Detecting selection with a genetic cross

Abstract

AbstractDistinguishing which traits have evolved under natural selection, as opposed to neutral evolution, is a major goal of evolutionary biology. Several tests have been proposed to accomplish this, but these either rely on false assumptions or suffer from low power. Here, I introduce a new approach to detecting lineage-specific selection that makes minimal assumptions and only requires phenotypic data from ∼10 individuals. The test compares the phenotypic difference between two populations to what would be expected by chance under neutral evolution, which can be estimated from the phenotypic distribution of an F2cross between those populations. Simulations show that the test is robust to parameters such as the number of loci affecting the trait, the distribution of locus effect sizes, heritability, dominance, and epistasis. Comparing its performance to the QTL sign test—an existing test of selection that requires both genotype and phenotype data—the new test achieves comparable power with 50- to 100-fold fewer individuals (and no genotype data). Applying the test to empirical data spanning over a century shows strong directional selection in many crops, as well as on naturally selected traits such as head shape in HawaiianDrosophilaand skin color in humans. Applied to gene expression data, the test reveals that the strength of stabilizing selection acting on mRNA levels in a species is strongly associated with that species’ effective population size. In sum, this test is applicable to phenotypic data from almost any genetic cross, allowing selection to be detected more easily and powerfully than previously possible.Significance StatementNatural selection is the force that underlies the spectacular adaptations of all organisms to their environments. However, not all traits are under selection; a key question is which traits have been shaped by selection, as opposed to the random drift of neutral traits. Here, I develop a test of selection on quantitative traits that can be applied to almost any genetic cross between divergent populations or species. The test is robust to a wide range of potential confounders, and has greater power to detect selection than existing tests. Applied to empirical data, the test reveals widespread selection in both domesticated and wild species, allowing selection to be detected more easily and powerfully than previously possible.