Lou Xiang-Yang, Yang Mark C K
Department of Psychiatric Medicine, University of Virginia, 1670 Discovery Dr., Suite 110, Charlottesville, VA 22911-5844, USA.
Genetica. 2006 Sep-Nov;128(1-3):471-84. doi: 10.1007/s10709-006-7853-y.
A genetic model is developed with additive and dominance effects of a single gene and polygenes as well as general and specific reciprocal effects for the progeny from a diallel mating design. The methods of ANOVA, minimum norm quadratic unbiased estimation (MINQUE), restricted maximum likelihood estimation (REML), and maximum likelihood estimation (ML) are suggested for estimating variance components, and the methods of generalized least squares (GLS) and ordinary least squares (OLS) for fixed effects, while best linear unbiased prediction, linear unbiased prediction (LUP), and adjusted unbiased prediction are suggested for analyzing random effects. Monte Carlo simulations were conducted to evaluate the unbiasedness and efficiency of statistical methods involving two diallel designs with commonly used sample sizes, 6 and 8 parents, with no and missing crosses, respectively. Simulation results show that GLS and OLS are almost equally efficient for estimation of fixed effects, while MINQUE (1) and REML are better estimators of the variance components and LUP is most practical method for prediction of random effects. Data from a Drosophila melanogaster experiment (Gilbert 1985a, Theor appl Genet 69:625-629) were used as a working example to demonstrate the statistical analysis. The new methodology is also applicable to screening candidate gene(s) and to other mating designs with multiple parents, such as nested (NC Design I) and factorial (NC Design II) designs. Moreover, this methodology can serve as a guide to develop new methods for detecting indiscernible major genes and mapping quantitative trait loci based on mixture distribution theory. The computer program for the methods suggested in this article is freely available from the authors.
基于双列杂交设计的子代，构建了一个包含单基因和多基因的加性及显性效应以及一般和特殊正反交效应的遗传模型。建议采用方差分析、最小范数二次无偏估计（MINQUE）、约束最大似然估计（REML）和最大似然估计（ML）方法来估计方差分量，采用广义最小二乘法（GLS）和普通最小二乘法（OLS）来估计固定效应，同时建议采用最佳线性无偏预测、线性无偏预测（LUP）和调整无偏预测来分析随机效应。进行了蒙特卡罗模拟，以评估涉及两种双列设计（常用样本量分别为6个和8个亲本，分别有无杂交和缺失杂交）的统计方法的无偏性和效率。模拟结果表明，GLS和OLS在估计固定效应方面几乎同样有效，而MINQUE(1)和REML对方差分量的估计更好，LUP是预测随机效应最实用的方法。以果蝇实验（Gilbert 1985a，Theor appl Genet 69:625 - 629）的数据作为实例来演示统计分析。新方法也适用于筛选候选基因以及其他多亲本的杂交设计，如巢式（NC设计I）和析因（NC设计II）设计。此外，该方法可作为基于混合分布理论开发检测不可分辨主基因和定位数量性状位点新方法的指南。本文建议方法的计算机程序可从作者处免费获取。
