An analysis of signatures of selective sweeps in natural populations of the house mouse

Population and locus-specific reduction of variability of polymorphic loci could be an indication of positive selection at a linked site (selective sweep) and therefore point toward genes that have been involved in recent adaptations. Analysis of microsatellite variability offers a way to identify such regions and to ask whether they occur more often than expected by chance. We studied four populations of the house mouse (Mus musculus) to assess the frequency of such signatures of selective sweeps under natural conditions. Three samples represent the subspecies Mus m. dometicus [corrected] and came from Germany, France, and Cameroon. One sample came from Kazakhstan and constitutes a population of the subspecies Mus m. [corrected] musculus. Mitochondrial D-loop sequences from all animals confirm their respective assignments. Approximately 200 microsatellite loci were typed for up to 60 unrelated individuals from each population and evaluated for signs of selective sweeps on the basis of Schl?tterer's ln RV and ln RH statistics. Our data suggest that there are slightly more signs of selective sweeps than would have been expected by chance alone in each of the populations and also highlights some of the statistical challenges faced in genome scans for detecting selection. Single-nucleotide polymorphism typing of one sweep signature in the M. m. domesticus populations around the beta-defensin 6 locus confirms a lowered nucleotide diversity in this region and limits the potential sweep region to about 20 kb. However, no amino acid exchange has occurred in the coding region when compared to M. m. musculus. If this sweep signature is due to a recent adaptation, it is expected that a regulatory change would have caused it. Our data provide a framework for conducting a systematic whole genome scan for signatures of selective sweeps in the mouse genome.     

A hierarchical Bayesian model for next-generation population genomics

The demography of populations and natural selection shape genetic variation across the genome and understanding the genomic consequences of these evolutionary processes is a fundamental aim of population genetics. We have developed a hierarchical Bayesian model to quantify genome-wide population structure and identify candidate genetic regions affected by selection. This model improves on existing methods by accounting for stochastic sampling of sequences inherent in next-generation sequencing (with pooled or indexed individual samples) and by incorporating genetic distances among haplotypes in measures of genetic differentiation. Using simulations we demonstrate that this model has a low false-positive rate for classifying neutral genetic regions as selected genes (i.e., Φ(ST) outliers), but can detect recent selective sweeps, particularly when genetic regions in multiple populations are affected by selection. Nonetheless, selection affecting just a single population was difficult to detect and resulted in a high false-negative rate under certain conditions. We applied the Bayesian model to two large sets of human population genetic data. We found evidence of widespread positive and balancing selection among worldwide human populations, including many genetic regions previously thought to be under selection. Additionally, we identified novel candidate genes for selection, several of which have been linked to human diseases. This model will facilitate the population genetic analysis of a wide range of organisms on the basis of next-generation sequence data.     

Identification of selective sweeps using a dynamically adjusted number of linked microsatellites

There is currently large interest in distinguishing the signatures of genetic variation produced by demographic events from those produced by natural selection. We propose a simple multilocus statistical test to identify candidate sites of selective sweeps with high power. The test is based on the variability profile measured in an array of linked microsatellites. We also show that the analysis of flanking markers drastically reduces the number of false positives among the candidates that are identified in a genomewide survey of unlinked loci and find that this property is maintained in many population-bottleneck scenarios. However, for a certain range of intermediately severe population bottlenecks we find genomic signatures that are very similar to those produced by a selective sweep. While in these worst-case scenarios the power of the proposed test remains high, the false-positive rate reaches values close to 50%. Hence, selective sweeps may be hard to identify even if multiple linked loci are analyzed. Nevertheless, the integration of information from multiple linked loci always leads to a considerable reduction of the false-positive rate compared to a genome scan of unlinked loci. We discuss the application of this test to experimental data from Drosophila melanogaster.     

A new approach for using genome scans to detect recent positive selection in the human genome

Genome-wide scanning for signals of recent positive selection is essential for a comprehensive and systematic understanding of human adaptation. Here, we present a genomic survey of recent local selective sweeps, especially aimed at those nearly or recently completed. A novel approach was developed for such signals, based on contrasting the extended haplotype homozygosity (EHH) profiles between populations. We applied this method to the genome single nucleotide polymorphism (SNP) data of both the International HapMap Project and Perlegen Sciences, and detected widespread signals of recent local selection across the genome, consisting of both complete and partial sweeps. A challenging problem of genomic scans of recent positive selection is to clearly distinguish selection from neutral effects, given the high sensitivity of the test statistics to departures from neutral demographic assumptions and the lack of a single, accurate neutral model of human history. We therefore developed a new procedure that is robust across a wide range of demographic and ascertainment models, one that indicates that certain portions of the genome clearly depart from neutrality. Simulations of positive selection showed that our tests have high power towards strong selection sweeps that have undergone fixation. Gene ontology analysis of the candidate regions revealed several new functional groups that might help explain some important interpopulation differences in phenotypic traits.     

Detecting bottlenecks and selective sweeps from DNA sequence polymorphism

A coalescence-based maximum-likelihood method is presented that aims to (i) detect diversity-reducing events in the recent history of a population and (ii) distinguish between demographic (e.g., bottlenecks) and selective causes (selective sweep) of a recent reduction of genetic variability. The former goal is achieved by taking account of the distortion in the shape of gene genealogies generated by diversity-reducing events: gene trees tend to be more star-like than under the standard coalescent. The latter issue is addressed by comparing patterns between loci: demographic events apply to the whole genome whereas selective events affect distinct regions of the genome to a varying extent. The maximum-likelihood approach allows one to estimate the time and strength of diversity-reducing events and to choose among competing hypotheses. An application to sequence data from an African population of Drosophila melanogaster shows that the bottleneck hypothesis is unlikely and that one or several selective sweeps probably occurred in the recent history of this population.     

Genome scans of DNA variability in humans reveal evidence for selective sweeps outside of Africa

The last 50,000-150,000 years of human history have been characterized by rapid demographic expansions and the colonization of novel environments outside of sub-Saharan Africa. Mass migrations outside the ancestral species range likely entailed many new selection pressures, suggesting that genetic adaptation to local environmental conditions may have been more prevalent in colonizing populations outside of sub-Saharan Africa. Here we report a test of this hypothesis using genome-wide patterns of DNA polymorphism. We conducted a multilocus scan of microsatellite variability to identify regions of the human genome that may have been subject to continent-specific hitchhiking events. Using published polymorphism data for a total of 624 autosomal loci in multiple populations of humans, we used coalescent simulations to identify candidate loci for geographically restricted selective sweeps. We identified a total of 13 loci that appeared as outliers in replicated population comparisons involving different reference samples for Africa. A disproportionate number of these loci exhibited reduced levels of relative variability in non-African populations alone, suggesting that recent episodes of positive selection have been more prevalent outside of sub-Saharan Africa.     

Evidence of a high rate of selective sweeps in African Drosophila melanogaster

Assessing the rate of evolution depends on our ability to detect selection at several genes simultaneously. We summarize DNA sequence variation data in three new and six previously published data sets from the left arm of the second chromosome of Drosophila melanogaster in a population from West Africa, the presumed area of origin of this species. Four loci [Acp26Aa, Fbp2, Vha68-1, and Su(H)] were previously found to deviate from a neutral mutation-drift equilibrium as a consequence of one or several selective sweeps. Polymorphism data from five loci from intervening regions (dpp, Acp26Ab, Acp29AB, GH10711, and Sos) did not show the characteristic deviation from neutrality caused by local selective sweeps. This genomic region is polymorphic for the In(2L)t inversion. Four loci located near inversion breakpoints [dpp, sos, GH10711, and Su(H)] showed significant structuring between the two arrangements or significant deviation from neutrality in the inverted class, probably as a result of a recent shift in inversion frequency. Overall, these patterns of variation suggest that the four selective events were independent. Six loci were observed with no a priori knowledge of selection, and independent selective sweeps were detected in three of them. This suggests that a large part of the D. melanogaster genome has experienced the effect of positive selection in its ancestral African range.     

Selective sweeps in a 2-locus model for sex-ratio meiotic drive in Drosophila simulans

A way to identify loci subject to positive selection is to detect the signature of selective sweeps in given chromosomal regions. It is revealed by the departure of DNA polymorphism patterns from the neutral equilibrium predicted by coalescent theory. We surveyed DNA sequence variation in a region formerly identified as causing "sex-ratio" meiotic drive in Drosophila simulans. We found evidence that this system evolved by positive selection at 2 neighboring loci, which thus appear to be required simultaneously for meiotic drive to occur. The 2 regions are approximately 150-kb distant, corresponding to a genetic distance of 0.1 cM. The presumably large transmission advantage of chromosomes carrying meiotic drive alleles at both loci has not erased the individual signature of selection at each locus. This chromosome fragment combines a high level of linkage disequilibrium between the 2 critical regions with a high recombination rate. As a result, 2 characteristic traits of selective sweeps--the reduction of variation and the departure from selective neutrality in haplotype tests--show a bimodal pattern. Linkage disequilibrium level indicates that, in the natural population from Madagascar used in this study, the selective sweep may be as recent as 100 years.     

A microsatellite-based multilocus screen for the identification of local selective sweeps

With the availability of completely sequenced genomes, multilocus scans of natural variability have become a feasible approach for the identification of genomic regions subjected to natural and artificial selection. Here, I introduce a new multilocus test statistic, ln RV, which is based on the ratio of observed variances in repeat number at a set of microsatellite loci in two groups of populations. The distribution of ln RV values captures demographic history of the populations as well as variation in microsatellite mutation among loci. Given that microsatellite loci associated with a recent selective sweep differ from the remainder of the genome, they are expected to fall outside of the distribution of neutral ln RV values. The ln RV test statistic is applied to a data set of 94 loci typed in eight non-African and two African human populations.     

Determinants of synonymous and nonsynonymous variability in three species of Drosophila

We estimated the intensity of selection on preferred codons in Drosophila pseudoobscura and D. miranda at X-linked and autosomal loci, using a published data set on sequence variability at 67 loci, by means of an improved method that takes account of demographic effects. We found evidence for stronger selection at X-linked loci, consistent with their higher levels of codon usage bias. The estimates of the strength of selection and mutational bias in favor of unpreferred codons were similar to those found in other species, after taking into account the fact that D. pseudoobscura showed evidence for a recent expansion in population size. We examined correlates of synonymous and nonsynonymous diversity in these species and found no evidence for effects of recurrent selective sweeps on nonsynonymous mutations, which is probably because this set of genes have much higher than average levels of selective constraints. There was evidence for correlated effects of levels of selective constraints on protein sequences and on codon usage, as expected under models of selection for translational accuracy. Our analysis of a published data set on D. melanogaster provided evidence for the effects of selective sweeps of nonsynonymous mutations on linked synonymous diversity, but only in the subset of loci that experienced the highest rates of nonsynonymous substitutions (about one-quarter of the total) and not at more slowly evolving loci. Our correlational analysis of this data set suggested that both selective constraints on protein sequences and recurrent selective sweeps affect the overall level of codon usage.     

Learning Natural Selection from the Site Frequency Spectrum

Genetic adaptation to external stimuli occurs through the combined action of mutation and selection. A central problem in genetics is to identify loci responsive to specific selective constraints. Many tests have been proposed to identify the genomic signatures of natural selection by quantifying the skew in the site frequency spectrum (SFS) under selection relative to neutrality. We build upon recent work that connects many of these tests under a common framework, by describing how selective sweeps affect the scaled SFS. We show that the specific skew depends on many attributes of the sweep, including the selection coefficient and the time under selection. Using supervised learning on extensive simulated data, we characterize the features of the scaled SFS that best separate different types of selective sweeps from neutrality. We develop a test, SFselect, that consistently outperforms many existing tests over a wide range of selective sweeps. We apply SFselect to polymorphism data from a laboratory evolution experiment of Drosophila melanogaster adapted to hypoxia and identify loci that strengthen the role of the Notch pathway in hypoxia tolerance, but were missed by previous approaches. We further apply our test to human data and identify regions that are in agreement with earlier studies, as well as many novel regions.     

S/HIC: Robust Identification of Soft and Hard Sweeps Using Machine Learning

Detecting the targets of adaptive natural selection from whole genome sequencing data is a central problem for population genetics. However, to date most methods have shown sub-optimal performance under realistic demographic scenarios. Moreover, over the past decade there has been a renewed interest in determining the importance of selection from standing variation in adaptation of natural populations, yet very few methods for inferring this model of adaptation at the genome scale have been introduced. Here we introduce a new method, S/HIC, which uses supervised machine learning to precisely infer the location of both hard and soft selective sweeps. We show that S/HIC has unrivaled accuracy for detecting sweeps under demographic histories that are relevant to human populations, and distinguishing sweeps from linked as well as neutrally evolving regions. Moreover, we show that S/HIC is uniquely robust among its competitors to model misspecification. Thus, even if the true demographic model of a population differs catastrophically from that specified by the user, S/HIC still retains impressive discriminatory power. Finally, we apply S/HIC to the case of resequencing data from human chromosome 18 in a European population sample, and demonstrate that we can reliably recover selective sweeps that have been identified earlier using less specific and sensitive methods.     

Identification of selective sweeps in closely related populations of the house mouse based on microsatellite scans

Genome scans of polymorphisms promise to provide insights into the patterns and frequencies of positive selection under natural conditions. The use of microsatellites as markers has the potential to focus on very recent events, since in contrast to SNPs, their high mutation rates should remove signatures of older events. We assess this concept here in a large-scale study. We have analyzed two population pairs of the house mouse, one pair of the subspecies Mus musculus domesticus and the other of M. m. musculus. A total of 915 microsatellite loci chosen to cover the whole genome were assessed in a prescreening procedure, followed by individual typing of candidate loci. Schlötterer's ratio statistics (lnRH) were applied to detect loci with significant deviations from patterns of neutral expectation. For eight loci from each population pair we have determined the size of the potential sweep window and applied a second statistical procedure (linked locus statistics). For the two population pairs, we find five and four significant sweep loci, respectively, with an average estimated window size of 120 kb. On the basis of the analysis of individual allele frequencies, it is possible to identify the most recent sweep, for which we estimate an onset of 400–600 years ago. Given the known population history for the French–German population pair, we infer that the average frequency of selective sweeps in these populations is higher than 1 in 100 generations across the whole genome. We discuss the implications for adaptation processes in natural populations.     

Demography and natural selection have shaped genetic variation in Drosophila melanogaster: a multi-locus approach

Demography and selection have been recognized for their important roles in shaping patterns of nucleotide variability. To investigate the relative effects of these forces in the genome of Drosophila melanogaster, we used a multi-locus scan (105 fragments) of X-linked DNA sequence variation in a putatively ancestral African and a derived European population. Surprisingly, we found evidence for a recent size expansion in the African population, i.e., a significant excess of singletons at a chromosome-wide level. In the European population, such an excess was not detected. In contrast to the African population, we found evidence for positive natural selection in the European sample: (i) a large number of loci with low levels of variation and (ii) a significant excess of derived variants at the low-variation loci that are fixed in the European sample but rare in the African population. These results are consistent with the hypothesis that the European population has experienced frequent selective sweeps in the recent past during its adaptation to new habitats. Our study shows the advantages of a genomic approach (over a locus-specific analysis) in disentangling demographic and selective forces.     

Localizing recent adaptive evolution in the human genome

Identifying genomic locations that have experienced selective sweeps is an important first step toward understanding the molecular basis of adaptive evolution. Using statistical methods that account for the confounding effects of population demography, recombination rate variation, and single-nucleotide polymorphism ascertainment, while also providing fine-scale estimates of the position of the selected site, we analyzed a genomic dataset of 1.2 million human single-nucleotide polymorphisms genotyped in African-American, European-American, and Chinese samples. We identify 101 regions of the human genome with very strong evidence (p < 10⁻⁵) of a recent selective sweep and where our estimate of the position of the selective sweep falls within 100 kb of a known gene. Within these regions, genes of biological interest include genes in pigmentation pathways, components of the dystrophin protein complex, clusters of olfactory receptors, genes involved in nervous system development and function, immune system genes, and heat shock genes. We also observe consistent evidence of selective sweeps in centromeric regions. In general, we find that recent adaptation is strikingly pervasive in the human genome, with as much as 10% of the genome affected by linkage to a selective sweep.     

Selective sweeps reveal candidate genes for adaptation to drought and salt tolerance in common sunflower, Helianthus annuus

Here we report the results of an analysis of variation at 128 EST-based microsatellites in wild Helianthus annuus, using populations from the species' typical plains habitat in Kansas and Colorado, as well as two arid desert and two distinct brackish marsh areas in Utah. The test statistics lnRV and lnRH were used to find regions of the genome that were significantly less variable in one population relative to the others and thus are likely to contain genes under selection. A small but detectable percentage (1.5-6%) of genes showed evidence for selection from both statistics in any particular environment, and a total of 17 loci showed evidence of selection in at least one environment. Distance-based measures provided additional evidence of selection for 15 of the 17 loci. Global F(ST)-values were significantly higher for candidate loci, as expected under divergent selection. However, pairwise F(ST)-values were lower for populations that shared a selective sweep. Moreover, while spatially separated populations undergoing similar selective pressures showed evidence of divergence at some loci, they evolved in concert at other loci. Thus, this study illustrates how selective sweeps might contribute both to the integration of conspecific populations and to the differentiation of races or species.     

Pervasive Hitchhiking at Coding and Regulatory Sites in Humans

Much effort and interest have focused on assessing the importance of natural selection, particularly positive natural selection, in shaping the human genome. Although scans for positive selection have identified candidate loci that may be associated with positive selection in humans, such scans do not indicate whether adaptation is frequent in general in humans. Studies based on the reasoning of the MacDonald–Kreitman test, which, in principle, can be used to evaluate the extent of positive selection, suggested that adaptation is detectable in the human genome but that it is less common than in Drosophila or Escherichia coli. Both positive and purifying natural selection at functional sites should affect levels and patterns of polymorphism at linked nonfunctional sites. Here, we search for these effects by analyzing patterns of neutral polymorphism in humans in relation to the rates of recombination, functional density, and functional divergence with chimpanzees. We find that the levels of neutral polymorphism are lower in the regions of lower recombination and in the regions of higher functional density or divergence. These correlations persist after controlling for the variation in GC content, density of simple repeats, selective constraint, mutation rate, and depth of sequencing coverage. We argue that these results are most plausibly explained by the effects of natural selection at functional sites—either recurrent selective sweeps or background selection—on the levels of linked neutral polymorphism. Natural selection at both coding and regulatory sites appears to affect linked neutral polymorphism, reducing neutral polymorphism by 6% genome-wide and by 11% in the gene-rich half of the human genome. These findings suggest that the effects of natural selection at linked sites cannot be ignored in the study of neutral human polymorphism.     

Limited Evidence for Classic Selective Sweeps in African Populations

While hundreds of loci have been identified as reflecting strong-positive selection in human populations, connections between candidate loci and specific selective pressures often remain obscure. This study investigates broader patterns of selection in African populations, which are underrepresented despite their potential to offer key insights into human adaptation. We scan for hard selective sweeps using several haplotype and allele-frequency statistics with a data set of nearly 500,000 genome-wide single-nucleotide polymorphisms in 12 highly diverged African populations that span a range of environments and subsistence strategies. We find that positive selection does not appear to be a strong determinant of allele-frequency differentiation among these African populations. Haplotype statistics do identify putatively selected regions that are shared across African populations. However, as assessed by extensive simulations, patterns of haplotype sharing between African populations follow neutral expectations and suggest that tails of the empirical distributions contain false-positive signals. After highlighting several genomic regions where positive selection can be inferred with higher confidence, we use a novel method to identify biological functions enriched among populations’ empirical tail genomic windows, such as immune response in agricultural groups. In general, however, it seems that current methods for selection scans are poorly suited to populations that, like the African populations in this study, are affected by ascertainment bias and have low levels of linkage disequilibrium, possibly old selective sweeps, and potentially reduced phasing accuracy. Additionally, population history can confound the interpretation of selection statistics, suggesting that greater care is needed in attributing broad genetic patterns to human adaptation.     

Selection signatures for fiber production in commercial species: A review

Natural fibers derived from diverse animal species have gained increased attention in recent years due to their favorable environmental effects, long-term sustainability benefits, and remarkable physical and mechanical properties that make them valuable raw materials used for textile and non-textile production. Domestication and selective breeding for the economically significant fiber traits play an imperative role in shaping the genomes and, thus, positively impact the overall productivity of the various fiber-producing species. These selection pressures leave unique footprints on the genome due to alteration in the allelic frequencies at specific loci, characterizing selective sweeps. Recent advances in genomics have enabled the discovery of selection signatures across the genome using a variety of methods. The increased demand for ‘green products’ manufactured from natural fibers necessitates a detailed investigation of the genomes of the various fiber-producing plant and animal species to identify the candidate genes associated with important fiber attributes such as fiber diameter/fineness, color, length, and strength, among others. The objective of this review is to present a comprehensive overview of the concept of selection signature and selective sweeps, discuss the main methods used for its detection, and address the selection signature studies conducted so far in the diverse fiber-producing animal species.     

Levels of polymorphism on the sex‐limited chromosome: a clue to Y from W?

Nucleotide diversity of the human Y chromosome is much lower than that in the rest of the genome. A new hypothesis postulates that this invariance may result from mutations in maternally inherited mitochondrial DNA (mtDNA), leading to impaired reproduction among males and lowered male effective population size. If correct, we should expect to see low levels of polymorphism in the male-specific Y chromosome of many organisms but not necessarily in the female-specific W chromosome in organisms with female heterogamety. However, recent observations from birds suggest that the avian W chromosome is very low in nucleotide diversity. This indicates that mtDNA mutations cannot broadly explain the evolution of the sex-limited chromosome. Other work has suggested that sexual selection at loci involved in sex determination or secondary sexual characteristics might reduce levels of genetic variability on Y through hitch-hiking effects. Although the W chromosome does not seen to play a dominant role for sex determination in birds, it cannot be excluded that selective sweeps arising from natural or sexual selection contribute to the low levels of genetic variability seen on this chromosome.