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多种群GWAS在一个新成立的六排冬品种计划中检测到强大的标记协会

Cathrine Kiel Skovbjerg^1,2, Pernille Sarup³, Ellen Wahlström³

¹Nordic Seed A/S, Odder, Denmark. cask@nordicseed.com.

|November 28, 2024

概括

多种群全基因组关联研究 (GWAS) 在新的大麦育种计划中显著提高了标记特征发现的力量. 这种方法有效地确定了标题日期和存放位置的强有力的定量特征位置,加速了遗传收益.

科学领域:

植物遗传学植物遗传学
定量遗传学是一种定量遗传学.
农业科学农业科学

背景情况:

全基因组关联研究 (GWAS) 对于识别标记特征关联至关重要,以推进作物育种.
新成立的育种计划往往缺乏足够的数据来进行强大的GWAS.
从已建立的计划中整合数据可以克服新种群的数据限制.

研究的目的:

评估多种群GWAS在新建立的大麦种群中检测标记特征关联的有效性.
为了比较多种群GWAS的单变量和多变量模型.
为了确定标题日期和存款的强有力的定量特征位置 (QTL).

主要方法:

在行程日期执行单种和多种群GWAS,并在四个大麦种群中进行寄宿.
专注于6行冬季 (6RW) 麦种群,将其与其他种群进行比较.
使用单变量 (MP1) 和多变量 (MP2) 模型用于多种群GWAS.

主要成果:

在6RW群体中,单个群体GWAS产生了很少的显著关联.
多种群GWAS分别确定了四个和五个强大的候选QTL,分别为标题日期和投放.
多变量模型 (MP2) 显示出优越的功率,并确定了跨种群更现实的标志物-特征关联.

结论:

多种群GWAS是一种强大的策略,可以在新生育种计划中启动基因组学基础的育种.
这种方法有效地检测出显著的标记特征关联,即使对于单个种群分析中遗漏的位置.
多变量模型 (MP2) 为强大的QTL检测和特定人群特定位置的识别提供了优势.

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