Quantifying the Variation in the Effective Population Size Within a Genome

Abstract

The effective population size (N e ) is one of the most fundamental parameters in population genetics. It is thought to vary across the genome as a consequence of differences in the rate of recombination and the density of selected sites due to the processes of genetic hitchhiking and background selection. Although it is known that there is intragenomic variation in the effective population size in some species, it is not known whether this is widespread or how much variation in the effective population size there is. Here, we test whether the effective population size varies across the genome, between protein-coding genes, in 10 eukaryotic species by considering whether there is significant variation in neutral diversity, taking into account differences in the mutation rate between loci by using the divergence between species. In most species we find significant evidence of variation. We investigate whether the variation in N e is correlated to recombination rate and the density of selected sites in four species, for which these data are available. We find that N e is positively correlated to recombination rate in one species, Drosophila melanogaster, and negatively correlated to a measure of the density of selected sites in two others, humans and Arabidopsis thaliana. However, much of the variation remains unexplained. We use a hierarchical Bayesian analysis to quantify the amount of variation in the effective population size and show that it is quite modest in all species-most genes have an N e that is within a few fold of all other genes. Nonetheless we show that this modest variation in N e is sufficient to cause significant differences in the efficiency of natural selection across the genome, by demonstrating that the ratio of the number of nonsynonymous to synonymous polymorphisms is significantly correlated to synonymous diversity and estimates of N e , even taking into account the obvious nonindependence between these measures.T HE effective population size (N e ) is one of the most fundamental quantities in population genetics, evolutionary biology, and molecular ecology, since it determines the effectiveness of natural selection and the level of neutral genetic diversity that a population contains (Charlesworth 2009). Populations and regions of the genome with small N e tend to have low levels of genetic diversity, to be susceptible to the accumulation of deleterious mutations through genetic drift, and to have potentially low rates of adaptive evolution (Charlesworth 2009).The effective population size is expected to vary across the genome as a consequence of genetic hitchhiking (Smith and Haigh 1974) and background selection (Charlesworth et al. 1993). The action of both positive and negative natural selection, particularly in regions of the genome with low rates of recombination, is expected to reduce the effective population size leading to lower levels of genetic diversity and reduced effectiveness of selection. Hence variation in the rate of recombination and the density of selected sit...

Heterogeneity in effective population size and its implications in conservation genetics and animal breeding

“…Although these proxies are expected to be correlated to levels of variation in N e , empirical studies have not been able to show this relationship in a consistent way. From the four species tested, Gossmann et al (2011) only found a significant correlation of the heterogeneity in N e with the recombination rate in D. melanogaster (positive), and with density of genic sites in Homo sapiens (positive) and Arabidopsis thaliana (negative). The authors argue that these inconsistent correlations between N e and recombination rates and density of selected sites might be explained by their measure of the mutation rate, which was indirectly obtained from the synonymous diversity.…”

“…1 Empirical distributions of the variation in local N e found in the species over which heterogeneity in N e have been studied (Gossmann et al 2011;Jiménez-Mena et al in review). These distributions of local N e were all fitted from empirical data by assuming that variation in local N e follows a log-normal distribution.…”

“…By their nature these studies can only indirectly document heterogeneity in N e over long historical periods. Gossmann et al (2011) estimated the long-term N e of 10 eukaryotic species from data of joint patterns of population polymorphism and divergence at neutral sites within protein-coding regions. The number of loci used for each species differed, ranging from 49 to 918 loci.…”

“…Although significant, the variation in N e found was modest, ranging from 7.2-fold (Capsella rubella) to\ four-fold (Mus musculus castaneus, Capsella grandiflora, Boechera strycta, and Saccharomyces paradoxus). The study of Gossmann et al (2011) represents the first study that directly assessed the existence of heterogeneity in N e across the genome and quantified it. However, this study does not specifically report the locations in the genome where N e is heterogeneous.…”

“…Based on population genomics data, recent studies in model animals and humans suggest that different segments of the genome might undergo different rates of genetic drift, potentially challenging the idea that a single N e can account for the evolution of the genome (Gossmann et al 2011;Jiménez-Mena et al, in review). Heterogeneity in N e across the genome has been specifically estimated and reported in eleven species (Fig.…”