调整表型和遗传趋势:比较猪值和线性模型的趋势
Alberto Cesarani1,2, Jorge Hidalgo1, Matias Bermann1
1Animal and Dairy Science Department, University of Georgia, Athens, GA.
Journal of animal science
|July 28, 2025
概括
转换为概率尺度的基因组繁殖值 (GEBV) 与线性和值模型保持一致,特别是在像前腿结构 (FLS) 等具有更高遗传性的特征方面. 断奶到完成的死亡率 (WFM) 由于遗传性和发病率较低,显示出较少的对齐.
科学领域:
- 动物育种与遗传学
- 量化遗传学 量化遗传学
- 畜牧业 生产 畜牧业 生产
背景情况:
- 准确估计遗传趋势对于有效的动物选择至关重要.
- 基因组繁殖值 (GEBV) 可以使用线性或值模型计算,这取决于特征的分布.
- 将GEBV转换为概率尺度可以帮助在不同特征类型之间进行比较.
研究的目的:
- 从线性和值模型中使用GEBV比较表型和遗传趋势.
- 评估将GEBV转换为概率尺度对趋势估计的影响.
- 评估遗传和表型趋势对断奶到终结死亡率 (WFM) 和前腿结构 (FLS) 的调整.
主要方法:
- 使用WFM和FLS的线性和值模型计算了GEBV.
- 用两种方法将GEBV转换为线性模型中的概率.
- 基因和表型趋势是通过平均GEBV和表型根据出生年来计算的.
主要成果:
- 原始和转化GEBV之间的Spearman相关性很高 (≥0.98),表明转化对选择候选人的影响很小.
- 在概率尺度上从GEBV获得的遗传趋势与FLS的表型趋势保持一致.
- 对于WFM,遗传和表型趋势显示出较少的对齐,归因于较低的遗传性,发病率和环境影响.
结论:
- 从线性模型的GEBV可以有效地转换为概率尺度,显示与值模型的GEBV有很强的对齐.
- 遗传和表型趋势的对齐受选择的模型,遗传性和特征发生率的影响.
- 转换为概率尺度有助于比较不同分布的特征中的遗传趋势.
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