一种递归模型方法,将表观遗传效应纳入基因评估中,使用模拟的DNA甲基化效应
Adrián López-Catalina1,2,3, Mohamed Ragab1, Antonio Reverter3
1Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), CSIC, Madrid, Spain.
概括
这项研究引入了一个多原子模型 (GOBLUP),将DNA甲基化数据整合到动物育种中. 为了提高准确性,GOBLUP通过分离附加遗传和表观遗传变异来改善育种决策.
科学领域:
- 动物遗传学和动物基因组学
- 表观遗传学和定量遗传学
- 生物信息学和统计建模.
背景情况:
- 基因甲基化是影响基因调节和动物特征的关键表观遗传机制.
- 高通量测序的进步使得大规模,负担得起的甲基化数据的捕获成为可能.
- 将多原子数据集成到遗传评估模型中,对于改善动物育种至关重要.
研究的目的:
- 调整和评估一个多原子模型 (GOBLUP),将DNA甲基化数据纳入遗传评估中.
- 评估模型分离附加遗传和表观遗传变异的能力.
- 开发和验证一个估计表观遗传价值 (EEV) 以改善育种决策.
主要方法:
- 基于6只奶牛的数据,对13,183只基因型动物的模拟甲基化概况.
- 作为添加性特征对甲基化敏感性进行了处理,并模拟了甲基化调节性特征.
- 调整了GOBLUP多原子模型,并将其与传统BLUP方法进行了比较.
主要成果:
- 戈布卢普准确估计了甲基化责任和表观遗传学调节性特征的遗传性.
- 该模型有效地分离了附加遗传和表观遗传变异.
- 新的估计表观遗传值 (EEV) 与传统的EBV相比,与真正的育种值的相关性更高.
结论:
- GOBLUP多原子模型有效地整合了DNA甲基化数据,以改善动物育种中的遗传评估.
- 考虑到对DNA甲基化的遗传责任,可以提高育种决策和选择精度.
- 具有成本效益的同时获取遗传和表观遗传数据将进一步提高育种准确性.
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