Georgia C. Eizenga

TL;DR: 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.

TL;DR: A high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop, provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation.

TL;DR: These analyses highlight the power of population genomics in agricultural systems to identify functionally important regions of the genome and to decipher the role of human-directed breeding in refashioning the genomes of a domesticated species.

TL;DR: A suite of SNP-based resources have been developed and made publicly available for broad application in rice research, including large SNP datasets, tools for identifying informative SNPs for targeted applications, and a suite of custom-designed SNP assays for use in marker-assisted and genomic selection, association and QTL mapping, positional cloning, pedigree analysis, variety identification and seed purity testing as mentioned in this paper.

TL;DR: A large number of loci significantly associated with variation in grain arsenic, copper, molybdenum and zinc were revealed and a number of candidate genes for the uptake or transport of these elements were located near significantly associated SNPs.