Genetic Diversity and Population Structure Analyses of Some Bread Wheat (Triticum aestivum L) Genotypes
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Understanding the magnitude of the genetic diversity, population structure, and LD that exist in the crop germplasm are necessary precondition for achieving the genomic predictions of desired traits. This study investigated the genetic diversity and population structure of 185 bread wheat genotypes as a prerequisite for GWAS and genomic selection. The genotypes were evaluated under drought-stressed and well-watered conditions. Chromosome-wise genomic SNP distribution, MAF, observed heterozygosity, and the PIC were performed using GBS-based SNP markers. The relationship matrix was determined with the UPGMA module of TASSEL 5.0 to compile dendrograms. The population structure was determined with the help of the STRUCTURE 2.3.4 program. A total of 13,230 high-quality SNPs were identified and distributed across the three wheat genomes, of which 35.7% of the markers were located on the B sub-genome, 34.3% on the sub-genome A, and 30.0% on the D sub-genome. Based on the analysis of population structure, the genotypes were divided into six clusters. The mean MAF, PIC, and genetic diversity of the population were 0.24, 0.27, and 0.34, respectively. The average LD decay for the whole genome of significant marker pairs at r 2 > 0.2 was 19.5 Mb for the A-genome, 23.2 Mb for the B-genome, and 24.3 Mb for the D genome. The percent membership of the genotypes to a specific cluster showed that cluster 6 had the largest membership with 22.1% of the population, whereas cluster 3 was the lowest with 12.5% of the population. The highest degree of genetic differentiation was detected in cluster 3 (F s t = 0.64), whereas the lowest was observed in cluster 2 (F st = 0.26). The high genetic diversity identified among the clusters can be used to develop new bread wheat cultivars with desired traits. The moderate to high divergence detected among bread wheat genotypes within clusters suggested that the genotypes could be used further for GWAS.
