Genetic Dissection of Heat Stress Tolerance in Soybean through Genome-Wide Association Studies and the Use of Genomic Prediction to Enhance Breeding Applications

ABSTRACT Rising temperatures and associated heat stress pose an increasing threat to soybean Glycine max L. (Merr.) productivity. Due to a limited choice of mitigation strategies, the primary arsenal in crop protection comes from improved genetic stress tolerance. Despite this current and looming threat to soybean production, limited studies have examined the genetics of heat stress tolerance. There is a need to conduct large-scale germplasm screening and genetic studies, including genome-wide association mapping and genomic prediction, to identify genomic regions and useful markers associated with heat tolerance traits that can be utilized in soybean breeding programs. We screened a diverse panel of 450 soybean accessions from MG 0-IV to dissect the genetic architecture of physiological and growth-related traits under optimal and heat stress temperatures and study trait relationships and predictive ability. The genetic architecture information of the response to heat revealed in this study provides insights into the genetics of heat stress tolerance. Thirty-seven significant SNPs were detected, with 20 unique SNPs detected in optimal, 16 detected in heat stress, and a single SNP detected for a heat tolerance index. Only one significant SNP was identified across temperature treatments indicating a genetic divergence in soybean responses to temperature. The genomic prediction worked well for biomass traits, but physiological traits associated with heat stress had poor model accuracy. Through our phenotyping efforts, we identified heat tolerant soybean accessions. The identification of heat tolerant accessions and significant SNPs are useful in heat tolerant variety development through marker-assisted and genomic selection. Core ideas Soybean exhibit phenotypic diversity in response to heat stress. Large scale phenotypic screening identified heat tolerant accessions. Previously unreported QTL and SNP associated with biomass and physiological parameters under heat stress are reported. Genomic prediction shows promise in abiotic stress breeding applications.