Kasule Faizo, Alladassi Boris M E, Aru Charles John, Adikini Scovia, Biruma Moses, Ugen Michael Adrogu, Kakeeto Ronald, Esuma Williams
Interdepartmental Genetics and Genomics (IGG), Iowa State University, Ames, IA, United States.
Department of Agronomy, Iowa State University, Ames, IA, United States.
Front Plant Sci. 2024 Oct 7;15:1458179. doi: 10.3389/fpls.2024.1458179. eCollection 2024.
Sorghum is an important source of food and feed worldwide. Developing sorghum core germplasm collections improves our understanding of the evolution and exploitation of genetic diversity in breeding programs. Despite its significance, the characterization of the genetic diversity of local germplasm pools and the identification of genomic loci underlying the variation of critical agronomic traits in sorghum remains limited in most African countries, including Uganda. In this study, we evaluated a collection of 543 sorghum accessions actively used in Ugandan breeding program across two cropping seasons at NaSARRI, Uganda, under natural field conditions. Phenotypic data analysis revealed significant (<0.01) variation among accessions for days to 50% flowering, plant height, panicle exsertion, and grain yield, with broad-sense heritability (H²) estimates of 0.54, 0.9, 0.81, and 0.48, respectively, indicating a high genetic variability for these traits. We used a newly developed genomic resource of 7,156 single nucleotide polymorphism (SNP) markers to characterize the genetic diversity and population structure of this collection. On average, the SNP markers exhibited moderately high polymorphic information content (PIC = 0.3) and gene diversity (He = 0.3), while observed heterozygosity (Ho = 0.07) was low, typical for self-pollinating crops like sorghum. Admixture-based models, PCA, and cluster analysis all grouped the accessions into two subpopulations with relatively low genetic differentiation. Genome-wide association study (GWAS) identified candidate genes linked to key agronomic traits using a breeding diversity panel from Uganda. GWAS analysis using three different mixed models identified 12 genomic regions associated with days to flowering, plant height, panicle exsertion, grain yield, and glume coverage. Five core candidate genes were co-localized with these significant SNPs. The SNP markers and candidate genes discovered provide valuable insights into the genetic regulation of key agronomic traits and, upon validation, hold promise for genomics-driven breeding strategies in Uganda.
高粱是全球重要的食物和饲料来源。开发高粱核心种质资源库有助于我们在育种计划中更好地理解遗传多样性的进化和利用。尽管其具有重要意义，但在包括乌干达在内的大多数非洲国家，对当地种质资源库的遗传多样性特征分析以及高粱关键农艺性状变异背后的基因组位点鉴定仍然有限。在本研究中，我们在乌干达纳萨里的自然田间条件下，于两个种植季节对乌干达育种计划中积极使用的543份高粱种质进行了评估。表型数据分析显示，在50%开花天数、株高、穗抽出度和籽粒产量方面，种质间存在显著（<0.01）差异，广义遗传力（H²）估计值分别为0.54、0.9、0.81和0.48，表明这些性状具有较高的遗传变异性。我们使用新开发的包含7156个单核苷酸多态性（SNP）标记的基因组资源来表征该种质的遗传多样性和群体结构。平均而言，SNP标记表现出中等偏高的多态信息含量（PIC = 0.3）和基因多样性（He = 0.3），而观察到的杂合度（Ho = 0.07）较低，这是高粱等自花授粉作物的典型特征。基于混合模型、主成分分析（PCA）和聚类分析均将种质分为两个亚群，遗传分化相对较低。全基因组关联研究（GWAS）使用来自乌干达的育种多样性面板鉴定了与关键农艺性状相关的候选基因。使用三种不同混合模型的GWAS分析确定了12个与开花天数、株高、穗抽出度、籽粒产量和颖壳覆盖率相关的基因组区域。五个核心候选基因与这些显著的SNP共定位。发现的SNP标记和候选基因对关键农艺性状的遗传调控提供了有价值的见解，经验证后，有望用于乌干达的基因组驱动育种策略。
