用多特征和随机回归模型评估鸟生长的遗传成分
C Nel1,2, A Gilmour3, P Muvhali1,2
1Directorate of Animal Sciences, Western Cape Department of Agriculture, Elsenburg, South Africa.
British poultry science
|January 17, 2025
概括
随机回归分析提供了一种灵活的方法来研究鸟活体重在不同年龄段的遗传性. 这种方法有助于管理复杂的遗传数据,揭示年龄依赖的变异和潜在的繁殖价值的重新排名.
科学领域:
- 动物遗传学动物遗传学
- 量化遗传学 量化遗传学
- 畜牧科学 畜牧科学 畜牧科学
背景情况:
- 鸟活体重 (LW) 的遗传性随年龄而有显著变化.
- 精确的遗传评估需要考虑到随着时间的推移重复的LW测量.
研究的目的:
- 评估随机回归 (RR) 作为一种替代多特征 (MT) 分析的选择,用于鸟LW.
- 分析鸟LW的年龄依赖的遗传变异.
主要方法:
- 利用了来自10052只鸟 (20-410天) 的74,683个LW记录.
- 在线混合模型框架内比较单特征 (ST),MT和RR模型.
- 对于遗传和永久的环境影响,RR模型纳入了莱根德多项式.
主要成果:
- 对LW的遗传概率估计在各种方法中是一致的,从中度 (小孩) 到高 (成人).
- 早期和后期的LW测量之间的遗传相关性是适度的.
- 与MT分析相比,随机回归显示了估计的繁殖价值的大量重新排名.
结论:
- 鸟LW表现出与年龄相关的遗传变异.
- 随机回归有效地解决了重复LW测量的MT分析的维度.
- 需要进一步研究以澄清RR模型中规模效应与动物效应的影响.
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