B. napus.

Furthermore, an essential component of our analysis was the manual re-annotation of individual

NBS-LRR genes that had been partially mis-annotated during the automated annotation process due

to minor errors such as incorrect start codon predictions, splicing errors, missed or extra exons,

fused genes or split genes. This step assisted to obtain reliable downstream analysis in domain

structure phylogenetic relation and to define gene duplications.

37

In total, 641 candidate NBS-LRR genes were identified in B. napus consisting of 615 genes from

the MAST output with reported E-value less -24 plus additional genes identified from consensus

sequences of TNL and CNL (Table 2.1). Approximately 80% of the identified NBS-LRR genes

were identified by both two methods (Table 2.1).

Table ‎2.1: The total number of predicted NBS-LRR genes identified in the B. napus genome. The

comparison between methods used: MEME / MAST and CNL and TNL BLAST

Initial analysis using BLAST searches for a number of genes that were not correlated between the

two methods showed that most of them were likely to be pseudogenes. They had very strong

identity with other full NBS protein but their sequence was truncated by either a premature stop

codon or a frameshift mutation causing them to fall under the level of significance of MAST or

CNL/TNL analysis.

In order to examine the motif compositions in the CNLs and TNLs they were subjected to domain

and motif analyses using the program MEME/MAST. The 20 putative conserved motifs were found

among them as shown in Table 2.2 and Figure 2.1. It can be seen that the 20 major motifs and

particularly eight motifs in the NBS domain have distinct patterns depending on whether they are

present in the TNL or CNL groups. They also differed in their divergence within and between the

CNL and TNL groups.

Species B. napus

Genome size (Mbp) 1284

Gene content 111,479

Total candidate NBS-LRR genes 641

Proportion of NBS-LRR genes 0.58%

Identified in MAST output 615

Common to MAST and CNL/TNL analysis 509

Not common to MAST and CNL/TNL analysis 136

Agreement % 79%

38

Table ‎2.2: NBS-LRR specific motifs sequence identified with MEME/MAST.

Motif No. Length

(bp) Motif domain

Group or class

Motif sequence

1 21 P-loop kinase 1 NB-ARC CNL/TNL PIWGMGGVGKTTLARAVYNDP

2 21 GLPL NB-ARC CNL/TNL CGGLPLAIKVWGGMLAGKQKT

3 15 Kinase 2 NB-ARC CNL/TNL YLVVLDDVWDTDQWD

4 15 RNBS-B NB-ARC CNL/TNL GSRIIITTRNKHVAN

5 15 RNBS-D NB-ARC CNL LKPCFLYCAIFPEDY

6 21 MHDV NB-ARC CNL/TNL CRMHDMMHDMCWYKAREQNFV

7 15 RNBS-A NB-ARC CNL HFDCRAWVCVSQQYD

8 21 -- Linker CNL/TNL MEDVGEYYFNELINRSMFQPI

9 21 LRR LRR CNL/TNL LIHLRYLNLSGTNIKHLPASI

10 19 RNBA-C NB-ARC CNL/TNL YHMQFLSHEESWQLFHKHA

11 19 LRR LRR CNL/TNL MPNLETLDIRNCPNLEEIP

12 21 -- Pre-NB CNL IDRNKLIWLWMAEGFVPHENG

13 15 -- NB-ARC CNL/TNL NEIMPILRLSYHHLP

14 25 TIR 3 TIR TNL QIVIPIFYDVDPSDVRHQTGSFGEA

15 17 -- Pre-NB CNL DAAYDAEDVIDSFKYHA

16 50 -- Monocot -- AIKDIQEQLQKVADRRDRNKVFVPHPTRPIAIDPCLRALYAEATELVGIY

17 21` TIR 2 TIR TNL KNYATSRWCLNELVKIMECKE

18 50 EDVID Monocot CNL ETSSFELMDLLGERWVPPVHLREFKSFMPSQLSALRGWIQRDPSHLSNLS

19 27 LRR LRR -- FLDIACFFRGRKKDYVMQILESCDFGA

20 21 TIR 1 TIR TNL KYDVFLSFRGPDTRKTFTSHL

39

Figure ‎2.1: Example of representation of motif patterns in NBS-LRR genes in B. napus. The different coloured boxes indicated distinct motifs

as shown in boxes below identified by MEME/MAST program. Refer to Table 2.2 for the type of each motif.

40

2.4.2 Genomic distribution and organisation of NBS-LRR encoding genes in the B. napus

genome

To find the distribution of NBS-LRR genes in the B. napus genome, the genes were plotted on a

chromosomal map based on their physical position in the genome. The NSB-LRR genes were found

to be distributed randomly and unevenly across the genome. The TNLs and CNLs are present on all

19 chromosomes in B. napus. However, TNL genes are more widely distributed across the B. napus

chromosomes (Figures 2.2 and 2.3).

The comparison of the total number of NBS-LRRs and whether they were classified as TNLs or

CNLs in both A and C genomes showed that there was a predominant presence of TNLs over CNLs

with about 70% of the genes comprising TNLs. This represents a ratio of 1:2.5 of CNLs to TNLs

(Table 2.3).

Approximately 40% of the NBS-LRR genes in the A genome of B. napus are located on

chromosomes A9 and A2 harbouring 58 and 44 genes, respectively. The chromosomes A5 and A10

contain the lowest number of NBS-LRR genes in the A genome (Figure 2.2). In the C genome,

chromosome C9 has the highest number of NBS-LRR genes followed by chromosome C3 (Figure

2.3).

All predicted NBS-LRR genes were surveyed to further determine their domain structure order to

classify these NBS genes with their predicted domains into subfamilies accordingly. The analysis of

the 641 candidate NBS-LRR genes against the non-redundant protein database and MEME/MAST

identified 366 (57%) genes were typical or regular NBS-LRR genes: 124 CNLs and 242 TNLs

(Table 2.4). These 366 genes show highly conserved NBS regions and complete open reading

frames. The remaining 188 genes (29%) were classified as non–regular genes because of the lack of

specific domains. These genes were classified into three distinct groups for TNL and CNL. Non-

regular TNLs were TN (74), N (9) and NL (43). Non-regular CNLs were classified as: CN (24), N

(8) and NL (23). These non-regular genes were described as partial or truncated within the N-

terminal domains and/or absence of LRR domains. In addition, 87 TIR genes which lack both NBS

and LRR domain were also identified in B. napus.

Furthermore, 75 NBS-LRR genes (44 CNL and 31 TNL (21 TIR + 10 TNL) are encoded by a single

reading frame without introns (single exon). The average number of exons in the total NBS-LRR is

4 exons where the average in CNLs is 3 exons, which was lower than that in TNLs which have an

average of 5 exons.

41

Table ‎2.3: The distribution and organisation of candidate NBS-LRR genes in B. napus

Ch

rom

oso

me

Tota

l

TNL

CN

L

No

. of

gen

e

clu

ste

r

No

. of

gen

e in

clu

ste

rs

No

. of

du

plic

ate

d

gen

es

(TN

L+C

NL)

No

. of

du

plic

ate

d

gen

es in

cl

ust

ers

A g

eno

me

B. n

ap

us

Dar

mo

r

A1 28 17 11 2 7 18(10+8) 4

A2 44 33 11 5 31 22(20+2) 15

A3 24 20 4 5 18 16(13+3) 6

A4 13 12 1 1 7 5(5+0) 3

A5 10 4 6 1 4 9(3+6) 5

A6 21 7 14 2 6 16(5+11) 5

A7 19 16 3 2 10 14(14+0) 8

A8 24 17 7 3 12 13(9+4) 3

A9 58 38 20 10 43 38(23+5) 24

A10 11 7 4 0 0 6(4+2) 0

Total 252 171 81 31 138

(54%) 157 (106+51)

(62%) 73 (28%)

C g

en

om

e B

. na

pu

s D

arm

or

C1 37 24 13 3 21 16(9+7) 10

C2 51 47 4 5 34 21(18+3) 13

C3 56 46 10 7 35 20(14+6) 12

C4 18 12 6 1 4 5(3+2) 2

C5 19 11 8 4 13 13(8+5) 7

C6 44 33 11 4 30 28(20+8) 17

C7 38 30 8 5 25 14(10+4) 8

C8 39 21 18 4 23 19(9+10) 11

C9 79 62 17 8 55 26(19+7) 18

Total 381 286 95 41 240

(62%) 162 (110+52)

(42%) 98 (25%)

Un assigned

8 4 4 0 0 0 0

Total 641 461 180 72 378

(59%) 319

(50%) 171

(53%)

42

Figure ‎2.2: Physical locations of NBS-LRR genes on the chromosome of the A genome of B. napus. Closed circles and triangles above and below

each chromosome (grey bars) with different colour system are designated for class: TNL and CNL, and their subfamily. The black straight line

connecting the NBS-LRR genes represents tandemly duplicated genes. Genes inside red rectangles represent homogenous cluster, whereas the blue

rectangles represent heterogeneous cluster. Numbers above the rectangles represent cluster size in kbp. Chromosome lengths are shown in megabase

pairs on the scale at top.

43

Figure ‎2.3: Physical locations of NBS-LRR genes on the chromosome of the C genome of B. napus. Closed circles and triangles above and below

each chromosome (grey bars) with different colour system are designated for class: TNL and CNL, and their subfamily. The black straight line

connecting the NBS-LRR genes represents tandemly duplicated genes. Genes inside red rectangles represent homogenous cluster, whereas the blue

rectangles represent heterogeneous cluster. Numbers above the rectangles represent cluster size in kbp. Chromosome lengths are shown in megabase

pairs on the scale at top.

44

Table ‎2.4: The number of NBS-LRR genes classified into different classes and their subfamilies

and domain compositions

2.4.3 NBS-LRR gene clustering

The gene cluster was defined as a cluster of three or more NBS-LRR genes located within the 200

kb or the presence of no more than eight non- NBS-LRR genes between the two adjacent NBS-LRR

genes. Using these parameters, 59% (378) of the total NBS-LRR genes identified in B. napus reside

in a gene cluster and are unevenly distributed over the chromosomes. Interestingly, the A and C

sub-genome in B. napus exhibited similar patterns of gene clustering. Moreover, some of these

NBS-LRR genes are located closely to clustered genes or even create a rich region of NBS-LRR

genes. A total of 72 clusters were observed in B. napus where the highest number was 10 clusters

found in A9 followed by 8 clusters in C9 and 7 clusters in C3 (Figures 2.2 and 2.3). The

chromosome A10 does not have any NBS-LRR clusters. The highest gene number in a cluster was

found in C6 and C9 with 11 genes followed by 10 genes in C9 and 9 genes in A2. The average

number of genes in a cluster was 5 genes where the average in the A genome (average 4 genes) was

found to be smaller than in the C genome (average 6 genes). With respect to TNLs and CNLs

clustering, there were more TNL clusters (23 clusters across the A genomes and 28 clusters on the

C genome) than CNL clusters (6 clusters on the A genome and 8 clusters on the C genome).

Although CNLs are rarely mixed with TNL genes, there are two mixed clusters of TNLs and CNLs

in the A genome and 6 mixed clusters in the C genome.

In addition, cluster size was determined by the sequence length between the two NBS-LRR located

on both side of the gene cluster. The cluster size varied in the A genome between 10 kbp (cluster in

A8) and 488 kbp (cluster in A9) (Figure 2.2). For the C genome, the cluster size varied between

14kbp (cluster in C8) and 837kbp (cluster in C9) (Figure 2.3).

When combining phylogenetic analyses and physical clustering of NBS-LRR genes, out of the total

72 clusters, 32 clusters were located in monophyletic clades and shared recent common ancestor.

CNL 180 TNL 461 Total 641

CNL - NBS - LRR 124 TIR - NBS - LRR 242 Regular

NBS-LRR gene 366(57%)

NBS - LRR 23 NBS - LRR 43

None Regular

NBS-LRR gene 188(29%)

NBS 8 NBS 9

CC - NBS 24 TIR - NBS 74

LINKER-LRR 1 LINKER-LRR 3

TIR - LRR 3

TIR 87 87(14%)

45

These clusters were considered to be homogeneous (highly similar to other NBS genes in the same

genomic cluster). The remaining 40 clusters are heterogeneous, as they contained more distantly

related NBS-LRR genes.

2.4.4 Alignment and phylogenetic analysis

To assess the sequence diversity and evolutionary relationships among the predicted NBS-LRR

genes, a phylogenetic tree was estimated from the protein alignment of the conserved NBS

domains. NBS sequences were used because they are present in both CNL and TNL proteins and

contain numerous conserved motifs that assist proper alignment. The alignment and phylogenetic

analysis of 176 CNL genes and 366 TNL genes were performed separately to identify the similarity

and relationship between genes. There were many genes excluded from the analysis due to more

than 50% deletion in the NBS domain or lack of an NBS domain, such as TIR genes. The multiple

alignments showed that the eight major motifs differed in their conserved residue and there was

divergence between TNLs and CNLs (Table 2.5).

Two phylogenetic trees were constructed separately using a neighbour-joining (NJ) method from

NBS sequences of CNLs and TNLs (CNL, Figure 2.4 and TNL, Figure 2.5). Bootstrap values

(1000 replicates) were used as a tree reliability test to estimate the confidence for each branch point.

From the values obtained in the bootstrap analysis, it was apparent that most of tree branches had a

value of more than 50% confidence. There were branches with low bootstrap scores in which it

does not necessarily indicate unreliable branching, but low confidence of assigning a particular

group.

The analysis revealed different evolutionary patterns of CNL and TNL genes. The phylogenetic

trees were divided into clades on the basis of clade rooting. This resulted in 16 clades for CNLs and

20 clades for TNLs (Figures 2.4 and 2.5).

The phylogenetic trees of TNLs and CNLs with their chromosome of origin provide a relationship

between genes from homeologous chromosome. Therefore, the TNL genes located in the

homeologous chromosomes of B. napus sub-genomes were likely found in the same clade. For

example, TNLs on chromosome A7 are often present in the same clade as TNLs on chromosome

C6 (Figure 2.5). There were 26 TNLs on chromosome C6 located next to 14 TNLs on chromosome

A7. This further confirms that the genes involved in formation of homogeneous clusters in

chromosomes A7 and C6 tend to be located in the same clade.

46

Table ‎2.5: Conserved and consensus sequence of NBS domain motifs found in the NBS-LRR genes identified in B. napus

Class Motif Consensus sequence* Class Motif Consensus sequence*

TNL

P-loop Kinase 1 VRMIGIWGPAGIGKTTIARALFNQLS

CNL

P-loop Kinase 1 VGIVGIYGMGGVGKTTLLRQINN

RNBS-A DDYNLKGIXXLLHLQEELLSKILNQK RNBS-A VIWVVVSQXFXDXXXGLDXXKKIQQ

Kinase 2 HLGVAXERLKDKKVLVVLDDVDDLXQLE

Kinase 2 LXXKKFLLVLDDIWXKVDLDWDLIGVPF

RNBS-B WFGPGSRIIITTRDK RNBS-B NGCKVVFTTRSXEVCGRMGXDDPM

RNBS-C HIYEVXFPSXXEALQIFCXYAFGQKSPP

RNBS-C VXCLTXEEAWELFXKKVGE

GLPL LAXEVVXLAGGLPLGLRVLGSXLRGKSXEEW

GLPL VAXKCGGLPLALNVIGE

RNBS-D LRXSYDGLXXEDKXLFLHIACFFNG

RNBS-D KSCFLYCALFPEDYKIXKEXLIEYWIAEG

MHDV MHXLLQQXGREIVR MHDV VKMHDVVREMALWIAS

* Conserved and Consensus amino acid sequence was derived from ClustalW multiple alignments of all predicted TNL or CNL genes. Bold residues indicate conserved sequence

identical to the motifs detected in Brassica rapa (Mun et al., 2009) and CNL/TNL consensus sequence (Ameline-Torregrosa et al., 2008). There is high agreement in conserved

sequence of NBS motifs between B. rapa and CNL/TNL consensus sequences

47

Figure ‎2.4: A phylogenetic tree of 176 CNL encoding genes of B. napus for NBS domains based

on the neighbour-joining method using MEGA 6.0 software. The numbers on the branches indicate

the percentage of 1000 bootstrap replicates. The tree only shows values > 50%. Gene names are

intended to represent chromosome and domain configurations. The blue and red coloured branches

are to separate the clades. The closed green triangle represent a homogenous cluster on

chromosome C6 where all genes sequence are related and located within a clade as well as their

relationship with genes on homologous chromosome A7 as represented by unfilled green triangles.

48

Figure ‎2.5: A phylogenetic tree of 366 TNL encoding genes of B. napus for NBS domains based on

the neighbour-joining method using MEGA 6.0 software. The numbers on the branches indicate the

percentage of 1000 bootstrap replicates. The tree only shows values > 50%. Gene names are

intended to represent chromosome and domain configurations. The blue and red coloured branches

are to separate the clades. The closed green triangles represent a homogenous cluster on

chromosome C6 where all genes sequence are related and located within a clade as well as their

relationship with genes on homologous chromosome A7, as represented by unfilled green triangles.

49

2.4.5 NBS-LRR gene duplication

The gene duplications of B. napus NBS-LRRs were confirmed by the BLAST comparison of all the

predicted proteins against each other. A total of 319 (50%) of the total NBS-LRR genes were

identified as duplicates (Table 2.3). There were 216 TNL duplicates and 103 CNL. The number of

duplicated genes was consistent between the two sub-genomes. Among the 19 chromosomes,

chromosome A9, C6 and C9 contain the highest number of duplicated NBS-LRR genes.

The duplicated genes were distributed randomly and 53% (171 duplicated genes) of total duplicate

genes were involved in formation of gene clusters, which may explain that tandem duplication plays

a role in gene cluster expansion (Table 2.3). Gene clusters containing tandemly duplicated genes

are shown in Figures 2.2 and 2.3. For instance, the gene cluster in chromosome A1 consists of

three TNL duplicates and one gene outside the cluster. Another example is the gene cluster in

chromosome A5 where all CNL genes are duplicates and form a cluster.

Two types of genomic duplication were observed (Figure 2.6). Intra-genomic duplications within

the B. napus A or C sub-genome are involved in duplication events at the level of an intra-

chromosomal region of the sub-genome. The A and C genomes had 16 and 24 duplication events,

respectively, involved in intra-chromosomal duplications. Moreover, chromosome A4 and A7 did

not show intra-genomic duplications. In contrast, inter-genomic duplication between the B. napus

genome (between A and C genome) involved a duplication between homeologous chromosomes of

the A and C genomes. There were 41 duplication events involved in duplicate loci between A and C

genome. The duplicated genes showed collinearity between homeologous chromosomes. For

example, 14 genes on chromosome A1 were collinear with chromosome C1 (Figure 2.6). However,

there are examples where they had a collinear relationship with a gene in non-homeologous

chromosomes. For example, five genes in chromosome A1 were collinear with a gene on

chromosome C3, C5 and C7 (Figure 2.6).

Furthermore, block duplication is considered as segmental duplication and defined as duplication of

a chromosomal region that includes more than one gene. Eleven duplication blocks were observed

between the B. napus homeologous chromosomes in which a block contained four to five genes

together in the duplication.

50

Figure ‎2.6: Inter-genomic and intra-genomic duplication relationship of NBS-LRR -genes between

the two sub-genomes of B. napus: the A and C genomes. Coloured lines represent the relationship

of paralogous gene pairs between homeologous chromosomes. Red lines represent the gene

duplication between chromosomes within a sub-genome. Black lines represent the gene duplication

between homologous chromosomes with collinearity. Blue lines represent the gene duplication

between non homeologous chromosomes. The green block represents a duplicated block where

there is more than one gene involved in duplication. Chromosomes are scaled based on the number

of NBS-LRR genes.

51

A study identified 21 conserved blocks within the Arabidopsis genome which showed synteny to

almost 90% of the B. napus genome (Parkin et al., 2005). This ancestral karyotype (AK) block

system was used to find a correlation between the B. napus NBS-LRR duplications and the

conserved blocks.

According to the conserved AK blocks relationships with B. napus chromosomes, the duplication

between NBS-LRR genes was defined as duplication between conserved genome regions within B.

napus chromosomes similar to the pattern of conserved blocks. Hence, the duplications between B.

napus chromosomes can be predicted based on the conserved blocks patterns between different

chromosomes. For example, conserved block 3A appeared in six chromosomes: A1, A3, A5, C1,

C3 and C5 (Table 2.6) suggesting that duplication may occur between them. This results in

comparison of the genome duplications based on NBS-LRR genes within and between B. napus A

and C sub-genomes.

In this study, the NBS-LRR genes duplication patterns in all B. napus chromosomes would be

expected to be correlated with the conserved AK blocks (Parkin et al., 2005). For instance, there

were two intra-genomic duplications in A1 with A6 and A8. The correlation indicated that the

duplication could occur between A1 and A8 but not with A6, because the conserved blocks in A1

have similar conserved blocks in A8 whereas there are no matching blocks between A1 and A6.

The correlation between NBS-LRR gene duplication and conserved blocks were significant as I

found that duplication pattern matching was about 70% and 85% in intra-genomic and inter-

genomic duplications, respectively (Table 2.6).

52

Table ‎2.6: The correlation between B. napus NBS-LRR intra-genomic and inter-genomic duplications and conserved blocks found between B. napus

and Arabidopsis

chr Arabidopsis Conserved blocks1 NBS-LRR

Intra-genomic duplication 2

Duplicated patterns

matching3

NBS-LRR Inter-genomic Duplication2

Duplicated patterns matching3

A1 4B 3A

A6 , A8 A8 C1 , C3 , C5, C7 , C9 C1 , C3 , C5 , C7

A2 5A 5E 1E 5D 3B 5B 5F

A10 A10 C1 , C2 , C7 C2 , C7

A3 5A 5E 2C 2B 4A 3A 4B

A9 A9 C2 , C3 , C7 C2, C3 , C7

A4 3D 4B 5C 2B 2C

--- --- C3 , C4 C3 , C4

A5 2C 1B 1C 3A

A9 --- C4 , C5 , C6 , C9 C4 , C6 , C5

A6 1C 1A 1B 5E 5F 5B 5C 3B 5D

A1 , A8 , A9 A8 , A9 C1 , C2 , C5, C6 , C7 , C8 , C9 C2 , C5, C6 , C7 , C8 , C9

A7 2A 1B 2B 3D 1E

--- --- C6 C6

A8 1C 4B 1B 1A

A1 , A6 , A9 A6 , A9 C1 , C3 , C5 , C6 , C7 , C8 C1 , C3 , C5 , C6 , C7 , C8

A9 4A 5B 1D 5D 4A 1B 3D 2B 1A

A3 , A5 , A6 , A8 A3 , A6 , A8 C2 , C3 , C4 , C5 , C7 , C8 , C9 C2 , C3 , C4 , C5 , C7 , C8 , C9

A10 1A 5E 5A

A2 A2 C2 , C6 , C9 C1 , C2

16 11(68%) 41 35(85%)

C1 4B 3A

C2 , C3 , C5 , C6 , C7 C3 , C5 A1 , A2 , A6 , A8 A1 , A8

C2 5A 5E 1E 5D 3B 5B 5F

C7 , C9 C7 , C9 A2 , A3 , A6 , A9 , A10 A2 , A3 , A6 , A9 , A10

C3 5A 5E 2C 2B 4A 3A 3B 3C 1B 4B C1 , C6 , C7 , C9 C1 , C7 , C9 A3 , A8 , A9 A3 , A8 , A9

C4 2C 2B 1D 3D 4B 5C 2B 2C

C9 C9 A4 , A5 , A9 A4 , A5 , A9

C5 1A 1B 3A

C1 , C8 , C9 C1 , C8 A1 , A5 , A6 , A8 , A9 A1 , A5 , A6 , A8 , A9

C6 1C 1E

C3 --- A1 , A5, A6 , A7 , A8 , A10 A5, A6 , A7 , A8

C7 2A 1B 5D 3B 5C 5B 4B

C1, C2 , C3 C1 , C2 , C3 A1 , A2 , A3 , A6 , A9 A1 , A2 , A3 , A6 , A9

C8 1C 4B 1A 1B 3D 1A

C1 , C5 C1 , C5 A6 , A8 , A9 A6 , A8 , A9

C9 4A 5B 5F 1D 5D 4A 5E 5A

C2 , C4 , C5 C2 , C4 A1 , A2 , A3 , A5 , A6 , A9 , A10 A2 , A3 , A6 , A9 , A10

24 17(70%) 41 35(85%)

1. Identified genome conserved blocks showing conservation of loci content and order between Arabidopsis and B. napus genome (Parkin et al., 2005). Blocks are arranged in

order from the top to bottom of the B. napus chromosomes.

2. The NBS-LRR gene intra-genomic or inter-genomic duplication confirmed by BLAST comparison of each individual NBS-LRR against all NBS-LRR genes in B. napus.

Then, the chromosome was determined based on the location of NBS-LRR gene in B. napus chromosomes

3. Based on the correlation between conserved blocks and NBS-LRR duplications on B. napus chromosomes.

53

2.5 Discussion

2.5.1 Genome wide identification of B. napus NBS-LRR genes

The recent whole genome sequencing of B. napus enables the genome wide identification, mapping

and characterization of candidate NBS-LRR genes in economically important plants such as

Brassica species. The genome wide NBS-LRR resistance genes have been extensively studied

because they represent the largest class of disease resistance gene and play a critical role in

defending plants from pathogens. Thus, identification of NBS-LRR resistance genes is one of the

most important objectives of understanding the resistance genetics. Here, this study aimed to

analyse the Brassica genomes for identification and characterization of candidate NBS-LRR genes

and to determine their distribution, domain structure, gene clustering, duplication and conservation.

In this study, I have characterized the complete set of 641 NBS-LRR genes in the Darmor B. napus

genome with about 70% of the genes comprising TNLs. This represents a ratio of 1:2.5 of CNLs to

TNLs. The TNL genes make the largest proportion of the NBS LRR genes and show large domain

diversity compared with the CNLs genes, as was also previously reported in B. rapa (Mun et al.,

2009, Yu et al., 2014), Arabidopsis (Meyers et al., 2003, Yu et al., 2014), Medicago truncatula

(Ameline-Torregrosa et al., 2008), poplar (Kohler et al., 2008) and linseed (Kale et al., 2012). The

high number of NBS-LRR resistance genes identified in this study could be explained mainly by the

complexity of the B. napus genome duplication and recombination

The predominance of TNL or CNL genes in a genome may be contributed by the nature of

pathogens that infect the plant species, or may be driven by another evolutionary force that could be

related to the success of one or another type of NBS-LRR genes (Leister, 2004, Lozano et al.,

2012). Moreover, TNL types are found widely in dicot genomes but not in monocot genomes,

whereas the CNL type is found in both monocot and dicot genomes (Bai et al., 2002).

The NBS-LRR genes were found to be distributed randomly and unevenly across the genomes. This

uneven distribution of NBS-LRR genes on chromosomes appears to be common in plants such as in

Arabidopsis, rice and poplar (Meyers et al., 2003, Zhou et al., 2004, Kohler et al., 2008, Yang et al.,

2008).

Most NBS-LRRs (59%) were found to be in clustered in the B. napus genome. This compares to

61% of all NBS genes in clusters in Arabidopsis (Meyers et al., 2003), 50% in Medicago truncatula

(Ameline-Torregrosa et al., 2008) and 58% in potato (Jupe et al., 2012). Large numbers of TNL

54

genes occur in clusters and tend to form large cluster, whereas, most of the CNLs were not in

clusters (singletons). This attributes to the predominance of TNLs to CNLs in B. napus.

Several identification approaches are available for NBS-LRRs, such as Pfam, mining ESTs, or

cloning resistance gene analogues (RGAs) using degenerate PCR. However, these methods each

have disadvantages. For example, RGAs has the limitation that the number of R genes identified is

affected by PCR and sequencing qualities. Pfam only finds gene models existing in the search

database, which might cause underestimation of the number of R genes. In this study, the MEME

and MAST analysis used in Jupe et al (2012) is a web based tool and the most common motif-

finding tool. The analysis is feasible and very efficient in identifying common specific motifs

between homologous protein sequences that show different motif compositions. By utilizing NBS-

LRR specific motifs from wide range of plant species, it enables 20 NBS-LRR specific motifs to be

distinguished between NBS-LRR subfamilies: TNLs and CNLs. In contrast, the domain based

identification of large NBS-LRR gene family members is very laborious and time-consuming. It

involves conserved domain searches followed by generating a hidden Markov models (HMMs)

profile. The domain based search does not identify homologous protein sequences if a domain has

diverged to another family.

Here, a combination of MAST and CNL/TNL analyses were utilized to have a more feasible and

accurate identification of potential candidate NBS-LRRs. The MEME/MAST analysis relies on 20

sequence motifs, putatively characteristic of NBS-LRR proteins, as queries against the predicted

genes of the B. napus genome to search for genes containing patterns matching the motifs giving an

E-value for each hit. Therefore, it is highly dependent on the gene prediction and annotation.

As expected, MEME/MAST analyses not only identified the number of NBS-LRR gene but, also

identified specific consensus sequence motifs for B. napus NBS-LRR genes showing similar motifs

sequence and patterns to those in other plants species such as Arabidopsis, potato, papaya, poplar

and Medicago. In contrast, consensus CNL and TNL analysis using either tBLASTn against

nucleotide sequence of the genome or BLASTp against amino acid sequence of the genome were

straightforward approaches to identify any gene or protein sequence with characteristics of NBS-

LRRs or even pseudogenes. The TNL and CNL consensus sequence BLAST analyses are suitable

for any plant genomes that have not yet been completed or assembled. In addition, CNL and TNL

consensus sequence were useful to ensure no related NBS-LRR genes are missing from the gene

prediction and mis-annotated. Thus, this analysis shows a good correlation between the two

methods indicating that it is deep enough for the genome wide identification of NBS-LRR genes

across the Brassica genomes.

55

The B. napus NBS-LRR genes were further divided into regular and non-regular NBS-LRR

encoding genes. The regular NBS-LRR genes have all domains and a complete open reading frame

whereas the non-regular NBS-LRR resistance genes have partial motifs of the NBS domain or lack

CC, TIR or LRR domains. They are probably considered as truncated or pseudogenes. For example,

TIR, TIR-NBS, and CC-NBS and NBS- LRR genes have been described in plant genomes and were

often distributed unevenly and surrounded regular NBS-LRR genes, for example in Arabidopsis

(Meyers et al., 2003), Medicago truncatula (Ameline-Torregrosa et al., 2008) and potato (Jupe et

al., 2012). One possible explanation for the presence of non-regular NBS-LRR genes is the partial

deletion of redundant NBS-LRR genes after whole genome duplication occurred. Interestingly, the

non-regular CNL or TNL genes were dispersed with regular genes among various clades throughout

the phylogenetic tree, indicating a diverse rather than a monophyletic origin due to domain deletion.

Thus, I anticipate that these non-regular NBS-LRR genes might show significant polymorphism

between B. napus cultivars.

Additionally, genes that encode for only a TIR domain lacking both NBS and LRR domains in B.

napus were reported. These genes might be truncated NBS LRR genes or a part of TIR containing

proteins as they have been previously identified in Arabidopsis and B. rapa (Meyers et al., 2002, Yu

et al., 2014). The majority of TIR genes were found residing in a cluster mixed with TNL and TN

suggesting they might have derived from TNs or TNLs and co-evolved (Yang et al., 2008). Thus,

TIR genes could interact and function together with TNL or NL proteins for their involvement in a

disease resistance response (Nandety et al., 2013).

The exon structure in TNLs is more complex than CNLs with an average of five exons in TNLs and

three exons in CNLs. The average number of exons in the total NBS-LRR is four exons. This result

is consistent with previous findings in B. rapa and A. thaliana. In B. rapa, the average exon number

in NBS-LRR genes was 4.2, but CNLs and TNLs have 2.3 and 5.2, respectively. Similarly, In A.

thaliana, NBS-LRR genes contain 4.2 exons, but CNLs and TNLs have 2.2 and 5.3 exons per gene

on average, respectively (Meyers et al., 2003, Mun et al., 2009).

2.5.2 Alignment and phylogenetic analysis

In the phylogenetic analysis using NBS domains, the NBS domain sequences in CNLs formed

distinct clades separated by higher genetic distances than in the TNLs. In addition, the average

number of genes per clades was similar for both TNLs and CNLs, despite there being a much larger

number of TNLs. This suggests that the NBS domains in CNLs were relatively more diverged in

sequence than TNLs due to greater selective pressure on the CNLs. This phenomenon was also

56

observed in previous studies in Fabaceae, Brassicaceae, Poaceae, and Solanaceae species (Bai et al.,

2002, Cannon et al., 2002, Wan et al., 2013). The results here concur with the hypothesis that the

CNL family is highly diverse and originated prior to the split between gymnosperms and

angiosperms while, the TNL family is more homogeneous and are found only in dicotyledons,

suggesting that the family arose after the divergence of monocotyledons and dicotyledons. In

addition, it can be attributed to the exon structure where the CNL proteins are mostly encoded by a

single exon, unlike TNLs that usually are encoded by a complex exon structure (Tarr and

Alexander, 2009). In this study, I also found that the TNL family of genes showed complex

structures and various domains (TIR, NBS, and LRR) which were often separated by introns and

usually consisted of many short exons in the LRR region.

Phylogenetic relationships also showed that the NBS-LRR genes located in the homeologous

chromosomes of the B. napus sub-genomes were likely to be found in the same clade. For instance,

the phylogenetic and sequence comparison between most of TNL genes in chromosomes A7 and C6

were found to be related to each other and located in the same clade suggesting that these genes

have been maintained without substantial divergence or selection pressure during B. napus

formation from its progenitor species. In addition, I found mixed clades dominated by sequences

from one chromosome (and usually from one or a small number of genomic clusters), but many also

contained small numbers of sequences from other chromosomes. This could arise in several ways:

by chromosomal rearrangements or by large-scale genomic duplication. Accordingly, this further

confirmed that gene duplication in B. napus might play a major role in the expansion and diversity

of NBS-LRR encoding genes.

2.5.3 NBS-LRR gene clustering

The combination of phylogenetic analyses and physical clustering of NBS-LRR genes was used to

study the nature of genes involved in clusters and whether they share homology. More

homogeneous than heterogeneous cluster were found (Figure 2.2 and 2.3). The existence of highly

related homologies in NBS-LRR gene clusters implies that NBS-LRR gene duplication can lead to

gain of resistance function (Grant et al., 1998). This is compared to heterogeneous clusters where

genes involved in the cluster are distantly related. These clusters of mixed unrelated genes could

have arisen as a result of either selective pressures or arranged and co-localized randomly in the

genome (Richly et al., 2002, Meyers et al., 2003). Moreover, clusters contain genes from non-

regular NBS LRR genes often located adjacent to regular NBS-LRR genes in gene clusters and this

is consistent with phylogenetic lineages. Therefore, the clustered organisation and arrangement of

these genes may be a critical attribute allowing the generation of novel resistance specificities via

57

intergenic rearrangement, duplication (especially tandem duplication) or gene conversion (Hulbert

et al., 2001).

Previously, it was hypothesized (Friedman and Baker, 2007) that R-gene distribution and quantity is

dependent on the size and cluster complexity of these genes so that these NBS-LRR genes keep

growing in number, complexity and expand the different functions of these genes. Thus, there could

be a correlation between the gene number and the size in the gene clusters as the large cluster size is

often associated with a higher gene number.

In addition, it has been suggested (Guo et al., 2011) that analyses of individual genes involved in

clusters provided evidence of gene diversity and selection pressure, suggesting NBS-LRR genes

within clusters to be more polymorphic and prone to evolutionary process while, singleton genes

remain a simple locus with no relatives in the genome reflect a relatively stable region. This is

supported by the finding that the gene clusters contained tandemly duplicated genes and formed

homogeneous clusters of many related genes.

2.5.4 NBS-LRR gene duplication

Since allotetraploid B. napus was formed from two ancestral diploid genomes of B. rapa and B.

oleracea via a polyploidization process, B. napus has undergone extensive genome rearrangement

and duplication. The level of gene duplication in the B. napus genome is thought to be significant

and there are high levels of genomic redundancy (Parkin et al., 2003, Rana et al., 2004, Parkin et al.,

2005). Thus, gene duplication, including tandem and whole-genome duplication (WGD) could have

resulted in a substantial increase or substitution of the gene number to compensate the gene losses

during formation of B. napus.

In this study, I found that 50% of B. napus NBS-LRR were duplicated, or in pairs of paralogs. The

distribution of duplicate genes was random which could be as a result of genome rearrangements or

gene loss/gain occurring after whole genome duplication events.

Intra-genomic and inter-genomic duplication events between B. napus NBS-LRR genes has been

observed suggesting that these genes possibly originated via tandem duplication where duplicated

genes are contiguous with its original copy. There was considerable collinearity between duplicated

genes in homeologous chromosomes, with the exception of some showing duplication between non

homeologous chromosomes due to possible translocation or genome mis-assembly.

58

In addition, block duplication between the B. napus homeologous chromosomes were observed and

considered as segmental duplication and defined as duplication of a chromosomal region that

includes more than one gene. It can be assumed that the duplication block might suggest gene losses

or rearrangement in B. napus. However, the level of genomic duplication reported based on NBS-

LRR genes is insufficient to provide a better resolution about the segmental duplication. Therefore,

this could be determined by analysis of sequence information flanking the NBS LRR genes.

A study by (Parkin et al., 2005) identified almost 90% of the B. napus mapped into conserved

syntenic blocks relative to Arabidopsis. In this study, I utilized the comparative duplication analysis

with conserved blocks to find the correlation with the intra-genomic and inter-genomic duplication

of NBS-LRR genes. This showed that these conserved blocks can be correlated with NBS-LRR

duplication, with about 70 to 85%. It was found that conserved blocks within Arabidopsis had

similar chromosomal rearrangements between A and C genome. This further supports my finding

that the NBS-LRR duplication between B. napus sub-genomes exhibited similar duplication

patterns suggesting that the NBS-LRR genes in B. napus might have experienced tandem gene

duplications and chromosomal rearrangements between the A and C genomes. However, the

duplications that did not correlate may be due to genome mis-assembly, or it may be due to location

of NBS-LRR genes in a region not covered by conserved blocks.

The duplication of NBS-LRR genes may be related to its physical location or cluster and occur

between chromosomes in two sub-genomes on B. napus. Theoretically, NBS-LRR derived from

gene duplications would share high similarity to NBS-LRR in the same or different genomic

clusters. It been suggested that duplication in combination with divergent selection acting on

duplicated genes, influences the generation of gene diversity within existing gene clusters (Parniske

and Jones, 1999, Richly et al., 2002, Wei et al., 2013). Approximately, 53% of duplicated genes

were involved in formation of gene clusters. This indicates that gene clusters could be chromosomal

hot spots in which the NBS genes get duplicated and then gene clusters may have been expanded by

tandem duplication followed by selection pressure (Wei et al., 2013). Indeed, previous studies

revealed that NBS-LRR genes are often present as tightly linked genes with high homology and are

prone to gene duplication and recombination, and thus evolve more rapidly than the rest of genome

(Grant et al., 1998). Therefore, the clustered distribution of NBS-LRR genes provides a reservoir of

genetic variation by which new specificities to pathogens can evolve via gene duplication

(Michelmore and Meyers, 1998, Yang et al., 2008). For instance, duplicated genes could be allelic

variants that show specificity for different pathogen strains. Together, these findings suggested that

59

tandem duplication in combination with recombination and selection pressure played a major role in

NBS gene expansion and diversity in B. napus.

60

Chapter 3

Comparative and conservation

analysis of NBS-LRR genes in

Brassica

*This chapter contributed to the science paper being published (Chalhoub et al., 2014)

61

Chapter 3 : Comparative and conservation analysis of NBS-LRR genes in

Brassica

3.1 Abstract

NBS-LRR genes are one of the most dominant gene families in plant genomes. The recent

completion of the genome sequences of B. napus and its related species: B. rapa and B. oleracea

provide an important opportunity for identification and comparative analysis of disease resistance

genes. The comparative analysis enables the understanding of the genomic structure and

conservation between Brassica species.

This chapter presents a comprehensive NBS-LRR comparative analysis between the three Brassica

species: B. napus, B. rapa and B. oleracea. From the genome wide NBS-LRR identification, a total

of 641, 249 and 443 NBS-LRR genes have been identified in B. napus, B. rapa and B. oleracea,

respectively. The distribution and synteny of NBS-LRR genes in the A genomes of B. napus and B.

rapa and C genomes of B. napus and B. oleracea are consistent and highly conserved in size and

orientation, particularly regions containing major gene clusters. This provided evidence that there

was a selective advantage to maintaining similar features of NBS-LRR genes in B. napus to both B.

rapa and B. oleracea following polyploidization. However, the differences in NBS-LRR gene

numbers could be attributed to gene losses or selection pressure to offer novel resistance genes in

the three species. More than 60% of NBS-LRR genes from the progenitor species were conserved

and maintained in B. napus. The differences in NBS-LRR content and conservation between B.

napus and its progenitors suggest differential selection for disease resistance that is either shared or

divergent.

This chapter provides an insight into NBS-LRR genome organisation and evolution between

Brassica species and enables understanding the candidate genes similarities and differences for

disease resistance traits.

62

3.2 Introduction

Comparative genomics is the study of sequence similarity/differences and chromosomal distribution

of gene homologues in related species. Comparative analysis provides an insight into genome

organisation, rearrangement and evolution between related species. The degree to which genome

comparison can facilitate cross-species analysis of gene evolution and function depends on the

conservation of gene content and synteny, collinearity between homologous chromosomes or

genomes.

The conservation of the NBS-LRR genes has been used to study the genomic architecture because

they are abundant, widely distributed throughout the genome and present in gene clusters. Genome

wide analyses of NBS-LRR genes in many genomes have showed that NBS-LRR genes are diverse

in number, structure and organization and suggested that these genes do not distribute randomly

within a genome (Baumgarten et al., 2003, Plocik et al., 2004, Yang et al., 2008, Zhang et al., 2011,

Gu et al., 2014, Yu et al., 2014). They often occur in a cluster at a specific location on the

chromosome. NBS-LRR genes and their syntenic positions were found conserved across the

genomes of tomato and potato (Pan et al., 2000).

Genomic comparison of NBS-LRR sequence similarity and chromosomal distribution in related

species is important to understand different perspectives towards NBS-LRR gene evolution. The

variation in NBS-LRR gene diversity within a species may be a fundamentally important strategy to

produce novel resistance specificities (Li et al., 2010). Evolutionary mechanisms generating

resistance gene diversity such as duplication, homeologous recombination and diversifying

selection have been proposed to contribute to the conservation and evolution of resistance genes

(Meyers et al., 2003, Ameline-Torregrosa et al., 2008, Ratnaparkhe et al., 2011). Comparative

analyses in soybean showed that the polyploidization did not result in increasing the number of

NBS-LRR genes. However, divergent selection acting on duplicated genes could result in creating

NBS-LRR number/cluster variation (Richly et al., 2002, Ashfield et al., 2012). NBS-LRR clustering

due to duplication and recombination may also be important factors that influence the evolution of

resistance genes.

Allotetraploid B. napus was formed from two ancestral diploid genomes of B. rapa and B. oleracea

via a polyploidization process. Previous studies have shown extensive genome collinearity and

structural conservation between Brassica species (Parkin et al., 2005, Cheung et al., 2009, Jiang et

al., 2011, Cheng et al., 2012a). However, considerable genome changes may have occurred via

duplication events (tandem duplication of genes), genomic rearrangements and homeologous

63

recombination between the A and C genomes. This often causes novel variations in B. napus

relative to its progenitors.

Polyploidization is considered to be the major mechanism of duplication in plants genomes. The

duplicated genes are produced by duplications arising from the alloploidy nature and post-

speciation duplications. The duplication arising by polyploidization originated from the ancestral

species, whereas the post speciation duplications take place independently after the polyploidization

event (Lawton-Rauh, 2003, Carretero-Paulet and Fares, 2012). In comparative genomics, it is

possible to examine the origin of duplications in polyploidy of B. napus through orthology,

paralogy and syntenic relationships to its ancestral species: B. rapa and B. oleracea. However, this

can be challenging in B. napus due the homeologous relationships between the progenitor genomes

as it is requires extensive genome wide analysis.

The completed genome sequences of the three Brassica species: B. napus (Chalhoub et al., 2014),

B. rapa (Wang et al., 2011) and B. oleracea (Parkin et al., 2014) offer a great opportunity for

functional and comparative analysis of genetic diversity and evolution between these Brassica

species. For instance, the effect of genomic variations on important genes such as disease resistance

genes can be studied.

Understanding the syntenic structure of NBS-LRR genes in ancestral genomes is required for

informative synteny analysis between different genomes. It also helps to study the genomic

rearrangements, such as duplication and translocation that might have occurred within the B. napus

genome. The comparative analysis serves as an invaluable resource for the identification and

cloning of the candidate genes and establishing an evolutionary relationship between species to

address the question of how NBS-LRR genes orthologous are highly conserved and evolved in B.

napus when compared to its two ancestral species in regards to disease resistance genetics.

The aim of this chapter is to find the NBS-LRR gene orthology and collinearity relationships

between B. napus and its diploid progenitor species: B. rapa and B .oleracea.

64

3.3 Methods

3.3.1 Brassica reference genomes

The genome sequence and annotation of B. napus cv. Darmor was used as the reference genome

(Chalhoub et al., 2014). The genome sequences of B. rapa v3.0 (Wang et al., 2011) and B. oleracea

cv. To1000 v1.0 (Parkin et al., 2014) were also used for comparative analysis.

3.3.2 Identification of NBS-LRR genes in B. rapa and B. oleracea

NBS-LRR candidate genes in B. rapa and B. oleracea were identified using the same methods in B.

napus as described in Chapter 2 section 2.3.2 and 2.3.4.

3.3.3 Reciprocal Best BLAST (RBB) of NBS-LRR for comparative analysis between B.

napus, B. rapa and B. oleracea

A reciprocal best BLAST (RBB) analysis was used to compare which of the NBS-LRR genes

predicted across the three genomes: B. napus, B. rapa and B. oleracea, were conserved. The NBS

LRR genes from B. rapa (v3.0) were compared with the identified NBS LRR genes from the B.

napus cv. Darmor (A genome) and vice versa using BLAST. The identified NBS-LRR genes from

B. oleracea (To1000 v1.0) were also compared with identified NBS-LRR genes from the B. napus

cv. Darmor (C genome), and vice-versa using BLAST.

The NBS-LRR genes were used to determine the chromosomal synteny between B. napus and B.

rapa as well as B. napus and B. oleracea according to their chromosome positions. Genes showing

orthology and collinearity were regarded as syntenic genes.

65

3.4 Results


species B. rapa and B. oleracea

The identification of NBS-LRR gene indicates that there are 641 NBS-LRR encoding genes in B.

napus. In the diploid species, a total 249 genes in B. rapa and 443 genes in B. oleracea were

identified (Table 3.1). The proportion of all genes encoding NBS-LRR in B. napus, B. rapa and B.

oleracea are 0.58%, 0.60% and 0.75%, respectively (Table 3.1).

Table ‎3.1: The total number of predicted NBS-LRR genes identified in the three Brassica genomes.

The table shows comparison between the methods used: MEME / MAST and CNL and TNL

BLAST

The number and distribution of NBS-LRR genes in the A and C genome of B. napus compared to

the A genome of B. rapa or C genome of B. oleracea are consistent across the chromosomes and

exhibit similar patterns (Tables 3.2 and 3.3 and Figures 3.1 and 3.2). The comparison of the total

number of NBS-LRRs and whether they were classified as TNL or CNL in both A and C genomes

also showed that the proportion of CNLs and TNLs was consistent across the three species, with

approximately 70% of NBS-LRR genes comprising TNLs (Figure 3.3). This represents a ratio of

1:2 of TNLs and CNLs in the A genome and 1:2.5 in C genome. The NBS-LRR in B. rapa and B.

oleracea were organised in gene clusters with approximately 53% and 61%, respectively. This is

very similar to the gene cluster percentage in B. napus (54% for A genome and 62% for C genome,

an average of 59%).

Species B. napus B. oleracea B. rapa

Genome size (Mbp) 1284 650 552

Gene content 111,479 59,225 41,019

Total candidate NBS-LRR genes 641 443 249

Proportion of NBS-LRR genes 0.58% 0.74% 0.60%

Identified in MAST output 615 437 248

Common to MAST and CNL/TNL analysis

509 379 208

Agreement % 79% 85% 83%

66

Table ‎3.2: The number of candidate NBS-LRR genes in B. napus. The total numbers of genes in

each chromosome with their classification into TNL or CNL as well as the reciprocal best BLAST

results are presented

Chromosome Total TNL CNL Reciprocal best BLAST

total conserved

TNL CNL A

gen

om

e B

. na

pu

s D

arm

or

A1 28 17 11 17 9 8

A2 44 33 11 26 24 2

A3 24 20 4 15 11 4

A4 13 12 1 6 6 0

A5 10 4 6 5 2 3

A6 21 7 14 11 4 7

A7 19 16 3 12 10 2

A8 24 17 7 12 8 4

A9 58 38 20 40 29 11

A10 11 7 4 5 5 0

Total in A genome

252 171

(68%) 81

(32%) 149 108 41

C g

en

om

e B

. na

pu

s D

arm

or

C1 37 24 13 25 14 11

C2 51 47 4 32 29 3

C3 56 46 10 33 27 6

C4 18 12 6 11 7 4

C5 19 11 8 14 7 7

C6 44 33 11 33 27 6

C7 38 30 8 32 25 7

C8 39 21 18 24 13 11

C9 79 62 17 54 42 12

Total in C genome

381 286

(75%) 95

(24%) 258 191 67

Unassigned 8 4 4 2 1 1

Total 641

461 (71%)

180 (28%)

409 300 109

67

Table ‎3.3: The number of candidate NBS-LRR genes in B. rapa and B. oleracea. The total numbers

of genes in each chromosome with their classification into TNL or CNL as well as the reciprocal

best BLAST results are presented.

Chromosome Total TNL CNL Reciprocal best BLAST

Total conserved

TNL CNL

A g

eno

me

B. r

ap

a

A1 18 10 8 16 8 8

A2 39 36 3 24 22 2

A3 29 25 4 16 12 4

A4 8 8 0 6 6 0

A5 11 2 9 5 1 4

A6 25 7 18 12 6 6

A7 19 16 3 13 11 2

A8 22 14 8 11 7 4

A9 59 40 19 41 29 12

A10 9 6 3 4 4 0

Unassigned 10 4 6 1 1 0

Total in B. rapa 249 168

(68%) 81

(32%) 149 107 42

C g

en

om

e B

. ole

race

a

C1 33 18 15 23 14 9

C2 52 43 9 30 27 3

C3 52 43 9 30 23 7

C4 24 15 9 10 5 5

C5 18 9 9 14 7 7

C6 45 32 13 31 24 7

C7 49 40 9 34 29 5

C8 41 23 18 27 12 15

C9 87 66 21 51 38 13

Unassigned 42 30 12 10 8 2

Total in B. oleracea

443 319

(72%) 124

(28%) 260 187 73

68

Table ‎3.4: Comparative analysis of synteny of NBS-LRR genes in B. napus to its progenitor

species

Chro Total Conserved Syntenic

genes

Syntenic genes in cluster

No. of conserved genes in clusters

No. of conserved genes not in clusters

A g

eno

me

B. n

ap

us

Dar

mo

r

A1 28 17 13 5 4 13

A2 44 26 20 16 17 9

A3 24 15 13 10 6 9

A4 13 6 3 2 2 4

A5 10 5 4 1 1 4

A6 21 11 7 2 3 8

A7 19 12 10 4 5 6

A8 24 12 10 5 5 6

A9 58 40 35 30 32 8

A10 11 5 4 1 0 5

Total in A genome

252 149 119 76 75 72

C g

en

om

e B

. na

pu

s D

arm

or

C1 37 25 21 12 13 12

C2 51 32 15 12 21 11

C3 56 33 26 20 20 13

C4 18 11 8 5 6 5

C5 19 14 14 10 10 4

C6 44 33 29 23 22 10

C7 38 32 31 25 21 11

C8 39 24 19 18 14 10

C9 79 54 42 33 33 20

Total in C genome

381 258 205 158 160 96

Unassigned

8 -- -- -- -- --

Total 641 409 324

(50%) 234

(72%) 235 168

69

Figure ‎3.1: The distribution of NBS-LRR genes in the A genome of B. napus and B. rapa

(Chalhoub et al., 2014).

Figure ‎3.2: The distribution of NBS-LRR genes in the C genome of B. napus and B. oleracea

(Chalhoub et al., 2014).

70

Figure ‎3.3: The proportion of TNL and CNL genes to the total number of NBS-LRR genes in B.

napus, B. rapa and B. oleracea.

Further NBS-LRR physical location of B. napus when compared to its diploid progenitors of B.

rapa and B. oleracea was performed to assess the NBS-LRR genes synteny and clustering (Figures

3.4, 3.5, 3.6 and 3.7). Comparison of the NBS-LRR genes of B. napus chromosomes with their

homeologous counterparts in the B. rapa and B. oleracea genomes indicated that the NBS-LRR

distribution showed clear syntenic and collinearity relationships between the A genome of B. napus

and B. rapa and the C genome of B. napus and B. oleracea. Approximately 324 (50%) of NBS-

LRR in the A and C genomes of B. napus were found to be syntenic and collinear to their respective

progenitor genomes (Table 3.4). They were highly consistent in size and orientation between

homeologous chromosomes in B. napus and its related species especially at the gene clustering

level (Figures 3.4, 3.5, 3.6 and 3.7). In addition, 72% of these syntenic and collinear genes in B.

napus were located within a gene cluster (Tables 3.4). However, there was evidence from local

gene clusters that the genes have been formed or lost between corresponding chromosomes of the

three Brassica species. In total, there were eight gene clusters formed in B. napus (four clusters in

the A genome and four clusters in the C genome) whereas there were ten gene clusters lost from the

B. napus (three clusters in the A genome and seven clusters in the C genomes) compared to the

diploid progenitors. For example, there are two gene clusters present on B. napus chromosome A1,

but absent in B. rapa. Likewise, two gene clusters are absent from B. napus chromosome C2 and C3

compared to B. oleracea.

71


Ar genome of B. rapa (chromosomes A1 to A5). Circles and triangles designate TNL and CNL

genes, respectively. Solid triangles and circles represent where the genes have orthologous copies,

blue and red symbols represent where genes were found to be in a cluster and grey symbols

represent where genes were not in a cluster. Unfilled symbols show genes without orthologs. A

solid line between genes represents genes that have a syntenic relationship in clusters, dotted lines

between genes show genes with syntenic relationships, but not in clusters. Chromosome lengths are

shown in Mb pairs. Published in (Chalhoub et al., 2014).

72


Ar genome of B. rapa (chromosomes A6 to A10). Circles and triangles designate TNL and CNL







73


Co genome of B. oleracea (chromosomes C1 to C5). Circles and triangles designate TNL and CNL







74


Co genome of B. oleracea (chromosomes C6 to C9). Circles and triangles designate TNL and CNL







75

3.4.2 Conservation analysis of B. napus NBS-LRR genes to its related diploid species B. rapa

and B. oleracea

In order to identify orthologous genes between each pair of genomes, the NBS-LRR genes

identified in the B. napus genome were individually compared to genes in both B. rapa and B.

oleracea by reciprocal best BLAST (RBB) to determine the number of reciprocal best hits for each

pairwise comparison.

In total 260 and 149 B. napus NBS-LRR have orthologous genes in B. oleracea and B. rapa,

respectively. NBS-LRR gene conservation was evident among the Brassica species representing

more than 60% of the genes in B. napus, B. rapa and B. oleracea which are conserved (retained)

(Tables 3.4 and 3.5). In contrast, 100 NBS-LRR genes were lost in the B. napus A genome and 183

in the C genome. There were also NBS-LRR genes present in B. napus which are absent in B. rapa

and B. oleracea; 103 and 121, respectively (Table 3.5).

In addition, the level of conservation (presence/absence and homology) tends to be higher within

gene clusters. There was high conservation in genes involved in gene cluster than singleton genes.

Approximately 80 (53%) and 160 (61%) of conserved genes in the A and C genome, respectively,

were within gene clusters. This compared to 96 (37%) and 72 (48%) of singleton genes were

conserved in A and C genome, respectively (Tables 3.4 and 3.5). There was conservation bias

towards TNLs in the A genome with 63% of TNLs conserved compared to 53% of CNLs

conserved. The conservation patterns do not seem to be consistent within the C genome (Tables 3.4

and 3.5).

Table ‎3.5: Comparative analysis of the number of NBS-LRR genes in the three Brassica species

and the reciprocal best BLAST hits

Genome B. oleracea C genome

B. napus Darmor

C genome

B. rapa A genome

B. napus Darmor

A genome

Total NBS LRR 443 381 249 252

Total TNL and CNL 319 , 124 286 , 95 168 , 81 171 , 81

Reciprocal BLAST hits conserved genes “retained”

260 (60%) 260 (75%) 149 (60%) 149 (60%)

Conserved TNL and CNL 187 , 73 192 , 68 107 , 42 108 , 41

% Conserved TNL and CNL 58% , 58% 67% , 71% 63% , 52% 63% , 52%

No. of conserved genes in cluster 160 (61%) 75 (50%)

No. of conserved genes not in cluster 96 (37%) 72 (48%)

Not conserved 183 121 100 103

Lost 183 0 100 0

Gained 0 121 0 103

76

3.4.3 Comparative analysis of chromosome A7 and C6 in B. napus

The genome wide NBS-LRR analysis enabled us to study the synteny and conservation comparison

of NBS-LRR genes on homeologous chromosomes A7 and C6 with their homologous counterparts

in B. rapa and B. oleracea. The gene content was similar with 19 NBS-LRR genes on chromosome

A7 of both B. rapa and B. napus, and 44 NBS-LRR genes on chromosome C6 in B. napus

compared to 45 genes in B. oleracea. There were 14 NBS-LRR genes involved in inter-genomic

duplications between B. napus A7 and C6 (Figure 3.8). The duplication events showed consistent

patterns with syntenic orthologous relationship. The comparison between chromosomes A7 genes in

B. napus and B. rapa showed 15 genes were orthologous and showed a clear syntenic relationship.

Similarly, 33 genes from chromosomes C6 in B. napus and B. oleracea were orthologous and

showed a clear syntenic relationship.

The comparison indicated that 15 and 33 genes on chromosomes A7 and C6, respectively, in B.

napus were produced by polyploidization. In addition, there were two tandemly duplicated genes on

chromosome C6 of B. napus produced by post-speciation (gene duplication) (Figure 3.8).

Phylogenetic analysis was further performed to study the relationships between the NBS-LRR

genes on A7 and C6. Figure 3.9 shows the phylogenetic analysis of NBS-LRR genes on

chromosomes A7 and C6 in B. napus and their homologs in its diploid progenitor species: B. rapa

and B. oleracea. As expected, the phylogenetic analysis separates the TNL and CNL gene products

into two distinct clades (Figure 3.9). TNL and CNL groups were further divided into distinct

subgroups represented by conserved and orthologous genes from all the three species grouped

together. The number of NBS-LRR genes for the three species in each subgroup was almost

identical. For example, two TNL subgroups were found to be the largest, containing 19 NBS-LRR

genes in total. A greater part in this subgroup was from B. napus (nine genes) compared to five

genes from B. rapa and five genes from B. oleracea.

77


between B. napus (Bn), B. rapa (Br) and B. oleracea (Bo). The squares and triangles represent

NBS-LRR type: TNL and CNL, respectively. Genes in syntenic relationships are connected by

lines. Red lines show inter-genomic duplications between B. napus A7 and C6. Closed bars are

orthologous genes. Genes within green squares are in a gene cluster.

78

Figure ‎3.9: A phylogenetic tree of TNL and CNL genes located on chromosomes A7 and C6 in B.

napus and the diploid species B. rapa and B. oleracea based on a neighbour-joining method using

MEGA 6.0 software. The numbers on branches indicate the percentage of 1000 bootstrap replicates.

The coloured squares indicate the gene origin: red from B. napus, blue from B. rapa and green from

B. oleracea.

79

3.5 Discussion


progenitor species B. rapa and B. oleracea

In this study, a total of 249 and 443 NBS-LRR genes in B. rapa and B. oleracea, respectively, were

identified. This is compared to 641 NBS-LRR genes in the B. napus cv. Darmor genome. This

shows a gene reduction in B. napus compared to the diploid progenitors, which meets the

expectation that the number of NBS-LRR genes is reduced in B. napus compared to B. rapa and B.

oleracea due to gene losses during the polyploidization events.

A recent study (Yu et al., 2014) has identified 206, 176 and 157 NBS-LRR genes in B. rapa, B.

oleracea and Arabidopsis, respectively. The NBS-LRR genes were identified through Hidden

Markov Model (HMM) profile corresponding to the Pfam NBS family domain. The number of

NBS-LRR identified in B. rapa was close to what is identified in here, but, the number of NBS-

LRR in B. oleracea was underestimated compared to this study. They also found that the number of

NBS-LRR genes in these three species was very close despite the differences in genome size and

complexity. This is surprising as B. rapa and B. oleracea genomes would be expected to contain

higher numbers of NBS-LRR genes than Arabidopsis because the B. rapa and B. oleracea genomes

have undergone extensive genome triplication events since divergence from the common ancestor

of Arabidopsis. The difference may be due to a poorer quality genome sequence assembly than was

used in this study.

The comparison of the total number of NBS-LRRs and whether they were classified as TNLs or

CNLs in both the A and C genomes showed that the proportion of CNLs and TNLs was consistent

across the three species, with about 70% of NBS-LRR genes comprising TNLs. This represents a

ratio of 1:2 of TNL and CNL in the A genome and a ratio of 1:2.5 in the C genome. This is

consistent with findings in Arabidopsis (Meyers et al., 2003).

The proportion of all genes encoding NBS-LRR in B. napus, B. rapa and B. oleracea are 0.58%,

0.60% and 0.75%, respectively, which is in line with estimates for other plant species that range

between 0.6- 1.8% (Meyers et al., 2003, Monosi et al., 2004, Ameline-Torregrosa et al., 2008,

Kohler et al., 2008, Yang et al., 2008). Thus, there does not seem to be correlation between genome

size and the number of NBS LRR genes. This is consistent with a previous study which suggested

that the relationship between total predicted gene number and total NBS-LRR gene number is likely

to be non-linear and not proportional to genome size (Porter et al., 2009).

80

The distribution and synteny of NBS-LRR genes in the A genomes of B. napus and B. rapa and C

genomes of B. napus and B. oleracea are consistent. Indeed, they are highly conserved in size and

orientation particularly region containing major gene clusters since 72% of these syntenic and

collinear genes in B. napus were located within gene cluster. The gene conservation and syntenic

relationship between sub-genomes has been found previously in other plants (Lagercrantz, 1998,

Grant et al., 2000, McCouch, 2001). However, loss of synteny for a gene cluster or presence of non-

orthologous genes in a local cluster suggests gene deletion, translocation or divergence in the B.

napus genome. This study also confirmed the absence or presence at the DNA level of gene clusters

by which a gene cluster is formed in B. napus, whereas there is no corresponding gene cluster in the

diploid genome of either B. rapa or B. oleracea in syntenic regions in the chromosomes.

Overall, these comparisons do not reveal significant deletion of NBS-LRR in B. napus as compared

to the diploid species. Thus, B. napus may have been subjected to less evolutionary selection or

pressure leading to maintaining NBS-LRR properties with its diploid progenitors.

3.5.2 Conservation analysis of B. napus NBS-LRR genes to its related diploid species B. rapa

and B. oleracea

The reciprocal best BLAST between the three genomes indicated that about 60% of NBS-LRR

genes were conserved and retained in the three Brassica species. These conserved orthologous

genes indicate that they have been maintained after polyploidisation. However, there could be an

underestimation in conserved orthologous genes due to the fact that reciprocal best BLAST counts

only once if a gene is duplicated. Previous studies on the fate of duplicated genes in polyploids

found that the duplicated resistance genes are preferentially lost after genome duplication, most

likely via a deletion mechanism (Nobuta et al., 2005, Yu et al., 2005, Yang et al., 2008). After

hybridisation of B. napus from B. rapa and B. oleracea, NBS-LRR genes in Brassica species

experienced species-specific gene deletion resulting in gene losses. A similar phenomenon of

redundant NBS-LRR gene loss has also been reported in other plant genomes presumably because

the duplicates would have redundant functions (Bancroft, 2001, Rana et al., 2004).

The duplicate genes were classified as resulting from polyploidization or post-speciation. Based on

their conservation and synteny, it can be difficult to distinguish among orthologs and paralogs

without extensive genome wide analysis. However, the results gave indication that a large number

of duplicated genes were originated via polyploidization from the ancestral species: B. rapa and B.

oleracea, while the tandemly duplicated genes were more likely produced by post speciation

duplications.

81

Gene conservation in syntenic region between B. napus and its related species: B. rapa and B.

oleracea suggests that orthologous copies are likely to retain their original function whilst, non-

orthologous genes in B. napus may have become specific or gained novel disease resistance. A

study by Yang et al. (2008) suggested that species specific NBS-LRR genes tend to be chromosome

specific and arranged in one or a small number of genomic cluster. In my study, the conservation

analysis revealed that there were more conserved NBS-LRR genes in gene clusters than singletons

suggesting that the chromosomal locations of NBS-LRR gene clusters show significant level of

conservation between B. napus and its related species: B. rapa and B. oleracea. In addition, this

also may suggest different evolutionary patterns for singleton and clustered NBS-LRR genes.

Further studies would be required to investigate whether the orthologous genes maintained in B.

napus show similar or divergent gene expression. In previous studies, gene expression data has

suggested that most duplicated NBS-LRR genes exhibited different expression patterns (Tan et al.,

2007, Cheng et al., 2012b).

The differences in NBS-LRR genes between the B. napus genome and its diploid species: B. rapa

and B. oleracea represent genes losses compared to B. rapa and B. oleracea as well as genes gained

in B. napus. The NBS-LRR genes reduction is expected in B. napus compared to B. rapa and B.

oleracea mainly due to gene losses via deletion during the polyploidization events. At the same

time, gene duplication and recombination have also created novel NBS-LRR resistance genes

specific to B. napus and have resulted in substitution of the gene number to compensate the gene

losses during formation of B. napus. A study by Yue et al. (2012) suggested that the NBS-LRR

gene number difference within species is either driven by gene losses or expansion through

duplication or divergence. Moreover, previous studies have shown evidence of gene loss and gain in

B. napus (Cho et al., 2010, Chalhoub et al., 2014). It could be speculated that the NBS-LRR genes

lost in B. napus suggested that these genes in B. rapa and B. oleracea might be species or disease

specific and have undergone different selection pressure to offer a novel resistance to same

pathogen or some pathogens for B. napus.

Together, the variation in NBS-LRR gene number between B. napus and the diploid species

indicates that only a single copy of some NBS-LRR genes may be conserved in the B. napus

genome, whilst the presence of resistance genes in B. napus and not the diploids may suggest

exposure to different pathogen stresses between the species, which has driven NBS-LRR genes

evolution. Furthermore, the differences in NBS-LRR gene numbers and conservation between B.

82

napus and its progenitors could be also attributed to genome mis-assembly and/or annotation

differences. Moreover, the cultivar specific differences are another factor affecting the NBS-LRR

variation as some NBS-LRR genes were present in one genotype but absent in another.

3.5.3 Comparative analysis of chromosomes A7 and C6 in B. napus

The number of NBS-LRR genes on chromosomes A7 and C6 between the three species were

consistent suggesting that they might have been maintained and not affected much during the

formation of B. napus.

Moreover, a comparative phylogenetic relationship of the NBS-LRR genes located on

chromosomes A7 and C6 in B. napus B. oleracea and B. rapa represents two major groups of TNL

and CNL genes from the three species. The phylogenetic comparison revealed that NBS-LRR

sequences from the three species are grouped together indicating that these are highly conserved

and suggests gene duplication from a common ancestral source of NBS-LRR genes. It also showed

that orthologous genes located in the homeologous chromosomes were likely found in the same

subgroups. This further confirmed that tandem duplication plays a major role in the duplication of

NBS-LRR genes. Thus, it appears that these NBS-LRR genes in B. rapa and B .oleracea may have

undergone similar selection pressure to offer novel resistance to same or different pathogen for B.

napus.

This study found several candidate NBS-LRR genes in B. napus that could confer resistance to

blackleg disease caused by L. maculans, the most devastating fungal pathogen of B. napus. These

genes were conserved orthologous genes in B. rapa and shared a duplicated copy in both

chromosomes A7 and C6 suggesting chromosomal duplication or rearrangements of this region. An

interesting NBS-LRR cluster on B. napus A7 and B. rapa A7 associated with candidate resistance

genes was identified. Further comparison analyses are discussed in more details later in chapter 5.

83

Chapter 4

Association and localization of NBS-

LRR genes with disease resistance

QTL in Brassica napus

84

Chapter 4 : Association and localization of NBS-LRR genes with disease

resistance QTL in Brassica napus

*This chapter contributed towards a paper being submitted

4.1 Abstract

The availability of the genome sequence and disease resistance NBS-LRR genes, together with

linked or flanking markers and QTL genetic maps, provide an efficient strategy to examine the

characteristics of QTL intervals. The association and co-localization between NBS-LRRs and

disease resistance QTL is a common feature of plant genomes. Here, this chapter presents the study

of the association and correlation between disease resistance QTL intervals and the NBS-LRR

resistance genes in Brassica napus.

A total of 27 QTL intervals for qualitative resistance to clubroot, downy mildew and blackleg

disease resistance traits in B. napus were identified and classified into primary and homeologous

QTL intervals. It also indicated that the QTL intervals in B. napus were originally contributed by

the parental species: B. rapa and B. oleracea. The identified QTL intervals appeared to co-localize

with NBS-LRR genes. There was a significant correlation between the number of NBS-LRR genes

within the QTL intervals and the number of genes involved in gene clusters. These gene clusters

and duplicated genes were likely to be associated with QTL.

The results provide evidence that NBS-LRR gene clusters are associated with disease resistance

QTL. The comparative analysis of disease resistance QTL between B. napus and its related species

reveal the structural conservation of NBS-LRR genes and provide a set of candidate resistance

genes. Further investigation of the similarity/divergence in sequence and gene content of these

QTLs will help elucidate their conservation and evolution.

85

4.2 Introduction

In the three major cultivated Brassica species, B. napus B. rapa, and B. oleracea, clubroot (caused

by Plasmodiophora brassicae), downy mildew (caused by Hyaloperonospora Parasitica) and

blackleg (caused by Leptosphaeria maculans) diseases have become an increasing problem causing

heavy yield losses to Brassica crops world-wide and have been a major focus in Brassica disease

resistance research (Delourme et al., 2011).


their corresponding Rlm (Resistance to Leptosphaeria maculans) genes in B. napus. All the

blackleg resistance genes identified to date have been found on the A genome of B. napus, with

none found on the C genome (Rouxel et al., 2003b, Ananga et al., 2006, Leflon et al., 2007). In

addition, genetic mapping studies have shown that all blackleg resistance genes in B. napus are

organised in clusters in two genomic regions: the Rlm2 resistance gene on chromosome A10 (Pilet

et al., 2001) and five specific resistance genes: Rlm1, Rlm3, Rlm4, Rlm7, and Rlm9 on chromosome

A7 (Delourme et al., 2004, Mayerhofer et al., 2005). It remains unclear whether these genes are a

cluster of tightly linked genes, or a single gene with different alleles, or a combination of both

(Delourme et al., 2004). Other blackleg resistance genes have also been identified on the A genome

of B. rapa: LepR1 on chromosome A2 and LepR2 on chromosome A10 (Yu et al., 2005) , LepR3 on

chromosome A10 (Li and Cowling, 2003, Larkan et al., 2014) and BLMR1 and BLMR2 on

chromosome A10 (Long et al., 2011). Recently, the first blackleg resistance gene in Brassica,

LepR3, has also been cloned in B. napus lines with introgressions from B. rapa ssp. Sylvestris

(Larkan et al., 2013).

Different sources of resistance to clubroot have been found in B. oleracea, B. rapa and B. napus

(Hirai, 2006, Diederichsen et al., 2009). At least eight clubroot resistance loci have been identified

in B. rapa and allocated to five different chromosomes: Crr1 on A8, Crr2 on A1, Crr4 on A6

(Suwabe et al., 2006), CRc on A2 (Sakamoto et al., 2008), CRa, CRb , CRk and Crr3 on A3 (Piao

et al., 2004, Saito et al., 2006, Hayashida et al., 2008, Sakamoto et al., 2008). In B. oleracea,

various QTL have also been reported (Landry et al., 1992, Figdore et al., 1993, Grandclément and

Thomas, 1996, Voorrips et al., 1997, Moriguchi et al., 1999, Rocherieux et al., 2004, Nomura et al.,

2005). Recently, two major QTL: PbBo(Anju)1 and PbBo(Anju)3 on chromosomes C2 and C3,

respectively, and other QTLs with minor effects have been identified (Nagaoka et al., 2010). This

study also showed that the B. rapa chromosomal regions harbouring B. rapa clubroot resistance

gene specific markers are homologous to the corresponding region of B. oleracea.

86

Several major qualitative resistance loci to downy mildew have been identified in Brassica species.

In B. oleracea, four resistance loci have been identified: Pp523 on chromosome C8(Farinhó et al.,

2004, Farinhó et al., 2007, Carlier et al., 2011, Carlier et al., 2012), the dominant single locus Ppa3

(Singh et al., 2012), downy mildew resistance locus Dm (Giovannelli et al., 2002) and

PpALG1(Alabaça, 2009). In B. rapa, three resistance loci were found, BraDM on chromosome A8

(Yu et al., 2009, Li et al., 2011, Yu et al., 2011b), the BrRHP1 locus on chromosome A1 (Kim et

al., 2011) and candidate resistance gene locus RPP13MK on chromosome A9 (Yu et al., 2010). In

addition, multiple sources of resistance have been reported in B. napus (Nashaat et al., 1997, Ge et

al., 2008).

Although numerous disease resistance QTL and qualitative genes mapped as QTL have been

identified, isolating and cloning a gene underlying the QTL/gene mapped region is relatively

difficult through map based cloning because the QTL region is still large and often not tightly

linked to the candidate gene(s). This is often further complicated by the complexity of the genomic

region due to duplication and rearrangement events. The availability of functional genome

annotations makes it possible to investigate the association and distribution between NBS-LRR

resistance genes and disease resistance QTL. The association of qualitative resistance (R) genes or

major resistance genes and QTL has been widely noted (Gebhardt and Valkonen, 2001, Quint et al.,

2003, Wisser et al., 2005). Candidate NBS-LRR resistance genes were previously found to be co-

localized with disease resistance QTL such as barley, potato and apple (Ramalingam et al., 2003,

Calenge et al., 2005, Bakker et al., 2011). Therefore, the significant co-localization of NBS-LRR

and QTL provide an excellent template for further studies of the involvement of NBS-LRR with

disease resistance QTL and genetic mapping of qualitative genes in B. napus.

The genetic maps are an important component representing sets of inherited DNA markers in

relation to the position of a gene conferring a trait. In contrast, the physical gene mapping

determines the location and function of a gene on a chromosome and its relative distance to the

QTL. Thus, genomic approaches can be used to analyse the disease resistance QTL using a

homology search. The sequence information and genome position of markers linked to, or flanking,

the previously reported QTL can be used to identify the physical boundaries of the QTL region onto

genome chromosomal maps. This allows narrowing down the size and position of the QTL to a

small genomic region in which candidate genes can be found based on the genome wide

identification of disease resistance NBS-LRR genes. Once the physical distance of the QTL and

flanking markers are determined, the correlation or association between a given disease’s QTL

regions and the associated NBS-LRR genes is further studied to enable prioritization and selection

of potential NBS-LRR candidate genes. Additionally, NBS-LRR genes associated with the QTL

87

physical and flanking markers can be used as a comparative approach to study the conservation and

syntenic regions between B. napus and its progenitor species, B. rapa and B. oleracea.

This chapter describes the physical location identification of disease resistance QTL intervals for

three important disease resistance traits in B. napus: blackleg, clubroot and downy mildew. It also

presents the physical association between QTL intervals and the numbers of NBS-LRR genes to

address the question whether the clustered and duplicated NBS-LRR genes are structurally and

functionally relevant to disease resistance QTL characteristics. If the clustering of functionally

related disease resistance genes occurred within QTL as a result of evolutionary mechanisms such

as duplication and divergent selection pressure, it is possible that the NBS-LRR gene/cluster

associated with QTL contributes to genetic variation and is under selection for the functional

conservation.

88

4.3 Methods

4.3.1 Brassica reference genome sequences

The genome sequence and annotation of B. napus cv. Darmor v6 was used as the reference genome

(Chalhoub et al., 2014). The genome sequence of B. rapa v3.0 (Wang et al., 2011) and B. oleracea

cv. To1000 v1.0 (Parkin et al., 2014) were also used for comparative analysis. The NBS-LRR gene

annotation and identification was described previously in chapters 2 and 3.

4.3.2 Identification of QTL intervals in B. napus by marker homology BLAST search

To identify the location of QTL intervals on the genome, available marker data and sequences were

retrieved from previously published studies (Tables 4.1, 4.2 and 4.3). These sequences were used

to perform homology searches against the reference genomes using BLAST (maximum E-value 1E-

1) (Altschul et al., 1997). Markers with 100% identical sequence alignments, with over 90%

coverage and that each marker of a QTL region were placed on the same chromosome

corresponding to the genetic map were selected. If the markers could not be placed on the

chromosome, or had no BLAST hit, they were discarded from the analysis.

The physical position of each marker was assigned based on the BLAST hit position of the marker

sequences against the reference genomic sequence. The genetic locations of associated QTL

intervals were estimated based on the distance between linked or flanking markers. For each QTL

interval, any NBS-LRR genes located within the markers flanking the QTL interval were

considered associated and included in the analysis. The correlation between the number of NBS-

LRR genes and disease QTL intervals was analysed using linear regression in Microsoft Excel.

For co-mapping the QTL intervals between B. napus and its progenitor species, B. rapa and B.

oleracea, the BLAST searches of the QTL linked or flanking markers with respect to their physical

hit locations, order and coverage were compared between them. A syntenic region in B. rapa and B.

oleracea was characterized by marker locations present in the same chromosome and in the same

order as in B. napus.

89

4.4 Results

4.4.1 Identification and localization of QTL intervals in B. napus

The genetic mapping studies (Piao et al., 2009, Delourme et al., 2011) indicated the presence of

several resistance genes for clubroot and downy mildew in the Brassica A and C genomes with

most of these genes showing race specificity. Similarly, blackleg resistance is controlled by a major

gene for gene interaction and the resistance is contributed by the Brassica A genome. Thus, these

identified QTL intervals are for qualitative resistance controlled by major resistance genes that have

been identified in B. napus, B. rapa or B. oleracea.

A number of flanking, or linked, markers of these disease resistance QTL for qualitative genes in

the three species: B. napus, B. rapa, and B. oleracea, were utilized to determine the physical

location of QTL intervals on the B. napus genome. The QTL flanking or linked markers were

initially screened by BLAST homology searches to locate their physical positions on the genome,

then, the location of QTL intervals on the genome were estimated.

A total of 27 QTL intervals for qualitative resistance to clubroot, downy mildew and blackleg in B.

napus were identified. The number of QTL detected ranged from 12 QTL intervals for clubroot and

downy mildew and three QTL intervals for blackleg (Tables 4.1, 4.2 and 4.3). The distribution of

these QTL was found across all 19 of the B. napus chromosomes except A4, A5 and C6. The length

of the QTL intervals ranged from 0.7 to 23 Mbp with the majority (66 %) of the identified QTL

intervals less than 2.8 Mbp in length (Table 4.4).

Twelve QTL intervals involved in clubroot resistance were identified in B. napus (Table 4.1 and

Figure 4.1). These QTL intervals corresponded to the eight and two clubroot resistance loci which

have been identified in B. rapa and B. oleracea, respectively. These 12 QTL intervals were

classified into eight primary QTL intervals corresponding to their respective genetic maps and four

homeologous QTL intervals due to the amphidiploid nature of B. napus. The eight primary QTL

intervals in B. napus are Crr1 on chrA8, Crr2 on chrA1, Crr3 and CRk on chrA3, CRa and CRb on

chrA3, Crr4 on chrA6, CRc on chrA2, pbBo(Anju)1 on chrC2 and PbBo(Anju)3 on chrC3 (Table

4.1). The four homeologous QTL intervals in B. napus are Crr3 on chrC3, Crr4 on chrC6, CRa and

CRb on chrC7 and pbBo(Anju)1 on chrA2 (Table 4.1). The primary Crr3 QTL is overlapping with

the primary CRk QTL, so they are considered as one primary QTL for both Crr3 and CRk locus.

The primary and homeologous CRa QTL are overlapping with the primary and homeologous CRb

QTL, so they are considered as one primary QTL and one homeologous QTL for both CRa and CRb

locus.

90

Likewise, 12 QTL intervals involved in downy mildew resistance were identified in B. napus

(Table 4.2 and Figure 4.1). These QTL intervals were corresponding to the three mildew

resistance loci which have been identified each in B. rapa and B. oleracea. These QTL intervals

were also classified into seven primary QTL intervals and five homeologous QTL intervals. The

seven primary QTL intervals in B. napus are BraDM on chrA8, RPP13MK on chrA9, BrRHP1 on

chrA1, two Pp523 on chrC8 and PpALG1 on chrC4 and Dm on chrC2 (Table 2). The five

homeologous QTL intervals in B. napus are RPP13MK on chrC9, two BrRHP1 on chrC1, two

Pp523 on chrA9 (Table 4.2). The BrRHP1 locus had two homeologous QTL intervals separated by

a region of ~14 Mbp, so they are considered as two separate QTL intervals. The Pp523 locus had

two primary QTL intervals and two homeologous QTL intervals separated by a 19 Mbp region, so

they are considered as two separate QTL intervals.

The flanking markers search and QTL intervals for blackleg resistance was restricted only to the A

genome of B. napus because genetic mapping studies showed that all blackleg resistance genes are

found on the A genome (Rouxel et al., 2003b, Ananga et al., 2006, Leflon et al., 2007). In addition,

the homology search of flanking, or linked markers for the blackleg Rlm QTL revealed that the

flanking markers showed good correspondence between the A genome of B. napus and B. rapa.

However, the flanking markers did not show sequence and collinear similarity between the A and C

genome of B. napus and some markers even failed to be located in the C genome. As a result, the

flanking marker analysis in the C genome of B. napus was not considered in this study.

Hence, three QTL intervals involved in blackleg resistance were identified in the A genome of B.

napus (Table 4.3 and Figure 4.1). These three QTL intervals were small QTL intervals on

chromosome A2 for resistance loci, LepR1, major QTL on chromosome A7 for resistance genes:

Rlm1, Rlm3, Rlm4, Rlm7, and Rlm9 and major QTL on chromosome A10 for resistance genes:

LepR3, BLMR1 and BLMR2. The Rlm2 and LepR2 genes could not be mapped in this study because

there was no available markers sequence. The LepR2, LepR3, BLMR1 and BLMR2 genes were

identified in B. rapa. However, the B. napus genome might harbour orthologous genes for LepR2,

LepR3, BLMR1 and BLMR2 located in the same position in B. rapa.

The overlapping QTL intervals were identified as the QTL flanking markers were found to overlap

by their physical position and order on the genome. For example, clubroot primary and

homeologous QTL intervals for resistance loci CRa and CRb were overlapping in the A and C

genome of B. napus. Furthermore, clubroot QTL intervals for resistance loci Crr3 and CRk were

overlapping in the A genome but only the Crr3 locus showed homeologous QTL intervals in the C

genome.

91

The QTL intervals for downy mildew BrRHP1 had primary QTL intervals in the A genome of B.

napus and two adjacent homeologous QTL intervals separated by a region in the C genome.

Similarly, QTL intervals for downy mildew for Pp523 had two adjacent primary QTL intervals in

the C genome of B. napus and two adjacent homeologous QTL intervals separated by a region in

the A genome.

The co-mapping of the flanking markers of QTL intervals were performed to compare the syntenic

relationship between B. napus and its progenitor species. The physical distance of flanking markers

and location of the QTL intervals between B. napus and B. rapa and B. oleracea were mostly

consistent. Almost all QTL intervals identified in B. napus were co-mapped and contributed by the

progenitor species. However, there were several QTL intervals only co-mapped to either the A or C

sub-genome B. napus and its corresponding genome in the related species. For example, the

clubroot loci, Crr1 and Crr2 had only primary QTL intervals in the A genome of B. napus and they

co-mapped to the A genome of B. rapa.

92

Table ‎4.1: Marker homology search of clubroot resistance QTL flanking or linked markers for identification of QTL intervals in B. napus

Origin species

Gene or locus

Flanking marker

Marker homology search, Chromosome and QTL interval region (Mbp)

References B. napus v6

primary B. napus v6

Homeologous B. rapa v3 B. oleracea v1

B. rapa

Crr1

BRMS-088 BRMS-297 BRMS-173

chrA8 (9,157,719 -12,043,127)

No XA8 (9,066,423 -11,186,261)

No (Suwabe et al., 2003, Suwabe et al., 2006, Suwabe et al., 2012)

Crr2

BRMS-096 BRMS-056 BRMS-100 BSA3

chrA1 (4,791,456 -6,335,486 )

No XA1 (4,934,358 -6,345,669)

No (Suwabe et al., 2003, Suwabe et al., 2006, Nagaoka et al., 2010)

Crr3*

BRMS058 BrSTS-54 BrSTS-20 BrSTS-44 BrSTS-41 BrSTS-33 OPC11-2S BrSTS-61 BrSTS-78 BrSTS-26 BN308CAPS BN142CAPS OPC11-1S BRMS206

chrA3 (14,411,852 -18,264,109)

chrC3 (22,088,816 -24,102,086)

XA3 (14,571,901 -18,141,486)

C3 (21,404,891 -23,862,433)

(Hirai et al., 2004, Saito et al., 2006, Nagaoka et al., 2010)

Crr4 BRMS-125 BRMS-101 BRMS-027

chrA6 (100,821 - 2,122,156)

chrC6 (9,621,029 -3,923,239)

XA6 (322,565 -1,915,926 )

C6 (31,002,743 -35,909,761)

(Suwabe et al., 2006, Sakamoto et al., 2008)

CRa**

HC352b-SCAR GC2360 SC2930

chrA3 (24,281,973 -25,363,967)

chrC7 (43,472,000 -44,774,737)

XA3 (8,639,804 -7,449,703)

C7 (41,356,755-42,582,200)

(Sakamoto et al., 2008, Matsumoto et al., 2012)

93

HC181

CRb**

TCR05 KBrH059N21F KB59N07 B1210 B1005 KBrH129J18R TCR09 KBrB091M11R TCR02-F

chrA3 (24,657,890 – 26,478,686)

chrC7 (43,811,909 – 45,640,146)

XA3 ( 6,596,824- 8,359,700)

C7 (41,700,554 – 43,396,450)

(Piao et al., 2004, Kato et al., 2012, Kato et al., 2013)

CRc

PW155

BRMS-082

m6R

BRAS011

B50

chrA2 (12,021,130 – 23,656,219)

No XA2 (11,817,414-21,197,733)

No (Sakamoto et al., 2008, Matsumoto et al., 2012)

CRk* HC688

BRMS-158

chrA3 (16,540,113 -19,198,438)

No XA3 (17,852,750 -15,564,520)

No (Sakamoto et al., 2008, Matsumoto et al., 2012)

B. oleracea pbBo(Anju)1

pW176

KBrH059L13R

BRMS-228

chrC2 (51,280,390-54,799,276)

chrA02 (26,445,222-28,289,273)

XA2 (24,048,282-25,751,675)

C2 (47,638,250-50,630,426)

(Nagaoka et al., 2010)

PbBo(Anju)3

BRMS-330

KBrH008J04R

BRMS-008

chrC3 (2,031,456 -3,680,316)

No XA3 (30,530,122 -32,176,756)

C3 (2,048,895 -3,655,161)

(Nagaoka et al., 2010)

(*)The primary Crr3 QTL is overlapping with the primary CRk QTL, so they are considered as one primary QTL for both the Crr3 and CRk locus.

(**) The primary and homeologous CRa QTL are overlapping with the primary and homeologous CRb QTL, so they are considered as one

primary QTL and one homeologous QTL for both the CRa and CRb locus.

94

Table ‎4.2: Marker homology search of downy mildew resistance QTL flanking or linked markers for identification of QTL intervals in B. napus

Origin species

Gene or locus

Flanking marker

Marker homology search, Chromosome and QTL interval region (Mbp)

References

B. napus v6 primary

B. napus v6 Homeologous

B. rapa v3 B. oleracea

v1

B. rapa BraDM SCAR SCK14-825 K14-1030 kbrb058m10-1 Brh019-SNP137 Brb062-Indel230

Brb094-DraⅠ787 kbrb006c05-2 Ol12G04

Brb043-BglⅡ715

Brb094-AatⅡ666

chrA8 (17,655,647 – 18,527,339)

No XA8 (3,003,191 – 3,715,750 )

No (Yu et al., 2009, Li et al., 2011, Yu et al., 2011b)

RPP13MK RPP13MK marker chrA9 3,964,312

chrC9 5,472,171

XA9 35,017,366

C9 6,297,979

(Yu et al., 2010)

BrRHP1* A03 SCAR N18 SCAR M05 SCAR BrPERK15A SCAR BrPERK15B SCAR J11 SCAR G17 SCAR M22 SCAR]

chrA1 (11,636,716 -28,936,570)

chrC1 (18,207,518 – 23,807,810) and chrC01 (37,139,336 -46,454,126)

XA1 (9,119,600 – 24,979,656)

C1 (17,054,176–17,059,862) and (32,805,430- 42,695,072)

(Kim et al., 2011)

B. oleracea Pp523** CB10139 159G23_R 33N5_R 24H17_R

chrC8 (23,172,112) and chrC08

chrA9 (30,451,080 ) and chrA09 (42,648,154 –

XA9 (149,523- 1,595,774)

C8 (38,878,775 – 41,519,284)

(Farinhó et al., 2004, Farinhó et al., 2007, Carlier et al., 2011, Carlier et al., 2012)

95

AGC.CAT_300(SCAFB1) AAG.CTA_113 CB10028 OPR15_920 (SCR15) OPJ19_550 (SCJ19) OPK17_980 SCAR AT.CTA 133/134

(42,851,417 – 44,412,664)

43,351,988)

PpALG1 OPU20_1307 ScJ18_530 ScK04_434 OPK04 667 OPU20_970y OPT08_1112y ScAN12

chrC4 (14,179,370 – 37,643,262)

No No C4 (13,684,813- 24,945,714)

(Alabaça, 2009)

Downy mildew resistance locus Dm

UBC359620

OPM16750 chrC2 (54,044,677 -54278743)

No No C2 (50,021,049-50,193,751)

(Giovannelli et al., 2002)

(*) The BrRHP1 locus had two homeologous QTL intervals separated by a region of ~14 Mbp, so, they are considered as two separate QTL intervals.

(**) The Pp523 locus had two primary QTL intervals and two homeologous QTL intervals separated by a 19 Mbp region, so they are considered as

two separate QTL intervals.

96

Table ‎4.3: Marker homology search of blackleg resistance QTL flanking or linked markers for identification of QTL intervals in B. napus

Origin species

Gene or locus

Flanking marker

Marker homology search Chromosome and QTL interval region (Mbp)

References B. napus v6 A genome

B. rapa v3

B. rapa

LepR1 BnGMS254 BRMS-215

chrA2 (808,646 -2,314,919)

XA2 (3,976,187-3,052,782)

(Yu et al., 2005, Yu et al., 2008)

LepR3 Ind10-04 Ind10-17 Ind10-12 Ind10-13 Ind10-08 Ind10-07 Ind10-03

chrA10 (16,001,480 -16,265,343)

XA10 (3,096,287 -3,422,354)

(Larkan et al., 2013)

BLMR1 1128BG275 87B10a 9B23c 9B23a 9B23b 80A08a 80E24

chrA10 (13,961,320 – 16,241,031)

XA10 (2,600,133- 4,586,316)

(Long et al., 2011)

BLMR2 G278 10B23a 12D09a 1J13a 1J13b R278

chrA10 (10,781,132 – 13,515,501)

XA10 (6,989,137- 9,650,582)

(Long et al., 2011)

B. napus

Rlm gene cluster Rlm9, Rlm4, Rlm7 and Rlm1

chrA7 (10,985,714 – 25,262,138)

XA7 (6,721,636 – 22,178,571)

(Delourme et al., 2004, Leflon et al., 2007, Raman et al., 2012b)

Rlm9 BnGMS665 CB10450

chrA7 (12,963,123– 14,389,391)

XA7 (8,889,906 – 9,867,760)

97

BRAS023

Rlm4 BRMS075 Na12-E11b BRMS040 BRMS005b

chrA7 (14,214,108 -15,000,000)

XA7 (9,728,451 – 10,819,936)

Rlm7 na14B03 chrA7 15,894,933

XA7 13,033,236

Rlm1 kbrh143h15 bn204 na12-a02 ra2-a05

chrA7 (22,005,183- 25,262,138)

XA7 (16,180,246 – 19,196,267)

98

Figure ‎4.1: The location of disease resistance loci QTL in the chromosomal map of B. napus. The

disease resistance loci QTL indicated clubroot (red), downy mildew (black) and blackleg (green).

The number within brackets shows the QTL interval size in Mbp. The “h” means that the QTL

intervals are homeologous. Brackets are not to scale the distance but to indicate the relative location

of genes within QTL interval.

99

4.4.2 Co-localization and association of NBS-LRR genes and QTL intervals

The co-localization of the disease resistance NBS-LRR genes and the QTL intervals on each

chromosome were examined and correlated with the NBS-LRR genes clusters and duplications.

Based on the findings by (Kang et al., 2012) that QTL and NBS-LRR genes tended to be co-

localized and NBS-LRR genes are often positioned in the 2 Mbp flanking regions of a QTL, all the

NBS-LRR genes located in the QTL, including the 2 Mbp flanking regions were considered

associated NBS-LRR genes and included in the analysis.

The number of NBS-LRR genes associated with the QTL intervals ranged from 1 to 19, from a total

number of 232 genes in all the QTL intervals (Table 4.4). Approximately 40% of the associated

NBS-LRR genes are involved in a gene cluster, 58% are duplicates and 62% are conserved between

B. napus and its related species (Table 4.4). The number of associated NBS-LRR genes was

variable between primary and homeologous QTL intervals. For instance, downy mildew BrRHP1

contained 19 NBS-LRR genes in the primary QTL intervals and 12 NBS-LRR genes in the

homeologous QTL intervals.

Regression analysis showed that there are significant correlations between the number of NBS-LRR

genes within the QTL intervals and the number of genes involved in gene clusters or duplication

(Figure 4.2 and 4.3). The R2

value of 0.84 and 0.80 for the correlation of number of genes involved

in gene clusters or duplications was observed, respectively.

100

Table ‎4.4: Correlation between the number of NBS-LRR resistance genes and disease resistance QTL intervals in chromosomes of B. napus

Chromosome

Total No. of NBS LRR

genes

Number of QTL

QTL Disease resistance loci

in B. napus

Physical interval, Size and location (Mbp)

No. of NBS LRR

within 2 Mbp

flanking region of QTL

Gene cluster

No. of genes in cluster

No. of duplicate

genes

No. of conserved

genes

chrA1 28 2 clubroot Crr2

1 Mbp (4,791,456 -6,335,486)

3 0 0 3 3

downy mildew BrRHP1

17 Mbp (11,636,480 -28,936,570)

19 1 4 11 9

chrA2 44 3

blackleg lepR1 1.5 Mbp

(808,646 -2,314,919) 10 1 7 5 7

clubroot Crc 11.5 Mbp

(12,021,130 -23,656,219) 19 2 14 11 12

homeologous clubroot

pbBo(Anju)1

1.8 Mbp (26445222 -28289273)

14 1 7 6 6

chrA3 24 2

clubroot Crr3 and CRk

4.7 Mbp (14411852 -19198438)

8 1 4 5 4

clubroot CRa and CRb

2 Mbp (24281973 -26478686)

7 0 0 5 4

chrA6 21 1 clubroot Crr4 2 Mbp

(100,821 -2,122,156) 8 0 0 7 4

chrA7 19 4

Blackleg gene cluster Rlm3 Rlm9 Rlm4 Rlm7 Rlm1

14 Mbp (10,985,714 -25,262,138)

12 1 4 7 8

chrA8 24 2 clubroot Crr1 2.8 Mbp

(9,157,719- 12,043,127) 5 0 0 4 3

101

downy mildew BraDM

809 kbp (17,718,157- 18,527,908)

9 1 3 5 4

chrA9 58 2

downy midlew RPP13MK

3,964,312 3 1 3 3 2

homeologous downy mildew

Pp523

30,451,080 And

703kbp (42,648,154- 43,351,988)

15 2 10 13 10

chrA10 11 1 blackleg BLMR2

, BLMR1 and lepR 3

6 Mbp (10,781,132- 16,770,124)

10 0 0 5 5

chrC1 37 2 homeologous downy mildew

BrRHP1

5 Mbp (18,781,127- 23,808,081)

and 9 Mbp

(37,139,336 – 46,454,793)

12 1 4 6 8

chrC2 51 2

Clubroot pbBo(Anju)1

51,280,390 1 0 0 1 1

Downy mildew resistance locus Dm

54,278,743 1 0 0 1 1

chrC3 56 2

clubroot PbBo(Anju)3

1.6 Mbp (2,031,456- 3,680,316)

9 1 5 4 6

homeologous region to Crr3

2 Mbp (22,088,816- 24,102,086)

1 0 0 1 1

chrC4 18 1 downy mildew

PpALG1 23 Mbp

(14,179,370- 37,643,262) 10 0 0 2 7

chrC6 44 1 homeologous region to Crr4

5 Mbp (3,923,239- 9,621,029)

12 1 7 10 7

chrC7 38 1 homeologous region to CRa

and CRb

1.3 Mbp (43,472,000- 44,774,737)

13 1 6 6 12

chrC8 39 2 downy mildew

Pp523 23,172,112

and 27 3 16 12 17

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837 kbp (42,851,417- 44,412,664)

chrC9 79 1 homeologous

RPP13MK 5,472,171 4 0 0 3 3

Total 591 29 -------- ----------------- 232 18 94 (40%) 136(58%) 144(62%)

103


regions of QTL and the number of NBS-LRR genes involved in gene clusters

104


regions of QTL and the number of duplicated NBS-LRR genes.

105

4.5 Discussion

4.5.1 Identification and localization of QTL intervals in B. napus

Several mapping studies have previously identified QTL for diseases such as blackleg, clubroot and

downy mildew in B. napus, B. rapa and B. oleracea. The availability of linked or flanking markers

and QTL genetic maps, together with the genome sequence and disease resistance NBS-LRR genes,

provide an efficient strategy to examine the characteristics of QTL intervals. This allows

identification and determination of the physical locations of these QTL intervals, based on the

physical location of marker information against the B. napus genome. Ultimately, this results in a

comprehensive co-localization of disease resistance QTL intervals and their association with NBS-

LRR genes in B. napus.

A total of 27 QTL intervals for major resistance genes for clubroot, downy mildew and blackleg

disease resistance traits were identified in B. napus. These QTL intervals are distributed throughout

the genomes. The number of identified QTL intervals in B. napus was 12, 12 and three for

resistance for clubroot, downy mildew and blackleg, respectively.

The QTL intervals identified in B. napus were classified into primary QTL intervals and

homeologous QTL intervals. The primary QTL intervals correspond to similar locations on the

respective genetic maps whereas homeologous QTL intervals are due to the polyploid genome in B.

napus and genome duplication (Li et al., 2013). Given that B. napus originated from two highly

conserved diploid genomes of B. rapa and B. oleracea, the relationships between homologous

regions of QTL or major resistance genes can support the inheritance pattern of the resistance traits.

Therefore, it could be hypothesized that B. napus has retained the homeologous QTL intervals

inherited from the ancestral species: B. rapa and B. oleracea. This is also seen by (Lestari et al.,

2013) showing that the major QTL for soybean seed protein and oil in Chr20 had duplicated

homeologous regions in Chr10 that occurred due to duplication event. Therefore, the primary and

homeologous QTL intervals on different chromosomes might result from genome duplication and

then undergo rapid divergence and reorganization. The primary and homeologous QTL in B. napus

could also correspond to a homeologous region in either B. rapa or B. oleracea. For this reason, the

present study assumed that these two QTL are produced by polyploidization.

Interestingly, there were differences in the number of associated NBS-LRR genes and the QTL

interval sizes between primary and homeologous QTL intervals. This emphasizes that the

polyploidy and genome rearrangements might have a major impact on the structure of QTL interval

and the contribution to disease resistance.

106

Overlapping QTL intervals for several resistance loci were found. For instance, four overlapping

QTL intervals for blackleg resistance genes Rlm9, Rlm7, Rlm4 and Rlm1 were on chromosome A7

of B. napus (Delourme et al., 2004). In addition, these QTL are located within an extensive intra-

chromosomal tandem duplication region (Raman et al., 2012b, Tollenaere et al., 2012). If a QTL

overlapped with other QTL identified from different research, this region could contain a potential

cluster of genes or allelic variants with resistance to different pathogen races.

Co-mapping of QTL intervals identified in B. napus to its related species, B. rapa and B. oleracea

were performed for identifying genomic syntenic relationships. I found that most QTL intervals co-

mapped between B. napus and the corresponding species. This is an indication that the QTL

intervals in B. napus were originally contributed by the parental species. Synteny and conservation

between the B. napus, B. rapa and B. oleracea genome has been previously established (Parkin et

al., 2003, Rana et al., 2004, Jiang et al., 2011, Chalhoub et al., 2014). The comparative QTL

intervals between B. napus, B. rapa and B. oleracea revealed the majority of NBS-LRR genes in

associated QTL intervals are conserved suggesting that the QTL underlying these resistance traits

might show some structural and functional conservation. A study by Jiang et al. (2011) also found

that the QTL region for seed oil, total seed glucosinolates, and seed protein content were conserved

between the A sub-genome of B. rapa and B. napus.

The primary and homeologous QTL intervals in B. napus which existed in syntenic region between

the sub-genomes were originally derived from the genomic region of the ancestral genome and

distributed into two different genomic regions following genome hybridization. Werner et al. (2008)

has suggested that a resistance locus controlled by a major gene in the progenitor genome might

have been duplicated to give rise to two functionally different genes. Alternatively, a resistance

locus containing a cluster of genes within the progenitor genome may have separated into two

different genomic regions due to major chromosomal rearrangements. This further supports our

finding that the primary and homeologous QTL intervals on different chromosomes of B. napus

might result from genome rearrangement and duplication.

I also observed several QTL intervals in the B. napus sub-genome that had no counterpart QTL

intervals in the corresponding sub-genome of either A or C genome. However, they were

corresponding to either the A genome of B. rapa or C genome of B. oleracea. This indicates that the

two ancestral species are not likely to share disease resistance QTL. These could be species-specific

QTL.

107

Taken together, it is interesting to observe how the syntenic QTL intervals regions between B.

napus and its related species B. rapa and B. oleracea show similar gene content, sequence and

structural similarities of NBS-LRR genes. This would further assist in understanding their

conservation and evolution on the diversity of NBS-LRR genes.

4.5.2 Co-localization and association of NBS-LRR genes and QTL intervals

After the identification of QTL intervals, the association and co-localization between the QTL

intervals for disease resistance loci and NBS-LRR genes was analyzed. In this study, I found that

the identified QTL intervals for the three resistance traits appeared to co-localize with NBS-LRR

genes. The total number of NBS-LRR genes associated with the QTL intervals was 239 genes

representing approximately 37% of the total NBS-LRR genes in B. napus. This suggests that, as

expected, localization of QTL intervals for major resistance genes are correlated with the presence

of disease resistance genes. A similar co-localization between disease resistance QTL and NBS-

LRR resistance genes has been found in other plants (Kang et al., 2012, Wei et al., 2013). For

example, QTL resistance loci were found to be co-localized with NBS-LRR resistance genes and

resistance gene analogues (RGAs) in common bean (Geffroy et al., 2000), apple (Calenge et al.,

2005), Barley (Madsen et al., 2003) and potato (Bakker et al., 2011). Therefore, the association and

co-localization between NBS-LRRs and QTL disease resistance loci is a common feature of plant

genomes.

Furthermore, the correlation between NBS-LRR gene cluster and duplication within the 2 Mbp

flanking region of QTL intervals was studied. The majority of QTL intervals harbor NBS-LRR

gene clusters. There was a significant correlation and co-localization between the number of NBS

LRR genes within the QTL intervals and the number of genes involved in gene clusters or

duplication. This is consistent with previous studies which found QTL located in a resistance gene-

rich region harbouring NBS-LRR gene clusters which, confer resistance to a number of different

pathogens (Jeong et al., 2001, Wang et al., 2010).

A clustered region of NBS-LRR genes were found to be co-located with different QTL conferring

fungal resistance in soybeans (Kang et al., 2012). Moreover, synteny analysis between B. rapa and

Arabidopsis revealed that two clubroot resistance loci: Crr1 and Crr2, overlap and align to a region

in chromosome 4 of Arabidopsis (Suwabe et al., 2006). This region in Arabidopsis was previously

identified as containing clusters of disease resistance genes (Speulman et al., 1998). For example,

RPP5 for resistance to downy mildew pathogen Peronospora parasitica and RPS2 for resistance to

Pseudomonas syringae (Bevan et al., 1998, Suwabe et al., 2012).

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The correlation and association of NBS-LRR genes in the B. napus genome were apparent between

gene clusters and QTL intervals to a particular disease resistance. The duplicated NBS-LRR genes

are also retained in disease resistance QTL suggesting that genes involved in tandem duplication

raise the likelihood of creating redundant NBS-LRR genes underlying QTL resistance between

recently duplicated regions. This explains why the presence of gene clusters and duplications in a

major disease resistance QTL can play a role in the resistance evolution. In addition, this suggests

that the NBS-LRR genes are clustered and associated with particular QTL resistance loci in a

manner that reflects their functional relevance to disease resistance.

In this study, there was a correlation between the number of NBS-LRR genes within the QTL

intervals and the number of genes involved in gene clusters or duplication. Complex structures of

QTL can be as a result of resistance gene clustering and duplication leading to closely linked genes

which differ in their pathogen race specificity (Michelmore and Meyers, 1998). Thus, the clustering

of resistance genes in QTL intervals is advantageous by maintaining resistance while allowing

novel specificities to evolve. The results here provide evidence that NBS-LRR are distributed and

clustered throughout the genome and tend to be linked and associated with QTL intervals. These

QTL intervals containing gene clusters are likely to be major components of the resistance.

In order to validate whether the associated NBS-LRR genes with the identified QTL intervals are

related to any disease resistance genes that have been identified and sequenced in Brassica species.

I confirmed that B. rapa Cra clubroot resistance gene (Ueno et al., 2012) was orthologous and

conserved with a TIR-NBS-LRR gene in the reported CRa primary QTL intervals on chromosome

A3 in B. napus. Similarly, another B. rapa clubroot resistance gene Crr1a (Hatakeyama et al.,

2013) was also orthologous and conserved with a TIR-NBS-LRR in the primary Crr1a QTL

intervals on chromosome A8 in B. napus. Moreover, the blackleg LepR3 resistance gene (Larkan et

al., 2013) and Rlm2 candidate gene (Larkan et al., 2014) were found to be located within identified

LepR3 QTL intervals on chromosome A10 in B. napus. In addition, a Rlm4 blackleg candidate gene

was identified within the Rlm4 QTL intervals (Tollenaere et al., 2012).

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Chapter 5

Comparative analysis enabled the

identification of candidate Rlm9

blackleg resistance genes in Brassica

napus

110

Chapter 5 : Comparative analysis enabled the identification of candidate Rlm9

blackleg resistance genes in Brassica napus

5.1 Abstract

The availability of genome sequences of Brassica species have made it possible to study and

understand the structure of disease resistance genes in Brassica napus. This provides an invaluable

resource for the identification and comparative analysis of disease resistance genes. A total of 58

disease resistance genes on chromosome A7 of B. napus: 19 NBS-LRRs, 15 LRR-RLPs and 24

LRR-RLKs were identified. The gene content and order between B. napus and B. rapa was

consistent and further confirmed the chromosome microsynteny and conservation.

Twelve NBS-LRR and 18 LRR-containing genes on B. napus chromosome A7 were located within

a Rlm (Resistance to Leptosphaeria maculans) QTL region of interest. Through previous genetic

mapping studies, this region is known to harbour a cluster of genes: Rlm9, Rlm4, Rlm7, Rlm3 and

Rlm1 that confer resistance to blackleg disease (Leptosphaeria maculans), the most devastating

fungal pathogen of B. napus. The comparative analysis of resistance genes in the Rlm QTL revealed

that there was higher functional conservation of resistance genes in chromosome A7 of B. napus

and B. rapa than in chromosome C6 of B. napus and B. oleracea.

In this study, a candidate gene approach combined with comparative analysis was exploited for

identification of Rlm9 candidate genes in B. napus. Six NBS-LRR and eight LRR-containing genes

were associated with the Rlm9 QTL region. The NBS-LRR genes were selected for further analysis

as the highest priority candidate genes. It was possible to amplify and sequence these genes in B.

napus cultivars that differ in Rlm9-based resistance. This confirmed that three genes can be

excluded as no polymorphism was observed while another three genes became strong candidates for

further investigation. This chapter provides a detailed analysis of the identification of candidate

blackleg resistance genes and further understating of the structural conservation.

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5.2 Introduction

Genetic mapping studies showed that all Leptosphaeria maculans resistance genes in B. napus, the

most devastating fungal pathogen of B. napus, are found on the A genome of B. napus (Ananga et

al., 2006, Leflon et al., 2007) and are organised in clusters in two genomic regions: the Rlm2 and

LepR3 resistance genes on chromosome A10 (Pilet et al., 2001, Larkan et al., 2013, Larkan et al.,

2014) and five specific resistance genes: Rlm1, Rlm3, Rlm4, Rlm7, and Rlm9 are on chromosome

A7 (Delourme et al., 2004). A cluster of NBS-LRR genes on B. napus chromosome A7

corresponding to the mapped genetic resistance genes to L. maculans were identified based on a

marker homology based approach and genome wide NBS-LRR gene identification (described in

chapters 2 and 3). At present, none of these Rlm genes on chromosome A7 have been sequenced

and validated in B. napus.

A QTL for the Rlm9 resistance gene has been identified from a mapping population derived from B.

napus cultivars Darmor and Yudal (Delourme et al., 2004). This QTL is located on chromosome A7

of B. napus, which also contains other resistance genes: Rlm1, Rlm3, Rlm4 and Rlm7 (Delourme et

al., 2004). The identification of candidate blackleg resistance genes in B. napus has proven difficult

by map-based cloning approaches due to the complex genomic structure of this polyploid species

(Mayerhofer et al., 2005, Tollenaere et al., 2012).

An alternative approach called the candidate genes approach can be used to solve the problems

faced by map based cloning, in which QTL length intervals may be in mega base pairs (Mbp) and

include hundreds of genes. This approach is used to eliminate the need for fine mapping and

narrowing down the genomic regions by searching to discover the genes of interest all at once using

gene annotation and prediction. The rationale of the candidate gene approach is based on the

hypothesis that candidate genes should correspond to the loci controlling traits of interest if a

relationship between candidate gene and disease phenotype exist then significant polymorphism

between contrasting species or cultivars should be observed. Thus, comparison of disease resistance

genes between related species may provide insight into the conservation of these genes. Also,

comparison of syntenic loci known to harbour resistance genes may indicate candidate genes

governing the trait of interest that is yet to be identified. In a previous study, the collinearity

between B. napus and B. rapa was exploited to identify a number of candidate genes associated

with the Rlm4 blackleg resistance gene (Raman et al., 2012b, Tollenaere et al., 2012). In addition,

LepR3 gene identification and cloning was facilitated by the comparative collinearity of genetic

markers between B. napus and Arabidopsis (Larkan et al., 2013).

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A common feature of plant resistance genes is the presence of leucine rich repeats (LRR). The LRR

domain plays a major role in recognition of pathogen effectors by facilitating protein–protein

interactions (McDowell and Woffenden, 2003). The LRR domain is found in NBS-LRR, as well as

LRR-containing proteins. The NBS-LRR genes are the largest class of plant resistance genes and

function predominantly as disease resistance proteins. They are located intracellularly and may

interact directly or indirectly with the effector proteins encoded by Avr genes. In contrast, the LRR-

containing proteins, classified into LRR-receptor-like proteins (LRR-RLPs) and LRR-receptor-like

kinases (LRR-RLKs) have an extracellular LRR domain and are anchored to the plasma membrane

(Kruijt et al., 2005, Yang et al., 2012). The LRR-RLPs differ from LRR-RLKs in that they lack the

cytoplasmic kinase domain. LRR-RLPs and LRR-RLKs are involved in both defence and

developmental pathways and play a role in perceiving extracellular signals to initiate an

intracellular response (Fritz-Laylin et al., 2005, Kemmerling et al., 2011)

The availability of sequenced Brassicas genomes makes candidate genes discovery more effective

by offering genomics resources. These genomics resources can be combined together with

information from QTL mapping to enable disease resistance gene identification (NBS-LRR and

LRR containing genes) and in this study for comparative analysis to investigate the Rlm9 QTL

region for candidate genes that can have potential for future sequencing and validation.

In this chapter, identification and characterization of Rlm9 candidate genes was attempted using

genomics approaches. Firstly, the localization of disease resistance genes such as NBS-LRR and

LRR-containing genes in chromosome A7 of B. napus cv. Darmor were identified and association

with Rlm9 resistance performed (chapter 4). Secondly, SNP genotyping (Illumina Infinium assay)

was used to genotype a number of B. napus cultivars carrying different complements of Rlm genes,

including Rlm9-positive and Rlm9-negative B. napus cultivars for genome wide association studies

(GWAS) with the Rlm9 QTL. Then, the comparative analysis of disease resistance genes between

B. napus and other Brassica species can be performed to help to identify any functional sequence

variations.

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5.3 Methods

5.3.1 Brassica genome and gene prediction

The genome sequence and annotation of B. napus cv. Darmor v6 was used as the reference genome

(Chalhoub et al., 2014). The genome sequence of B. rapa v3.0 (Wang et al., 2011) and B. oleracea

cv. To1000 v1.0 (Parkin et al., 2014) were also used for comparative analysis. The NBS-LRR gene

annotation and identification was described previously chapters 2 and 3.

5.3.2 Identification of NBS-LRR and LRR- containing genes in B. napus

NBS-LRR candidate genes in B. napus were identified as described in chapter 2.

The identification of LRR containing proteins identification on A7 and C6 were based on

MAST/MEME output (chapter 2). All B. napus predicted genes were sorted by the MAST E-value.

Predicted genes containing more than 10 LRR motifs to be considered as LRR containing genes

with an E-value between -24 to 10 were selected. Then, they were further verified by BLASTp with

a threshold of E < -10 against the NCBI non-redundant (nr) protein database to check if they were

LRR-RLP or LRR-RLK.

5.3.3 Comparative analysis of NBS-LRR and LRR-containing gene on the A7 and C6

chromosome of B. napus

A reciprocal best BLAST (RBB) analysis of genes in B. napus was used to identify orthologous

genes in the B. rapa and B. oleracea genomes (chapter 3). The identification of homeologous or

paralogous genes were confirmed by the BLASTp comparison between genes between B. napus A7

and C6. In addition, the gene sequences were used to determine the syntenic positions between

chromosome A7 in B. napus and B. rapa, as well as chromosome C6 in B. napus and B. oleracea.

The genes showing homology and collinearity were regarded as syntenic genes. Then, the gene

sequences were aligned using CLUSTAL W in Geneious Pro v6.1.2 (Kearse et al., 2012).

5.3.4 Genetic mapping of the Rlm9 QTL

The genetic map position for Rlm9 was determined in a B. napus Darmor x Yudal mapping

population, segregating for blackleg resistance (Delourme et al., 2004). The markers underlying the

QTL on chromosome A7 were physically assigned to the B. napus Darmor A genome using

BLAST (Altschul et al., 1990) in Geneious Pro v6.1.2 (Kearse et al., 2012). The gene prediction

and genome wide identification of NBS LRR disease resistance across B. napus cv. Darmor

genome, particularly on chromosome A7, was used to identify the putative NBS-LRR or LRR-

114

containing genes to be selected as potential candidate genes for further analysis. Furthermore, all

Rlm9 candidate genes were subject to comparative sequence analysis between B. napus cv. Darmor,

B. napus cv. Tapidor and B. rapa.

Illumina short-sequence reads for B. napus cv. Skipton and cv. Ag-Spectrum, generated on the

Illumina Genome Analyser IIx (GAIIx) system, by the Batley lab, in collaboration with Prof

Edwards’ bioinformatics group, UQ, were mapped to the B. napus cv. Darmor genome by Prof

Edwards’ group. Given that Skipton is known to contain Rlm4 and Rlm9 genes, while Ag-Spectrum

contains Rlm9 (Raman et al., 2012), they were selected in this analysis. It is expected that there

would be no sequence variation in candidate Rlm9 genes when compared to cv. Darmor (Rlm9), but

they should show sequence variations if the candidate gene is Rlm4. The reads mapping in the

Rlm9 candidate genes underlying the Rlm9 QTL were visualized using Geneious Pro v6.1.2 (Kearse

et al., 2012) to assess sequence coverage and variation between the cultivars: Skipton and Ag-

Spectrum when compared to Darmor. Consensus sequences from short-sequence reads were

obtained for B. napus cultivars Skipton and Ag-Spectrum for each individual gene.

5.3.5 SNP genotyping of B. napus cultivars

Total genomic DNA was extracted from different B. napus cultivars and genotyped using a B.

napus custom array Infinium HD 60K assay with 52,157 SNPs throughout the B. napus genome as

implemented in the Illumina Infinium assay (Illumina Inc., San Diego, CA). The Infinium assay

was performed as described in the Illumina manual protocol.

SNP data processing, clustering and genotype calling were performed using the genotyping module

in the GenomeStudio software (Illumina, San Diego, CA) with default parameters. The software

assigns three clusters on a graph based on the fluorescence obtained. The clusters were reviewed

and manually edited when necessary. Limiting the analysis in this study to SNPs present on

chromosome A7, genotype calls for all SNPs loci were imported into Microsoft Excel 2013

(Microsoft) for further analysis.

For genotyping analysis, 26 B. napus cultivars including Darmor and Yudal were classified as Rlm9

resistant and susceptible cultivars based on the Rlm gene composition obtained from published

literature (Marcroft et al., 2012a) (Table 5.1). The cultivar Darmor (Rlm9 resistant) was selected as

a reference for the resistant individuals and Yudal (Rlm9 susceptible) for the susceptible

individuals. To aid in the comparison, all Darmor genotype calls were renamed as ‘AA’ and all

115

Yudal calls as ‘BB’, while the calls in the other lines varied depending on whether they carried the

Darmor or Yudal genotype at that position.

Table ‎5.1: List of B. napus cultivars genotyped with the SNP genotyping assay

B. napus cultivars

Rlm gene composition

Darmor Resistant reference Rlm9

Yudal Susceptible reference rlm9

Skipton

Positive Rlm9 cultivars

Rlm4 & Rlm9

Bravo-TT Rlm4 & Rlm9

Tornado-TT Rlm4 & Rlm9

AV-Sapphire Rlm4 & Rlm9

ATR-Stingray Rlm3 & Rlm9

ATR_Cobbler Rlm4(H) & Rlm9(H)

Ag-Spectrum Rlm9(H)

ATR-Stingray Rlm3 & Rlm9

Dunkeld

Negative Rlm9 cultivars

Rlm4

Nurendra Rlm4

Telfer Rlm4

Thunder-TT Rlm4

ATR-Summit Rlm4

Monty_028DH Rlm4

Taparoo Rlm3

Carousel Rlm1 & Rlm2

Surpass400 Rlm1 & RlmS

Argyle Rlm1 & RlmS

B2 B. napus "Lynx_037DH"

Unknown

C2 B. napus "Ningyou7"

RSO

Trilogy

Trigold

Boomer

“H” Indicates partial resistance.

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5.3.6 Extraction of genomic DNA

Seeds for B. napus cultivars used in this study were obtained from a seed collection at the Batley

lab at the University of Queensland. They were germinated and planted in small polyvinyl pot filled

with potting mix in a temperature controlled glasshouse under 28o

C with natural lighting. Young

leaf tissue was collected for DNA extraction.

Genomic DNA was extracted from the different B. napus cultivars, according to a DNeasy Plant

Mini Kit (QIAGEN). Approximately 200 mg of leaf tissue was ground (dry) with a pestle and

mortar, sitting in liquid nitrogen, into a fine powder, then, transferred into a 1.5 mL microcentrifuge

tube. Then DNA was extracted following the manufacturer’s instructions. DNA concentration and

purity were measured using the NanoDrop (ND-1000 Spectrophotometer, Thermo Scientific). DNA

was also electrophoresed on a 1% TAE agarose gel containing ethidum bromide at 100 V for 30

min to check the DNA quality.

5.3.7 PCR amplification and sequencing of Rlm9 candidate genes

The selected Rlm9 candidate genes were amplified from genomic DNA of B. napus cv. Darmor and

B. napus cv. Yudal as well as other B. napus cultivars (Table 5.2) using PCR with the primers

listed in Table 5.3.

The primers pairs were designed based on the B. napus Darmor reference genome (Chalhoub et al.,

2014). The primer pair specificity was checked by BLAST analysis against the whole genome to

avoid non-specific binding as a result of duplications.

Long range PCR was carried out using the Expand Long Template PCR kit (Roche) following the

manufacturer’s instructions. A 50 ng aliquot of genomic DNA was amplified in a reaction mix

containing 1x PCR buffer, 1 U DNA polymerase mix, 500 μM dNTPs, and 400 nM forward and

reverse primers. The thermal cycling conditions were: 92 °C for 2 min; followed by 10 cycles of 92

°C for 10 sec, Tm °C for 15 sec, 68 °C for 60 sec/1Kbp; followed by 25 cycles of 92 °C for 10 sec,

Tm °C for 15 sec, 68 °C for 60sec/1Kbp +20 sec increment each cycle; then 68 °C for 7 min. PCR

products were resolved by electrophoresis in a 1 % agarose gel stained with ethidium bromide.

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Table ‎5.2: List of the B. napus cultivars and their Rlm complement used for the PCR amplification

B. napus cultivar Rlm composition Remarks

Darmor Rlm9 Resistant Rlm9 reference. It is the reference genome for B. napus.

Yudal rlm9 Susceptible Rlm9 reference

Tapidor Rlm2 The genome sequence was available in-house.

Skipton Rlm4 and Rlm9 They have short sequence reads available. They both

contain the Rlm9 gene, but differ in Rlm4 Ag-Spectrum Rlm9

Jet Neuf Rlm4 and Rlm1

Westar No Rlm Used as negative control because it has no Rlm gene

Table ‎5.3: List of primer pairs used for long range PCR amplification of Rlm9 candidate genes

Target gene

sequence 5' --------> 3' Product size bp

PCR and sequencing

Results

BnDRG 13 and 14

F. TCCACGCTTACAACGGATAATTCTAGCC 14,900 Successful

R. ACAGCAGATGGATTACACGTACAACACC

BnDRG 17

F. GTTCTAAGGCTCTGACCAGTGT 3,000

Not Successful

R. CGGTGGCAGTGTTTCGAAACAT

F. TTACGGTTAGTACTTAGTAGCGGTGG

4,200 Not

Successful R. GCTTGTGCAGTTGAAGAATGGATAAC

F. ACTGCTATATTGTTATAGGTCGGCCG 2,000

Not Successful

R. TTGATGTTCTAAGGCTCTGACCAGTG

BnDRG 19

F. CGGTTCGTAAGCCACCTAATCTAAGACC 17,500

Not Successful

R. GAATCGGAATTGAGGAGAGGCTTAGAGG

F. GTAGCTATGTTCTCTCCGAGTATCCAC 11,800

Not Successful

R. GAAGGAAGTAGTAGAGCCAAGCATGAC

F. ATGCCAAATTTCTGCGTTTCG 1,740

Successful but not

sequenced R. TCAGGTCGAAATGTTGGAGGA

F. TTGGCCATATTATTCGGAACCG 6,400

Successful for all

cultivars except Ag-

R. GTAGTCACCTATGTACATCCGC

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Spectrum

BnDRG 20

F.CTAAGCCTCTCCTCAATTCCGATTCAGC 18,000

Not Successful

R. GTCTACAGGTTGAAGTACACGATCTGGC

F. TGAAGACATTACGGTCGACTATGC 18,900

Not Successful

R. GAGAAGATCGTCGGTGCATTAACG

F. AGTATAGGATACGGTGTTGTAGTGCC 18,900

Not Successful

R. CTTGAGAAGATCGTCGGTGCATTAAC

F. TTACAGTGATGACTAGTTCATGGCCG

6,400

Successful for all

cultivars except Ag-Spectrum

R. TTGCTAGCTCATTACTGATCTCGGAG

F. ATGGCTTCTTCTTCTCACCGG ATA AGG

4,000

Successful for all

cultivars except Ag-Spectrum

R. CTAATCCATTGCGCTGCTACTACT CTC

BnDRG 23 F. CTTCAGGGTTGGTCCATTGGCACATGTC

16,000 Successful R. GTCATCTTCCTCACAGTCATCGTCAAGG

5.3.8 DNA Sequencing and Sequence Analysis

Purified PCR products were sequenced using the Sanger sequencing method via the Australian

Genome Research Facility (AGRF, http://www.agrf.org.au). Sequencing samples were prepared and

submitted according to AGRF guidelines to be sequenced in both forward and reverse directions.

Raw sequences (ABI sequence chromatograms), obtained from AGRF, were analyzed using

Geneious Pro v6.1.2 (Kearse et al., 2012). The sequence analysis included mapping to reference

genome or de novo assemblies and sequenced candidate gene from cultivars, nucleotide and protein

alignments. Then, full gene sequence and sequence variation were confirmed.

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5.4 Results

5.4.1 Identification and characterization of NBS LRR and LRR-containing genes on B.

napus chromosome A7

Based on the genome wide NBS-LRR identification, 19 NBS-LRR genes on chromosome A7 of B.

napus were identified (Table 5.4). Further sequence analysis and characterization of these candidate

NBS LRR genes indicated that 10 genes contained a typical motif pattern characteristic of NB-LRR

proteins: three CNLs and seven TNLs. The other genes were truncated. Four of them were truncated

with the TIR-NBS domain, but lacking the LRR domain. Truncated genes lacking a portion of the

NBS domain or the LRR region are often associated with typical NBS-LRR genes, but, due to

frameshift mutation or deletion, they become truncated. Five genes were TIR-containing proteins.

In addition, LRR-containing genes were identified by MEME/MAST analysis. This identified 15

Leucine-rich repeat receptor-like proteins (LRR-RLPs) genes and 24 Leucine-rich repeat receptor-

like kinase (LRR-RLKs) genes (Table 5.4).

There was correlation in the number of genes between the NBS-LRR and LRR-containing genes.

The majority of disease resistance genes are distributed towards the distal end of the short arm of

chromosome A7. The LRR-RLPs and LRR-RLKs genes were found to be clustered or dispersed

with the NBS-LRR genes. There were four gene clusters. The largest gene cluster consisted of five

NSB-LRR genes and five LRR-containing genes. Two gene clusters were located within the Rlm

QTL region (Figure 5.1).

Annotation of these NBS-LRR and LRR-containing genes on chromosome A7 show they share

high homology to known disease resistance genes in other plant species. They were designated

BnDRG 1 (Brassica napus Disease Resistance Gene 1) to BnDRG 58 (Table 5.4).

120

Table ‎5.4: List of characterized NBS-LRR and LRR-containing genes on chromosome A7 of B.

napus cv. Darmor. Candidate Rlm9 genes located within the Rlm9 QTL are highlighted

Given name GenBank AC Gene Position on B. napus

Darmor V6 Gene class

BnDRG 1 CDY31987 GSBRNA2G00050797001 412,213 LRR-RLP

BnDRG 2 NA GSBRNA2G00067320001 1,179,872 LRR-RLP

BnDRG 3 CDY31412 GSBRNA2T00047634001 3,824,209 LRR-RLP


BnDRG 5 CDX77472 GSBRNA2T00128337001 8,533,320 LRR-RLP

BnDRG 6 CDY43181 GSBRNA2G00076179001 10,010,633 LRR-RLK





BnDRG 11 CDY15668 GSBRNA2T00089880001 11,054,163 LRR-RLK

BnDRG 12 CDY01430 GSBRNA2T00112430001 13,928,484 LRR-RLK

BnDRG 13 CDY01454 GSBRNA2T00112460001 14,052,790 NBS-LRR (CNL)

BnDRG 14 CDY01455 GSBRNA2T00112461001 14,057,850 NBS-LRR (CNL)



BnDRG 17 CDY67955 GSBRNA2T00068325001 16,055,043 NBS-LRR (TNL)

BnDRG 18 CDX67490 GSBRNA2G00098602001 16,703,378 LRR-RLK

BnDRG 19 NA chrA07-snap.4041 16,765,735 NBS-LRR (TNL)

BnDRG 20 CDX67500 GSBRNA2T00098616001 16,783,435 NBS-LRR (TNL)

BnDRG 21 CDX67564 GSBRNA2G00098700001 17,128,516 LRR-RLP


BnDRG 23 CDX67660 GSBRNA2T00098829001 17,769,448 NBS-LRR (CNL)

BnDRG 24 CDX67736 GSBRNA2T00098923001 18,186,595 LRR-RLK

















121

BnDRG 41 CDY38804 GSBRNA2G00066610001 24,695,717 LRR-RLP


BnDRG 43 NA GSBRNA2G00102501001 25,150,024 LRR-RLK






BnDRG 49 NA GSBRNA2T00102609001 25,598,597 NBS-LRR (TNL)










Figure ‎5.1: Distribution of NBS-LRR and LRR-containing genes on chromosome A7 of B. napus.

Different colours represent different gene types: blue (TNL), red (CNL), green (LRR-RLKs) and

yellow (LRR-RLPs). Genes inside the black rectangles are in a gene cluster. The Genes inside the

red rectangle are within the Rlm QTL.

122

5.4.2 Comparative analysis of NBS-LRR and LRR-containing genes on chromosome A7 of

B. napus

In order to study the gene conservation between chromosome A7 and its homeologous chromosome

C6 in the Brassica species: B. napus, B. rapa and B. oleracea, the protein sequences and gene

collinearity were compared. The total numbers of NBS-LRR and LRR-containing genes were

consistent (Table 5.5). Genes in B. napus showed good orthology and collinearity relationships

with genes in B. rapa and B. oleracea (Figures 5.2 and 5.3). The B. napus chromosome A7 is

collinear and syntenic around gene clusters to the same chromosome of B. rapa which includes non-

collinear genes. Likewise, the B. napus chromosome C6 also exhibited the same gene pattern to B.

oleracea. The majority of the NBS-LRR and LRR-containing genes of B. napus chromosomes A7

and C6 have orthologs in B. rapa and B. oleracea, although a number of genes showed presence

and absence between species.

Table ‎5.5: Comparative analysis of the number of NBS-LRR and LRR-containing genes on

chromosomes A7 and C6 of the three Brassica species: B. napus, B. rapa and B. oleracea

Species

Gene

The whole chromosome Within Rlm QTL

B. n

ap

us

A0

7

B. n

ap

us

C0

6

B. r

ap

a

A0

7

B. o

lera

cea

C

06

B. n

ap

us

A0

7

B. n

ap

us

C0

6

B. r

ap

a

A0

7

B. o

lera

cea

C

06

NBS-LRR 19 44 18 45 12 18 9 18

LRR-RLP 15 10 14 9 9 6 9 6

LRR-RLK 24 25 23 25 9 8 8 7

Total 58 79 55 79 30 32 26 31

The comparison revealed that 14/19 (73%) and 34/39 (87%) genes of NBS-LRR and LRR-

containing genes, respectively, between A7 B. napus and B. rapa were highly conserved with high

protein sequence similarity. Six and 12 genes of NBS-LRR and LRR-containing genes,

respectively, were not collinear. Four and three genes of NBS-LRR and LRR-containing genes,

respectively, showed substantial protein sequence differences. Three NBS-LRR genes showed

presence and absence between the species (Figures 5.2 and 5.3).

The comparison also revealed that 27/44 (61%) and 33/35 (68%) genes of NBS-LRR and LRR-

containing genes, respectively, between chromosome C6 of B. napus and B. oleracea were highly

conserved with high protein sequence similarity and collinearity. Two and 10 genes of NBS-LRR

123

and LRR-containing genes, respectively, were not collinear. Six NBS-LRR genes showed

substantial protein sequence differences. No NBS-LRR and LRR-containing genes showed

presence and absence variation between species (Figures 5.2 and 5.3).

Furthermore, the resistance genes between A7 and C6 B. napus are considered homeologous

(duplicates). The comparison between chromosomes A7 and C6 B. napus revealed that 14 of each

NBS-LRR and LRR-containing genes between A7 B. napus and B. rapa were homeologous

between chromosomes A7 and C6 of B. napus. There were 6/14 (42%) and 14/14 (100%) genes of

NBS-LRR and LRR-containing genes, respectively, highly conserved with high protein sequence

similarity. One and five genes of NBS-LRR and LRR-containing genes, respectively, were not

collinear. Six NBS-LRR genes showed substantial protein sequence differences (Figures 5.2 and

5.3).

Taken together, the comparison revealed that the LRR-containing genes showed higher sequence

conservation than the NBS-LRR genes. The NBS-LRR genes show protein sequence divergence

and presence and absence while, the LRR-containing genes show non-collinearity.

In order to be more specific, the NBS-LRR and LRR-containing genes within the Rlm QTL were

the great of interest for the comparison. Twelve NBS-LRR and 18 LRR-containing genes were

identified to be located within the Rlm QTL. There were slight differences in the gene number

between the chromosomes A7 of B. napus and B.rapa as well as chromosomes A7 and C6 of B.

napus (Table 5.5). These identified resistance genes could be Rlm9, Rlm4, Rlm, Rlm3 or Rlm1

candidates for blackleg disease resistance. However, because B. napus cv. Darmor is carrying Rlm9

gene, it is expected that the comparison should be informative within the Rlm9 QTL rather than

other Rlm QTL.

The comparison of NBS-LRR and LRR-containing genes within the Rlm QTL between

chromosome A7 in B. napus and B. rapa showed that 10 and 17 genes of NBS-LRR and LRR-

containing genes in B. napus were orthologous and conserved with B. rapa. Three NBS-LRR genes

showed substantial differences with 85, 84 and 87% amino acid identity, but one LRR-containing

genes showed substantial differences with 98% amino acid identity and 50% sequence aligned

coverage. Two NBS-LRR genes were absent from the A7 B. rapa (Figure 5.2 and 5.3).

To find the homeologous relationship between genes on chromosomes A7 and C6, the NBS-LRR

and LRR-containing genes within the Rlm QTL between the two homeologous chromosomes: A7

and C6 in B. napus were compared. Seven NBS-LRR genes were homeologous. Four NBS-LRR

124

gene were conserved with 96, 95, 93, 95% amino acid identity. Three genes showed substantial

differences with 88, 84 and 80% amino acid identity. There were five genes on chromosome A7

that were not homeologous. Only one gene was not collinear (Figure 5.2). Likewise, Seven LRR-

containing genes were homeologous with two genes on chromosome A7 that were corresponding to

two duplicates copies on chromosome C6. These genes showed high conservation with >94%

amino acid identity and 90% amino acid identity. Two genes were not collinear (Figure 5.3). There

were 11 genes on chromosome A7 that were not homeologous.

Above all, there were considerable variations, collinearity, presence/absence or substantial

differences in the protein sequence of several NBS-LRR and LRR-containing genes within the Rlm

QTL region, particularly in the Rlm9 QTL of interest. This comparison confirmed that the genes in

the Rlm9 QTL did not show good conservation and chromosome collinearity. For example, the

observed differences within the Rlm QTL between chromosome A7 of B. rapa and B. napus

indicated that there were three NBS-LRR genes and five LRR-containing genes, located in the Rlm9

QTL of interest that showed non-collinearity. There was also one NBS-LRR gene that was absent

from B. rapa and three NBS-LRR genes that showed substantial protein sequence differences.

Similarly, within the Rlm QTL between chromosome A7 and C6 in B. napus, there was one NBS-

LRR gene and three LRR-containing genes showing non-collinearity. Three and four NBS-LRR

LRR-containing genes, respectively, were not homeologous.

125


between B. napus (Bn), B. rapa (Br) and B. oleracea (Bo). The squares and triangles represent

NBS-LRR; TNL and CNL, respectively. Orthologous genes are connected by lines. Genes within

circles are clustered. The numbers represent the amino acid alignments with alignment coverage in

bracket. Different colours represent different domain structures of TNL and CNL genes: blue (TIR-

NBS-LRR), red (CC-NBS-LRR), yellow (TIR- NBS or CC-NBS), green (NBS-LRR), orange

(NBS) and purple (TIR).

126

Figure ‎5.3: Comparative chromosomal map of LRR-containing genes on chromosomes A7 and C6

between B. napus (Bn), B. rapa (Br) and B. oleracea (Bo). The yellow and green semicircles

represent LRR-RLP and LRR-RLK genes, respectively. Orthologous genes are connected by lines.

Genes within circles are clustered. The numbers represent the alignment coverage with amino acid

alignments in brackets

127

5.4.3 Haplotype analysis of Rlm9 and mapping potential SNPs in B. napus

A 60 K Illumina Infinium SNP genotyping assay was performed for GWAS analysis to determine

the SNP association between the B. napus Darmor (Rlm9 resistant) genotype and B. napus Yudal

(Rlm9 susceptible) for blackleg resistance. This allows identification of any haplotypes associated

with Rlm9 resistance genes located in the QTL region on chromosome A7. A total of 26 B. napus

cultivars with different Rlm gene composition were also included in the assay, phenotypic data for

all cultivars was based on resistance and susceptibility to the blackleg disease reported in the

literature (Marcroft et al., 2012a).

The haplotype analysis of the 60K SNPs genotyping data was analysed based on the Rlm9 resistant

and susceptible B. napus cultivars, Darmor and Yudal, respectively. A total of 813 out of 2467

SNPs on chromosome A7 were polymorphic between the cultivars Darmor and Yudal. The majority

of SNPs on chromosome A7 did not show significant correlation with the resistance genotype

between different B. napus cultivars with different Rlm genes. However, a set of 10 SNPs with good

correlation patterns were observed to distinguish the resistance and susceptible phenotype within a

region on chromosome A7 (Table 5.6).

These SNPs showed 100% association to the Rlm9 resistant phenotype in all cultivars predicted to

carry the Rlm9 gene, except for the cultivar Ag-Spectrum. Ag-Spectrum, one of cultivars predicted

to be carrying Rlm9, showed association with the Rlm9 susceptible phenotype (Table 5.6). In

contrast, these ten SNPs did not show 100% association to the Rlm9 susceptible phenotype between

all cultivars predicted not to be carrying the Rlm9 gene. For example, Dunkeld, Argyle, Narendra,

ATR-Summit, and Taparoo showed the SNP genotype associated with the Rlm9 resistant

phenotype, even though they are classified as susceptible cultivars (Table 5.6).

Physical location and annotation of the SNP positions on the B. napus Darmor revealed that these

SNPs were located on chromosome A7 within the region between 12,606,759 bp to 14,533,279 bp

(Table 5.7). This region contained 85 SNPs being assayed, but only these ten SNPs identified in

this study were showing a good association to Rlm9 resistant phenotype. Two of them, SNPs (Bn-

A07-p9079474 and Bn-A07-p9791002), were located in predicted genes on A7. These were

annotated as zinc finger protein transcription factors and receptor protein kinase-like protein (LRR-

RLK), respectively.

128

Table ‎5.6: The potential SNPs on chromosome A7 with a good correlation to the Rlm9 gene and association with disease and susceptibility in B. napus

cultivars. AA allele refers to Darmor resistant allele and BB allele refers to Yudal susceptible allele. NA indicates a no genotype call

Resistance ( Rlm9 positive)

Susceptibale ( Rlm9 negative)

Unknown

SNP ID

Dar

mo

r

Skip

ton

Bra

vo-T

T

Torn

ado

-TT

ATR

-Sti

ngr

ay

ATR

_Co

bb

ler

Ag-

Spe

ctru

m

Y

ud

al

Du

nke

ld

Nu

ren

dra

Telf

er

Thu

nd

er-

TT

ATR

-Su

mm

it

Mo

nty

_02

8D

H

Tap

aro

o

Car

ou

sel

Surp

ass4

00

_0

24

DH

Arg

yle

B

2 B

. nap

us

"Lyn

x_0

37

DH

"

C2

B. n

apu

s "N

ingy

ou

7"

RSO

Trilo

gy

Trig

old

Bo

om

er

Bn-A07-p8531068 AA AA AA AA AA AA BB BB AA AA BB BB AA AA AA BB AA AA BB AA AA BB BB BB

Bn-A07-p8854569 AA AA AA AA AA AA BB BB AA AA BB BB AA BB AA BB BB AA AA AA AA BB BB BB

Bn-A07-p8745024 AA AA AA AA AA AA BB BB AA AA BB BB AA AA AA BB BB AA BB BB AA BB BB BB

Bn-A07-p8775069 AA AA AA AA AA AA BB BB AA AA BB BB AA BB AA BB BB AA BB NC AA BB BB BB

Bn-A07-p8941260 AA AA AA AA AA AA BB BB AA AA BB BB AA BB AA BB BB AA AA AA AA BB BB BB

Bn-A07-p9020570 AA AA AA AA AA AA BB BB AA AA NA NA AA BB AA NA NA AA AA AA AA BB BB NA

Bn-A07-p9079474 AA AA AA AA AA AA BB BB AA AA BB BB AA AA AA BB BB AA AA AA AA BB BB BB

Bn-A07-p9791002 AA AA AA AA AA AA BB BB AA AA BB BB AA BB AA BB BB AA AA AA BB BB BB BB

Bn-A07-p9831545 AA AA AA AA AA AA BB BB AA AA BB BB AA BB AA BB BB AA AA BB BB BB BB BB

Bn-A07-p10347794 AA AA AA AA AA AA BB BB AA AA BB BB AA AA BB BB AA AA BB AA BB BB BB BB

129

Table ‎5.7: Mapping and annotation of the potential SNPs identified in B. napus cv. Darmor

SNP ID SNP B. napus Darmor v6

origin SNP

SNP in Darmor

location of SNP Predicted gene Blast hit chro

position top hit

Bn-A07-p8531068 [A/C] chrA07 12,606,759 A A Intergenic region GSBRNA2G00085931001 and GSBRNA2G00085930001

No hit

Bn-A07-p8854569 [T/C] chrA07 12,855,583 T C Intergenic region GSBRNA2G00030498001 and GSBRNA2G00030500001

No hit

Bn-A07-p8745024 [A/C] chrA07 13,039,112 A C Intron GSBRNA2G00112258001 or chrA07-snap.3025 and 3026

nodulin family protein

Bn-A07-p8775069 [T/C] chrA07 13,075,780 T T Intron GSBRNA2G00112264001 or chrA07-snap.3045

protein disulfide isomerase

Bn-A07-p8941260 [A/C] chrA07 13,262,125 A A 3’ UTR chrA07-snap.3091 putative pol polyprotein

Bn-A07-p9020570 [T/C] chrA07 13,325,277 T C 5’ UTR GSBRNA2G00112311001 or chrA07-snap.3110

small nuclear ribonucleoprotein helicase-like

Bn-A07-p9079474 [A/G] chrA07 13,391,183 A A Exon GSBRNA2G00112326001 or chrA07-snap.3130

zinc finger protein transcription factors

Bn-A07-p9791002 [T/C] chrA07 13,925,780 T T 5’ UTR chrA07-snap.3302 and 3303 receptor protein kinase-like protein

Bn-A07-p9831545 [T/C] chrA07 13,956,273 T T Intergenic region GSBRNA2G00112433001 and GSBRNA2G00112434001 or chrA07-snap.3307 and 3308

No hit

Bn-A07-p10347794 [A/G] chrA07 14,533,279 A G 5’ UTR chrA07-snap.3457 No hit

130

5.4.4 The identification of candidate Rlm9 blackleg resistance genes in B. napus

An Rlm9 QTL was identified on chromosome A7 through a marker based approach where linked

markers were physically mapped to the reference B. napus genome. The Rlm9 QTL was roughly

spanning 5 Mbp in the B. napus Darmor chromosome A7 from 13,488,533 Mbp to 19,031,520

Mbp. In addition, the potential ten SNPs, identified from haplotype analysis, were physically

mapped to B. napus Darmor chromosome A7 located near or within the Rlm9 QTL region (Figure

5.4). The genome wide identification of disease resistance genes enabled the identification of six

NBS-LRR and eight LRR-containing genes co-localized with the Rlm9 QTL region.

131

Figure ‎5.4: Mapping based identification of the Rlm9 candidate gene using marker physical mapping, NBS LRR genome wide identification and SNP

haplotypes. Different colours represent different gene types: blue (TNL), red (CNL), green (LRR-RLKs) and yellow (LRR-RLPs). The orange triangles

represent the identified SNPs associated with Rlm9 resistance. Genes inside the black rectangles are in a gene cluster. The genes inside red rectangle

are within the Rlm QTL.

132

The following results describe the comparative analysis of six NBS-LRR candidate genes (Table

5.8).

5.4.4.1 Candidate gene BnDRG 13

The BnDRG 13 gene has a coding region consisting of seven exons of 2613 bp in length encoding a

870 aa protein This gene is a typical CC-NBS-LRR (CNL) consisting of the three domains: CC,

NBS and LRR. It has no homeologous copy in the C genome of B. napus cv. Darmor. The gene is

orthologous and in a collinear position in B. rapa chromosome A7 and showed 99% amino acid

identity (Table 5.8 and Figure 5.5). The corresponding gene in B. rapa is lacking the CC domain.

The gene is also present and in a collinear position in B. napus cv. Tapidor and showed 99% amino

acid identity. The gene in B. napus cv. Tapidor lacks half of the CC domain (about the first 60 aa)

(Table 5.8 and Figure 5.5). The gene had high coverage of Ag-Spectrum sequence reads of 80%

with 98% DNA sequence identity, whereas Skipton showed low read coverage of about 5% (Table

5.9 and Figure 5.11).


The BnDRG 14 gene has a coding region consisting of five exons of 2244 bp in length encoding a

754 aa protein. This gene is a typical CNL. It has no homeologous copy in the C genome of B.

napus cv. Darmor. The gene is orthologous and in a collinear position in B. rapa chromosome A7

and showed 99% amino acid identity in the NBS and LRR domain but showed substantial sequence

variation at the CC domain (Table 5.8 and Figure 5.6). The gene is also present in a collinear

position in A7 B. napus cv. Tapidor. Most of the gene shared 100% amino acid identity except a

region of about 60 aa where there was substantial difference in the CC domain (Table 5.8 and

Figure 5.6). The gene had high coverage of Skipton sequence reads (78%) with 98% DNA

sequence identity, whereas Ag-Spectrum showed low read coverage of about 5% (Table 5.9 and

Figure 5.11).


The gene BnDRG 17 has a coding region consisting of two exons of 1296 bp in length encoding a

431 aa protein. This gene is a truncated TNL consisting of two domains TIR and NBS and lacking

the LRR domain. It has a homeologous copy as a duplicate on chromosome C6 of B. napus cv.

Darmor. This duplicate copy is also truncated and not in a collinear position with 95% amino acid

identity (Table 5.8 and Figure 5.8). The gene is orthologous and not in a collinear position on

chromosome A7 in B. rapa with 97% amino acid identity (Table 5.8 and Figure 5.7). It is missing

the first 23 aa of the TIR domain in B. napus Darmor compared to B. rapa. The gene seems to be

133

present in an unplaced chromosome of B. napus cv. Tapidor, but, it was not possible to compare the

entire sequence similarity because of presence of N-gapped sequence in B. napus Tapidor. There

were no Skipton or Ag-Spectrum sequence reads for this gene.

5.4.4.4 Candidate gene BnDRG19

The gene BnDRG19 has a coding region consisting of three exons of 2763 bp in length encoding a

920 aa protein. This gene is a truncated TNL lacking the TIR domain and contains the NBS and

LRR domains. It has a homeologous copy as duplicate on chromosome C6 of B. napus cv. Darmor.

This duplicate copy is also truncated and not in collinear position with 96% amino acid identity

(Table 5.8 and Figure 5.8). The gene is orthologous and not in a collinear position in B. rapa on

chromosome A2 with 97% amino acid identity (Table 5.8 and Figure 5.8). The corresponding

gene in B. rapa is a typical TNL. The gene is also present on chromosome A7 B. napus cv. Tapidor

and showed 95% amino acid identity with a deletion of 30 aa in the NBS domain (Table 5.8 and

Figure 5.8). There was high coverage of Skipton and Ag-Spectrum sequence reads of about 99%

and 86% of the gene with 100% and 98% DNA sequence identity, respectively (Table 5.9 and

Figure 5.11).

5.4.4.5 Candidate gene BnDRG20

The gene BnDRG20 has a coding region consisting of four exons of 2979 bp in length encoding a

992 aa protein. This gene is a typical TNL containing all three domains: TIR, NBS and LRR. It has

a homeologous copy as a duplicate on chromosome C6 of B. napus cv. Darmor. This duplicate copy

is also a typical TNL and not in a collinear position and showed 88% amino acid identity (Table 5.8

and Figure 5.9). The gene is orthologous and not in a collinear position on chromosome A2 in B.

rapa and showed 98% amino acid identity (Table 5.8 and Figure 5.9). This gene is not present in

B. napus cv. Tapidor. There was high coverage of Skipton sequence reads covering 96% with 100%

DNA sequence identity, whereas, the Ag-Spectrum sequence reads coverage was about 55% of the

gene with 99% DNA sequence identity (Table 5.9 and Figure 5.11).


The gene BnDRG23 has a coding region consisting of six exons of 2346 bp in length encoding a

781 aa protein. This gene is a truncated CNL lacking the CC domain and consisting of the NBS and

LRR domains. It has no homeologous copy in the C genome of B. napus cv. Darmor. This gene is

not present in B. rapa. The gene is present on chromosome A7 of B. napus cv. Tapidor and showed

81% amino acid identity (Table 5.8 and Figure 5.10). There was high coverage of Skipton and Ag-

134

Spectrum sequence reads of about 90% and 98% of the gene with 100% DNA sequence identity,

respectively (Table 5.9).

5.4.5 Amplification and sequencing of Rlm9 candidate genes

The comparative analysis of NBS-LRR genes gave an initial indication that these genes could be

candidate Rlm9 genes because of their conservation or sequence variation between B. napus Darmor

(Rlm9 resistant) and B. rapa.

In order to validate these candidate genes, individual genes were amplified and sequenced using

primer pairs designed based on B. napus cv. Darmor sequence as a reference. In this study,

sequencing of six Rlm9 candidate genes is being attempted in B. napus Darmor and Yudal, resistant

and susceptible cultivars, respectively. It was very difficult to develop gene specific primers

because the B. napus genome is polyploid, highly duplicated and sequence similarity between the A

and C genome exists extensively between homeologous chromosomes.

BnDRG 13, BnDRG 14 and BnDRG 23 were successfully amplified and completely sequenced the

gene from B. napus cv. Darmor and c.v Yudal and no polymorphism was observed. I did not test

these on other B. napus cultivars because no polymorphism was observed. The two potential genes:

BnDRG 19 and BnDRG 20 were successfully amplified and sequenced complete gene sequence

from different B. napus cultivars: Darmor, Yudal, Skipton, Tapidor, Jet Neuf and, but no

polymorphism was observed. These two genes: BnDRG 19 and BnDRG 20 failed to amplify from

B. napus Ag-Spectrum and Westar. The presence of the BnDRG 20 gene in B. napus cv. Tapidor

was confirmed and showed 100% identity even though the comparative analysis of BnDRG 20

showed that was not present in B. napus Tapidor genome (Table 5.8). The amplification of the

candidate BnDRG 17 gene was not successful with any of B. napus cultivars.

135

Table ‎5.8: Comparative analysis of NBS-LRR Rlm9 candidate genes between B. napus cv. Darmor, B. napus cv. Tapidor and B. rapa. The sequence

identity is based on protein sequence alignment

Rlm9 gene in B. napus Darmor

A genome v6 B. napus Darmor C genome B. rapa v1

B. napus Tapidor A genome

Gene position Gene Identity (aligned coverage)

position Gene Identity (aligned coverage)

position Gene Identity (aligned coverage)

Position in Tapidor v4

BnDRG 12 870aa

14,052,790 Not present XA07-Bra012116 693aa

99 (80)

9,918,855 chrA07-snap.3272 805aa

99(94)

8,509,720

BnDRG 14 754aa

14,057,850 Not present XA07-Bra012114 735

84(100) 9,930,135 chrA07- snap.3274 755aa

100(90)

8,504,784

BnDRG 17 431aa

16,055,043 chrC06 GSBRNA2T00-049133001 432aa

95(100)

30,798,375 XA07-Bra003864 454aa

97(94)

15,441,277 unplaced

98 % of aligned sequence (not possible to check the entire gene due to N-gapped sequence in Tapidor)

BnDRG 19 920aa

16,765,735 chrC06 GSBRNA2T00-057893001 918aa

96(100)

19,526,985 XA02-Bra028499 1077aa

97( 85)

696,153 chrA07- snap.3935 921aa

95(100)

10,3013,17

BnDRG 20 992aa

16,783,435 chrC06 GSBRNA2T00-057889001 933aa

88(90)

19,487,657 XA02-Bra028500 992aa

98(100)

714,674 Not present

BnDRG 23 781aa

17,769,448 Not present Not present chrA07- snap.4091 905aa

81(100)

10,9775,76

136

Table ‎5.9: The coverage of Skipton and Ag-Spectrum sequence short reads of candidate Rlm9 genes on B. napus. The identity is based on gene

sequence alignment

Rlm9 gene in

B. napus Darmor

Sequence Reads B. napus Skipton

Sequence Reads B. napus Ag-Spectrum

Gene Coverage % Identity% Coverage % Identity%

BnDRG 13 3635bp

Very low coverage 5% 80% 98

BnDRG 14 2942bp

78% 98 Very low coverage 5%

BnDRG 17 1296 bp

No reads mapped to this gene

BnDRG 19 3183bp

99% 100 86% 99%

BnDRG 20 4029bp

96% 100 55% 99

BnDRG 23 2655bp

90 100 98 100

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Figure ‎5.5: Comparison of deduced amino acid sequences of BnDRG 13 in B. napus Darmor A7 to its homologous genes in B. napus Tapidor and B.

rapa.

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Figure ‎5.6: Comparison of deduced amino acid sequences of BnDRG 14 in B. napus Darmor A7 to its homologous genes in B. napus Tapidor A7 and

B. rapa.

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Figure ‎5.7: Comparison of deduced amino acid sequences of BnDRG 17 in B. napus Darmor A7 to its homologous genes in B. napus Darmor C6 and

B. rapa.

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Figure ‎5.8: Comparison of deduced amino acid sequences of BnDRG 19 in B. napus Darmor A7 to its homologous genes in B. napus Darmor C6, B.

napus Tapidor A7 and B. rapa.

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Figure‎5.8:‎continued‎….

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Figure ‎5.9: Comparison of deduced amino acid sequences of BnDRG 20 in B. napus Darmor A7 to its homologous genes in B. napus Darmor C6 and

B. rapa.

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Figure ‎5.10: Comparison of deduced amino acid sequences of BnDRG 23 in B. napus Darmor A7 to its homologous genes in B. napus Tapidor A7.

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Figure ‎5.11: Assembly of B. napus Skipton and Ag-Spectrum sequence short reads to B. napus

Darmor reference genome within the Rlm9 candidate resistance genes: BnDRG 12, BnDRG 13 ,

BnDRG 18 and BnDRG 19.

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5.5 Discussion

5.5.1 Identification and characterization of NBS-LRR and LRR-containing genes on B.

napus chromosome A07

The fully sequenced B. napus genome has provided an invaluable resource in the identification and

comparative analysis of disease resistance genes. In total, 58 disease resistance genes were

identified on chromosome A7 of B. napus: 19 NBS-LRRs, 15 LRR-RLPs and 24 LRR-RLKs. The

NBS-LRR and LRR-containing genes have been demonstrated to play a major role in resistance to a

wide range of plant pathogens (Hulbert et al., 2001). In addition, the association and correlation

between disease resistance genes and QTL regions has been widely noted (Gebhardt and Valkonen,

2001, Quint et al., 2003, Wisser et al., 2005). This is suggesting that candidate resistance genes, co-

localized within QTL, are probably major genes contributing to qualitative resistance. In this study,

30 out of 58 genes in chromosome A7 were located with Rlm QTL. This region is of interest

harbouring five race specific blackleg resistance genes, Rlm1, Rlm3, Rlm4, Rlm7 and Rlm9.

It has been shown that blackleg resistance genes in B. napus such as Rlm1, Rlm3, Rlm4, Rlm7 and

Rlm9 are mapped to a genomic loci that correspond to the chromosome segment on Arabidopsis

harbouring AtRlm1 (Mayerhofer et al., 2005). AtRlm1 and another two genes, AtRlm2 and AtRlm3

have been identified as Arabidopsis thaliana Resistance to Leptosphaeria maculans gene. These

genes encode NBS-LRR proteins (Staal et al., 2006, Staal et al., 2008). Therefore, it could be

hypothesized that L. maculans resistance genes are related to the NBS-LRR protein family.

5.5.2 Comparative analysis of NBS-LRR and LRR-containing genes on chromosome A7

The identification of NBS-LRR and LRR-containing genes enabled the study of synteny,

collinearity and conservation between genes on chromosomes A7 and C6 with their homologous

counterparts in B. rapa and B. oleracea. The number of NBS-LRR and LRR-containing genes

between the three species were consistent suggesting that they might have been maintained and not

affected much during the formation of B. napus.

This comparison showed that the majority of genes were conserved and collinear between the

chromosomes A7 and its homeologous chromosome C6 in Brassica species: B. napus, B. rapa and

B. oleracea. However, there were considerable variations, collinearity, presence/absence or

substantial differences in the protein sequence of several NBS-LRR and LRR-containing genes.

This might be due to genome mis-assembly or genomic rearrangements. The genomic

rearrangements may imply genome structural changes such as translocations.

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The LRR-RLP and LRR-RLK genes were more highly conserved than the NBS-LRR genes. This is

because NBS-LRR genes are often under diversifying selection, producing highly divergent

sequences and structural variants with distinct recognition capacities (Bai et al., 2002, Meyers et al.,

2003). By contrast, LRR-containing genes are under evolutionary pressure to maintain a specific

function (Fritz-Laylin et al., 2005). It has been hypothesized that LRR containing genes can play a

role in plant defence, as well as other biological processes. This makes them less likely to be

undergo diversifying selection than NBS-LRR genes (Leister, 2004, Guo et al., 2011). However,

such high sequence conservation in the LRR-containing genes does not rule out that LRR-

containing genes could be a potential candidate resistance gene. There are several examples

involving the LRR containing proteins in the plant resistance defence. For example, Cf genes in

tomato confer resistance against leaf mould disease caused by Cladosporium fulvum (Wulff et al.,

2009). LepR3 in B. rapa confers resistance to blackleg disease caused by L. maculans carrying

AvrLm1 (Larkan et al., 2013)

Furthermore, comparative analysis of NBS-LRR and LRR-containing genes between chromosome

A7 of B. napus and B. rapa as well as chromosomes A7 and C6 of B. napus were utilized to find

out how the structural diversity of resistance genes are associated with blackleg disease resistance.

A total of 12 NBS-LRR and 18 LRR-containing genes on B. napus chromosome A7 were identified

and located within the Rlm QTL region of interest.

The comparative analysis of resistance genes in the Rlm QTL region between B. napus and B. rapa

chromosome A7, as well as between B. napus chromosomes A7 and C6 confirmed the nature of

gene conservation with regards to gene order, content and sequence similarity. Even though there

were considerable variations; either gene presence/absence or substantial differences in the protein

sequence, there was significant structural conservation in the majority of resistance genes between

chromosome A7 of B. napus and B. rapa. In contrast, there was not high structural conservation

between chromosomes A7 and C6 of B. napus. For instance, more than 90 % of the resistance genes

have been retained in chromosome A7, whereas, about 50% of the resistance genes were found to

be duplicated between chromosomes A7 and C6. A previous studies (Fopa Fomeju et al., 2014)

found that the genomic region involved in resistance to blackleg in B. napus is expected to be linked

to the significant structural conservation between B. napus and B. rapa, but not between B. napus

and B. oleracea, because the source of blackleg resistance is only contributed by the A genome and

none has been found on the C genome (Rouxel et al., 2003b, Ananga et al., 2006, Leflon et al.,

2007). Therefore, it can be hypothesized that the resistance gene involved in blackleg resistance is

supposed to be retained in B. napus and B. rapa, however, some genome rearrangements or

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sequence variation might have occurred during the formation of B. napus. Several candidate

resistance genes were identified underlying the Rlm QTL region of blackleg resistance on B. napus

chromosomeA7. These genes were orthologous and conserved with chromosome A7 of B. rapa,

but, they were not homeologous or showed substantial protein differences on B. napus chromosome

C6.

This study revealed that there is high functional conservation of resistance genes on chromosome

A7 of B. napus and B. rapa compared to chromosomes A7 and C6 of B. napus by Rlm QTL

comparison. This information provides an invaluable resource to identify a number of candidate

genes associated with blackleg disease resistance and further characterisation of the Rlm QTL

region is likely to resolve whether the various Rlm genes are distinct or different allelic versions of

the same blackleg resistance genes.

5.5.3 Haplotype analysis of Rlm9 and mapping potential SNPs on B. napus

The Illumina Infinium SNP data was used to study the association between the SNP alleles and

blackleg resistance. This allows identification of or narrowing down the list of candidate genes

underlying the blackleg resistance QTL region. In this study, the haplotype analysis revealed that

the SNPs showed a random pattern of polymorphism and was not perfectly showing association

between SNPs and the Rlm9 resistance and susceptibility. However a set of ten SNPs with a good

correlation towards Rlm9 resistance were identified. Five of the six cultivars predicted to be Rlm9

resistance were shown to carry SNP alleles that strongly correlated to Rlm9 resistance allele of cv.

Darmor at the SNPs assayed. Ag-Spectrum, one of the predicted resistant lines, had no Darmor

resistant allele in any of the selected SNP. But, it revealed an allele that was consistent with the

susceptible lines. This is probably because Ag-Spectrum is heterozygous for resistance towards the

Rlm9 gene (Raman et al., 2012b). In contrast, five of the ten cultivars predicted to be Rlm9

susceptible were shown to carry alleles that associated with the Rlm9 susceptible allele in Yudal at

the SNP assayed. However, there were five cultivars showed a good correlation to the resistant line

by having a Darmor resistant allele even though they are predicted to be Rlm9 susceptible.

It is could be assumed that there was misinterpretation of the phenotypic data for these cultivars due

to subjectivity or errors during the phenotyping process. It is often difficult to determine how much

of phenotypic variation is explained in the literature. In addition, the Rlm9-mediated response is

heat-sensitive. Therefore, the phenotypic analysis is particularly difficult to analyse and often

conflicting results are found in the literature (J. Batley, personal communication). Thus, it is highly

recommended to re-phenotype these cultivars to determine the true results in the future.

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A number of the identified SNPs were located in the 3’ UTR and 5’ UTR of predicted genes. This

might suggest the involvement of transcription factors or regulatory factors in Rlm9 resistance.

Furthermore, sequence analysis of the predicted genes with these potential SNPs is required to

reveal whether there are any predicted genes that could be involved or work together with the

candidate Rlm9 genes.

5.5.4 The physical location and identification of candidate Rlm9 blackleg resistance gene in

B. napus

An Rlm9 QTL has been identified on chromosome A7 through a marker based approach where

linked markers were physically mapped to the reference B. napus genome (Delourme et al., 2004).

Based on the 60K SNP haplotype analysis, the potential ten SNPs, identified were mapped and

positioned along the Rlm9 QTL region on the chromosome A7. This result further strengthens the

hypothesis that Rlm9 lies somewhere within the targeted QTL region.

The Rlm QTL region on chromosome A7 co-localized with 12 NBS-LRR and 18 LRR-containing

genes in B. napus. These resistance genes could be candidates for blackleg disease resistance.

However, The A7 chromosome harbours several Rlm QTL regions underlying blackleg disease

resistance, where a cluster of blackleg resistance genes reside such as Rlm9, Rlm4, Rlm7, Rlm3 and

Rlm1 as identified previously (Delourme et al., 2004). In this study, this comparative analysis

confirmed that there were genes within the Rlm QTL region, particularly in Rlm9 QTL of interest

showed considerable variations, collinearity, presence/absence or substantial differences in the

protein sequence.

Based on these results, therefore, six NBS-LRR and eight LRR-containing genes were identified

and associated with the Rlm9 QTL region. The NBS-LRR genes were selected for further analysis.

The genes are referred to as BnDRG 13 BnDRG 14, BnDRG 17, BnDRG 19, BnDRG 20 and

BnDRG 23. Comparative analysis has made it possible to further investigate the structural diversity

in terms of protein sequence conservation or presence/absence between B. napus cv. Darmor and

other related species such as B. napus cv.Tapidor and B. rapa. This allowed initial prediction and

prioritization for targeting these candidate genes. The BnDRG 13 and BnDRG 14 genes were

considered as possible candidate genes because they were highly conserved and showed structural

difference in the CC domain between B. rapa and B. napus. They are presents as singleton gene in

B. napus without a homeologous (duplicate copy) in the B. napus C genome.

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Since blackleg resistance was found to be contributed by the A genome of B. napus and B. rapa,

this implies that the resistance gene might be present with sequence variation in both species. The

BnDRG 23 was not considered as strong candidate gene because it is not present in the A genome of

B. rapa. The genes BnDRG 17, BnDRG 19 and BnDRG 20 were prioritized as the most promising

candidate genes. The genes BnDRG 19, BnDRG 20 were not syntenic and non-collinear between B.

napus Darmor and B. rapa. The gene BnDRG 19 was highly conserved and showed structural

difference as the TIR domain is present in the B. rapa but not in the B. napus gene. The gene

BnDRG 19 was highly conserved in B. rapa and showed substantial sequence variations in the B.

napus C genome duplicate. This gene was initially not found in B. napus cv. Tapidor. The genes

BnDRG 19 and BnDRG 20 had high sequence read coverage in Skipton and low sequence reads

coverage in Ag-Spectrum. The low sequence reads coverage in Ag-Spectrum may be due to

significant sequence variation or loss. It may also be explained by the fact that Ag-Spectrum is

heterozygous for resistance towards Rlm9 gene.

The gene BnDRG 17 was highly conserved between B. napus Darmor and B. rapa but not collinear.

This gene was found in B. napus cv. Tapidor but due to genome assembly issue of presence of N-

gapped sequence, it was not possible to compare the gene sequence between the cultivars Darmor

and Tapidor. In addition, this gene had no sequence read coverage for both Skipton and Ag-

Spectrum. Preliminary analysis of the genomic region where BnDRG 17 resides is believed to be a

complex region in Darmor as the assembly is not accurate. However, since sequencing of the

BnDRG 17 gene is yet to be obtained, it is still as a strong candidate Rlm9 gene possible and efforts

to fully sequence the gene should be continued.

In conclusion, the comparison of NBS-LRR and LRR-containing genes between the four

chromosomes for the three species: B. napus, B. napus and B. oleracea not only confirmed genomic

microsynteny and conservation between Brassica species but, also provided an invaluable resource

in the identification and prioritization of candidate resistance genes

5.5.5 Amplification and sequencing Rlm9 candidate genes

In this study, sequencing of four Rlm9 candidate genes was attempted to identify polymorphisms in

the identified Rlm9 candidate genes between the resistant and the susceptible cultivars. The

complexity of the QTL region of interest due to genome duplication and rearrangement events has

complicated the PCR amplification. It may be worthwhile in future to use different PCR approaches

in amplification and sequencing the Rlm candidate genes such as RACE-PCR or even advanced

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approaches such as targeted sequence capture (Salmon et al., 2012, Winfield et al., 2012) or

resistance gene enrichment sequencing (Jupe et al., 2013).

Despite that, BnDRG 13, BnDRG 14 and BnDRG 23 candidate genes were successfully amplified

which revealed that there was no sequence polymorphism between two contrasting Rlm9 cultivars,

Darmor and Yudal. This clearly indicates that these genes are not a candidate Rlm9 gene.

The sequence for BnDRG 19 and BnDRG 20 genes between two contrasting Rlm9 cultivars,

Darmor and Yudal and other B. napus cultivars such as Skipton, was successful and showed 100%

identity without any polymorphism observed. However, BnDRG 19 and BnDRG 20 failed to

amplify from B napus Ag-Spectrum. This is supported by the low sequence reads coverage

(presence gapped sequence) which might have caused failure of amplification of Ag-Spectrum. I

believe that it is too early to make a deduction either to eliminate or to strongly nominate these

genes BnDRG 19 and BnDRG 20 from the blackleg candidate gene list. These two genes might be

of interest to be further investigated between other Rlm cultivars such as Rlm4. The Rlm9 QTL

region is believed to overlap or be adjacent to the Rlm4 QTL. These results confirmed the findings

of Delourme et al., (2004) stating that the QTLs for Rlm4 and Rlm9 are located next to each other.

The BnDRG 20 gene was not initially present in B. napus cv. Tapidor but that may be due to an

assembly problem, making the mapping and sequence comparison impossible. However, it was

confirmed by PCR and sequencing that this gene is present in B. napus cv. Tapidor with 100%

DNA sequence identity to B. napus cv. Darmor. This indicates that there is missing sequence

information resulting from the genome mis-assembly.

There is still one candidate gene BnDRG 17 that amplification has been attempted for, but has been

unsuccessful. This may be due to the assembly issue. This gene is still strong candidate gene to be

considered for future sequencing.

While sequencing and validation of these candidates must still occur, this study has proven that

candidate gene comparative analysis is quick and is becoming more affordable due to the generation

sequencing getting faster and cheaper. This method should occur in the future discovery of genes of

interest in Brassicas and can be followed in other crop species. In conclusion, none of the Rlm9

NBS-LRR candidate genes, that have been sequenced, showed a significant polymorphism

associated with Rlm9. However, it appears that one of LRR-containing genes located on

chromosome A7 is likely to be a candidate. There are eight LRR containing genes identified within

the Rlm9 QTL region that could become a strong prospect for further analysis.

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The list of disease resistance genes in B. napus chromosome A07 is certainly not complete. The B.

napus cv. Darmor genome sequence still contains unmapped contigs and the presence of N-gapped

sequences. This means that valuable sequence information is missing. I believe that one sequenced

genome does not sufficiently facilitate identification of the total number of disease resistance genes.

This is probably because the resistance genes are often located within unannotated regions of the

genome or they may be interrupted by gapped sequence leading to separation the gene into different

partial genes. There are artefacts from genome assembly and annotation that could potentially cause

identification of gene loss. For instance, the gene BnDRG 20 in the B. napus cv. Darmor genome

assembly was not present in the B. napus cv. Tapidor genome assembly in the comparative analysis.

However, the presence of the gene was confirmed in B. napus cv. Tapidor by PCR in this study.

Moreover, some resistance genes may be present in one genotype or cultivars but absent in another

exhibiting presence/absence variation (PAV). This causes differences in the NBS-LRR genes

number between cultivars. Therefore, the improved and revised genome assembly and re-

sequencing of other B. napus cultivars will definitely result in identification of additional resistance

genes.

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Chapter 6

General discussion and future

directions

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Chapter 6 : General discussion and future directions

This thesis aims to provide the foundation for study of the conservation and evolution of disease

resistance genes in Brassica napus. The availability of genome sequences and comparative analysis

together with disease resistance QTL mapping is an invaluable resource to study functional and

structural variations of NBS-LRR resistance genes between Brassica species. Hence, the

comparative analysis between Brassica species is likely to identify number of resistance genes that

affect important disease traits in Brassica. This study provides a good starting point in the effort to

identify and sequence candidate blackleg resistance (Rlm) genes in B. napus.

6.1 Genome wide identification of NBS-LRR resistance genes in Brassica

For the discovery of candidate genes involved in traits of interest, the genome wide identification of

NBS-LRR resistance genes has become an essential component for better understanding of the

genomics and evolution of resistance genes. Thus, the main focus was to characterize the NBS-LRR

genes with regards to their structural diversity, conservation, domain structure, chromosomal

locations, gene cluster and duplications. More importantly, it aimed to identify more genes with

NBS-LRR characteristics that could be potential candidates for disease resistance in Brassica.

In this study, a total of 641 NBS-LRR genes in the B. napus cv. Darmor were identified. This is

compared to 249 and 443 genes identified in B. rapa and B. oleracea, respectively. The

comparative analysis provided evidence that NBS-LRR genes in B. napus genome exhibited similar

distribution, structure and syntenic relationships to its progenitor species. The gene contents and

order on B. napus chromosomes are generally very similar to those on the corresponding

chromosomes of the diploid progenitors. Overall, these comparisons did not show massive

differences of NBS-LRR in B. napus as compared to its parental species.

To address the question as to what extent resistance genes are structurally conserved between

Brassica species, the NBS-LRR genes with their genomic structure was compared. There was

evidence that the 50% of NBS-LRR genes showed high synteny and collinearity between the A

genome of B. napus and B. rapa and the C genome of B. napus and B. oleracea. They were

positionally well conserved in size and orientation particularly regions containing major gene

clusters. Thus, it appears that these NBS-LRR genes in B. rapa and B .oleracea species may have

undergone similar selection pressure and they might have not been largely affected during the

formation of B. napus. In other words, B. napus might have been subjected to less evolutionary

selection or pressure leading to maintaining NBS-LRR properties with its diploid progenitors.

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The majority of B. napus NBS-LRR genes have orthologues in the progenitor species providing

evidence of evolution and genome duplication. More than 60% of NBS-LRR genes from the

progenitor species were conserved and maintained in B. napus. The differences in NBS-LRR gene

conservation could be attributed to gene losses or selection pressure to offer species-specific

resistance gene. After hybridisation of B. rapa and B. oleracea to form B. napus, NBS-LRR genes

in Brassica species experienced species-specific gene deletion resulting in gene losses. Similar

phenomenon of redundant NBS-LRR gene loss have also been reported in other plant genomes,

presumably because the duplicates would have had redundant functions (Bancroft, 2001, Rana et

al., 2004). At the same time, the gene duplication and recombination have also created novel NBS-

LRR resistance genes specific to B. napus and have resulted in substitutes the gene number to

compensate the gene losses during formation of B. napus.

It has been shown that the level of gene duplication in the B. napus genome is significant and

increases the genomic complexity (Parkin et al., 2003, Rana et al., 2004, Parkin et al., 2005). This is

also seen by the finding that 50% of B. napus NBS-LRR genes were identified as duplicates. The

NBS-LRR duplications exhibited the similar patterns and homeologous collinear between the two

sub-genomes of B .napus.

Previous genetic and genomics studies demonstrated that the majority of NBS-LRR genes are

present in gene clusters in plant genomes (Hulbert et al., 2001). The clustered arrangement of these

genes may be a critical attribute of the generation of novel resistance specificities via gene

duplication or recombination (Meyers et al., 2003). Indeed, previous studies revealed that NBS-

LRR genes are often present as tightly linked genes with high homology and are prone to gene

duplication and recombination, and thus evolve more rapidly than the rest of the genome (Grant et

al., 1998, Wei et al., 2013). Thus, the clustering of NBS-LRR genes provides a reservoir of genetic

variation by which new specificities to pathogens can evolve and allows for rapid evolutionary

response to pathogen effectors. This study found that 59% of the NBS-LRR genes in Brassica

species were found to be physically clustered and individual genes involved in clusters were more

polymorphic and subject to evolutionary selection pressure. This was further supported by the

observation that there was high conservation in genes involved in gene cluster than singleton genes.

The relative contributions of gene clustering and duplication in generating diversity in resistance

gene specificities remain to be further determined. However, duplication and divergent selection

may apparently play a major role in the evolution of resistance to major pathogens. A complex

pattern of tandem duplications was identified in the B. napus genome particularly within a gene

cluster suggesting that gene clusters could be chromosomal hot spots in which the NBS-LRR genes

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get duplicated and expanded by tandem duplication followed by selection pressure. In addition,

there was a significant correlation and co-localization between the number of NBS-LRR genes

within the QTL intervals and the number of genes involved in gene clusters or duplication. The

results provide evidence that NBS-LRR are distributed and clustered throughout the genome and

tend to be linked and associated with disease resistance QTL. However, because the genomic

duplication reported in this study based on NBS-LRR genes tend to be insufficient to provide a

better resolution about the genomic structure around the NBS-LRR. Therefore, it may be

worthwhile to conduct large-scale NBS-LRR duplication analysis by including predicted genes

flanking the NBS-LRR genes.

To conclude, evidence for resistance gene clustering and duplication within Brassica species should

now be further used to study the sequence and structural variation within disease resistance QTL. It

is possible that clustered and duplicated resistance genes underlying the QTL of interest are likely

to be major components of the resistance and cause resistance gene specificities.

6.2 Identification of candidate blackleg resistance genes in B. napus


their corresponding Rlm (Resistance to Leptosphaeria maculans) genes in B. napus. In addition,

genetic mapping studies have shown that in B. napus there are five specific major blackleg

resistance genes: Rlm1, Rlm3, Rlm4, Rlm7, and Rlm9 on chromosome A7 (Delourme et al., 2004,

Mayerhofer et al., 2005, Ananga et al., 2006). It remains unclear whether these genes are a cluster

of tightly linked genes, or a single gene with different alleles, or a combination of both. Even

though QTL mapping of quantitative resistance to L. maculans has been pursued in B. napus, none

of the genetically mapped Rlm genes in chromosome A7 have been sequenced and validated in B.

napus.

The chromosomal region of Rlm QTL for blackleg resistance shows genome complexity. The

physical location of disease resistance QTL or even a major resistance gene in complex genome

such as B. napus is highly challenging. This is complicated by genome duplications and tandem

intra-chromosomal duplication between homeologous chromosomes which make characterization

of genes underlying QTL of interest extremely difficult. For example, several overlapping QTL

intervals for blackleg resistance genes Rlm9, Rlm7, Rlm4, Rlm3 and Rlm1 were genetically

identified on chromosome A7 of B. napus (Delourme et al., 2004). In addition, these QTL are

located within an extensive intra-chromosomal tandem duplication region (Raman et al., 2012b,

Tollenaere et al., 2012). Thus, the identification of candidate blackleg resistance gene(s) in B. napus

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might also identify other blackleg resistance genes and elucidate their conservation and evolution in

Brassica species.

The resistance gene mediated blackleg resistance is inherited qualitatively. In addition, the source of

blackleg resistance is only contributed by the A genome and none found on the C genome. This is

due to significant structural conservation between B. napus and B. rapa and absence of blackleg

resistance sources in B. oleracea. However, paralogous genes in B. napus should have specific

recognition created by selective pressure to maintain the resistance source origin in the A genome.

Therefore, it can be hypothesized that the resistance genes involved in blackleg resistance should be

retained and conserved in the A genome of B. napus and B. rapa, whereas the resistance gene is

probably absent or highly divergent in the C genome of B. napus and B. oleracea.

In this study, co-mapping of QTL intervals identified in B. napus to its related species, B. rapa and

B. oleracea indicates that the QTL intervals in B. napus were originally contributed by the parental

species. The comparative QTL between B. napus, B. rapa and B. oleracea revealed the majority of

NBS-LRR genes in associated QTL intervals are syntenic and conserved. However, there were

differences in the number of associated NBS-LRR genes and the disease QTL interval sizes

between QTL regions in B. napus compared to its parental species. This suggests that the QTL

underlying resistance traits might show more structural and functional conservation towards one of

the B. napus progenitor species. There was a significant correlation and co-localization between the

number of NBS-LRR genes within the QTL intervals and the number of genes involved in gene

clusters or duplication. This is consistent with previous studies (Jeong et al., 2001, Wang et al.,

2010). The complex structure of QTL can be as a result of resistance gene cluster and duplication

leading to closely linked genes which differ in their pathogen race specificity (Michelmore and

Meyers, 1998). This implies that gene clusters are a good starting point for studying functional

molecular mechanisms and evolution of NBS-LRR resistance genes underlying resistance traits.

The identification of candidate blackleg resistance genes in B. napus by map-based cloning

approaches is a laborious and time consuming effort. Therefore, another approach which can be

undertaken is direct identification of candidate genes through next generation sequencing and whole

genome NBS-LRR analysis. This approach, combined with genome comparative analysis, allows

studying the genomic region for the disease resistance QTL with respect to the NBS-LRR genes

conservation and syntenic relationships between related species. This could facilitate the rapid

selection of putative candidate NBS-LRR genes involving in the blackleg resistance in Brassica.

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Since chromosome A7 in B. napus was the major of interest in this study carrying major sources of

blackleg resistance genes in Brassica, The comparative analysis enabled me to study the synteny,

collinearity and conservation between NBS-LRR and LRR-containing genes on A7 and C6 with

their homologous counterparts in B. rapa and B. oleracea. In general, there was significant

structural conservation in the majority resistance genes between chromosome A7 of the B. napus

and B. rapa. However, there were considerable variations either as gene presence/absence or

substantial sequence differences for several resistance genes.

Interestingly, of the total NBS-LRR and LRR-containing genes identified on the chromosome A7 of

B. napus, there were 12 NBS-LRR and 18 LRR-containing genes underlying blackleg resistance

Rlm QTL. These resistance genes could be Rlm9, Rlm4, Rlm7, Rlm3 or Rlm1 candidates for

blackleg disease resistance. The Rlm QTL comparison analysis revealed that these genes were

orthologous and conserved in A7 B. rapa, but, they were not homeologous or showed substantial

protein differences in B. napus C6. Furthermore, the comparative analysis confirmed that there were

genes within the Rlm QTL region, particularly in Rlm9 QTL of interest showed considerable

variations, collinearity, presence/absence or substantial differences in the protein sequence

In this study, identification and characterization of Rlm9 candidate genes was attempted. A QTL for

the Rlm9 gene has been identified from a mapping population derived from crossing B. napus cv.

Darmor to cv. Yudal (Delourme et al., 2004). This QTL is located on chromosome A7 of B. napus,

which also contains other resistance genes: Rlm1, Rlm3, Rlm4 and Rlm7. In this study, six NBS-

LRR and eight LRR-containing genes were associated with Rlm9 QTL region. The NBS-LRR genes

were selected for further analysis. These genes are referred to as BnDRG 13 BnDRG 14, BnDRG

17, BnDRG 19, BnDRG 20 and BnDRG 23. The comparative analysis between Brassica species and

cultivars has made it possible to make initial prediction and prioritization for targeting these

identified genes. PCR amplification and sequencing confirmed that five of these candidate genes

showed no polymorphisms associated with Rlm9 resistance/susceptibility. However, there is still

one candidate BnDRG 17 gene considered a potential candidate gene for future sequencing. In

addition, it appears that LRR-containing genes identified within the Rlm9 QTL region could

become a strong prospect for further analysis.

The results of this study have also been used to identify and sequence other blackleg resistance

genes on chromosome A7 in B. napus such as Rlm4 and Rlm1. The sequencing and validation of

these candidate genes is still underway in our laboratory.

158

Although there has been relatively little research on the isolation and sequencing of blackleg

resistance genes in Brassica, this work has significantly increased our understanding of the

resistance genes organization and association in Brassica where several members of NBS-LRR

resistance genes on A7 that could confer resistance to blackleg resistance have been identified.

Furthermore, the comparative analyses yield valuable insight into the understanding of the structure,

evolution and organization of NBS-LRR genes in Brassica genomes.

6.3 Future directions

The identification of blackleg resistance genes in B. napus remains a key objective. To date, the

complete genome sequence of only one B. napus cv. Darmor (carrying Rlm9 resistance gene) is

available and used as reference genome in this study. This is why progress has been steady in

detailed genetic analysis of blackleg resistance even though considerable progress has been made in

genomics analysis of resistance genes between B. napus and its progenitor species. Therefore, it

would be even more useful to sequence B. napus cultivars with different Rlm gene composition in

the near future. However, caution is required to overcome the sequencing and assembly problems

that cause complications in the analysis. I would recommend that future work should be carried out

which will increase the quality and quantity of genomic sequence information within Brassica

species or cultivars providing the opportunity to conduct extensive comparative studies. This

includes:

Chromosome-based sequencing

It has been shown that genomic sequencing approaches can result in an error during the sequencing

or assembly and mis-mapping contigs associated with the nature of B. napus polyploidy. Thus,

alongside application of the genome sequence and NGS, another approach is to be undertaken to

overcome the Brassica genome complexity and mis-assembly problems, such as chromosome-

based sequencing. The analysis of sequence at the single chromosome level is a convenient means

of verifying genome sequence assemblies and increases the quantity of genomic information to

conduct more comparative studies within or between related species (Ruperao et al., 2014) . The

chromosome genomics approach has been successfully adapted in the wheat genome sequencing

(The International Wheat Genome Sequencing Consortium, 2014). Thus, chromosome sequence

comparisons and functional analysis will allow analysing candidate genes organization and

evolution and dissection of the molecular basis of specificity and allelic variations.

159

Copy number variation

Copy number variation (CNV) refers to differences in the number of gene loci between different

genotypes either species or cultivars. This structural variation (SV) is often observed as large

deletions or duplications and occurs from single genes to multi-genic regions. It is likely that

structural variation may play a role in the resistance. There is evidence that structural variation such

as copy number variations is associated with disease resistance and this variation is co-localized

with QTL and resistance genes (Cook et al., 2012, Jamann et al., 2014). Thus, it is possible that

structural variation, such as copy number variation and tandem repeats, rather than the sequence

variation between Brassicas species could play an important role in blackleg

resistance/susceptibility. Therefore, I would suggest future efforts should be devoted to identify any

CNVs associated with resistance genes using re-sequencing approach where sequence reads from

individual B. napus cultivars are assembled to the reference genome. The reference B. napus

Darmor genome could now be used as a template for re-sequencing of NBS-LRR profile from

diverse B. napus cultivars. This, indeed, will provide further motivation to study the effect of gene

duplication or sequence tandem repeats on the disease resistance genes.

160

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Genome wide identification of NBS-LRR genes in Brassica …360384/s4255… · · 2017-01-18caused by the fungal pathogen Leptosphaeria maculans, is one of the most devastating diseases