Brhane Haftom, Hammenhag Cecilia
Department of Plant Breeding, Swedish University of Agricultural Sciences, Lomma, Sweden.
Front Genet. 2024 May 30;15:1396888. doi: 10.3389/fgene.2024.1396888. eCollection 2024.
Breeding resilient cultivars with increased tolerance to environmental stress and enhanced resistance to pests and diseases demands pre-breeding efforts that include understanding genetic diversity. This study aimed to evaluate the genetic diversity and population structure of 265 pea accessions. The diversity arrays technology (DArT) genotyping method was employed to identify single-nucleotide polymorphisms (SNPs) and silico markers. After stringent filtering, 6966 SNP and 8,454 silico markers were selected for diversity analysis. Genetic diversity was estimated by grouping accessions based on plant material type, geographic origin, growth habit, and seed color. Generally, diversity estimations obtained using SNPs were similar to those estimated using silico markers. The polymorphism information content (PIC) of the SNP markers ranged from 0.0 to 0.5, with a quarter of them displaying PIC values exceeding 0.4, making them highly informative. Analysis based on plant material type revealed narrow observed heterozygosity (Ho = 0.02-0.03) and expected heterozygosity (He = 0.26-0.31), with landrace accessions exhibiting the highest diversity. Geographic origin-based diversity analysis revealed Ho = 0.02-0.03 and He = 0.22 to 0.30, with European accessions showing the greatest diversity. Moreover, private alleles unique to landrace (4) and European (22) accessions were also identified, which merit further investigation for their potential association with desirable traits. The analysis of molecular variance revealed a highly significant genetic differentiation among accession groups classified by seed color, growth habit, plant material types, and geographic origin ( < 0.01). Principal coordinate analysis and neighbor-joining cluster analysis revealed weak clustering of accessions at different grouping levels. This study underscores the significance of genetic diversity in pea collections, offering valuable insights for targeted breeding and conservation efforts. By leveraging genomic data and exploring untapped genetic resources, pea breeding programs can be fortified to ensure sustainable plant protein production and address future challenges in agriculture.
培育对环境胁迫具有更高耐受性且对病虫害具有更强抗性的适应性强的品种，需要开展包括了解遗传多样性在内的预育种工作。本研究旨在评估265份豌豆种质的遗传多样性和群体结构。采用多样性阵列技术（DArT）基因分型方法来鉴定单核苷酸多态性（SNP）和电子标记。经过严格筛选，选择了6966个SNP和8454个电子标记用于多样性分析。基于植物材料类型、地理起源、生长习性和种子颜色对种质进行分组，从而估计遗传多样性。一般来说，使用SNP获得的多样性估计值与使用电子标记估计的结果相似。SNP标记的多态性信息含量（PIC）范围为0.0至0.5，其中四分之一显示PIC值超过0.4，使其具有高度信息性。基于植物材料类型的分析显示观察到的杂合度（Ho = 0.02 - 0.03）和预期杂合度（He = 0.26 - 0.31）较窄，但地方品种种质表现出最高的多样性。基于地理起源的多样性分析显示Ho = 0.02 - 0.03，He = 0.22至0.30，欧洲种质表现出最大的多样性。此外，还鉴定了地方品种（4个）和欧洲（22个）种质特有的私有等位基因，它们与优良性状的潜在关联值得进一步研究。分子方差分析显示，按种子颜色、生长习性、植物材料类型和地理起源分类的种质组之间存在高度显著的遗传分化（<0.01）。主坐标分析和邻接法聚类分析显示，在不同分组水平上种质的聚类较弱。本研究强调了豌豆种质中遗传多样性的重要性，为有针对性的育种和保护工作提供了有价值的见解。通过利用基因组数据和探索未开发的遗传资源，可以加强豌豆育种计划，以确保可持续的植物蛋白生产并应对未来农业面临的挑战。
