差异组件估计对内罗尔牛生长和生殖相关特征的基因组预测的影响
Daniel Cardona-Cifuentes1,2, Juan Diego Rodriguez Neira3, Lucia G Albuquerque1,4
1Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (UNESP), Jaboticabal, SP, Brazil.
概括
在Nellore牛的基因组选择 (GS) 之前丢弃旧记录改善了生长和生殖特征的遗传概率估计. 基因组育种值 (GEBV) 保持准确,显示GS实施增强了遗传评估.
科学领域:
- 动物遗传学和动物繁殖
- 量化遗传学 量化遗传学
- 基因组选择 基因组选择
背景情况:
- 基因组选择 (GS) 通过结合基因组信息来预测繁殖值,彻底改变了畜牧养殖.
- 实施GS需要重新评估估计方差组件 (VC) 和它们对基因组繁殖值 (GEBV) 的影响的传统方法.
- 了解VC和GEBV如何受到历史数据的影响,以及将基因组关系纳入其中,对于优化育种计划至关重要.
研究的目的:
- 为了估计Nellore牛的生长 (W120,W450) 和生殖特征 (SC450) 的变异成分 (VC).
- 为了比较使用血统 (A) 与联合血统和基因组 (H) 关系矩阵对VC和GEBV估计的影响.
- 评估包括或排除基因组前选择记录对VC和GEBV准确性,偏差和分散性的影响.
主要方法:
- 使用A和H矩阵估计VC,数据集包括所有记录 (All),GS之前的记录 (Before) 和GS之后的记录 (After).
- 基因组繁殖值 (GEBV) 使用单步基因组最佳线性无偏预测 (ssGBLUP) 和不同的VC估计进行了预测.
- 使用LR方法评估预测准确性,偏差和分散,并纠正表型,比较使用所有数据与后GS数据的策略.
主要成果:
- 使用A矩阵时,所有特征的遗传概率估计从"之前"数据集增加到"之后"数据集,而"所有"数据集产生中间值.
- 与A矩阵相比,H矩阵一般降低了W450和SC450的遗传性估计.
- 通过使用数据集1 (所有数据) 和来自A_After.的VC来实现W120 GEBV的最高准确性. 对于W450,具有H_AfterVC的数据集1显示了最高的准确性,紧随其后的是具有相同VC来源的数据集2 (后GS数据). 对于SC450,具有H_After VC的数据集2产生了最高的准确性.
- 使用GS后数据 (数据集2) 与使用所有数据 (数据集1) 相比,没有显著改变偏差或分散.
结论:
- 纳罗尔牛的生长和生殖特征的变异组件和遗传参数受到GS实施前或之后的记录的包含的影响.
- 对于W450和SC450,基因变异和可遗传性估计增加了GS,而W120从基因组预测的基于矩阵的VC估计中受益最多.
- 使用H矩阵和/或丢弃GS前记录观察到W450和SC450的精度增长,这表明在不引入对年轻候选人的GEBV偏差或分散的情况下排除旧数据是可行的.
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