Gianola Daniel, Heringstad Bjorg, Odegaard Jorgen
Department of Animal Sciences, University of Wisconsin, Madison 53706, USA.
Genetics. 2006 Aug;173(4):2247-55. doi: 10.1534/genetics.105.054197. Epub 2006 Apr 19.
Finite mixture models are helpful for uncovering heterogeneity due to hidden structure. Quantitative genetics issues of continuous characters having a finite mixture of Gaussian components as statistical distribution are explored in this article. The partition of variance in a mixture, the covariance between relatives under the supposition of an additive genetic model, and the offspring-parent regression are derived. Formulas for assessing the effect of mass selection operating on a mixture are given. Expressions for the genetic and phenotypic correlations between mixture and Gaussian traits and between two mixture traits are presented. It is found that, if there is heterogeneity in a population at the genetic or environmental level, then genetic parameters based on theory treating distributions as homogeneous can lead to misleading interpretations. Some peculiarities of mixture characters are: heritability depends on the mean values of the component distributions, the offspring-parent regression is nonlinear, and genetic or phenotypic correlations cannot be interpreted devoid of the mixture proportions and of the parameters of the distributions mixed.
有限混合模型有助于揭示由于隐藏结构导致的异质性。本文探讨了具有高斯成分有限混合作为统计分布的连续性状的数量遗传学问题。推导了混合中方差的划分、加性遗传模型假设下亲属间的协方差以及亲子回归。给出了评估对混合物进行质量选择效果的公式。给出了混合物性状与高斯性状之间以及两个混合物性状之间的遗传和表型相关性的表达式。研究发现，如果群体在遗传或环境水平上存在异质性，那么基于将分布视为同质的理论的遗传参数可能会导致误导性解释。混合性状的一些特点是：遗传力取决于成分分布的均值，亲子回归是非线性的，并且遗传或表型相关性在没有混合比例和混合分布参数的情况下无法解释。
