使用双基因组预测模型预测耐药性,毒性和宿主对病原体的相互作用
Owen Hudson1, Marcio F R Resende2,3, Charlie Messina2,3
1Plant Pathology, University of Florida, Gainesville, FL, USA.
概括
整合基因组和疾病查数据提供了一种统一的方法来开发作物疾病耐药性. 这种方法增强了预测模型,使育种者能够识别耐药品种并有效管理病原体种群.
科学领域:
- 植物病理学 植物病理学
- 基因组学就是基因组学.
- 定量遗传学 是一个量子遗传学.
背景情况:
- 培养作物抗病能力对于粮食安全至关重要.
- 传统方法涉及将繁殖种群暴露在特定的病原体中,限制广泛的耐药性发展.
- 整合各种病原体数据在后勤上具有挑战性.
研究的目的:
- 展示如何整合疾病查和基因组数据可以改善疾病耐药性的预测模型.
- 探索宿主-病原体相互作用对遗传参数估计的影响.
- 为育种者和病理学家提供统一的框架.
主要方法:
- 使用了使用多种甜玉米和病原体隔离物的替代性疾病查系统.
- 在预测模型中使用宿主和病原体种群的基因组数据.
- 将宿主-病原体相互作用效应纳入统计模型.
主要成果:
- 当仅包括病原体相关性时,观察到基因变异估计的通胀.
- 宿主-病原体相互作用效应缓和了遗传变异膨胀.
- 主体,病原体和相互作用效应对病变大小的表型变化也有类似的贡献.
结论:
- 使用基因组和疾病查数据的统一框架有助于开发作物疾病耐药性.
- 宿主-病原体相互作用预测对于识别耐药作物品种和指导耐药性部署是有价值的.
- 这种方法增强了农作物中广泛而持久的抗病能力的发展.
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