Linking Genome Wide Association Studies (GWAS) and Genomic Selection (GS) to better utilize Natural Variation in Rice

Understanding the relationship between genotypic and phenotypic variation lies at the heart of the study of genetics and is also critically important to applications in plant breeding. Here we present a genome-wide association study (GWAS) based on genotyping a rice diversity panel with a high-density SNP array and systematically phenotyping the panel for a range of agronomic, physiological and morphological traits. Seeds conserved in global germplasm repositories, including wild rice ancestors, ancient landrace varieties and modern elite cultivars provide insight into a wide range of natural genetic variation that remains underutilized in modern rice genetics and breeding. Using high throughput sequencing and genotyping technologies, we examine genome-wide patterns of variation and document deep sub-population structure within Oryza sativa. We use GWAS to identify common variants influencing complex traits and demonstrate heterogeneity of genetic architecture across subpopulations and environments. We use genomic selection (GS) in combination with de novo GWAS to predict breeding values and improve the rate of genetic gain. This work establishes an open-source translational research platform for genome-wide association studies and genomic selection in rice that directly links molecular variation in genes and metabolic/regulatory pathways with the germplasm resources needed to accelerate varietal development and crop improvement for diverse environments.