Population Growth Inflates the Per-Individual Number of Deleterious Mutations and Reduces Their Mean Effect

Abstract

This study addresses the question of how purifying selection operates during recent rapid population growth such as has been experienced by human populations. This is not a straightforward problem because the human population is not at equilibrium: population genetics predicts that, on the one hand, the efficacy of natural selection increases as population size increases, eliminating ever more weakly deleterious variants; on the other hand, a larger number of deleterious mutations will be introduced into the population and will be more likely to increase in their number of copies as the population grows. To understand how patterns of human genetic variation have been shaped by the interaction of natural selection and population growth, we examined the trajectories of mutations with varying selection coefficients, using computer simulations. We observed that while population growth dramatically increases the number of deleterious segregating sites in the population, it only mildly increases the number carried by each individual. Our simulations also show an increased efficacy of natural selection, reflected in a higher fraction of deleterious mutations eliminated at each generation and a more efficient elimination of the most deleterious ones. As a consequence, while each individual carries a larger number of deleterious alleles than expected in the absence of growth, the average selection coefficient of each segregating allele is less deleterious. Combined, our results suggest that the genetic risk of complex diseases in growing populations might be distributed across a larger number of more weakly deleterious rare variants.

Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants

“…It has also been shown that genetic architecture (Gazave et al 2013;Simons et al 2014), the performance of single-marker tests of association (Lohmueller 2014a,b), and selection scans (Teshima et al 2006) are also sensitive to nonequilibrium evolutionary forces. However, these studies have focused on stepwise population growth (rather than state-of-the-art models of explosive growth) (Lohmueller 2014a,b), investigated simplified selection models (rather than models inferred from human polymorphism data) (Simons et al 2014), or have only indirectly considered the impact on complex traits (Gazave et al 2013).…”

“…It has also been shown that genetic architecture (Gazave et al 2013;Simons et al 2014), the performance of single-marker tests of association (Lohmueller 2014a,b), and selection scans (Teshima et al 2006) are also sensitive to nonequilibrium evolutionary forces. However, these studies have focused on stepwise population growth (rather than state-of-the-art models of explosive growth) (Lohmueller 2014a,b), investigated simplified selection models (rather than models inferred from human polymorphism data) (Simons et al 2014), or have only indirectly considered the impact on complex traits (Gazave et al 2013). Some debate over the parameterization of complex trait models has resulted in a range of conclusions about the impact of evolutionary events on trait variance and the relative importance of rare alleles to complex traits (Lohmueller 2014b;Simons et al 2014); and although recent work has argued that demographic events have had little effect on deleterious load in humans (Simons et al 2014;Do et al 2015), it is less clear how demography affects the genetic variance of traits under selection.…”

A model of compound heterozygous, loss-of-function alleles is broadly consistent with observations from complex-disease GWAS datasets

“…While changes in population size do affect the relationship between effect size and mutation frequency [48][49][50][51][52][53][54][55][56][57][58][59][60][61] (Fig 1 and S5 Fig), different mappings of genotype to trait value do this in radically different ways for the same demographic history (Fig 1). From an empirical perspective, our findings suggest that re-sequencing in large samples is likely the best way forward in the face of the allelic heterogeneity imposed by the presence of rare alleles of large effect.…”

“…The increase in the number of rare alleles due to population growth is a well established theoretical and empirical result [48][49][50][51][52][53][54][55][56][57][58][59][60][61]. The exact relationship between rare alleles [4,17,26,62,63], and the demographic and/or selective scenarios from which they arose [21,22,64], and the genetic architecture of common complex diseases in humans is an active area of research.…”

“…At which point, the genetic variance is much less dependent on λ (S1 Fig). When λ is large, however, the average allele frequency does continue to decrease (S5 Fig) which drives power down. Across all genetic models, the single marker logistic regression has less power under population expansion (Fig 3A). The loss of power is attributable to a combination of rapid growth resulting in an excess of rare variants overall [48][49][50][51][52][53][54][55][56][57][58][59][60][61], and the increasing efficacy of selection against causal variants in growing populations [21]. While complete resequencing is more powerful than a gene-chip design, the relative power gained is modest under growth (Fig 3A).…”