Laboratory of Molecular Biology and Bioinformatics Applied to Genomics, National University of Sciences, Technologies Engineering and Mathematics of Abomey, Dassa-Zoumé, Benin.
Centre of Excellence in Genomics and Systems Biology, International Crop Research Institute for the Semi-Arid Tropics, Hyderabad, India.
PLoS One. 2022 Jul 20;17(7):e0271565. doi: 10.1371/journal.pone.0271565. eCollection 2022.
Genetic diversity studies provide important details on target trait availability and its variability, for the success of breeding programs. In this study, GBS approach was used to reveal a new structuration of genetic diversity and population structure of pigeonpea in Benin. We used a total of 688 high-quality Single Nucleotide Polymorphism markers for a total of 44 pigeonpea genotypes. The distribution of SNP markers on the 11 chromosomes ranged from 14 on chromosome 5 to 133 on chromosome 2. The Polymorphism Information Content and gene diversity values were 0.30 and 0.34 respectively. The analysis of population structure revealed four clear subpopulations. The Weighted Neighbor Joining tree agreed with structure analyses by grouping the 44 genotypes into four clusters. The PCoA revealed that genotypes from subpopulations 1, 2 and 3 intermixed among themselves. The Analysis of Molecular Variance showed 7% of the total variation among genotypes while the rest of variation (93%) was within genotypes from subpopulations indicating a high gene exchange (Nm = 7.13) and low genetic differentiation (PhiPT = 0.07) between subpopulations. Subpopulation 2 presented the highest mean values of number of different alleles (Na = 1.57), number of loci with private alleles (Pa = 0.11) and the percentage of polymorphic loci (P = 57.12%). We discuss our findings and demonstrate how the genetic diversity and the population structure of this specie can be used through the Genome Wide Association Studies and Marker-Assisted Selection to enhance genetic gain in pigeonpea breeding programs in Benin.
遗传多样性研究为成功的育种计划提供了目标性状的可用性和变异性的重要细节。在这项研究中,GBS 方法被用于揭示贝宁的羽扇豆遗传多样性和群体结构的新结构。我们使用了总共 688 个高质量的单核苷酸多态性标记,用于总共 44 个羽扇豆基因型。SNP 标记在 11 条染色体上的分布范围从第 5 号染色体上的 14 个到第 2 号染色体上的 133 个。多态信息含量和基因多样性值分别为 0.30 和 0.34。群体结构分析显示有四个明显的亚群。加权邻接法树通过将 44 个基因型分为四个聚类与结构分析一致。PCoA 显示来自亚群 1、2 和 3 的基因型相互混合。分子方差分析表明,基因型之间存在 7%的总变异,而其余的变异(93%)是在亚群内的基因型之间,这表明亚群之间存在高度的基因交流(Nm = 7.13)和低遗传分化(PhiPT = 0.07)。亚群 2 呈现出最高的平均不同等位基因数(Na = 1.57)、特有等位基因数(Pa = 0.11)和多态性位点比例(P = 57.12%)。我们讨论了我们的发现,并展示了如何通过全基因组关联研究和标记辅助选择利用该物种的遗传多样性和群体结构来提高贝宁羽扇豆育种计划的遗传增益。