Investigating the Regulation of Grain Protein Concentration in the IPSRIs: Precision Phenotyping using Fluorescent Promoter Reporter Transgene

Expression

Christine Lucas1, Han Zhao2, Mayandi Sivaguru3, Steve Moose1 1Department of Crop Sciences; University of Illinois; Urbana, IL 61801

2Jiangsu Academy of Agricultural Sciences, Nanjing City, China 3Institute of Genomic Biology; University of Illinois; Urbana, IL 61801

Maize protein is deficient in several essential amino acids due to their low proportion within the α-zein storage proteins that constitute the majority (50-60%) of total protein in the kernel. Reducing α-zein protein accumulation is an important goal of Quality Protein Maize (QPM) breeders worldwide. QTL mapping efforts suggest that grain protein is governed by many genes with small phenotypic effects, but genetic regulators still remain largely unknown. NIR has been used, but it is known to be influenced by environmental factors and measures an indirect phenotype. An alternative strategy described here is a precision phenotyping method that involves a red fluorescent protein reporter, mRFP, fused to the regulatory sequences from a single α-zein gene. The mRFP transgene was crossed to the Illinois Protein Strain Recombinant Inbreds (IPSRIs), an advanced intermated RIL mapping population derived from the cross of Illinois High Protein (IHP) and Illinois Low Protein (ILP), and three years of phenotypic data have been collected on the IPSRIs using both NIR and mRFP methods. Candidate genes in the zein pathway and the asparagine cycling pathway, which exhibit allele frequency shifts and expression variation in both the IPSRIs and the IHP and ILP populations, were associated with both phenotypic data sets. The results indicate that the mRFP phenotype allows for the separation of genetic factors that indirectly influence α-zein accumulation, such as those that alter starch synthesis. GBS data on the IPSRIs will allow for a genome-wide association study using both sets of phenotypic data.

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Christine Lucas 49th Illinois Corn Breeders’ School

March 4, 2013

Investigating the regulation of grain protein concentration in the IPSRIs: Precision phenotyping using fluorescent

promoter reporter transgene expression

Outline Summary of previous findings Background

– Illinois Long-term Selection Experiment

Materials and Methods – NIR Phenotype – mRFP Phenotype

Results of Candidate Gene Associations with: – Zein Pathway Genes – Asparagine Cycling Pathway Genes

Comparison of Results using each Method (NIR vs. mRFP) Conclusions Ongoing work

– GWAS

Genetic architecture of kernel composition traits

• Reviewed in Moose et al., 2004 • Goldman et al., 1993 • Dijkhuizen et al., 1998 • Sene et al., 2001 • Dudley et al., 2004 • Dudley et al., 2007 • Cook et al., 2012

– 21-26 QTL for kernel composition traits using NAM

Main Conclusions with respect to genetic architecture: Tens to Hundreds of genes with small phenotypic effects.

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Inbred Protein Strains

The Illinois Long-term Selection Experiment

Lucas et al., 2013

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Inbred Protein Strains

The Illinois Long-term Selection Experiment

Lucas et al., 2013

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ILP1IR

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160906446

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10 SDS-PAGE of total protein (mature kernels)

The Illinois Long-term Selection Experiment

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Generation 65 Generation 105

The Illinois Long-term Selection Experiment

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Generation 65 Generation 105

Generation 65 Generation 105 IHP ILP IRHP IRLP IHO ILO IHP ILP IRHP IRLP IHO ILO

22kDa 19kDa

Zein Pathway Allele Frequencies in the Cycles (65 & 100)

22-kDa zein gene

mRNA PBF O2 + +

PBF contains an ASN rich region that varies in the number of ASN repeats.

PBF (umc1065) O2 (umc1066)

umc1066 described in Hartings et al., 1994

O2 contains a highly variable region that varies in the number of Pro-Gln repeats.

(Vicente Carbajosa et al., 1997)

Zein Pathway Allele Frequencies in the Cycles (65 & 100)

22-kDa zein gene

mRNA PBF O2 + +

Allele Frequency Heat Map in IPS Cycles 65 & 105 ILP 95 ILP 65 IRHP 100 IRLP 69 IRHP 67 IRLP 100 IHP 65 IHP 100

z22

Hap

loty

pe

A 0.00 0.00 0.62 0.00 0.32 0.00 0.35 0.55 B 0.25 0.78 0.00 0.45 0.05 0.67 0.00 0.00 C 0.75 0.22 0.00 0.15 0.05 0.33 0.00 0.00 F 0.00 0.00 0.00 0.40 0.00 0.00 0.65 0.45 G 0.00 0.00 0.38 0.00 0.58 0.00 0.00 0.00

PBF U 0.00 0.00 0.10 0.04 0.06 0.00 0.00 0.00

M 0.17 0.30 0.81 0.33 0.94 0.91 1.00 1.00 L 0.83 0.70 0.08 0.63 0.00 0.09 0.00 0.00

O2 U 0.00 0.03 0.00 0.02 0.00 0.00 0.13 0.00 M 1.00 0.95 1.00 0.98 1.00 1.00 0.71 0.20 L 0.00 0.03 0.00 0.00 0.00 0.00 0.17 0.80

INCREASING PROTEIN %

Zein Pathway Gene Expression (qRT-PCR) in the Cycles (65 & 105)

PBF

00.020.040.060.08

IHP

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ILP

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IHO

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ILP

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IHO

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O2

00.020.040.060.080.1

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ILP

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Zein 22kDa

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(Han Zhao)

22-kDa zein gene

mRNA PBF O2 + +

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The Illinois Protein Strain Recombinant Inbred (IPSRI) Mapping Population

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IHP x ILP RM7S6

The Illinois Protein Strain Recombinant Inbred (IPSRI) Mapping Population

(25%) IHP70 X ILP70 (4%)

F1, RM7

Selfing, 6 generations

500 Illinois Protein Strain Recombinant Inbreds (IPSRIs)

138 IPSRIs

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(25%) IHP70 X ILP70 (4%)

F1, RM7

Selfing, 6 generations

500 Illinois Protein Strain Recombinant Inbreds (IPSRIs)

The Illinois Protein Strain Recombinant Inbred (IPSRI) Mapping Population

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Total N % (NIR) 500 ful set (n=456) 138 reduced set (n=130)

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IHP x ILP RM7S6

(25%) IHP70 X ILP70 (4%)

F1, RM7

Selfing, 6 generations

500 Illinois Protein Strain Recombinant Inbreds (IPSRIs)

The Illinois Protein Strain Recombinant Inbred (IPSRI) Mapping Population

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Total N % (NIR) 500 ful set (n=456) 138 reduced set (n=130)

Low Protein Tail High Protein Tail

Materials and Methods IPSRI QTL Mapping Population

– 138 IPSRIs were grown in ‘06, ‘07, ‘08, ‘09, ‘10, ‘11 & ‘12. – In 2006, 2007, 2008 and 2009, IPSRIs were selfed

• 5 ears pollinated per genotype, bulk measurement taken.

– In 2010, 2011, 2012, the IPSRIs were used as females in crosses to B73:mRFP because of maternal effect

• 5 ears pollinated per genotype, collected data on 2 ears/ genotype

– IHP1 & ILP1 inbreds grown as controls

NIR Phenotypic Data – Approx. 125 seeds ground to a fine flour – % total N, % starch and % oil were estimated by near infrared

reflectance (NIR)

(mRFP Phenotypic Data) Candidate Gene Association

8.0 9.5 11.0 12.5 14.0 15.5 17.0 18.5 20.0 21.5 23.00

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NIR Phenotypic Data NIR

Year Mean Range Variance Std Dev. Coeff. Var. 2010 14.15 10.58 6.51 2.55 18.04 2011 16.14 13.11 6.13 2.48 15.35 2012 N/A

ANOVA Table NIR R-Square Coef. Var Root MSE Mean

0.98 7.51 1.15 15.27

Source DF Type III SS Mean Sq. F-Value Pr>F Year 1 154.46 154.46 117.26 <.0001 Geno 136 1135.02 8.35 6.34 <.0001 Earrep 4 19.2 4.8 3.64 0.0111 Year*Geno 106 888.1 8.38 6.36 <.0001 Year*Earrep 1 2.1 2.17 1.65 0.205 Geno*Earrep 146 276.17 1.89 1.44 0.0705

(2012 NIR data, in progress)

% Protein

z1D z1C z1A1 z1A2 z1B

The α-zeins are clustered into five locations on chromosomes 1, 4, 7

19-kD 22-kD 19-kD 19-kD 19-kD

Association of 22-kD Zein Pathway Genes with protein % (NIR) in the IPSRIs

• No significant trends for main effects, but interaction between PBF and a 22-kD α-zein.

• Contribution to phenotype likely small.

*IPSRI ears self-pollinated **IPSRI ears crossed with B73:mRFP pollen 22-kDa zein gene

mRNA PBF O2 + +

umc1065 umc1066

Candidate Genes 22-kD Zein Loci

PBF O2 22-kD PBF*O2 PBF*22-kD O2*22-kD 3-way Year umc1065 umc1066 zeinSSR1 1065*1066 1065*SSR1 1066*SSR1 3-way

NIR

2006*

2007*

2008* 0.0780 0.0215

2009* 0.0384

2010**

2011** 0.0970

Significant at 0.05 Significant at 0.10

Candidate Genes 19-kD Zein Loci PBF z1A1 z1B z1A2 PBF*z1A1 PBF*z1B PBF*z1A2 Year umc1065 umc1943 zeinSSR12 mmc0471 1065*1943 1065*SSR12 1065*0471

NIR

2006 0.0353 0.0606

2007 0.0635

2008

2009 0.0597

2010

2011

Association of 19-kD Zein Pathway Genes with protein % (NIR) in the IPSRIs

*IPSRI ears self-pollinated **IPSRI ears crossed with B73:mRFP pollen

Significant at 0.05 Significant at 0.10

• No significant trends except for one marker in the z1A2 cluster.

The floury2-mRFP1 transgene behaves like the endogenous floury2 gene

Floury2-mRFP1: • exhibits proper spatial

expression • expression follows

normal patterns of 22-kD α-zein expression

Lucas et al., 2013

Map of Floury2-mRFP1 transgene construct

Mohanty et al., 2009

IHP1 24 DAP ILP1 24 DAP

qRT-PCR mature seeds

http://maize.tigr.org/cellgenomics/index.shtml

embryo

12 14 16 18 20 24 Mature ears

IHP1

IRLP1

B73

Days After Pollination

The floury2-mRFP1 transgene behaves like the endogenous floury2 gene (continuted)

Floury2-mRFP1: • exhibits proper

temporal expression

• responds to genetic background

• is properly regulated by opaque2

Lucas et al., 2013

ILP1

IRHP1

+/ -/-

+/ RFP

-/- RFP

IHP1:o2/o2 x IHP1:mRFP

Precision Phenotyping Platform

2^16 = 65,536 possible shades!

Institute of Genomic Biology (UIUC)

IPSRIs x B73:floury2-mRFP

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Total N %

2007 Total N (NIR)

500 ful set (n=456) 138 reduced set (n=130)

ILP1 x B73:mRFP IHP1 x B73:mRFP

Controls

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ANOVA Table Red/Green R-Square Coef. Var Root MSE Mean

0.95 11.95 0.25 2.1

Source DF Type III SS Mean Sq. F-Value Pr>F Year 2 12.71 6.36 100.51 <.0001 Geno 138 85.18 0.62 9.76 <.0001 Earrep 9 2.42 0.27 4.25 <.0001 Year*Geno 239 34.08 0.14 2.25 <.0001 Year*Earrep 2 0.45 0.23 3.58 0.0301 Geno*Earrep 165 13.81 0.08 1.32 0.0372

mRFP Phenotypic Data 2010

2011

2012

Red Channel/ Green Channel Year Mean Range Variance Std Dev. Coeff. Var. 2010 2.09 2.46 0.15 0.38 18.42 2011 1.93 2.60 0.18 0.42 21.91 2012 2.29 4.68 0.37 0.61 26.56

% Protein

Candidate Genes 22-kD Zein Loci

PBF O2 22-kD PBF*O2 PBF*22-kD O2*22-kD 3-way Year umc1065 umc1066 zeinSSR1 1065*1066 1065*SSR1 1066*SSR1 3-way

mRF

P 2010 0.0030 0.0356 0.0936 0.0067 0.0012 0.0442

2011 0.0187 0.0827 0.0144 0.0700 0.0045 0.0128 0.0735 2012 0.0153 0.0002 0.0016 0.0092 0.0007 0.0001 0.0054

Candidate Genes 19-kD Zein Loci PBF z1A1 z1B z1A2 PBF*z1A1 PBF*z1B PBF*z1A2 Year umc1065 umc1943 zeinSSR12 mmc0471 1065*1943 1065*SSR12 1065*0471

mRF

P 2010

2011 0.0154 0.0251 2012 0.0599 0.0759

Association of Zein Pathway Candidate Genes with mRFP in the IPSRIs

• One z1B (19-kD) marker significant. • Main effects and interaction terms significant across

years for PBF, O2 and 22-kD zein marker. • mRFP method detecting genes NIR does not detect.

Why aren’t the ears segregating for protein segregating in kernel color?

Mature ears

IHP1

IRLP1

B73

ILP1

IRHP1

Floury2-mRFP1: • Expression not

segregating according to genotype

• Regulation on a whole-ear basis

IHP hyperaccumulates Asn and exhibits elevated N uptake, assimilation and remobilization

IHP hyperaccumulates Asn.

(Dembinski et al., 1991; Lohaus et al., 1998; Below et al., 2004)

6 5 4 3 2 1 0

R1 R6 R1 R6 IHP1 ILP1

B73 ILP IHP Total Shank AA 18 10 68 Glutamine 36% 43% 23% Aspartate 13 22 6 Asparagine 11 6 35

IHP exhibits elevated: • N uptake. • N assimilation by seedling leaves. • N remobilization from source to sink

tissues.

CO2

Aspartate + Glutamine AS3

ATP

Asparagine AMP

+ PPi

Asparaginase NH4+

bZIP

NO3- NH4+

The ASN cycling pathway is regulated by AS3, Asparaginase and bZIP1

• Growth • Vegetative

C/N

Seed C/N

IHP1 ILP1

IHP1 contains mutant AS3 and ASNase alleles

• IHP1 contains a 260bp insertion in the promoter

IHP1

B73 & ILP1

260bp

AS3 Gene Diagram

Promoter

IHP1

B73 & ILP1

Asparaginase Gene Diagram

3’UTR

Promoter

TSS ATG TGA

~3 kb ~2 kb

3’UTR TSS ATG TGA

[ ]

100+bp • IHP1 contains several

putative polymorphisms • 33bp 3’ UTR deletion • Several insertions in

promoter

[33bp ]

(Farag Ibraheem)

(Yuhe Liu)

AS3, bZIP and ASNase are promising candidates…

*IPSRI ears self-pollinated **IPSRI ears crossed with B73:mRFP pollen

Significant at 0.05 Significant at 0.1

Candidate Genes Asparagine Cycling Pathway Year AS ASNase bZIP AS*ASNase AS*bZIP ASNase*bZIP 3-way

NIR

2006 0.016 0.020

2007

2008 0.073 0.096

2009 0.020 0.053 0.007

2010

2011 0.059 0.095

Association of Asparagine Cycling Pathway Genes with protein % (NIR) in the IPSRIs

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Inbred Protein Strains

AS3 also associated with grain protein in an independent population

Lucas et al., 2013

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Inbred Protein Strains

AS3 also associated with grain protein in an independent population

AS3- significant: IRHP1/IHP1 avg protein: 13.39% ; IRHP1/IRHP1 avg protein: 11.97% (alpha 0.05, p-value 0.0011). ASNase- Not significant

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Protein Concentration (2009 NIR)

[IRHP1 x (IHP1 x IRHP1)] S1

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IRHP1/IRHP1 IRHP1/IHP1

Lucas et al., 2013

Candidate Genes Asparagine Cycling Pathway Year AS3 ASNase bZIP AS*ASNase AS*bZIP ASNase*bZIP 3-way

mRF

P 2010 2011 0.057 2012 0.002

Association of Asparagine Cycling Pathway Genes with mRFP in the IPSRIs

Why are we detecting different genes using mRFP vs. NIR?

C:N Balance in Seed Starch (biomass/ yield) Protein Zein

mRFP RANK 2010 2011 2012

NIR

RAN

K 2010 -0.07537 0.163234 0.158943 2011 0.470143 0.287994 2012 N/A

Rank correlation between NIR and mRFP NIR mRFP

PBF O2 22-kD zein 19-kD zein Asparaginase

AS3 bZIP Asparaginase

Sum

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We can use both methods to dissect apart the role of each pathway in regulating not just protein %, but α-zein protein %, as well as starch %.

Conclusions 1.) % zein is regulated by plant N:

– Asparagine cycling genes significant – No variation in color (mRFP) of segregating ear – Why there is a maternal effect. To change protein, select for different aspect of

ASN cycling pathway in the plant. Can make selections earlier in season without making crosses.

2.) % zein is regulated within the kernel as well, but this is the end product of the ASN cycling pathway:

– Zein pathway genes significant 3.) We confirm previous results of many genes, but they may not all have small effects.

– AS3 is an example of one gene with a large effect (1.4%). 4.) The mRFP precision phenotyping method works, but measures different aspects of zein regulation than the NIR method. 5.) The IPSRI mapping population is useful for testing if candidate genes in zein and ASN pathways were targets of selection in the ILTSE, but more markers needed across genome……….

Ongoing Work: GWAS using Genotyping By Sequencing (GBS)

Goals • To provide a significance threshold for candidate

genes • To identify new QTL regulating

A.) floury2/ 22-kD α-zein (mRFP phenotype) B.) protein, starch, oil (NIR phenotype),

• but not just QTL!!!! Genes! • Ultimate goal is to improve protein quality and to

understand regulatory variation underlying complex traits. Sequencing by the Institute of Genomic Diversity (Cornell University)

SNP Calling by Ed Buckler’s lab (Cornell University)

Acknowledgements UIUC PI Stephen Moose Committee members Pat Brown A. Lane Rayburn Sandra Rodriguez-Zas SDS-PAGE & qRT-PCR Han Zhao AS3, ASNase, bZIP marker development Farag Ibraheem Yuhe Liu

Phenotypic Data Collection Michael Zinder Jarai Carter Susann Uphoff Loren Goodrich Michael O’Mara Dominique Thomas mRFP Method Development (Institute of Genomic Biology UIUC) Mayandi (Shiv) Sivaguru Glen Fried

Graduate Student Support Wesley Barber Yuhe Liu …….many more! GBS (Cornell University) Institute of Genomic Diversity Ed Buckler’s lab IPSRI Development John Dudley Monsanto Moose Lab

Funding for this research is from the USDA. Support for Christine is from the William B. and Nancy L. Ambrose Fellowship

IHP 24 DAP ILP 24 DAP