Blangero J
Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX 78228-0147.
Hum Biol. 1993 Dec;65(6):941-66.
The genetic determinants of physiological and developmental responses to environmental stress are poorly understood. This has been primarily due to the difficulty of direct measurement of response and the lack of appropriate statistical genetic methods. Here, I present a unified statistical genetic methodology for human adaptability studies that permits evaluation of the inheritance of quantitative trait response to environmental stressors. The foundation of this approach is the mathematical relationship between genotype-environment interaction and the genetic variance of response to environmental challenge. I describe two basic methods that can be used for either discrete or continuous environments. Each method allows for major loci, residual polygenic variation, and genotype-environment interaction at both the major genic and the polygenic levels. The first method is based on multivariate segregation analysis and is appropriate for situations in which data are available for each individual in each environment. The second method is appropriate for the more common case when response to the environment cannot be observed directly. This method is based on an extension of a mixed major locus/variance component model and can be used when singly measured related individuals are observed in different environments. Three example applications using data on lipoprotein variation in pedigreed baboons are provided to show the utility of these methods.
人们对环境压力下生理和发育反应的遗传决定因素了解甚少。这主要是由于直接测量反应存在困难，且缺乏合适的统计遗传方法。在此，我提出一种用于人类适应性研究的统一统计遗传方法，该方法允许评估对环境应激源的数量性状反应的遗传情况。这种方法的基础是基因型 - 环境相互作用与对环境挑战反应的遗传方差之间的数学关系。我描述了两种可用于离散或连续环境的基本方法。每种方法都考虑了主基因座、残余多基因变异以及主基因和多基因水平上的基因型 - 环境相互作用。第一种方法基于多变量分离分析，适用于每个环境中每个个体都有数据的情况。第二种方法适用于更常见的情况，即无法直接观察到对环境的反应。该方法基于混合主基因座/方差成分模型的扩展，可用于在不同环境中观察到单次测量的相关个体的情况。提供了三个使用圈养狒狒脂蛋白变异数据的示例应用，以展示这些方法的实用性。
