验证效率指数的基因组预测及其早期哺乳期霍尔斯坦牛的成分特征
概括
乳牛的新效率指数 (NEI) 的基因组预测显示,提高使用效率和减少污染是有前途的. 从其组成特征来间接准确估计NEI的SNP影响.
科学领域:
- 动物遗传学动物遗传学
- 乳制品科学 乳制品科学
- 环境科学 环境科学
背景情况:
- (N) 使用效率 (NUE) 对奶牛经济和环境影响至关重要.
- 开发了一种新的效率指数 (NEI),将NUE和N污染整合在一起.
- 验证NEI的基因组预测对于其实际应用至关重要.
研究的目的:
- 为了验证NEI及其组件的基因组预测:N摄入量 (NINT),牛奶真蛋白N (MTPN) 和牛奶尿素N产量.
- 调查从NEI直接估计的SNP效应与从其组成特征间接估计的SNP效应之间的关系.
- 评估将基因组信息纳入常规NEI评估中的潜力.
主要方法:
- 使用了来自52,064头牛的132,899条记录和122,368头动物的血统数据的数据集.
- 采用单步基因组最佳线性无偏预测 (ssGBLUP) 和最佳线性无偏预测 (BLUP) 进行基因组预测验证.
- 直接从NEI获得的SNP效应与从其组成特征中间接计算的效应进行比较.
主要成果:
- ssGBLUP对于NEI及其组成特征 (0.57-0.72) 实现了比BLUP更高的预测准确度.
- 在ssGBLUP下的基因型牛显示了最高的精度,从0.48 (MTPN) 到0.66 (NINT).
- 对于NEI的SNP影响是一致的,无论是直接还是间接地从组成特征中估计.
结论:
- 基因组预测是乳牛中NEI的一个可行的工具.
- 从NEI的组件中可靠地间接计算NEI的SNP影响.
- 这项研究为将基因组选择纳入NEI为未来的育种计划提供了基础.
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