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.

Rice Root Architectural Plasticity Traits and Genetic Regions for Adaptability to Variable Cultivation and Stress Conditions

“…The effectiveness of this approach using just 20 genotypes per population in the field studies is evidenced by the identification of a locus for grain yield at the same locus on chromosome 10 as a QTL for grain yield reported by Sandhu et al (2015) from a population of 300 genotypes. In terms of plasticity, the region on chromosome 1 (loci id1023892 and id1024972) is located near qDTY 1.1 , a major-effect drought-yield QTL that has been observed to confer plastic responses to drought, including increased root growth at depth and regulation of shoot growth (Vikram et al, 2015), as well as a hot spot for root traits including an increased proportion of deep roots by drought in the OryzaSNP panel (Wade et al, 2015). No plasticity traits from this study were colocated with the recently identified QTL qLLRN-12 for plasticity in lateral root growth under soil moisture fluctuation stress (Niones et al, 2015), although a locus at which root traits were detected in the Aus 276 population (id12001321 on chromosome 12) colocates with qLLRN-12.…”

Root aquaporins contribute to whole plant water fluxes under drought stress in rice (Oryza sativa L.)

“…() and Wade et al . (). Traits related to plant water transport ( S r, S r_Inh, T r, T r_Inh and S r_DS) or plant water use (CT, SDW reduction and DRI) measured in Experiments 5, 6 and 7, together with traits related to water uptake previously measured on this panel including volumetric soil moisture (VSM) in the field (Henry et al .…”

Growing Out of Stress: The Role of Cell- and Organ-Scale Growth Control in Plant Water-Stress Responses

“…Recently, another QTL was identified (DRO3) that affects root growth angle in a DRO1-dependent manner (Uga et al, 2015). Additional QTL and genomewide association studies in rice revealed further QTLs for deeper root growth under water-deficit conditions (Courtois et al, 2009;Lou et al, 2015;Wade et al, 2015).…”