Scanning for genomic regions subject to selective sweeps using SNP-MaP strategy

Population genomic approaches,which take advantages of high-throughput genotyping,are powerful yet costly methods to scan for selective sweeps.DNA-pooling strategies have been widely used for association studies because it is a cost-effective alternative to large-scale individual genotyping.Here,we performed an SNP-MaP(single nucleotide polymorphism microarrays and pooling)analysis using samples from Eurasia to evaluate the efficiency of pooling strategy in genome-wide scans for selection.By conducting simulations of allelotype data,we first demonstrated that the boxplot with average heterozygosity(HET)is a promising method to detect strong selective sweeps with a moderate level of pooling error.Based on this,we used a sliding window analysis of HET to detect the large contiguous regions(LCRs)putatively under selective sweeps from Eurasia datasets.This survey identified 63 LCRs in a European population.These signals were further supported by the integrated haplotype score(iHS)test using HapMap Ⅱ data.We also confirrned the European-specific signatures of positive selection from several previously identified genes(KEL,TRPV5,TRPV6,EPHB6).In summary,our results not only revealed the high credibility of SNP-MaP strategy in scanning for selective sweeps,but also provided an insight into the population differentiation.     

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.     

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.     

Allele frequency distribution under recurrent selective sweeps

The allele frequency of a neutral variant in a population is pushed either upward or downward by directional selection on a linked beneficial mutation ("selective sweeps"). DNA sequences sampled after the fixation of the beneficial allele thus contain an excess of rare neutral alleles. This study investigates the allele frequency distribution under selective sweep models using analytic approximation and simulation. First, given a single selective sweep at a fixed time, I derive an expression for the sampling probabilities of neutral mutants. This solution can be used to estimate the time of the fixation of a beneficial allele from sequence data. Next, I obtain an approximation to mean allele frequencies under recurrent selective sweeps. Under recurrent sweeps, the frequency spectrum is skewed toward rare alleles. However, the excess of high-frequency derived alleles, previously shown to be a signature of single selective sweeps, disappears with recurrent sweeps. It is shown that, using this approximation and multilocus polymorphism data, genomewide parameters of directional selection can be estimated.     

Hitchhiking both ways: effect of two interfering selective sweeps on linked neutral variation

The neutral polymorphism pattern in the vicinity of a selective sweep can be altered by both stochastic and deterministic factors. Here, we focus on the impact of another selective sweep in the region of influence of a first one. We study the signature left on neutral polymorphism by positive selection at two closely linked loci, when both beneficial mutations reach fixation. We show that, depending on the timing of selective sweeps and on their selection coefficients, the two hitchhiking effects can interfere with each other, leading to less reduction in heterozygosity than a single selective sweep of the same magnitude and more importantly to an excess of intermediate-frequency variants relative to neutrality under some parameter values. This pattern can be sustained and potentially alter the detection of positive selection, including by provoking spurious detection of balancing selection. In situations where positive selection is suspected a priori at several closely linked loci, the polymorphism pattern in the region may also be informative about their selective histories.     

Discovery of Ongoing Selective Sweeps within Anopheles Mosquito Populations Using Deep Learning

Identification of partial sweeps, which include both hard and soft sweeps that have not currently reached fixation, provides crucial information about ongoing evolutionary responses. To this end, we introduce partialS/HIC, a deep learning method to discover selective sweeps from population genomic data. partialS/HIC uses a convolutional neural network for image processing, which is trained with a large suite of summary statistics derived from coalescent simulations incorporating population-specific history, to distinguish between completed versus partial sweeps, hard versus soft sweeps, and regions directly affected by selection versus those merely linked to nearby selective sweeps. We perform several simulation experiments under various demographic scenarios to demonstrate partialS/HIC’s performance, which exhibits excellent resolution for detecting partial sweeps. We also apply our classifier to whole genomes from eight mosquito populations sampled across sub-Saharan Africa by the Anopheles gambiae 1000 Genomes Consortium, elucidating both continent-wide patterns as well as sweeps unique to specific geographic regions. These populations have experienced intense insecticide exposure over the past two decades, and we observe a strong overrepresentation of sweeps at insecticide resistance loci. Our analysis thus provides a list of candidate adaptive loci that may be relevant to mosquito control efforts. More broadly, our supervised machine learning approach introduces a method to distinguish between completed and partial sweeps, as well as between hard and soft sweeps, under a variety of demographic scenarios. As whole-genome data rapidly accumulate for a greater diversity of organisms, partialS/HIC addresses an increasing demand for useful selection scan tools that can track in-progress evolutionary dynamics.     

A genome-wide survey of R gene polymorphisms in Arabidopsis

We used polymorphism analysis to study the evolutionary dynamics of 27 disease resistance (R) genes by resequencing the leucine-rich repeat (LRR) region in 96 Arabidopsis thaliana accessions. We compared single nucleotide polymorphisms (SNPs) in these R genes to an empirical distribution of SNP in the same sample based on 876 fragments selected to sample the entire genome. LRR regions are highly polymorphic for protein variants but not for synonymous changes, suggesting that they generate many alleles maintained for short time periods. Recombination is also relatively common and important for generating protein variants. Although none of the genes is nearly as polymorphic as RPP13, a locus previously shown to have strong signatures of balancing selection, seven genes show weaker indications of balancing selection. Five R genes are relatively invariant, indicating young alleles, but all contain segregating protein variants. Polymorphism analysis in neighboring fragments yielded inconclusive evidence for recent selective sweeps at these loci. In addition, few alleles are candidates for rapid increases in frequency expected under directional selection. Haplotype sharing analysis revealed significant underrepresentation of R gene alleles with extended haplotypes compared with 1102 random genomic fragments. Lack of convincing evidence for directional selection or selective sweeps argues against an arms race driving R gene evolution. Instead, the data support transient or frequency-dependent selection maintaining protein variants at a locus for variable time periods.     

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.     

Soft Selective Sweeps in Complex Demographic Scenarios

Adaptation from de novo mutation can produce so-called soft selective sweeps, where adaptive alleles of independent mutational origin sweep through the population at the same time. Population genetic theory predicts that such soft sweeps should be likely if the product of the population size and the mutation rate toward the adaptive allele is sufficiently large, such that multiple adaptive mutations can establish before one has reached fixation; however, it remains unclear how demographic processes affect the probability of observing soft sweeps. Here we extend the theory of soft selective sweeps to realistic demographic scenarios that allow for changes in population size over time. We first show that population bottlenecks can lead to the removal of all but one adaptive lineage from an initially soft selective sweep. The parameter regime under which such “hardening” of soft selective sweeps is likely is determined by a simple heuristic condition. We further develop a generalized analytical framework, based on an extension of the coalescent process, for calculating the probability of soft sweeps under arbitrary demographic scenarios. Two important limits emerge within this analytical framework: In the limit where population-size fluctuations are fast compared to the duration of the sweep, the likelihood of soft sweeps is determined by the harmonic mean of the variance effective population size estimated over the duration of the sweep; in the opposing slow fluctuation limit, the likelihood of soft sweeps is determined by the instantaneous variance effective population size at the onset of the sweep. We show that as a consequence of this finding the probability of observing soft sweeps becomes a function of the strength of selection. Specifically, in species with sharply fluctuating population size, strong selection is more likely to produce soft sweeps than weak selection. Our results highlight the importance of accurate demographic estimates over short evolutionary timescales for understanding the population genetics of adaptation from de novo mutation.     

Coherent synthesis of genomic associations with phenotypes and home environments

Local adaptation is often studied via (i) multiple common garden experiments comparing performance of genotypes in different environments and (ii) sequencing genotypes from multiple locations and characterizing geographic patterns in allele frequency. Both approaches aim to characterize the same pattern (local adaptation), yet the complementary information from each has not yet been coherently integrated. Here, we develop a genome‐wide association model of genotype interactions with continuous environmental gradients (G × E), that is reaction norms. We present an approach to impute relative fitness, allowing us to coherently synthesize evidence from common garden and genome–environment associations. Our approach identifies loci exhibiting environmental clines where alleles are associated with higher fitness in home environments. Simulations show our approach can increase power to detect loci causing local adaptation. In a case study on Arabidopsis thaliana, most identified SNPs exhibited home allele advantage and fitness trade‐offs along climate gradients, suggesting selective gradients can maintain allelic clines. SNPs exhibiting G × E associations with fitness were enriched in genic regions, putative partial selective sweeps and associations with an adaptive phenotype (flowering time plasticity). We discuss extensions for situations where only adaptive phenotypes other than fitness are available. Many types of data may point towards the loci underlying G × E and local adaptation; coherent models of diverse data provide a principled basis for synthesis.     

Soft sweeps: molecular population genetics of adaptation from standing genetic variation

A population can adapt to a rapid environmental change or habitat expansion in two ways. It may adapt either through new beneficial mutations that subsequently sweep through the population or by using alleles from the standing genetic variation. We use diffusion theory to calculate the probabilities for selective adaptations and find a large increase in the fixation probability for weak substitutions, if alleles originate from the standing genetic variation. We then determine the parameter regions where each scenario-standing variation vs. new mutations-is more likely. Adaptations from the standing genetic variation are favored if either the selective advantage is weak or the selection coefficient and the mutation rate are both high. Finally, we analyze the probability of "soft sweeps," where multiple copies of the selected allele contribute to a substitution, and discuss the consequences for the footprint of selection on linked neutral variation. We find that soft sweeps with weaker selective footprints are likely under both scenarios if the mutation rate and/or the selection coefficient is high.     

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.     

USING HITCHHIKING GENES TO STUDY ADAPTATION AND DIVERGENCE DURING SPECIATION WITHIN THE DROSOPHILA MELANOGASTER SPECIES COMPLEX

Several studies of intraspecific and interspecific DNA sequence variation from Drosophila loci have revealed a pattern of low intraspecific variation from genomic regions of low recombination. The mechanisms consistently invoked to explain these patterns are the selective sweep of advantageous mutations together with genetic hitchhiking of linked loci. To examine the effect of selective sweeps on genetic divergence during speciation, we studied two loci in different genomic regions thought to be subject to selective sweeps. We obtained DNA sequences from 1.1kb pair portions of the fourth chromosome locus cubitus interruptus Dominant (ci^D) and from the asense locus near the telomere of the X chromosome. At ci^D, we found very low variation among multiple lines of Drosophila mauritiana and D. sechellia. This finding is consistent with an earlier report of very low variation in D. melanogaster and D. simulans at ci^D and supports the conclusion of selective sweeps and genetic hitchhiking on the nonrecombining fourth chromosome. The pattern of variation found at asense suggests that a selective sweep has occurred recently at the tip of the X chromosome in D. simulans, but not in D. melanogaster or D. mauritiana. The data from ci^D and asense are compared with data from three X chromosome loci (period, zeste, and yolk protein 2) that experience normal levels of recombination. By examining estimated genealogies and the rates at which different classes of mutations have accumulated, we conclude that selective sweeps are common occurrences on the fourth chromosome but less common near the tip of the X chromosome. An interesting pattern of low variation at ci^D among D. simulans, D. mauritiana, and D. sechellia suggests that a selective sweep may have occurred among these forms even after divergence into separate species had begun.     

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.     

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.     

The signature of positive selection at randomly chosen loci

In Drosophila and humans, there are accumulating examples of loci with a significant excess of high-frequency-derived alleles or high levels of linkage disequilibrium, relative to a neutral model of a random-mating population of constant size. These are features expected after a recent selective sweep. Their prevalence suggests that positive directional selection may be widespread in both species. However, as I show here, these features do not persist long after the sweep ends: The high-frequency alleles drift to fixation and no longer contribute to polymorphism, while linkage disequilibrium is broken down by recombination. As a result, loci chosen without independent evidence of recent selection are not expected to exhibit either of these features, even if they have been affected by numerous sweeps in their genealogical history. How then can we explain the patterns in the data? One possibility is population structure, with unequal sampling from different subpopulations. Alternatively, positive selection may not operate as is commonly modeled. In particular, the rate of fixation of advantageous mutations may have increased in the recent past.     

Testing evolutionary hypotheses for DNA barcoding failure in willows

The goal of DNA barcoding is to enable the rapid identification of taxa from short diagnostic DNA sequence profiles. But how feasible is this objective when many evolutionary processes, such as hybridization and selective sweeps, cause alleles to be shared among related taxa? In this issue of Molecular Ecology, Percy et al. (2014) test the full suite of seven candidate plant barcoding loci in a broad geographic sample of willow species. They show exceptional plastid haplotype sharing between species across continents, with most taxa not possessing a unique barcode sequence. Using population genetic and molecular dating analyses, they implicate hybridization and selective sweeps, but not incomplete lineage sorting, as the historical processes causing widespread haplotype sharing among willow taxa. This study represents an exceptional case of how poorly barcoding can perform, and highlights methodological issues using universal organellar regions for species identification.     

Estimating the strength of selective sweeps from deep population diversity data

Selective sweeps are typically associated with a local reduction of genetic diversity around the adaptive site. However, selective sweeps can also quickly carry neutral mutations to observable population frequencies if they arise early in a sweep and hitchhike with the adaptive allele. We show that the interplay between mutation and exponential amplification through hitchhiking results in a characteristic frequency spectrum of the resulting novel haplotype variation that depends only on the ratio of the mutation rate and the selection coefficient of the sweep. On the basis of this result, we develop an estimator for the selection coefficient driving a sweep. Since this estimator utilizes the novel variation arising from mutations during a sweep, it does not rely on preexisting variation and can also be applied to loci that lack recombination. Compared with standard approaches that infer selection coefficients from the size of dips in genetic diversity around the adaptive site, our estimator requires much shorter sequences but sampled at high population depth to capture low-frequency variants; given such data, it consistently outperforms standard approaches. We investigate analytically and numerically how the accuracy of our estimator is affected by the decay of the sweep pattern over time as a consequence of random genetic drift and discuss potential effects of recombination, soft sweeps, and demography. As an example for its use, we apply our estimator to deep sequencing data from human immunodeficiency virus populations.     

A scan of molecular variation leads to the narrow localization of a selective sweep affecting both Afrotropical and cosmopolitan populations of Drosophila melanogaster

Drosophila melanogaster originated in tropical Africa but has achieved a cosmopolitan distribution in association with human habitation. Cosmopolitan populations of D. melanogaster are known to have reduced genetic variation, particularly on the X chromosome. However, the relative importance of population bottlenecks and selective sweeps in explaining this reduction is uncertain. We surveyed variation at 31 microsatellites across a 330-kb section of the X chromosome located between the white and kirre genes. Two linked clusters of loci were observed with reduced variation and a skew toward rare alleles in both an Ecuador and a Zimbabwe population sample. Examining Zimbabwe DNA sequence polymorphism within one of these regions allowed us to localize a selective sweep to a 361-bp window within the 5' regulatory region of the roughest gene, with one nucleotide substitution representing the best candidate for the target of selection. Estimates of sweep age suggested that this fixation event occurred prior to the expansion of D. melanogaster from sub-Saharan Africa. For both putative sweep regions in our data set, cosmopolitan populations showed wider footprints of selection compared to those in Zimbabwe. This pattern appears consistent with the demographic amplification of preexisting sweep signals due to one or more population bottlenecks.     

Novel linkage mapping approach using DNA pooling in human and animal genetics. II. Detection of quantitative traits loci in dairy cattle

Selective DNA pooling is an advanced methodology for linkage mapping of quantitative trait loci (QTL) in farm animals. The principle is based on densitometric estimates of marker allele frequency in pooled DNA samples of phenotypically extreme individuals from half-sib, backcross and F(2) experimental designs in farm animals. This methodology provides a rapid and efficient analysis of a large number of individuals with short tandem repeat markers that are essential to detect QTL through the genome - wide searching approach. Several strategies involving whole genome scanning with a high statistical power have been developed for systematic search to detect the quantitative traits loci and linked loci of complex traits. In recent studies, greater success has been achieved in mapping several QTLs in Israel-Holstein cattle using selective DNA pooling. This paper outlines the currently emerged novel strategies of linkage mapping to identify QTL based on selective DNA pooling with more emphasis on its theoretical pre-requisite to detect linked QTLs, applications, a general theory for experimental half-sib designs, the power of statistics and its feasibility to identify genetic markers linked QTL in dairy cattle. The study reveals that the application of selective DNA pooling in dairy cattle can be best exploited in the genome-wide detection of linked loci with small and large QTL effects and applied to a moderately sized half-sib family of about 500 animals.