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

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.Peer reviewedPublisher PD

The Woman and the Dragon. Exposition of Rev 12 in Christian Traditions

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Biplots for A) grain yield, B) root dry weight, C) maximum root depth, and D) % deep roots.

<p>Data previously reported by Henry et al (2011), Gowda et al (2012), and Shrestha et al (2013) were used to calculate some of the results shown in this figure.</p

The OryzaSNP germplasm set was phenotyped with a range of root-screening techniques.

<p>A) rhizotron (Ab09CR: Univ Aberdeen), B) penetration of nonwoven fabric (Ab09CNWNW: Univ Aberdeen), C) monoliths from line source sprinkler (Na10 and Na11; Nagoya Univ), D) soil-filled cylinders (Ba10C; Barwale Foundation, and CS09C; Charles Sturt Univ), E) hydroponics (Ab09CH: Univ Aberdeen), F) monoliths in the field (IR08FL and IR09dFL; IRRI), G) lysimeters (IR08C; IRRI, IC09C; ICRISAT), and (H) in the field by excavation (TN10F, TN11F; Tamil Nadu Agric. Univ).</p

A genomic region on chromosome 1 (39.7–40.7 Mb) was identified as a hot spot in which root dry weight, percent deep roots, and yield aligned.

<p>Colors indicate each experiment from which the phenotypic data and introgression regions were correlated. Experiments from which introgression regions fell within the hot spot are identified in the legend.</p

The 20 OryzaSNP genotypes used in this study.

<p>The 20 OryzaSNP genotypes used in this study.</p

The number of experiments with which the data from each experiment were correlated (p<0.05).

<p>These numbers are based on Pearson’s two-sided correlation matrix (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124127#pone.0124127.s001" target="_blank">S1</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124127#pone.0124127.s005" target="_blank">S5</a> Tables).</p><p>^aone correlation was negative</p><p>The number of experiments with which the data from each experiment were correlated (p<0.05).</p

Dendrograms of environmental groupings.

<p>A) grain yield, B) root dry weight, C) maximum root depth, and D) % deep roots. Data previously reported by Henry et al (2011), Gowda et al (2012), and Shrestha et al (2013) were used to calculate some of the results shown in this figure.</p

AMMI (mean polish) and location standardized model analysis of GxE interactions across all experiments from which yield, root dry weight (RDW), maximum root depth (MRL), and percent deep roots (%DR) were measured.

<p>AMMI (mean polish) and location standardized model analysis of GxE interactions across all experiments from which yield, root dry weight (RDW), maximum root depth (MRL), and percent deep roots (%DR) were measured.</p

Previously reported root-related QTLs within the regions of chromosomes 1 and 8 where the highest number of traits aligned in this study.

<p>Gramene QTL ID: the Gramene database accession code; List hits: the number of 100kb blocks in the current introgression bin that intersect the Gramene QTL; List total: the total number of 100kb blocks in current QTL bin; Population hits: the total number of genome-wide 100kb introgression blocks for the current Gramene QTL category (out of a total of 3680 100kb introgression blocks for all Gramene QTLs; P value: probability based on a one-tailed Fisher's Exact Test; Reference: the publication in which the QTL was reported.</p><p>Previously reported root-related QTLs within the regions of chromosomes 1 and 8 where the highest number of traits aligned in this study.</p