Genomic dissection of yield components in rice (Oryza sativa L.) using genome-wide association study and identification of novel genetic factors for yield-related traits

Abstract

Genome-wide association study (GWAS) is a powerful method for understanding the associations between phenotype and genomic variations. Given the growing population, increasing yield of rice as a staple food crop is important. Here, a GWAS with 33,839 single nucleotide polymorphisms (SNPs) was carried out to define genomic regions influencing rice (Oryza sativa L.) yield components under field condition in 219 rice accessions using mixed linear model-Q-K model. High-throughput phenotyping provided extensive data for grain weight (GW), length and width, number of tillers, number of filled and empty grains per panicle, plant height (PH), panicle length, internode length, flag leaf length (FLL), and flag leaf width. Fifty five significant quantitative trait loci tagged to 97 SNPs were detected across all chromosomes of rice. Except for grain width, 3–10 genomic regions were identified for other 10 morphological traits. In the close vicinity of GWAS signals, well-known genes (such as SD1 for PH) were identified. Furthermore, the role of few recently reported genes that affect yield and its components were validated including monosaccharide transporter 1, nitrate transporter NTL1 (both associated with GW), and a sugar transporter family protein that is associated with grain length. Several novel candidate genes were detected by GWAS including the genes of glycoside hydrolase family, associated with tiller number, and growth-regulating factor 7, associated with PH and FLL. In addition, several transcription factors were identified for different traits. The findings of this research give new insights into the genetic improvement of rice yield and its components using genome-based breeding strategies.