Rice root phenotyping of the OryzaSNP panel: associated genomic regions and

environmental effects

Amelia Henry, Len Wade, Adam Price, Akira Yamauchi, R. Chandra Babu, V. Shenoy, S. Mande, V. Bartolome, R. Mauleon , Kenneth McNally

OryzaSNP panel • 20 genotypes • mapped for 160,000 SNP markers

GCP Roots project: • Develop and refine screening tools and protocols for high-throughput phenotyping of dehydration-avoidance root traits. • Characterize rice germplasm and genetic diversity for plant water use, dehydration avoidance root traits and yield under drought.

McNally et al. 2009

IR64 Dular N22 FR13

Root phenotyping systems

Total: 10 root study systems (field and containers) 19 grain yield environments(field) 38 datasets

R. Shrestha, Z. Al-Shugeairy, F. Al-Ogaidi, M. Munasinghe, M. Radermacher, J. Vandenhirtz, A. H. Price. 2013. Comparing simple root phenotyping methods on a core set of rice genotypes. Plant Biology. DOI: 10.1111/plb.12096 Gowda, V.R.P., Henry A, V. Vadez, H.E. Shashidhar and R. Serraj 2012. Water uptake dynamics under progressive drought stress drought stress in OryzaSNP panel rice accessions. Functional Plant Biology 39: 402-411. Henry, A., V.R.P. Gowda, R. Torres, K. McNally, R. Serraj. 2011. Genetic variation in root architecture and drought response in Oryza sativa: Rainfed lowland field studies of the Oryza SNP panel. Field Crops Res. 120: 205-214.

Recommendations after the experiments and data compilation:

1. Distribution of germplasm: • choice of genotypes (ability to germinate) • check seed quality before distribution • account for quarantines/regulations in project timeline

2. Determine how GIDs will be identified

3. Have a plan to include at least 1 common measurements among project partners

Recommendations

4. Have an understanding with the database managers about formatting, especially regarding curation of non-traditional traits

5. Distribute a data formatting template, and ask partners to enter all data into this template as it is generated

GxE analysis

• Root dry weight • maximum root depth • % deep roots • grain yield

Genotype grouping for root dry weight: Appears to be soil type related

Maximum root depth: most affected by method

L. Wade V. Bartolome

OryzaSNP panel: Correlation of putative introgressions with phenotypes

- Correlated introgression regions were identified - used a cutoff P-value of 0.001 183 regions to map (almost all japonica introgressions)

Looked for alignment of 5+ traits/environments

R. Mauleon McNally et al. 2009

Chromosome 1: alignment of traits around 39.7 - 40.7 Mb (root dry weight, yield % deep roots)

Chromosome 8: alignment of traits around 20.3-21.9 Mb (yield and % deep roots)

Enrichment analysis: previously reported root QTLs from the regions on chromosomes 1 and 8 that aligned in this study

Gene Category List Hits List Total Population Hits

Population Total Probability Reference

Chr 1 Vigor|root number|DQC3|Chr. 1 11 11 28 3680 5.19E-25 Price et al 2000 Vigor|root number|AQC003|Chr. 1 11 11 28 3680 5.19E-25 Price et al 2000 Vigor|root number|AQO077|Chr. 1 11 11 28 3680 5.19E-25 Price et al 2002b Vigor|root dry weight|AQGI070|Chr. 1 11 11 42 3680 1.03E-22 Lian et al 2005

Abiotic stress|root dry weight to tiller number ratio|CQQ13|Chr. 1 9 11 56 3680 1.21E-15 Yadav et al 1997 Abiotic stress|root weight|CQQ6|Chr. 1 9 11 56 3680 1.21E-15 Yadav et al 1997 Abiotic stress|root weight|CQQ32|Chr. 1 9 11 56 3680 1.21E-15 Shen et al 2001 Abiotic stress|penetrated root thickness|DQF9|Chr. 1 9 11 56 3680 1.21E-15 Zheng et al 2000 Abiotic stress|relative root length|CQL2|Chr. 1 2 11 2 3680 8.12E-06 Wu et al 2000 Abiotic stress|relative root length|CQL1|Chr. 1 2 11 2 3680 8.12E-06 Wu et al 2000 Anatomy|seminal root length|CQS3|Chr. 1 2 11 2 3680 8.12E-06 Zhang et al 2001

Abiotic stress|penetrated root length|AQGC035|Chr. 1 3 11 60 3680 0.00061969 Ali et al 2000 Abiotic stress|penetrated root thickness|AQGC022|Chr. 1 3 11 60 3680 0.00061969 Ali et al 2000

Chr 8 Vigor|root to shoot ratio|AQO017|Chr. 8 13 17 22 3680 3.29E-28 Price et al 2002a and b

Vigor|root to shoot ratio|AQO025|Chr. 8 13 17 22 3680 3.29E-28 Price et al 2002a and b Vigor|root number|CQAW26|Chr. 8 17 17 97 3680 3.35E-28 Ray et al 1996 Abiotic stress|relative root length|CQL9|Chr. 8 14 17 42 3680 3.76E-26 Wu et al 2000 Abiotic stress|relative root length|CQL8|Chr. 8 14 17 42 3680 3.76E-26 Wu et al 2000 Anatomy|root length|AQZ004|Chr. 8 4 17 13 3680 2.17E-07 Nguyen et al 2003 Abiotic stress|relative root length|AQZ008|Chr. 8 4 17 13 3680 2.17E-07 Nguyen et al 2003

Anatomy|root thickness|AQAL029|Chr. 8 4 17 120 3680 0.00184121 Kamoshita et al 2002

Hydraulics and aquaporin inhibition

Tr_Inh Tr_Inh Tr_Inh

YLD_D

Br_W

Br_D

Tr_W Br_W

Br_D

YLD_W

Chrom. 8

Chrom. 4

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

Inhi

bitio

n of

tra

nspi

ratio

n

Transpiration VPD curves at ICRISAT

Xylem sap bleeding rate

A. Grondin

• cutoff P-value of 0.01 33 introgression regions to map

Phenotyping methods: Scaling up for association mapping

--> aus panel

3 field studies

1 lysimeter study

1 basket study

1 herbicide at depth study Univ. Aberdeen – A. Price

IRRI

Conclusions Refined root phenotyping systems root methods manual Data uploaded to IRIS Better understanding of most effective parameters (RDW vs MRL) Chromosome regions correlated with root architecture and grain yield phenotypes from multiple environments and study systems

Next: Scaling up to larger genotype sets (aus panel) to identify genes associated with drought resistance Better understanding of hydraulics/ root function for drought resistance in rice

Acknowledgements

Ken McNally Rolly Torres Marinell Ramirez

Len Wade CSU Australia

Akira Yamauchi Nagoya Univ. Japan

Vinay Shenoy Barwale Foundation India

Adam Price Univ. Aberdeen UK

R. Chandrababu TNAU India

M. Semon AfricaRice Nigeria