Soft Shoulders Ahead: Spurious Signatures of Soft and Partial Selective Sweeps Result from Linked Hard Sweeps

Characterizing the nature of the adaptive process at the genetic level is a central goal for population genetics. In particular, we know little about the sources of adaptive substitution or about the number of adaptive variants currently segregating in nature. Historically, population geneticists have focused attention on the hard-sweep model of adaptation in which a de novo beneficial mutation arises and rapidly fixes in a population. Recently more attention has been given to soft-sweep models, in which alleles that were previously neutral, or nearly so, drift until such a time as the environment shifts and their selection coefficient changes to become beneficial. It remains an active and difficult problem, however, to tease apart the telltale signatures of hard vs. soft sweeps in genomic polymorphism data. Through extensive simulations of hard- and soft-sweep models, here we show that indeed the two might not be separable through the use of simple summary statistics. In particular, it seems that recombination in regions linked to, but distant from, sites of hard sweeps can create patterns of polymorphism that closely mirror what is expected to be found near soft sweeps. We find that a very similar situation arises when using haplotype-based statistics that are aimed at detecting partial or ongoing selective sweeps, such that it is difficult to distinguish the shoulder of a hard sweep from the center of a partial sweep. While knowing the location of the selected site mitigates this problem slightly, we show that stochasticity in signatures of natural selection will frequently cause the signal to reach its zenith far from this site and that this effect is more severe for soft sweeps; thus inferences of the target as well as the mode of positive selection may be inaccurate. In addition, both the time since a sweep ends and biologically realistic levels of allelic gene conversion lead to errors in the classification and identification of selective sweeps. This general problem of “soft shoulders” underscores the difficulty in differentiating soft and partial sweeps from hard-sweep scenarios in molecular population genomics data. The soft-shoulder effect also implies that the more common hard sweeps have been in recent evolutionary history, the more prevalent spurious signatures of soft or partial sweeps may appear in some genome-wide scans.     

Patterns of neutral diversity under general models of selective sweeps

Two major sources of stochasticity in the dynamics of neutral alleles result from resampling of finite populations (genetic drift) and the random genetic background of nearby selected alleles on which the neutral alleles are found (linked selection). There is now good evidence that linked selection plays an important role in shaping polymorphism levels in a number of species. One of the best-investigated models of linked selection is the recurrent full-sweep model, in which newly arisen selected alleles fix rapidly. However, the bulk of selected alleles that sweep into the population may not be destined for rapid fixation. Here we develop a general model of recurrent selective sweeps in a coalescent framework, one that generalizes the recurrent full-sweep model to the case where selected alleles do not sweep to fixation. We show that in a large population, only the initial rapid increase of a selected allele affects the genealogy at partially linked sites, which under fairly general assumptions are unaffected by the subsequent fate of the selected allele. We also apply the theory to a simple model to investigate the impact of recurrent partial sweeps on levels of neutral diversity and find that for a given reduction in diversity, the impact of recurrent partial sweeps on the frequency spectrum at neutral sites is determined primarily by the frequencies rapidly achieved by the selected alleles. Consequently, recurrent sweeps of selected alleles to low frequencies can have a profound effect on levels of diversity but can leave the frequency spectrum relatively unperturbed. In fact, the limiting coalescent model under a high rate of sweeps to low frequency is identical to the standard neutral model. The general model of selective sweeps we describe goes some way toward providing a more flexible framework to describe genomic patterns of diversity than is currently available.     

Effects of Interference Between Selected Loci on the Mutation Load,Inbreeding Depression,and Heterosis

A classical prediction from single-locus models is that inbreeding increases the efficiency of selection against partially recessive deleterious alleles (purging), thereby decreasing the mutation load and level of inbreeding depression. However, previous multilocus simulation studies found that increasing the rate of self-fertilization of individuals may not lead to purging and argued that selective interference among loci causes this effect. In this article, I derive simple analytical approximations for the mutation load and inbreeding depression, taking into account the effects of interference between pairs of loci. I consider two classical scenarios of nonrandomly mating populations: a single population undergoing partial selfing and a subdivided population with limited dispersal. In the first case, correlations in homozygosity between loci tend to reduce mean fitness and increase inbreeding depression. These effects are stronger when deleterious alleles are more recessive, but only weakly depend on the strength of selection against deleterious alleles and on recombination rates. In subdivided populations, interference increases inbreeding depression within demes, but decreases heterosis between demes. Comparisons with multilocus, individual-based simulations show that these analytical approximations are accurate as long as the effects of interference stay moderate, but fail for high deleterious mutation rates and low dominance coefficients of deleterious alleles.     

Adaptation in isolated populations: when does it happen and when can we tell?

Isolated populations with novel phenotypes present an exciting opportunity to uncover the genetic basis of ecologically significant adaptation, and genomic scans have often, but not always, led to candidate genes directly related to an adaptive phenotype. However, in many cases these populations were established by a severe bottleneck, which can make identifying targets of selection problematic. Here, we simulate severe bottlenecks and subsequent selection on standing variation, mimicking adaptation after establishment of a new small population, such as an island or an artificial selection experiment. Using simulations of single loci under positive selection and population genetics theory, we examine how population size and age of the population isolate affect the ability of outlier scans for selection to identify adaptive alleles using both single‐site measures and haplotype structure. We find and explain an optimal combination of selection strength, starting frequency, and age of the adaptive allele, which we refer to as a Goldilocks zone, where adaptation is likely to occur and yet the adaptive variants are most likely to derive from a single ancestor (a ‘hard’ selective sweep); in this zone, four commonly used statistics detect selection with high power. Real‐world examples of both island colonization and experimental evolution studies are discussed. Our study provides concrete considerations to be made before embarking on whole‐genome sequencing of differentiated populations.     

Significance of Population Size on the Fixation of Nonsynonymous Mutations in Genes Under Varying Levels of Selection Pressure

Previous studies observed a higher ratio of divergences at nonsynonymous and synonymous sites (ω = d_N/d_S) in species with a small population size compared to that estimated for those with a large population size. Here we examined the theoretical relationship between ω, effective population size (N_e), and selection coefficient (s). Our analysis revealed that when purifying selection is high, ω of species with small N_e is much higher than that of species with large N_e. However the difference between the two ω reduces with the decline in selection pressure (s → 0). We examined this relationship using primate and rodent genes and found that the ω estimated for highly constrained genes of primates was up to 2.9 times higher than that obtained for their orthologous rodent genes. Conversely, for genes under weak purifying selection the ω of primates was only 17% higher than that of rodents. When tissue specificity was used as a proxy for selection pressure we found that the ω of broadly expressed genes of primates was up to 2.1-fold higher than that of their rodent counterparts and this difference was only 27% for tissue specific genes. Since most of the nonsynonymous mutations in constrained or broadly expressed genes are deleterious, fixation of these mutations is influenced by N_e. This results in a higher ω of these genes in primates compared to those from rodents. Conversely, the majority of nonsynonymous mutations in less-constrained or tissue-specific genes are neutral or nearly neutral and therefore fixation of them is largely independent of N_e, which leads to the similarity of ω in primates and rodents.     

SLiM: Simulating Evolution with Selection and Linkage

SLiM is an efficient forward population genetic simulation designed for studying the effects of linkage and selection on a chromosome-wide scale. The program can incorporate complex scenarios of demography and population substructure, various models for selection and dominance of new mutations, arbitrary gene structure, and user-defined recombination maps.     

Increased variation in mtDNA in patients with familial sensorineural hearing impairment

Analyses of mitochondrial DNA (mtDNA) sequences have revealed non-neutral patterns, suggesting that many amino acid mutations in animal mtDNA may be mildly deleterious, but this has not been verified in human clinical series. Since sensorineural hearing impairment (SNHI) is a common manifestation in many of the syndromes caused by mutations in mtDNA, this may be regarded as the phenotype of choice in attempts to detect mutations that may have a mildly deleterious effect on mitochondrial function. We selected 32 subjects from among 117 unrelated SNHI patients with SNHI in maternal relatives by means of family history, determined the entire coding region sequence of mtDNA and compared the sequence variation with that in 32 haplogroup-matched controls taken at random from 192 Finnish sequences. The 32 control sequences differed from the remaining 160 sequences by 36±9 substitutions (mean ± SD), while the difference for the 32 patients was 58±4 substitutions (P=0.005 for difference; Wilcoxon signed rank test). Differences were also found in the number of new haplotypes and new non-synonymous mutations or mutations in tRNA or rRNA genes. A total of 12 rare mtDNA variants were detected in the patients, and only 3 of these were considered to be neutral in effect. It is proposed that increased sequence variation in mtDNA may be a genetic risk factor for SNHI, and the increased frequency of rare haplotypes in these patients points to the presence of mildly deleterious mutations in mtDNA.     

How closely does genetic diversity in finite populations conform to predictions of neutral theory? Large deficits in regions of low recombination

Levels of genetic diversity in finite populations are crucial in conservation and evolutionary biology. Genetic diversity is required for populations to evolve and its loss is related to inbreeding in random mating populations, and thus to reduced population fitness and increased extinction risk. Neutral theory is widely used to predict levels of genetic diversity. I review levels of genetic diversity in finite populations in relation to predictions of neutral theory. Positive associations between genetic diversity and population size, as predicted by neutral theory, are observed for microsatellites, allozymes, quantitative genetic variation and usually for mitochondrial DNA (mtDNA). However, there are frequently significant deviations from neutral theory owing to indirect selection at linked loci caused by balancing selection, selective sweeps and background selection. Substantially lower genetic diversity than predicted under neutrality was found for chromosomes with low recombination rates and high linkage disequilibrium (compared with 'normally' recombining chromosomes within species and adjusted for different copy numbers and mutation rates), including W (median 100% lower) and Y (89% lower) chromosomes, dot fourth chromosomes in Drosophila (94% lower) and mtDNA (67% lower). Further, microsatellite genetic and allelic diversity were lost at 12 and 33% faster rates than expected in populations adapting to captivity, owing to widespread selective sweeps. Overall, neither neutral theory nor most versions of the genetic draft hypothesis are compatible with all empirical results.     

Detecting strong positive selection in the genome

New statistical tests have been developed in the past decade that enable us to infer evidence of recent strong positive selection from genome-wide data on single-nucleotide polymorphism and to localize the targets of selection in the genome. Based on these tests, past demographic events that led to distortions of the site-frequency spectrum of variation can be distinguished from selection, in particular if linkage disequilibrium is taken into account. These methods have been successfully applied to species from which complete sequence information and polymorphism data are available, including Drosophila melanogaster, humans, and several plant species. To make full use of the available data, however, the tests that were primarily designed for panmictic populations need to be extended to spatially structured populations.