Animal Science Unit, Gembloux Agro Bio-Tech, University of Liege, 5030 Gembloux, Belgium.
J Dairy Sci. 2013 Sep;96(9):5977-90. doi: 10.3168/jds.2012-6521. Epub 2013 Jul 17.
Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed to be homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of 2 groups of milk fatty acids (i.e., saturated and unsaturated fatty acids), and the content in milk of one individual fatty acid (i.e., oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least 3 records and a known sire. These sires had at least 10 cows with records and each herd × test-day had at least 5 cows. The 5 traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively expectation maximization-REML algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01×10(-3) and 4.17×10(-3) for all traits. The genetic standard deviation in residual variance (i.e., approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the 5 studied traits. The standard deviations due to herd × test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd × test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, nongenetic effects also contributed substantially to micro-environmental sensitivity. Addition of random regressions to the mean model did not reduce heterogeneity in residual variance and that genetic heterogeneity of residual variance was not simply an effect of an incomplete mean model.
在当前的奶牛养殖业中，适应环境变化的动物是理想的。可以通过研究动物之间的微环境敏感性的遗传差异来研究遗传差异。然而，在传统的遗传评估中，通常假定动物之间的剩余方差是同质的。本研究的目的是通过估计牛奶产量、体细胞评分、2 组牛奶脂肪酸（即饱和和不饱和脂肪酸）和牛奶中一种脂肪酸（即油酸，C18：1cis-9）的残留方差的方差分量，来研究比利时瓦隆大区荷斯坦奶牛的残留方差的遗传异质性。共有 747 个牛群的 26887 头奶牛的 146027 个测试日记录可用。所有奶牛至少有 3 个记录和一个已知的父亲。这些公牛至少有 10 头奶牛有记录，每个牛群×测试日至少有 5 头奶牛。这 5 个性状分别基于固定泌乳曲线和随机回归测试日模型进行分析。通过运行双层次广义线性模型的迭代期望最大化-REML 算法来估计方差分量。基于固定泌乳曲线测试日平均值模型，所有性状的剩余方差遗传率在 1.01×10(-3)和 4.17×10(-3)之间。剩余方差的遗传标准差（即剩余方差的遗传变异系数）在 0.12 和 0.17 之间。因此，在所研究的 5 个性状中，瓦隆荷斯坦奶牛的微环境敏感性存在一些遗传方差。剩余方差中 herd×test-day 和永久环境的标准差在 herd×test-day 效应中在 0.36 和 0.45 之间，在永久环境效应中在 0.55 和 0.97 之间。因此，非遗传效应也对微环境敏感性有很大贡献。在平均值模型中添加随机回归并没有降低剩余方差的异质性，并且剩余方差的遗传异质性并不是不完全均值模型的简单效应。
