METHODOLOGIES FOR ESTIMATION OF GENOTYPE WITH ENVIRONMENT INTERACTION
METHODOLOGIES FOR ESTIMATION OF GENOTYPE WITH ENVIRONMENT INTERACTION
复制标题
DOI：
10.1016/0301-6226(93)90095-y
复制
发表时间：
1993-06-01
期刊：
影响因子：
--
通讯作者：
CAMERON, ND
中科院分区：
文献类型：
--
作者：
CAMERON, ND
几种方法来估计基因型与环境的相互作用，一个性状记录在每只动物，进行了审查。使用双变量REML方法估计的遗传方差和协方差导致遗传相关性的无偏估计，遗传相关性是基因型与环境相互作用的量度。当遗传协方差通过单变量公畜育种值估计值的加权叉积估计时，遗传相关估计值将有偏差，除非适当考虑固定效应之间的子代分布。计算机技术的发展使更复杂的模型能够适用于比以前更大的数据集。无导数REML（DFREML）算法使个体动物模型具有不同的固定效应，每个性状有数千条记录，可用于多变量分析，以估计遗传方差和协方差。介绍了在基因型与环境框架中使用REML和DFREML算法估计遗传方差和协方差的示例，但在每种情况下都没有证据表明基因型与环境相互作用。
Several methods to estimate the genotype with environment interaction, with one trait recorded on each animal, are reviewed. Genetic variances and covariances estimated using bivariate REML methodology result in unbiased estimates of the genetic correlation, which is a measure of the genotype with environment interaction. When the genetic covariance is estimated by weighted crossproducts of univariate sire breeding value estimates, the genetic correlation estimate will be biased, unless appropriate account is taken of the progeny distribution between fixed effects. Developments in computer technology have allowed more complex models to be fitted to larger data sets than was previously possible. Derivative Free REML (DFREML) algorithms have enabled individual animal models with different fixed effects with several thousand records for each trait to be accommodated in multivariate analyses for the estimation of genetic variances and covariances. Examples of the estimation of genetic variances and covariance using REML and DFREML algorithms, in a genotype with environment framework, were presented, but in each case there was no evidence of a genotype with environment interaction.