Statistical genetic approaches to human adaptability.

Abstract

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.