Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa

TLDR

Asian rice, a staple for over half the world, relies on understanding its genetic basis for traits that influence yield, quality, and sustainability. The study aims to establish an open‑source platform linking genetic variation to germplasm for accelerating rice improvement. The platform uses genome‑wide association studies on 44,100 SNPs across 413 diverse accessions phenotyped for 34 traits. The GWAS identified dozens of common variants affecting 34 traits, revealing substantial heterogeneity linked to subpopulation structure and environment, including variants influencing seed size and flowering time. Zhao et al.

Abstract

Asian rice, Oryza sativa is a cultivated, inbreeding species that feeds over half of the world's population. Understanding the genetic basis of diverse physiological, developmental, and morphological traits provides the basis for improving yield, quality and sustainability of rice. Here we show the results of a genome-wide association study based on genotyping 44,100 SNP variants across 413 diverse accessions of O. sativa collected from 82 countries that were systematically phenotyped for 34 traits. Using cross-population-based mapping strategies, we identified dozens of common variants influencing numerous complex traits. Significant heterogeneity was observed in the genetic architecture associated with subpopulation structure and response to environment. This work establishes an open-source translational research platform for genome-wide association studies in rice that directly links molecular variation in genes and metabolic pathways with the germplasm resources needed to accelerate varietal development and crop improvement. Understanding the genetics and physiology of domesticated species is important for crop improvement. By studying natural variation and the phenotypic traits of 413 diverse accessions of rice, Zhao et al. identify many common genetic variants that influence quantitative traits such as seed size and flowering time.