1. 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

2. 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

3. IR64 Dular N22 FR13
Root
phenotyping
systems
Total:
10 root study systems (field and containers)
19 grain yield environments(field)
 38 datasets

4. 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.

5. 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

6. 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

7. 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. WadeV. Bartolome

8. 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

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

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

11. 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

12. 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
Inhibitionoftranspiration
Transpiration VPD curves at
ICRISAT
Xylem sap
bleeding rate
A. Grondin
• cutoff P-value of 0.01  33
introgression regions to map

13. 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

14. 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

15. 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