Genetic Dissection of Grain Yield Component Traits Under High Nighttime Temperature Stress in a Rice Diversity Panel.

To dissect the genetic complexity of rice grain yield (GY) and quality in response to heat stress at the reproductive stage, a diverse panel of 190 rice accessions in the United States Department of Agriculture (USDA) rice mini-core collection (URMC) diversity panel were treated with high nighttime temperature (HNT) stress at the reproductive stage of panicle initiation. The quantifiable yield component response traits were then measured. The traits, panicle length (PL), and number of spikelets per panicle (NSP) were evaluated in subsets of the panel comprising the rice subspecies ssp. and ssp. . Under HNT stress, the ssp. exhibited lower reductions in PL and NSP and a higher level of genetic variation compared with the other subpopulations. Whole genome sequencing identified 6.5 million single nucleotide polymorphisms (SNPs) that were used for the genome-wide association studies (GWASs) of the PL and NSP traits. The GWAS analysis in the Combined, , and populations under HNT stress identified 83, 60, and 803 highly significant SNPs associated with PL, compared to the 30, 30, and 11 highly significant SNPs associated with NSP. Among these trait-associated SNPs, 140 were coincident with genomic regions previously reported for major GY component quantitative trait loci (QTLs) under heat stress. Using extents of linkage disequilibrium in the rice populations, Venn diagram analysis showed that the highest number of putative candidate genes were identified in the population, with 20 putative candidate genes being common in the Combined, and populations. Network analysis of the genes linked to significant SNPs associated with PL and NSP identified modules that were involved in primary and secondary metabolisms. The findings in this study could be useful to understand the pathways/mechanisms involved in rice GY and its components under HNT stress for the acceleration of rice-breeding programs and further functional analysis by molecular geneticists.