使用GWAS预选变体和固定效果SNP增加了果的基因组预测能力
Norman Munyengwa1, Melanie J Wilkinson1,2,3,4, Daniel Ortiz-Barrientos2,3
1Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD, Australia.
Frontiers in plant science
|November 14, 2025
概括
果的基因组选择通过结合从全基因组关联研究 (GWAS) 和固定效应标记物中预先选择的变异来提高准确性. 这一策略增强了对关键水果特征的预测能力,提高了育种效率.
科学领域:
- 植物育种 植物育种
- 基因组学就是基因组学.
- 量化遗传学 量化遗传学
背景情况:
- 使用全基因组测序 (WGS) 数据的基因组选择 (GS) 提供了提高果树育种价值准确性的潜力.
- 之前的研究表明,与高密度标记集相比,WGS数据的收益有限,因此需要制定提高预测能力的策略.
- 从全基因组关联研究 (GWAS) 中纳入预选变体是一个有前途的方法来改进GS模型.
研究的目的:
- 研究将GWAS预选变体和固定效应标记物纳入基因组最佳线性无偏预测 (GBLUP) 模型的影响.
- 评估果 (Mangifera indica L.) 果实红色 (FBC),平均果实重量 (AFW),果实坚硬度 (FF) 和树干周长 (TC) 的预测能力的改善.
主要方法:
- 利用了来自225个果加入的WGS数据与跨越1999-2024年的表型数据.
- 使用GBLUP模型评估预测能力,比较通过固定主要组件忽略或考虑人口结构的方法.
- 评估了包括GWAS预选变体和固定效应单核酸多态 (SNP) 在预测能力上的影响.
主要成果:
- 考虑到人口结构显著降低了预测能力,这表明子群体影响了初步估计.
- 与使用所有WGS数据相比,GWAS预选的变体提高了预测能力,特别是当考虑人口结构时.
- 固定效应的SNP显著提高了FBC的预测能力,GWAS预选变体和固定效应标记物的组合为FBC和TC带来了最高的改善.
结论:
- 利用GWAS预选变体和固效SNP有效地提高了果基因组选择的预测能力.
- 这种精细的方法有可能通过提高准确性来显著提高果树的育种效率.
- GWAS确定了FBC,AFW和TC的特定特征相关SNP,为标记器辅助选择提供了有价值的标.
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