Investigating Genetic Diversity and Population Structure in Rice Breeding from Association Mapping of 116 Accessions Using 64 Polymorphic SSR Markers

Crops Pub Date : 2024-05-23 DOI:10.3390/crops4020014
Alok Singh, Devendra Kumar, Donato Gemmati, R. Ellur, Ashutosh Singh, V. Tisato, D. Dwivedi, Sanjay Singh, Kishor Kumar, Nawaz Khan, A. Singh
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Abstract

Genetic variability in rice breeding programs plays a very crucial role. It provides an outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For a greater understanding of population structure, the genetic relationship among different rice lines is indispensable prior to the setting of a correlation among dynamic alleles and traits. In the present investigation, the genetic diversity and population structure of 116 rice accessions were studied to understand genetic relatedness and diversity among them using 64 polymorphic SSR markers. A genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model- and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% was likely due to differences within groups. This study suggested that population structure and genetic relatedness should be considered to establish marker–trait associations for association mapping when working with the core collection of germplasm lines.
利用 64 个多态性 SSR 标记对 116 个品系的关联图谱研究水稻育种中的遗传多样性和种群结构
遗传变异在水稻育种计划中起着非常关键的作用。它通过关联图谱提供了一个优秀的等位基因库,这些等位基因调控着更好的农艺性状和品质特征。为了更好地了解种群结构,在建立动态等位基因与性状之间的相关性之前,不同水稻品系之间的遗传关系是必不可少的。本研究利用 64 个多态 SSR 标记研究了 116 个水稻品种的遗传多样性和种群结构,以了解它们之间的遗传亲缘关系和多样性。基于 SSR 标记的基因分型评估显示,共有 225 个等位基因,平均 PIC 值为 0.755。利用基于模型和距离的方法,通过种群结构分析将种质品系分为三个不同的亚群。AMOVA分析表明,11%的总变异可归因于组间差异,而其余89%可能是由于组内差异造成的。这项研究表明,在使用核心种质品系时,应考虑种群结构和遗传亲缘关系,以建立标记与性状之间的关联,从而绘制关联图谱。
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