Korol A B, Ronin Y I, Nevo E
Institute of Evolution, University of Haifa, Mount Carmel, Israel.
Genetics. 1998 Apr;148(4):2015-28. doi: 10.1093/genetics/148.4.2015.
An approach is presented here for quantitative trait loci (QTL) mapping analysis that allows for QTL x environment (E) interaction across multiple environments, without necessarily increasing the number of parameters. The main distinction of the proposed model is in the chosen way of approximation of the dependence of putative QTL effects on environmental states. We hypothesize that environmental dependence of a putative QTL effect can be represented as a function of environmental mean value of the trait. Such a description can be applied to take into account the effects of any cosegregating QTLs from other genomic regions that also may vary across environments. The conducted Monte-Carlo simulations and the example of barley multiple environments experiment demonstrate a high potential of the proposed approach for analyzing QTL x E interaction, although the results are only approximated by definition. However, this drawback is compensated by the possibility to utilize information from a potentially unlimited number of environments with a remarkable reduction in the number of parameters, as compared to previously proposed mapping models with QTL x E interactions.
本文提出了一种用于数量性状基因座（QTL）定位分析的方法，该方法允许在多个环境中进行QTL与环境（E）的相互作用分析，而不必增加参数数量。所提出模型的主要区别在于对假定QTL效应与环境状态之间依赖关系的近似选择方式。我们假设假定QTL效应的环境依赖性可以表示为性状环境均值的函数。这种描述可用于考虑来自其他基因组区域的任何共分离QTL的效应，这些QTL在不同环境中也可能有所不同。进行的蒙特卡罗模拟和大麦多环境实验的例子表明，尽管结果仅根据定义是近似的，但所提出的方法在分析QTL与E相互作用方面具有很高的潜力。然而，与先前提出的具有QTL与E相互作用的定位模型相比，该方法能够利用来自潜在无限数量环境的信息，同时显著减少参数数量，从而弥补了这一缺点。
