使用环境共变量改善植物疾病的基因组预测
Charlotte Brault1, Emily J Conley2, Andrew C Read3
1Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA. charlotte.brault@live.com.
Plant methods
|August 21, 2025
概括
了解基因型与环境的相互作用 (GxE) 可以改善小麦的菌头部炎 (FHB) 耐药性预测. 结合环境共变量的联合基因组回归分析 (JGRA) 提高了在不同地点选择耐药菌株的准确性.
科学领域:
- 农业科学
- 植物病理学
- 遗传学
背景情况:
- 虫 (Fusarium Head Blight) 严重影响小麦和大麦的产量和质量.
- 疾病耐药性是复杂的,受遗传学,环境和基因型对环境相互作用 (GxE) 的影响.
- 在各种环境中预测FHB耐药性对于育种计划来说是一个挑战.
研究的目的:
- 研究春季小麦的GxE,以改善FHB耐药性的预测.
- 评估在未经测试的环境中预测基因型性能的方法.
- 确定与FHB耐药性和环境敏感性相关的遗传标记.
主要方法:
- 比较了芬莱-威尔金森回归 (FW),联合基因组回归分析 (JGRA) 和混合模型.
- 纳入环境共变量来计算环境指数和关系矩阵.
- 与没有环境共变量的基因组选择 (GS) 模型进行比较.
主要成果:
- 在内部和跨环境预测方面,JGRA的准确性高于GS.
- 混合模型的性能可与JGRA进行环境内预测.
- 鉴于此,JGRA确定了FHB耐药性和环境敏感性的重要标志物,从而能够预测特定地点的育种价值.
结论:
- 结合环境共变量可以提高选择耐药基因型的预测能力.
- 利用GxE相互作用改善了小麦育种中的疾病管理策略.
- 这种方法为养者提供了一种具有成本效益的方法来利用GxE提高FHB的耐药性.
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