Su G, Madsen P, Lund M S, Sorensen D, Korsgaard I R, Jensen J
Danish Institute of Agricultural Sciences, Department of Genetics and Biotechnology, DK-8830, Tjele, Denmark.
J Anim Sci. 2006 Jul;84(7):1651-7. doi: 10.2527/jas.2005-517.
The reaction norm model is becoming a popular approach for the analysis of genotype x environment interactions. In a classical reaction norm model, the expression of a genotype in different environments is described as a linear function (a reaction norm) of an environmental gradient or value. An environmental value is typically defined as the mean performance of all genotypes in the environment, which is usually unknown. One approximation is to estimate the mean phenotypic performance in each environment and then treat these estimates as known covariates in the model. However, a more satisfactory alternative is to infer environmental values simultaneously with the other parameters of the model. This study describes a method and its Bayesian Markov Chain Monte Carlo implementation that makes this possible. Frequentist properties of the proposed method are tested in a simulation study. Estimates of parameters of interest agree well with the true values. Further, inferences about genetic parameters from the proposed method are similar to those derived from a reaction norm model using true environmental values. On the other hand, using phenotypic means as proxies for environmental values results in poor inferences.
反应规范模型正成为分析基因型与环境相互作用的一种流行方法。在经典的反应规范模型中，基因型在不同环境中的表达被描述为环境梯度或值的线性函数（反应规范）。环境值通常被定义为环境中所有基因型的平均表现，而这通常是未知的。一种近似方法是估计每个环境中的平均表型表现，然后将这些估计值作为模型中已知的协变量。然而，一个更令人满意的替代方法是与模型的其他参数同时推断环境值。本研究描述了一种方法及其贝叶斯马尔可夫链蒙特卡罗实现，从而使之成为可能。在一项模拟研究中测试了所提方法的频率特性。感兴趣参数的估计值与真实值吻合良好。此外，从所提方法得出的关于遗传参数的推断与使用真实环境值的反应规范模型得出的推断相似。另一方面，使用表型均值作为环境值的替代会导致推断不佳。
