在脉作物初步产量试验的多特征多环境基因组预测
Rica Amor Saludares1, Sikiru Adeniyi Atanda1, Lisa Piche1
1Department of Plant Sciences, North Dakota State University, Fargo, North Dakota, USA.
The plant genome
|August 5, 2024
概括
多特征多环境基因组预测 (MTME-GP) 提高了田间豆育种中种子产量和蛋白质的预测准确度. 这种方法提高了选择效率,特别是当面对有限的资源和敌对的特征时.
科学领域:
- 植物育种 植物育种
- 基因组学就是基因组学.
- 定量遗传学 是一种定量遗传学.
背景情况:
- 种子产量和蛋白质等复杂特征的表型选择受到种子可用性的限制,导致使用很少环境和复制的试验.
- 多特征多环境基因组预测 (MTME-GP) 是预测多种特征和环境中选择候选人的缺失表型的有价值工具.
研究的目的:
- 评估MTME-GP在提高田间豆种子蛋白质和种子产量的效率.
- 评估MTME-GP的预测能力与公共脉作物育种计划中的标准模型相比.
主要方法:
- 利用了300名代表北达科他州立大学田间豆育种计划的候选人.
- 在三个不同的环境中评估候选人,遗传能力不同.
- 使用MTME-GP和标准添加剂G-BLUP模型的整体和分割环境交叉验证方案.
主要成果:
- MTME-GP表现出比标准G-BLUP模型更高的预测能力.
- 整合重叠的基因型改善了MTME-GP的预测能力,在50%-80%的培训集大小处停滞不前.
- 在压力较大的环境中,预测准确度最低,这可能是由于目标特征的遗传性较低.
结论:
- MTME-GP显示了在公共脉作物育种计划中提高选择效率的巨大潜力.
- 通过在育种管道的早期加入更多的测试环境和额外的正交信息,可以实现对MTME-GP框架的进一步改进.
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