Genetic diversity, population structure, and linkage disequilibrium among tropical quality protein maize (QPM) lines assessed with high-density SNP markers

Introduction The study of genetic diversity (GD), population structure, and linkage disequilibrium (LD) provides better understanding of the genetic relationships between individuals in a population which can be utilized in crop research and improvement. Methods Genotyping by sequencing (GBS) was used to generate single nucleotide polymorphisms (SNPs) by genotyping a collection of 74 quality protein maize (QPM) lines and further characterize their genetic diversity, population structure, and linkage disequilibrium. A total of 235,214 high-quality SNPs were used for different genetic analyses except for structure and genetic diversity analyses where 11,950 and 7,841 SNPs, respectively, were used. Results and Discussion Analysis of molecular variance (AMOVA) based on these SNPs revealed high genetic heterozygosity among the five populations with 1% of the total genetic variation present among the subpopulations and 99% of the variation was among individuals within the populations. Population structure analysis using Bayesian-based clustering revealed that the 74 lines could be clustered into four groups. Similarly, the neighbor-joining tree indicated the lines are grouped into five major clusters. Further analysis using Principal Component Analysis (PCA) clustered the genotypes into five groups which are concordant with the groups based on pedigree information. Higher genetic diversity was detected in sub population 1 (Mid-Altitude) with a GD value of 0.484 and the lowest in population 5 (0.396) and overall, with mean of 0.434. The LD pattern in the quality protein maize was investigated, and we observed a relatively rapid LD decay of 3.53 kb and 10.66 kb at r 2 = 0.2 and r 2 = 0.1, respectively. Our findings provide important information for future Linkage mapping studies, genome-wide association analyses, and marker-assisted selective breeding of QPM as well as genomic prediction-based selection in tropical maize germplasm.