Han Lide, Yang Jian, Zhu Jun
Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310029, China.
J Genet Genomics. 2007 Jun;34(6):562-8. doi: 10.1016/S1673-8527(07)60062-9.
A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.
提出了一个遗传模型，用于同时分析二倍体植物数量性状的核基因、细胞质基因以及核质互作（NCI）的遗传效应，以及它们的基因型与环境互作（GE）效应。在该模型中，NCI效应进一步细分为加性和显性核质互作成分。采用混合线性模型方法进行统计分析。基于双列杂交设计的蒙特卡罗模拟表明，该遗传模型在几种无特定效应的情况下估计方差成分时具有稳健性。通过调整无偏预测（AUP）方法预测随机遗传效应。以陆地棉（Gossypium hirsutum L.）四个数量性状（棉铃数、皮棉百分率、纤维长度和马克隆值）的数据作为实例进行分析，以展示该模型的有效性。
