Population genetics and GWAS: A primer

Abstract

This primer provides some background to help non-specialists understand a new theoretical evolutionary genetics study that helps explain why thousands of variants of small effect contribute to complex traits.If population genetics is the study of allele frequencies and quantitative genetics the study of allelic effects, then evolutionary genetics aims to understand how they interact over time.Matching of models to data has traditionally been constrained by the bias of observation toward common alleles that have large effects, limiting our ability to address questions such as "what maintains variation in natural populations," "how many genes influence a trait," or "to what extent do drift and selection influence allele frequencies" [1].Now that we are well into the deep sequencing and genome-wide association study (GWAS) era, that situation is changing and it is now feasible to test models against comprehensive empirical data.The paper by Simons et al in this issue [2] goes a long way toward building a framework for synthesizing population genetics and the new quantitative genetics.Two findings differentiate GWAS from much of 20th century genetics: the extraordinarily high polygenicity of traits and the dearth of evidence for interaction effects, whether among genes or with the environment [3].Whereas a typical genetic mapping experiment in a cross between two lines or in a pedigree reveals perhaps 10-20 so-called quantitative trait loci (QTL), each explaining perhaps 5% of the phenotypic variation, GWAS on tens or hundreds of thousands of unrelated individuals discover hundreds and implicate many thousands of loci, each explaining a fraction of a percent of the variance.From height to educational attainment, diabetes to schizophrenia, human geneticists now embrace the infinitesimal model with little exception, accepting that as many as 5% of all common variants in an even greater percentage of genes might associate with any given trait [4], along with an unknown number of rare variants of larger effect [5].Despite this complexity, there are also signs that what is called the "genetic architecture" does differ among traits, namely that different numbers of genes with different spectra of allele frequencies (and perhaps propensity to interact) associate with each trait [6].This is partly reflected in the fact that the heritability, or proportion of the variance in a population that is attributable to genetic differences, varies, but is also true of traits that have similar heritabilities.Why?Very soon after the first GWAS studies appeared 10 years ago, it was recognized that considerably less genetic variation was being discovered than expected, given well-validated