Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

Len J. Wade, Violeta Bartolome, Ramil Mauleon, Vivek Deshmuck Vasant, Sumeet Mankar Prabakar, Muthukumar Chelliah, Emi Kameoka, K. Nagendra, K. R. Kamalnath Reddy, C. Mohan Kumar Varma, Kalmeshwar Gouda Patil, Roshi Shrestha, Zaniab Al-Shugeairy, Faez Al-Ogaidi, Mayuri Munasinghe, Veeresh Gowda, Mande Semon, Roel R. Suralta, Vinay Shenoy, Vincent VadezRachid Serraj, H. E. Shashidhar, Akira Yamauchi, Ranganathan Chandra Babu, Adam Price, Kenneth L. McNally, Amelia Henry*

*Corresponding author for this work

Research output: Contribution to journalArticle

15 Citations (Scopus)
5 Downloads (Pure)

Abstract

The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7-40.7 Mb) and on chromosome 8 (20.3-21.9 Mb). Across experiments, the soil type/growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions.

Original languageEnglish
Article number0124127
Number of pages25
JournalPloS ONE
Volume10
Issue number4
DOIs
Publication statusPublished - 24 Apr 2015

Keywords

  • QUANTITATIVE TRAIT LOCI
  • FED LOWLAND CONDITIONS
  • SOIL-FILLED CHAMBERS
  • SATIVA L.
  • GRAIN-YIELD
  • PENETRATION ABILITY
  • WATER-DEFICIT
  • MORPHOLOGICAL TRAITS
  • GENETIC BACKGROUNDS
  • ALUMINUM TOLERANCE

Cite this

Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems. / Wade, Len J.; Bartolome, Violeta; Mauleon, Ramil; Vasant, Vivek Deshmuck; Prabakar, Sumeet Mankar; Chelliah, Muthukumar; Kameoka, Emi; Nagendra, K.; Reddy, K. R. Kamalnath; Varma, C. Mohan Kumar; Patil, Kalmeshwar Gouda; Shrestha, Roshi; Al-Shugeairy, Zaniab; Al-Ogaidi, Faez; Munasinghe, Mayuri; Gowda, Veeresh; Semon, Mande; Suralta, Roel R.; Shenoy, Vinay; Vadez, Vincent; Serraj, Rachid; Shashidhar, H. E.; Yamauchi, Akira; Babu, Ranganathan Chandra; Price, Adam; McNally, Kenneth L.; Henry, Amelia.

In: PloS ONE, Vol. 10, No. 4, 0124127, 24.04.2015.

Research output: Contribution to journalArticle

Wade, LJ, Bartolome, V, Mauleon, R, Vasant, VD, Prabakar, SM, Chelliah, M, Kameoka, E, Nagendra, K, Reddy, KRK, Varma, CMK, Patil, KG, Shrestha, R, Al-Shugeairy, Z, Al-Ogaidi, F, Munasinghe, M, Gowda, V, Semon, M, Suralta, RR, Shenoy, V, Vadez, V, Serraj, R, Shashidhar, HE, Yamauchi, A, Babu, RC, Price, A, McNally, KL & Henry, A 2015, 'Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems', PloS ONE, vol. 10, no. 4, 0124127. https://doi.org/10.1371/journal.pone.0124127
Wade, Len J. ; Bartolome, Violeta ; Mauleon, Ramil ; Vasant, Vivek Deshmuck ; Prabakar, Sumeet Mankar ; Chelliah, Muthukumar ; Kameoka, Emi ; Nagendra, K. ; Reddy, K. R. Kamalnath ; Varma, C. Mohan Kumar ; Patil, Kalmeshwar Gouda ; Shrestha, Roshi ; Al-Shugeairy, Zaniab ; Al-Ogaidi, Faez ; Munasinghe, Mayuri ; Gowda, Veeresh ; Semon, Mande ; Suralta, Roel R. ; Shenoy, Vinay ; Vadez, Vincent ; Serraj, Rachid ; Shashidhar, H. E. ; Yamauchi, Akira ; Babu, Ranganathan Chandra ; Price, Adam ; McNally, Kenneth L. ; Henry, Amelia. / Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems. In: PloS ONE. 2015 ; Vol. 10, No. 4.
@article{1c967048ebc746cb9252a5b8730f1bb7,
title = "Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems",
abstract = "The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7-40.7 Mb) and on chromosome 8 (20.3-21.9 Mb). Across experiments, the soil type/growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions.",
keywords = "QUANTITATIVE TRAIT LOCI, FED LOWLAND CONDITIONS, SOIL-FILLED CHAMBERS, SATIVA L., GRAIN-YIELD, PENETRATION ABILITY, WATER-DEFICIT, MORPHOLOGICAL TRAITS, GENETIC BACKGROUNDS, ALUMINUM TOLERANCE",
author = "Wade, {Len J.} and Violeta Bartolome and Ramil Mauleon and Vasant, {Vivek Deshmuck} and Prabakar, {Sumeet Mankar} and Muthukumar Chelliah and Emi Kameoka and K. Nagendra and Reddy, {K. R. Kamalnath} and Varma, {C. Mohan Kumar} and Patil, {Kalmeshwar Gouda} and Roshi Shrestha and Zaniab Al-Shugeairy and Faez Al-Ogaidi and Mayuri Munasinghe and Veeresh Gowda and Mande Semon and Suralta, {Roel R.} and Vinay Shenoy and Vincent Vadez and Rachid Serraj and Shashidhar, {H. E.} and Akira Yamauchi and Babu, {Ranganathan Chandra} and Adam Price and McNally, {Kenneth L.} and Amelia Henry",
note = "Funding: This research was funded by the Generation Challenge Program (GCP) project G3008.06, “Targeting Drought-Avoidance Root Traits to Enhance Rice Productivity under Water-Limited Environments{"}. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.",
year = "2015",
month = "4",
day = "24",
doi = "10.1371/journal.pone.0124127",
language = "English",
volume = "10",
journal = "PloS ONE",
issn = "1932-6203",
publisher = "PUBLIC LIBRARY SCIENCE",
number = "4",

}

TY - JOUR

T1 - Environmental Response and Genomic Regions Correlated with Rice Root Growth and Yield under Drought in the OryzaSNP Panel across Multiple Study Systems

AU - Wade, Len J.

AU - Bartolome, Violeta

AU - Mauleon, Ramil

AU - Vasant, Vivek Deshmuck

AU - Prabakar, Sumeet Mankar

AU - Chelliah, Muthukumar

AU - Kameoka, Emi

AU - Nagendra, K.

AU - Reddy, K. R. Kamalnath

AU - Varma, C. Mohan Kumar

AU - Patil, Kalmeshwar Gouda

AU - Shrestha, Roshi

AU - Al-Shugeairy, Zaniab

AU - Al-Ogaidi, Faez

AU - Munasinghe, Mayuri

AU - Gowda, Veeresh

AU - Semon, Mande

AU - Suralta, Roel R.

AU - Shenoy, Vinay

AU - Vadez, Vincent

AU - Serraj, Rachid

AU - Shashidhar, H. E.

AU - Yamauchi, Akira

AU - Babu, Ranganathan Chandra

AU - Price, Adam

AU - McNally, Kenneth L.

AU - Henry, Amelia

N1 - Funding: This research was funded by the Generation Challenge Program (GCP) project G3008.06, “Targeting Drought-Avoidance Root Traits to Enhance Rice Productivity under Water-Limited Environments". The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

PY - 2015/4/24

Y1 - 2015/4/24

N2 - The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7-40.7 Mb) and on chromosome 8 (20.3-21.9 Mb). Across experiments, the soil type/growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions.

AB - The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7-40.7 Mb) and on chromosome 8 (20.3-21.9 Mb). Across experiments, the soil type/growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions.

KW - QUANTITATIVE TRAIT LOCI

KW - FED LOWLAND CONDITIONS

KW - SOIL-FILLED CHAMBERS

KW - SATIVA L.

KW - GRAIN-YIELD

KW - PENETRATION ABILITY

KW - WATER-DEFICIT

KW - MORPHOLOGICAL TRAITS

KW - GENETIC BACKGROUNDS

KW - ALUMINUM TOLERANCE

U2 - 10.1371/journal.pone.0124127

DO - 10.1371/journal.pone.0124127

M3 - Article

VL - 10

JO - PloS ONE

JF - PloS ONE

SN - 1932-6203

IS - 4

M1 - 0124127

ER -