Genome-Wide Association Studies for Improving Agronomic Traits in Foxtail Millet

Abstract

With the immense advancements in sequencing and data mining approaches, identification of genome-wide genetic variants in a population has become very popular. The use of these resources in the development of a dense genetic map of genome variations and to identify associated quantitative traits has become widespread in crop genetics. In recent years, genome-wide association study (GWAS) has become a powerful tool in revealing the relationship between natural variation of complex genotype and genetic locus. A slight variation in the genetic architecture of an individual in a population results in contrasting agronomic traits compared to the other individuals. GWAS utilized high-throughput genotyping platform and extensively phenotyping data to detect the links between genetic variations that underlie variations in agronomic traits. These studies can accelerate the use of genomic selection in marker-assisted breeding for crop improvement. Here, a brief discussion of available genomic resources and their utilization, quantitative trait loci (QTL) underlying agronomic traits, GWAS in foxtail millet, and the prospects for this field in crop designing is given.