Genome-wide association mapping to identify genomic regions related to physiological and agronomic traits in bread wheat under drought stress conditions

ObjectiveDrought is one of the major environmental stresses that adversely affect the growth and development of wheat. This study aimed to determine the structure of the population and to identify markers associated with physiological and agronomic traits in bread wheat under drought stress conditions. Materials and methodsA total of 238 bread wheat genotypes were evaluated using a randomized complete block design with two replications under drought stress conditions. Various physiological traits, including carbon dioxide exchange, photosynthesis rate, and chlorophyll content, as well as agronomic traits such as days to heading, days to maturity, flag leaf length and width, plant height, seed weight per plant, number of seeds per unit area, seed yield, and biological yield, were measured. Genotyping was performed using 9K SNP array. The population structure analysis was conducted using 17,093 SNP markers in R software. Marker-trait association (MATs) was carried out using GLM model in TASSEL. ResultsThe analysis of population structure divided the 238 wheat genotypes into five subgroups. A total of 132 MTAs were identified for different traits. Notably, four SNPs, on chromosomes 6B, 4A and 6A exhibited pleiotropic effects on traits such as seed number per unit area, seed weight, and yield. Furthermore, eight MTAs for seed weight were identified on chromosomes 4B, 5B, 6B, and 7A. Chromosome 6B contained the highest number of SNPs, covering a region between 481-519 Mbp. For the number of seeds per unit area, 12 MTAs were located on chromosomes 3B, 4A, 5A, 6A, and 6B. The region with the highest number of SNPs was found between 561-492 Mbp on chromosome 6B, which overlapped with the region associated with seed weight per plant. These findings highlight the significance of this specific region in the wheat genome for improving bread wheat yield.ConclusionsThe results of this research provide valuable insights for breeders seeking to enhance wheat yield potential. Identified markers associated with key agronomic traits can be utilized in marker-assisted selection programs, aiding in the selection of desired traits.