ASSESSING THE EFFECTS OF CANDIDATE GENES ON QUANTITATIVE TRAITS IN PRIMATE POPULATIONS

Recent progress in molecular and biochemical genetics has led to the identification of numerous polymorphic candidate genes likely to be important in the determination of quantitative variation in physiological processes. In this paper, we review a statistical framework ("measured genotype analysis") for assessing the effects of candidate genes on quantitative traits in primate populations. We consider situations in which pedigree information is available and also when such knowledge is absent. We also extend the method to allow for cases in which there is missing candidate locus data. Using likelihood methods, we show how to test a variety of genetic hypotheses. As an example of this type of analysis, we analyzed serum levels of apolipoprotein AI and high density lipoprotein cholesterol, in 585 pedigreed baboons, as a function of genotypic variability at an APOA1 PstI RFLP locus. Our analyses revealed that 7.5% of the total phenotypic variation in apo AI serum levels and 2% of variation in HDL-C levels is attributable to this locus. Future use of such methods will help to clarify the genetic basis of normal variation in physiological traits.