Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps

Genome-Wide Detection of Genes Under Positive Selection in Worldwide Populations of the Barley Scald Pathogen

Coevolution between hosts and pathogens generates strong selection pressures to maintain resistance and infectivity, respectively. Genomes of plant pathogens often encode major effect loci for the ability to successfully infect specific host genotypes. Hence, spatial heterogeneity in host genotypes coupled with abiotic factors could lead to locally adapted pathogen populations. However, the genetic basis of local adaptation is poorly understood. Rhynchosporium commune, the pathogen causing barley scald disease, interacts at least partially in a gene-for-gene manner with its host. We analyzed global field populations of 125 R. commune isolates to identify candidate genes for local adaptation. Whole genome sequencing data showed that the pathogen is subdivided into three genetic clusters associated with distinct geographic and climatic regions. Using haplotype-based selection scans applied independently to each genetic cluster, we found strong evidence for selective sweeps throughout the genome. Comparisons of loci under selection among clusters revealed little overlap, suggesting that ecological differences associated with each cluster led to variable selection regimes. The strongest signals of selection were found predominantly in the two clusters composed of isolates from Central Europe and Ethiopia. The strongest selective sweep regions encoded protein functions related to biotic and abiotic stress responses. Selective sweep regions were enriched in genes encoding functions in cellular localization, protein transport activity, and DNA damage responses. In contrast to the prevailing view that a small number of gene-for-gene interactions govern plant pathogen evolution, our analyses suggest that the evolutionary trajectory is largely determined by spatially heterogeneous biotic and abiotic selection pressures.

Estimating Time to the Common Ancestor for a Beneficial Allele

The haplotypes of a beneficial allele carry information about its history that can shed light on its age and the putative cause for its increase in frequency. Specifically, the signature of an allele's age is contained in the pattern of variation that mutation and recombination impose on its haplotypic background. We provide a method to exploit this pattern and infer the time to the common ancestor of a positively selected allele following a rapid increase in frequency. We do so using a hidden Markov model which leverages the length distribution of the shared ancestral haplotype, the accumulation of derived mutations on the ancestral background, and the surrounding background haplotype diversity. Using simulations, we demonstrate how the inclusion of information from both mutation and recombination events increases accuracy relative to approaches that only consider a single type of event. We also show the behavior of the estimator in cases where data do not conform to model assumptions, and provide some diagnostics for assessing and improving inference. Using the method, we analyze population-specific patterns in the 1000 Genomes Project data to estimate the timing of adaptation for several variants which show evidence of recent selection and functional relevance to diet, skin pigmentation, and morphology in humans.

Identifying the favored mutation in a positive selective sweep

Most approaches that capture signatures of selective sweeps in population genomics data do not identify the specific mutation favored by selection. We present iSAFE (for "integrated selection of allele favored by evolution"), a method that enables researchers to accurately pinpoint the favored mutation in a large region (∼5 Mbp) by using a statistic derived solely from population genetics signals. iSAFE does not require knowledge of demography, the phenotype under selection, or functional annotations of mutations.

Examination of Signatures of Recent Positive Selection on Genes Involved in Human Sialic Acid Biology

Sialic acids are nine carbon sugars ubiquitously found on the surfaces of vertebrate cells and are involved in various immune response-related processes. In humans, at least 58 genes spanning diverse functions, from biosynthesis and activation to recycling and degradation, are involved in sialic acid biology. Because of their role in immunity, sialic acid biology genes have been hypothesized to exhibit elevated rates of evolutionary change. Consistent with this hypothesis, several genes involved in sialic acid biology have experienced higher rates of non-synonymous substitutions in the human lineage than their counterparts in other great apes, perhaps in response to ancient pathogens that infected hominins millions of years ago (paleopathogens). To test whether sialic acid biology genes have also experienced more recent positive selection during the evolution of the modern human lineage, reflecting adaptation to contemporary cosmopolitan or geographically-restricted pathogens, we examined whether their protein-coding regions showed evidence of recent hard and soft selective sweeps. This examination involved the calculation of four measures that quantify changes in allele frequency spectra, extent of population differentiation, and haplotype homozygosity caused by recent hard and soft selective sweeps for 55 sialic acid biology genes using publicly available whole genome sequencing data from 1,668 humans from three ethnic groups. To disentangle evidence for selection from confounding demographic effects, we compared the observed patterns in sialic acid biology genes to simulated sequences of the same length under a model of neutral evolution that takes into account human demographic history. We found that the patterns of genetic variation of most sialic acid biology genes did not significantly deviate from neutral expectations and were not significantly different among genes belonging to different functional categories. Those few sialic acid biology genes that significantly deviated from neutrality either experienced soft sweeps or population-specific hard sweeps. Interestingly, while most hard sweeps occurred on genes involved in sialic acid recognition, most soft sweeps involved genes associated with recycling, degradation and activation, transport, and transfer functions. We propose that the lack of signatures of recent positive selection for the majority of the sialic acid biology genes is consistent with the view that these genes regulate immune responses against ancient rather than contemporary cosmopolitan or geographically restricted pathogens.

Multiple Modes of Positive Selection Shaping the Patterns of Incomplete Selective Sweeps over African Populations of Drosophila melanogaster

It remains a challenge in evolutionary genetics to elucidate how beneficial mutations arise and propagate in a population and how selective pressures on mutant alleles are structured over space and time. By identifying "sweeping haplotypes (SHs)" that putatively carry beneficial alleles and are increasing (or have increased) rapidly in frequency, and surveying the geographic distribution of SH frequencies, we can indirectly infer how selective sweeps unfold in time and thus which modes of positive selection underlie those sweeps. Using population genomic data from African Drosophila melanogaster, we identified SHs from 37 candidate loci under selection. At more than half of loci, we identify single SHs. However, many other loci harbor multiple independent SHs, namely soft selective sweeps, either due to parallel evolution across space or a high beneficial mutation rate. At about a quarter of the loci, intermediate SH frequencies are found across multiple populations, which cannot be explained unless a certain form of frequency-dependent positive selection, such as heterozygote advantage, is invoked given the reasonable range of migration rates between African populations. At one locus, many independent SHs are observed over multiple populations but always together with ancestral haplotypes. This complex pattern is compatible with a large number of mutational targets in a gene and frequency-dependent selection on new variants. We conclude that very diverse modes of positive selection are operating at different sets of loci in D. melanogaster populations.

A Simple Test Identifies Selection on Complex Traits

Important traits in agricultural, natural, and human populations are increasingly being shown to be under the control of many genes that individually contribute only a small proportion of genetic variation. However, the majority of modern tools in quantitative and population genetics, including genome-wide association studies and selection-mapping protocols, are designed to identify individual genes with large effects. We have developed an approach to identify traits that have been under selection and are controlled by large numbers of loci. In contrast to existing methods, our technique uses additive-effects estimates from all available markers, and relates these estimates to allele-frequency change over time. Using this information, we generate a composite statistic, denoted [Formula: see text] which can be used to test for significant evidence of selection on a trait. Our test requires pre- and postselection genotypic data but only a single time point with phenotypic information. Simulations demonstrate that [Formula: see text] is powerful for identifying selection, particularly in situations where the trait being tested is controlled by many genes, which is precisely the scenario where classical approaches for selection mapping are least powerful. We apply this test to breeding populations of maize and chickens, where we demonstrate the successful identification of selection on traits that are documented to have been under selection.

Localization of adaptive variants in human genomes using averaged one-dependence estimation

Statistical methods for identifying adaptive mutations from population genetic data face several obstacles: assessing the significance of genomic outliers, integrating correlated measures of selection into one analytic framework, and distinguishing adaptive variants from hitchhiking neutral variants. Here, we introduce SWIF(r), a probabilistic method that detects selective sweeps by learning the distributions of multiple selection statistics under different evolutionary scenarios and calculating the posterior probability of a sweep at each genomic site. SWIF(r) is trained using simulations from a user-specified demographic model and explicitly models the joint distributions of selection statistics, thereby increasing its power to both identify regions undergoing sweeps and localize adaptive mutations. Using array and exome data from 45 ‡Khomani San hunter-gatherers of southern Africa, we identify an enrichment of adaptive signals in genes associated with metabolism and obesity. SWIF(r) provides a transparent probabilistic framework for localizing beneficial mutations that is extensible to a variety of evolutionary scenarios.

Genetic diversity of the African malaria vector Anopheles gambiae

The sustainability of malaria control in Africa is threatened by the rise of insecticide resistance in Anopheles mosquitoes, which transmit the disease. To gain a deeper understanding of how mosquito populations are evolving, here we sequenced the genomes of 765 specimens of Anopheles gambiae and Anopheles coluzzii sampled from 15 locations across Africa, and identified over 50 million single nucleotide polymorphisms within the accessible genome. These data revealed complex population structure and patterns of gene flow, with evidence of ancient expansions, recent bottlenecks, and local variation in effective population size. Strong signals of recent selection were observed in insecticide-resistance genes, with several sweeps spreading over large geographical distances and between species. The design of new tools for mosquito control using gene-drive systems will need to take account of high levels of genetic diversity in natural mosquito populations.

Comparison of Single Genome and Allele Frequency Data Reveals Discordant Demographic Histories

Inference of demographic history from genetic data is a primary goal of population genetics of model and nonmodel organisms. Whole genome-based approaches such as the pairwise/multiple sequentially Markovian coalescent methods use genomic data from one to four individuals to infer the demographic history of an entire population, while site frequency spectrum (SFS)-based methods use the distribution of allele frequencies in a sample to reconstruct the same historical events. Although both methods are extensively used in empirical studies and perform well on data simulated under simple models, there have been only limited comparisons of them in more complex and realistic settings. Here we use published demographic models based on data from three human populations (Yoruba, descendants of northwest-Europeans, and Han Chinese) as an empirical test case to study the behavior of both inference procedures. We find that several of the demographic histories inferred by the whole genome-based methods do not predict the genome-wide distribution of heterozygosity, nor do they predict the empirical SFS. However, using simulated data, we also find that the whole genome methods can reconstruct the complex demographic models inferred by SFS-based methods, suggesting that the discordant patterns of genetic variation are not attributable to a lack of statistical power, but may reflect unmodeled complexities in the underlying demography. More generally, our findings indicate that demographic inference from a small number of genomes, routine in genomic studies of nonmodel organisms, should be interpreted cautiously, as these models cannot recapitulate other summaries of the data.

Detecting positive selection in the genome

Population geneticists have long sought to understand the contribution of natural selection to molecular evolution. A variety of approaches have been proposed that use population genetics theory to quantify the rate and strength of positive selection acting in a species’ genome. In this review we discuss methods that use patterns of between-species nucleotide divergence and within-species diversity to estimate positive selection parameters from population genomic data. We also discuss recently proposed methods to detect positive selection from a population’s haplotype structure. The application of these tests has resulted in the detection of pervasive adaptive molecular evolution in multiple species.

Population genomics of Wolbachia and mtDNA in Drosophila simulans from California

Wolbachia pipientis is an intracellular endosymbiont infecting many arthropods and filarial nematodes. Little is known about the short-term evolution of Wolbachia or its interaction with its host. Wolbachia is maternally inherited, resulting in co-inheritance of mitochondrial organelles such as mtDNA. Here I explore the evolution of Wolbachia, and the relationship between Wolbachia and mtDNA, using a large inbred panel of Drosophila simulans. I compare this to the only other large population genomic Wolbachia dataset from D. melanogaster. I find reduced diversity relative to expectation in both Wolbachia and mtDNA, but only mtDNA shows evidence of a recent selective sweep or population bottleneck. I estimate Wolbachia and mtDNA titre in each genotype, and I find considerable variation in both phenotypes, despite low genetic diversity in Wolbachia and mtDNA. A phylogeny of Wolbachia and of mtDNA suggest a recent origin of the infection derived from a single origin. Using Wolbachia and mtDNA titre as a phenotype, I perform the first association analysis using this phenotype with the nuclear genome and find several implicated regions, including one which contains four CAAX-box protein processing genes. CAAX-box protein processing can be an important part of host-pathogen interactions in other systems, suggesting interesting directions for future research.

Insights into DDT Resistance from the Drosophila melanogaster Genetic Reference Panel

Insecticide resistance is considered a classic model of microevolution, where a strong selective agent is applied to a large natural population, resulting in a change in frequency of alleles that confer resistance. While many insecticide resistance variants have been characterized at the gene level, they are typically single genes of large effect identified in highly resistant pest species. In contrast, multiple variants have been implicated in DDT resistance in Drosophila melanogaster; however, only the Cyp6g1 locus has previously been shown to be relevant to field populations. Here we use genome-wide association studies (GWAS) to identify DDT-associated polygenes and use selective sweep analyses to assess their adaptive significance. We identify and verify two candidate DDT resistance loci. A largely uncharacterized gene, CG10737, has a function in muscles that ameliorates the effects of DDT, while a putative detoxifying P450, Cyp6w1, shows compelling evidence of positive selection.

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit

Forward Wright–Fisher simulations are powerful in their ability to model complex demography and selection scenarios, but suffer from slow execution on the Central Processor Unit (CPU), thus limiting their usefulness. However, the single-locus Wright–Fisher forward algorithm is exceedingly parallelizable, with many steps that are so-called “embarrassingly parallel,” consisting of a vast number of individual computations that are all independent of each other and thus capable of being performed concurrently. The rise of modern Graphics Processing Units (GPUs) and programming languages designed to leverage the inherent parallel nature of these processors have allowed researchers to dramatically speed up many programs that have such high arithmetic intensity and intrinsic concurrency. The presented GPU Optimized Wright–Fisher simulation, or “GO Fish” for short, can be used to simulate arbitrary selection and demographic scenarios while running over 250-fold faster than its serial counterpart on the CPU. Even modest GPU hardware can achieve an impressive speedup of over two orders of magnitude. With simulations so accelerated, one can not only do quick parametric bootstrapping of previously estimated parameters, but also use simulated results to calculate the likelihoods and summary statistics of demographic and selection models against real polymorphism data, all without restricting the demographic and selection scenarios that can be modeled or requiring approximations to the single-locus forward algorithm for efficiency. Further, as many of the parallel programming techniques used in this simulation can be applied to other computationally intensive algorithms important in population genetics, GO Fish serves as an exciting template for future research into accelerating computation in evolution. GO Fish is part of the Parallel PopGen Package available at: http://dl42.github.io/ParallelPopGen/.

Signatures of soft sweeps across the Dt1 locus underlying determinate growth habit in soya bean [Glycine max (L.) Merr.]

Determinate growth habit is an agronomically important trait associated with domestication in soya bean. Previous studies have demonstrated that the emergence of determinacy is correlated with artificial selection on four nonsynonymous mutations in the Dt1 gene. To better understand the signatures of the soft sweeps across the Dt1 locus and track the origins of the determinate alleles, we examined patterns of nucleotide variation in Dt1 and the surrounding genomic region of approximately 800 kb. Four local, asymmetrical hard sweeps on four determinate alleles, sized approximately 660, 120, 220 and 150 kb, were identified, which constitute the soft sweeps for the adaptation. These variable-sized sweeps substantially reflected the strength and timing of selection and indicated that the selection on the alleles had been completed rapidly within half a century. Statistics of EHH, iHS, H12 and H2/H1 based on haplotype data had the power to detect the soft sweeps, revealing distinct signatures of extensive long-range LD and haplotype homozygosity, and multiple frequent adaptive haplotypes. A haplotype network constructed for Dt1 and a phylogenetic tree based on its extended haplotype block implied independent sources of the adaptive alleles through de novo mutations or rare standing variation in quick succession during the selective phase, strongly supporting multiple origins of the determinacy. We propose that the adaptation of soya bean determinacy is guided by a model of soft sweeps and that this model might be indispensable during crop domestication or evolution.

Fine scale mapping of genomic introgressions within the Drosophila yakuba clade

The process of speciation involves populations diverging over time until they are genetically and reproductively isolated. Hybridization between nascent species was long thought to directly oppose speciation. However, the amount of interspecific genetic exchange (introgression) mediated by hybridization remains largely unknown, although recent progress in genome sequencing has made measuring introgression more tractable. A natural place to look for individuals with admixed ancestry (indicative of introgression) is in regions where species co-occur. In west Africa, D. santomea and D. yakuba hybridize on the island of São Tomé, while D. yakuba and D. teissieri hybridize on the nearby island of Bioko. In this report, we quantify the genomic extent of introgression between the three species of the Drosophila yakuba clade (D. yakuba, D. santomea), D. teissieri). We sequenced the genomes of 86 individuals from all three species. We also developed and applied a new statistical framework, using a hidden Markov approach, to identify introgression. We found that introgression has occurred between both species pairs but most introgressed segments are small (on the order of a few kilobases). After ruling out the retention of ancestral polymorphism as an explanation for these similar regions, we find that the sizes of introgressed haplotypes indicate that genetic exchange is not recent (>1,000 generations ago). We additionally show that in both cases, introgression was rarer on X chromosomes than on autosomes which is consistent with sex chromosomes playing a large role in reproductive isolation. Even though the two species pairs have stable contemporary hybrid zones, providing the opportunity for ongoing gene flow, our results indicate that genetic exchange between these species is currently rare.

Convergent and divergent genetic changes in the genome of Chinese and European pigs

Since 10,000 BC, continuous human selection has led to intense genetic and phenotypic changes in pig (Sus scrofa) domestication. Through whole genome analysis of 257 individuals, we demonstrated artificial unidirectional and bidirectional selection as the primary force to shape the convergent and divergent changes between Chinese domestic pigs (CHD) and European domestic pigs (EUD). We identified 31 genes in unidirectional selection regions that might be related to fundamental domestication requirements in pigs. And these genes belong predominantly to categories related to the nervous system, muscle development, and especially to metabolic diseases. In addition, 35 genes, representing different breeding preference, were found under bidirectional selection for the distinct leanness and reproduction traits between CHD and EUD. The convergent genetic changes, contributing physical and morphological adaption, represent the common concerns on pig domestication. And the divergent genetic changes reflect distinct breeding goals between Chinese and European pigs. Using ITPR3, AHR and NMU as examples, we explored and validated how the genetic variations contribute to the phenotype changes.

Selection plays the hand it was dealt: evidence that human adaptation commonly targets standing genetic variation

Using a powerful machine learning approach, a recent study of human genomes has revealed widespread footprints of recent positive selection on standing genetic variation.

Soft Sweeps Are the Dominant Mode of Adaptation in the Human Genome

The degree to which adaptation in recent human evolution shapes genetic variation remains controversial. This is in part due to the limited evidence in humans for classic "hard selective sweeps", wherein a novel beneficial mutation rapidly sweeps through a population to fixation. However, positive selection may often proceed via "soft sweeps" acting on mutations already present within a population. Here, we examine recent positive selection across six human populations using a powerful machine learning approach that is sensitive to both hard and soft sweeps. We found evidence that soft sweeps are widespread and account for the vast majority of recent human adaptation. Surprisingly, our results also suggest that linked positive selection affects patterns of variation across much of the genome, and may increase the frequencies of deleterious mutations. Our results also reveal insights into the role of sexual selection, cancer risk, and central nervous system development in recent human evolution.

Inferring Demographic History Using Two-Locus Statistics

Population demographic history may be learned from contemporary genetic variation data. Methods based on aggregating the statistics of many single loci into an allele frequency spectrum (AFS) have proven powerful, but such methods ignore potentially informative patterns of linkage disequilibrium (LD) between neighboring loci. To leverage such patterns, we developed a composite-likelihood framework for inferring demographic history from aggregated statistics of pairs of loci. Using this framework, we show that two-locus statistics are more sensitive to demographic history than single-locus statistics such as the AFS. In particular, two-locus statistics escape the notorious confounding of depth and duration of a bottleneck, and they provide a means to estimate effective population size based on the recombination rather than mutation rate. We applied our approach to a Zambian population of Drosophila melanogaster Notably, using both single- and two-locus statistics, we inferred a substantially lower ancestral effective population size than previous works and did not infer a bottleneck history. Together, our results demonstrate the broad potential for two-locus statistics to enable powerful population genetic inference.

Refining the Use of Linkage Disequilibrium as a Robust Signature of Selective Sweeps

During a selective sweep, characteristic patterns of linkage disequilibrium can arise in the genomic region surrounding a selected locus. These have been used to infer past selective sweeps. However, the recombination rate is known to vary substantially along the genome for many species. We here investigate the effectiveness of current (Kelly's [Formula: see text] and [Formula: see text]) and novel statistics at inferring hard selective sweeps based on linkage disequilibrium distortions under different conditions, including a human-realistic demographic model and recombination rate variation. When the recombination rate is constant, Kelly's [Formula: see text] offers high power, but is outperformed by a novel statistic that we test, which we call [Formula: see text] We also find this statistic to be effective at detecting sweeps from standing variation. When recombination rate fluctuations are included, there is a considerable reduction in power for all linkage disequilibrium-based statistics. However, this can largely be reversed by appropriately controlling for expected linkage disequilibrium using a genetic map. To further test these different methods, we perform selection scans on well-characterized HapMap data, finding that all three statistics-[Formula: see text] Kelly's [Formula: see text] and [Formula: see text]-are able to replicate signals at regions previously identified as selection candidates based on population differentiation or the site frequency spectrum. While [Formula: see text] replicates most candidates when recombination map data are not available, the [Formula: see text] and [Formula: see text] statistics are more successful when recombination rate variation is controlled for. Given both this and their higher power in simulations of selective sweeps, these statistics are preferred when information on local recombination rate variation is available.

The Evolutionary Interplay between Adaptation and Self-Fertilization

Genome-wide surveys of nucleotide polymorphisms, obtained from next-generation sequencing, have uncovered numerous examples of adaptation in self-fertilizing organisms, especially regarding changes to climate, geography, and reproductive systems. Yet existing models for inferring attributes of adaptive mutations often assume idealized outcrossing populations, which risks mischaracterizing properties of these variants. Recent theoretical work is emphasizing how various aspects of self-fertilization affects adaptation, yet empirical data on these properties are lacking. We review theoretical and empirical studies demonstrating how self-fertilization alters the process of adaptation, illustrated using examples from current sequencing projects. We propose ideas for how future research can more accurately quantify aspects of adaptation in self-fertilizers, including incorporating the effects of standing variation, demographic history, and polygenic adaptation.

Analysis of large-scale next-generation sequencing datasets are finding more examples of adaptive evolution at the genomic level.

Advances in theoretical work has demonstrated how self-fertilisation affects different aspects of adaptation in these organisms, compared to outcrossers.

Current software and statistical methods do not take different mating systems into account, which risks mischaracterising the presence or strength of adaptive mutations from genome scans.

Development of new mathematical and statistical methods that explicitly consider self-fertilization and associated demographic effects will enable researchers to more accurately quantify adaptation in these organisms.

Molecular Population Genetics

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data.

Convergent evolution of SWS2 opsin facilitates adaptive radiation of threespine stickleback into different light environments

Repeated adaptation to a new environment often leads to convergent phenotypic changes whose underlying genetic mechanisms are rarely known. Here, we study adaptation of color vision in threespine stickleback during the repeated postglacial colonization of clearwater and blackwater lakes in the Haida Gwaii archipelago. We use whole genomes from 16 clearwater and 12 blackwater populations, and a selection experiment, in which stickleback were transplanted from a blackwater lake into an uninhabited clearwater pond and resampled after 19 y to test for selection on cone opsin genes. Patterns of haplotype homozygosity, genetic diversity, site frequency spectra, and allele-frequency change support a selective sweep centered on the adjacent blue- and red-light sensitive opsins SWS2 and LWS. The haplotype under selection carries seven amino acid changes in SWS2, including two changes known to cause a red-shift in light absorption, and is favored in blackwater lakes but disfavored in the clearwater habitat of the transplant population. Remarkably, the same red-shifting amino acid changes occurred after the duplication of SWS2 198 million years ago, in the ancestor of most spiny-rayed fish. Two distantly related fish species, bluefin killifish and black bream, express these old paralogs divergently in black- and clearwater habitats, while sticklebacks lost one paralog. Our study thus shows that convergent adaptation to the same environment can involve the same genetic changes on very different evolutionary time scales by reevolving lost mutations and reusing them repeatedly from standing genetic variation.

A survey of methods and tools to detect recent and strong positive selection

Positive selection occurs when an allele is favored by natural selection. The frequency of the favored allele increases in the population and due to genetic hitchhiking the neighboring linked variation diminishes, creating so-called selective sweeps. Detecting traces of positive selection in genomes is achieved by searching for signatures introduced by selective sweeps, such as regions of reduced variation, a specific shift of the site frequency spectrum, and particular LD patterns in the region. A variety of methods and tools can be used for detecting sweeps, ranging from simple implementations that compute summary statistics such as Tajima's D, to more advanced statistical approaches that use combinations of statistics, maximum likelihood, machine learning etc. In this survey, we present and discuss summary statistics and software tools, and classify them based on the selective sweep signature they detect, i.e., SFS-based vs. LD-based, as well as their capacity to analyze whole genomes or just subgenomic regions. Additionally, we summarize the results of comparisons among four open-source software releases (SweeD, SweepFinder, SweepFinder2, and OmegaPlus) regarding sensitivity, specificity, and execution times. In equilibrium neutral models or mild bottlenecks, both SFS- and LD-based methods are able to detect selective sweeps accurately. Methods and tools that rely on LD exhibit higher true positive rates than SFS-based ones under the model of a single sweep or recurrent hitchhiking. However, their false positive rate is elevated when a misspecified demographic model is used to represent the null hypothesis. When the correct (or similar to the correct) demographic model is used instead, the false positive rates are considerably reduced. The accuracy of detecting the true target of selection is decreased in bottleneck scenarios. In terms of execution time, LD-based methods are typically faster than SFS-based methods, due to the nature of required arithmetic.

The genomic basis of adaptation in plants

Plants are powerful models for the study of adaptive evolution. Since they are rooted in place, they must directly face environmental insults, making adaptation to local conditions vital. In addition to adaptation to natural conditions, some plant species have held a central role in human subsistence over the past several thousand years. In these species, humans exerted strong selective pressures on traits of agricultural importance. Recently, an increasing number of studies have aimed to identify the genomic basis of adaptation. These studies have provided insights into the mechanisms through which the raw materials of adaptation were introduced as well as the modes of adaptation in wild and domesticated species.

Novel Candidate Genes Underlying Extreme Trophic Specialization in Caribbean Pupfishes

The genetic changes responsible for evolutionary transitions from generalist to specialist phenotypes are poorly understood. Here we examine the genetic basis of craniofacial traits enabling novel trophic specialization in a sympatric radiation of Cyprinodon pupfishes endemic to San Salvador Island, Bahamas. This recent radiation consists of a generalist species and two novel specialists: a small-jawed "snail-eater" and a large-jawed "scale-eater." We genotyped 12 million single nucleotide polymorphisms (SNPs) by whole-genome resequencing of 37 individuals of all three species from nine populations and integrated genome-wide divergence scans with association mapping to identify divergent regions containing putatively causal SNPs affecting jaw size-the most rapidly diversifying trait in this radiation. A mere 22 fixed variants accompanied extreme ecological divergence between generalist and scale-eater species. We identified 31 regions (20 kb) containing variants fixed between specialists that were significantly associated with variation in jaw size which contained 11 genes annotated for skeletal system effects and 18 novel candidate genes never previously associated with craniofacial phenotypes. Six of these 31 regions showed robust signs of hard selective sweeps after accounting for demographic history. Our data are consistent with predictions based on quantitative genetic models of adaptation, suggesting that the effect sizes of regions influencing jaw phenotypes are positively correlated with distance between fitness peaks on a complex adaptive landscape.

Genetic signatures of natural selection in a model invasive ascidian

Invasive species represent promising models to study species’ responses to rapidly changing environments. Although local adaptation frequently occurs during contemporary range expansion, the associated genetic signatures at both population and genomic levels remain largely unknown. Here, we use genome-wide gene-associated microsatellites to investigate genetic signatures of natural selection in a model invasive ascidian, Ciona robusta. Population genetic analyses of 150 individuals sampled in Korea, New Zealand, South Africa and Spain showed significant genetic differentiation among populations. Based on outlier tests, we found high incidence of signatures of directional selection at 19 loci. Hitchhiking mapping analyses identified 12 directional selective sweep regions, and all selective sweep windows on chromosomes were narrow (~8.9 kb). Further analyses indentified 132 candidate genes under selection. When we compared our genetic data and six crucial environmental variables, 16 putatively selected loci showed significant correlation with these environmental variables. This suggests that the local environmental conditions have left significant signatures of selection at both population and genomic levels. Finally, we identified “plastic” genomic regions and genes that are promising regions to investigate evolutionary responses to rapid environmental change in C. robusta.

Resistance evolution in Drosophila: the case of CYP6G1

The massive use of DDT as an insecticide between 1940 and 1970 has resulted in the emergence of a resistant population of insects. One of the main metabolic mechanisms developed by resistant insects involves detoxification enzymes such as cytochrome P450s. These enzymes can metabolise the insecticide to render it less toxic and facilitate its elimination from the organism. The P450 Cyp6g1 was identified as the major factor responsible for DDT resistance in Drosophila melanogaster field populations. In this article, we review the data available for this gene since it was associated with resistance in 2002. The knowledge gained on Cyp6g1 allows a better understanding of the evolution of insecticide resistance mechanisms and highlights the major role of transposable elements in evolutionary processes. © 2016 Society of Chemical Industry.

Population genetic analysis of the DARC locus (Duffy) reveals adaptation from standing variation associated with malaria resistance in humans

The human DARC (Duffy antigen receptor for chemokines) gene encodes a membrane-bound chemokine receptor crucial for the infection of red blood cells by Plasmodium vivax, a major causative agent of malaria. Of the three major allelic classes segregating in human populations, the FY*O allele has been shown to protect against P. vivax infection and is at near fixation in sub-Saharan Africa, while FY*B and FY*A are common in Europe and Asia, respectively. Due to the combination of strong geographic differentiation and association with malaria resistance, DARC is considered a canonical example of positive selection in humans. Despite this, details of the timing and mode of selection at DARC remain poorly understood. Here, we use sequencing data from over 1,000 individuals in twenty-one human populations, as well as ancient human genomes, to perform a fine-scale investigation of the evolutionary history of DARC. We estimate the time to most recent common ancestor (TMRCA) of the most common FY*O haplotype to be 42 kya (95% CI: 34-49 kya). We infer the FY*O null mutation swept to fixation in Africa from standing variation with very low initial frequency (0.1%) and a selection coefficient of 0.043 (95% CI:0.011-0.18), which is among the strongest estimated in the human genome. We estimate the TMRCA of the FY*A mutation in non-Africans to be 57 kya (95% CI: 48-65 kya) and infer that, prior to the sweep of FY*O, all three alleles were segregating in Africa, as highly diverged populations from Asia and ≠Khomani San hunter-gatherers share the same FY*A haplotypes. We test multiple models of admixture that may account for this observation and reject recent Asian or European admixture as the cause.

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

The availability of large-scale population genomic sequence data has resulted in an explosion in efforts to infer the demographic histories of natural populations across a broad range of organisms. As demographic events alter coalescent genealogies, they leave detectable signatures in patterns of genetic variation within and between populations. Accordingly, a variety of approaches have been designed to leverage population genetic data to uncover the footprints of demographic change in the genome. The vast majority of these methods make the simplifying assumption that the measures of genetic variation used as their input are unaffected by natural selection. However, natural selection can dramatically skew patterns of variation not only at selected sites, but at linked, neutral loci as well. Here we assess the impact of recent positive selection on demographic inference by characterizing the performance of three popular methods through extensive simulation of data sets with varying numbers of linked selective sweeps. In particular, we examined three different demographic models relevant to a number of species, finding that positive selection can bias parameter estimates of each of these models-often severely. We find that selection can lead to incorrect inferences of population size changes when none have occurred. Moreover, we show that linked selection can lead to incorrect demographic model selection, when multiple demographic scenarios are compared. We argue that natural populations may experience the amount of recent positive selection required to skew inferences. These results suggest that demographic studies conducted in many species to date may have exaggerated the extent and frequency of population size changes.

On the performance of tests for the detection of signatures of selection: a case study with the Spanish autochthonous beef cattle populations

Background

Procedures for the detection of signatures of selection can be classified according to the source of information they use to reject the null hypothesis of absence of selection. Three main groups of tests can be identified that are based on: (1) the analysis of the site frequency spectrum, (2) the study of the extension of the linkage disequilibrium across the length of the haplotypes that surround the polymorphism, and (3) the differentiation among populations. The aim of this study was to compare the performance of a subset of these procedures by using a dataset on seven Spanish autochthonous beef cattle populations.

Results

Analysis of the correlations between the logarithms of the statistics that were obtained by 11 tests for detecting signatures of selection at each single nucleotide polymorphism confirmed that they can be clustered into the three main groups mentioned above. A factor analysis summarized the results of the 11 tests into three canonical axes that were each associated with one of the three groups. Moreover, the signatures of selection identified with the first and second groups of tests were shared across populations, whereas those with the third group were more breed-specific. Nevertheless, an enrichment analysis identified the metabolic pathways that were associated with each group; they coincided with canonical axes and were related to immune response, muscle development, protein biosynthesis, skin and pigmentation, glucose metabolism, fat metabolism, embryogenesis and morphology, heart and uterine metabolism, regulation of the hypothalamic–pituitary–thyroid axis, hormonal, cellular cycle, cell signaling and extracellular receptors.

Conclusions

We show that the results of the procedures used to identify signals of selection differed substantially between the three groups of tests. However, they can be classified using a factor analysis. Moreover, each canonical factor that coincided with a group of tests identified different signals of selection, which could be attributed to processes of selection that occurred at different evolutionary times. Nevertheless, the metabolic pathways that were associated with each group of tests were similar, which suggests that the selection events that occurred during the evolutionary history of the populations probably affected the same group of traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0258-1) contains supplementary material, which is available to authorized users.

Weak Polygenic Selection Drives the Rapid Adaptation of the Chemosensory System: Lessons from the Upstream Regions of the Major Gene Families

The animal chemosensory system is involved in essential biological processes, most of them mediated by proteins encoded in multigene families. These multigene families have been fundamental for the adaptation to new environments, significantly contributing to phenotypic variation. This adaptive potential contrasts, however, with the lack of studies at their upstream regions, especially taking into account the evidence linking their transcriptional changes to certain phenotypic effects. Here, we explicitly characterize the contribution of the upstream sequences of the major chemosensory gene families to rapid adaptive processes. For that, we analyze the genome sequences of 158 lines from a population of Drosophila melanogaster that recently colonized North America, and integrate functional and transcriptional data available for this species. We find that both, strong negative and strong positive selection, shape transcriptional evolution at the genome-wide level. The chemosensory upstream regions, however, exhibit a distinctive adaptive landscape, including multiple mutations of small beneficial effect and a reduced number of cis-regulatory elements. Together, our results suggest that the promiscuous and partially redundant transcription and function of the chemosensory genes provide evolutionarily opportunities for rapid adaptive episodes through weak polygenic selection.

Genetics on the Fly: A Primer on the Drosophila Model System

Fruit flies of the genus Drosophila have been an attractive and effective genetic model organism since Thomas Hunt Morgan and colleagues made seminal discoveries with them a century ago. Work with Drosophila has enabled dramatic advances in cell and developmental biology, neurobiology and behavior, molecular biology, evolutionary and population genetics, and other fields. With more tissue types and observable behaviors than in other short-generation model organisms, and with vast genome data available for many species within the genus, the fly's tractable complexity will continue to enable exciting opportunities to explore mechanisms of complex developmental programs, behaviors, and broader evolutionary questions. This primer describes the organism's natural history, the features of sequenced genomes within the genus, the wide range of available genetic tools and online resources, the types of biological questions Drosophila can help address, and historical milestones.

Multiple Independent Retroelement Insertions in the Promoter of a Stress Response Gene Have Variable Molecular and Functional Effects in Drosophila

Promoters are structurally and functionally diverse gene regulatory regions. The presence or absence of sequence motifs and the spacing between the motifs defines the properties of promoters. Recent alternative promoter usage analyses in Drosophila melanogaster revealed that transposable elements significantly contribute to promote diversity. In this work, we analyzed in detail one of the transposable element insertions, named FBti0019985, that has been co-opted to drive expression of CG18446, a candidate stress response gene. We analyzed strains from different natural populations and we found that besides FBti0019985, there are another eight independent transposable elements inserted in the proximal promoter region of CG18446. All nine insertions are solo-LTRs that belong to the roo family. We analyzed the sequence of the nine roo insertions and we investigated whether the different insertions were functionally equivalent by performing 5'-RACE, gene expression, and cold-stress survival experiments. We found that different insertions have different molecular and functional consequences. The exact position where the transposable elements are inserted matters, as they all showed highly conserved sequences but only two of the analyzed insertions provided alternative transcription start sites, and only the FBti0019985 insertion consistently affects CG18446 expression. The phenotypic consequences of the different insertions also vary: only FBti0019985 was associated with cold-stress tolerance. Interestingly, the only previous report of transposable elements inserting repeatedly and independently in a promoter region in D. melanogaster, were also located upstream of a stress response gene. Our results suggest that functional validation of individual structural variants is needed to resolve the complexity of insertion clusters.

Genomic and Transcriptomic Associations Identify a New Insecticide Resistance Phenotype for the Selective Sweep at the Cyp6g1 Locus of Drosophila melanogaster

Scans of the Drosophila melanogaster genome have identified organophosphate resistance loci among those with the most pronounced signature of positive selection. In this study, the molecular basis of resistance to the organophosphate insecticide azinphos-methyl was investigated using the Drosophila Genetic Reference Panel, and genome-wide association. Recently released full transcriptome data were used to extend the utility of the Drosophila Genetic Reference Panel resource beyond traditional genome-wide association studies to allow systems genetics analyses of phenotypes. We found that both genomic and transcriptomic associations independently identified Cyp6g1, a gene involved in resistance to DDT and neonicotinoid insecticides, as the top candidate for azinphos-methyl resistance. This was verified by transgenically overexpressing Cyp6g1 using natural regulatory elements from a resistant allele, resulting in a 6.5-fold increase in resistance. We also identified four novel candidate genes associated with azinphos-methyl resistance, all of which are involved in either regulation of fat storage, or nervous system development. In Cyp6g1, we find a demonstrable resistance locus, a verification that transcriptome data can be used to identify variants associated with insecticide resistance, and an overlap between peaks of a genome-wide association study, and a genome-wide selective sweep analysis.

A Genomic Map of the Effects of Linked Selection in Drosophila

Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of "linked selection" on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from 125 lines in Drosophila melanogaster and reliably predict diversity levels at the 1Mb scale. Our results corroborate estimates of a high fraction of beneficial substitutions in proteins and untranslated regions (UTR). They allow us to distinguish between the contribution of sweeps and other modes of selection around amino acid substitutions and to uncover evidence for pervasive sweeps in untranslated regions (UTRs). Our inference further suggests a substantial effect of other modes of linked selection and of adaptation in particular. More generally, we demonstrate that linked selection has had a larger effect in reducing diversity levels and increasing their variance in D. melanogaster than previously appreciated.

PReFerSim: fast simulation of demography and selection under the Poisson Random Field model

The Poisson Random Field (PRF) model has become an important tool in population genetics to study weakly deleterious genetic variation under complicated demographic scenarios. Currently, there are no freely available software applications that allow simulation of genetic variation data under this model. Here we present PReFerSim, an ANSI C program that performs forward simulations under the PRF model. PReFerSim models changes in population size, arbitrary amounts of inbreeding, dominance and distributions of selective effects. Users can track summaries of genetic variation over time and output trajectories of selected alleles.

AVAILABILITY AND IMPLEMENTATION

PReFerSim is freely available at: https://github.com/LohmuellerLab/PReFerSim CONTACT: klohmueller@ucla.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Recent demography drives changes in linked selection across the maize genome

Genetic diversity is shaped by the interaction of drift and selection, but the details of this interaction are not well understood. The impact of genetic drift in a population is largely determined by its demographic history, typically summarized by its long-term effective population size (Ne). Rapidly changing population demographics complicate this relationship, however. To better understand how changing demography impacts selection, we used whole-genome sequencing data to investigate patterns of linked selection in domesticated and wild maize (teosinte). We produce the first whole-genome estimate of the demography of maize domestication, showing that maize was reduced to approximately 5% the population size of teosinte before it experienced rapid expansion post-domestication to population sizes much larger than its ancestor. Evaluation of patterns of nucleotide diversity in and near genes shows little evidence of selection on beneficial amino acid substitutions, and that the domestication bottleneck led to a decline in the efficiency of purifying selection in maize. Young alleles, however, show evidence of much stronger purifying selection in maize, reflecting the much larger effective size of present day populations. Our results demonstrate that recent demographic change-a hall-mark of many species including both humans and crops-can have immediate and wide-ranging impacts on diversity that conflict with expectations based on long-term Ne alone.

Evaluating the performance of selection scans to detect selective sweeps in domestic dogs

Selective breeding of dogs has resulted in repeated artificial selection on breed-specific morphological phenotypes. A number of quantitative trait loci associated with these phenotypes have been identified in genetic mapping studies. We analysed the population genomic signatures observed around the causal mutations for 12 of these loci in 25 dog breeds, for which we genotyped 25 individuals in each breed. By measuring the population frequencies of the causal mutations in each breed, we identified those breeds in which specific mutations most likely experienced positive selection. These instances were then used as positive controls for assessing the performance of popular statistics to detect selection from population genomic data. We found that artificial selection during dog domestication has left characteristic signatures in the haplotype and nucleotide polymorphism patterns around selected loci that can be detected in the genotype data from a single population sample. However, the sensitivity and accuracy at which such signatures were detected varied widely between loci, the particular statistic used and the choice of analysis parameters. We observed examples of both hard and soft selective sweeps and detected strong selective events that removed genetic diversity almost entirely over regions >10 Mbp. Our study demonstrates the power and limitations of selection scans in populations with high levels of linkage disequilibrium due to severe founder effects and recent population bottlenecks.

Elevated Linkage Disequilibrium and Signatures of Soft Sweeps Are Common in Drosophila melanogaster

The extent to which selection and demography impact patterns of genetic diversity in natural populations of Drosophila melanogaster is yet to be fully understood. We previously observed that linkage disequilibrium (LD) at scales of ∼10 kb in the Drosophila Genetic Reference Panel (DGRP), consisting of 145 inbred strains from Raleigh, North Carolina, measured both between pairs of sites and as haplotype homozygosity, is elevated above neutral demographic expectations. We also demonstrated that signatures of strong and recent soft sweeps are abundant. However, the extent to which these patterns are specific to this derived and admixed population is unknown. It is also unclear whether these patterns are a consequence of the extensive inbreeding performed to generate the DGRP data. Here we analyze LD statistics in a sample of >100 fully-sequenced strains from Zambia; an ancestral population to the Raleigh population that has experienced little to no admixture and was generated by sequencing haploid embryos rather than inbred strains. We find an elevation in long-range LD and haplotype homozygosity compared to neutral expectations in the Zambian sample, thus showing the elevation in LD is not specific to the DGRP data set. This elevation in LD and haplotype structure remains even after controlling for possible confounders including genomic inversions, admixture, population substructure, close relatedness of individual strains, and recombination rate variation. Furthermore, signatures of partial soft sweeps similar to those found in the DGRP as well as partial hard sweeps are common in Zambia. These results suggest that while the selective forces and sources of adaptive mutations may differ in Zambia and Raleigh, elevated long-range LD and signatures of soft sweeps are generic in D. melanogaster.

Recurrent specialization on a toxic fruit in an island Drosophila population

Recurrent specialization on similar host plants offers a unique opportunity to unravel the evolutionary and genetic mechanisms underlying dietary shifts. Recent studies have focused on ecological races belonging to the same species, but it is hard in many cases to untangle the role of adaptive introgression versus distinct mutations in facilitating recurrent evolution. We discovered on the island of Mayotte a population of the generalist fly Drosophila yakuba that is strictly associated with noni (Morinda citrifolia). This case strongly resembles Drosophila sechellia, a genetically isolated insular relative of D. yakuba whose intensely studied specialization on toxic noni fruits has always been considered a unique event in insect evolution. Experiments revealed that unlike mainland D. yakuba strains, Mayotte flies showed strong olfactory attraction and significant toxin tolerance to noni. Island females strongly discriminated against mainland males, suggesting that dietary adaptation has been accompanied by partial reproductive isolation. Population genomic analysis indicated a recent colonization (∼29 kya), at a time when year-round noni fruits may have presented a predictable resource on the small island, with ongoing migration after colonization. This relatively recent time scale allowed us to search for putatively adaptive loci based on genetic variation. Strong signals of genetic differentiation were found for several detoxification genes, including a major toxin tolerance locus in D. sechellia Our results suggest that recurrent evolution on a toxic resource can involve similar historical events and common genetic bases, and they establish an important genetic system for the study of early stages of ecological specialization and speciation.

Rapid genomic changes in Drosophila melanogaster adapting to desiccation stress in an experimental evolution system

BACKGROUND

Experimental evolution studies, coupled with whole genome resequencing and advances in bioinformatics, have become a powerful tool for exploring how populations respond to selection at the genome-wide level, complementary to genome-wide association studies (GWASs) and linkage mapping experiments as strategies to connect genotype and phenotype. In this experiment, we analyzed genomes of Drosophila melanogaster from lines evolving under long-term directional selection for increased desiccation resistance in comparison with control (no-selection) lines.

RESULTS

We demonstrate that adaptive responses to desiccation stress have exerted extensive footprints on the genomes, manifested through a high degree of fixation of alleles in surrounding neighborhoods of eroded heterozygosity. These patterns were highly convergent across replicates, consistent with signatures of 'soft' selective sweeps, where multiple alleles present as standing genetic variation become beneficial and sweep through the replicate populations at the same time. Albeit much less frequent, we also observed line-unique sweep regions with zero or near-zero heterozygosity, consistent with classic, or 'hard', sweeps, where novel rather than pre-existing adaptive mutations may have been driven to fixation. Genes responsible for cuticle and protein deubiquitination seemed to be central to these selective sweeps. High divergence within coding sequences between selected and control lines was also reflected by significant results of the McDonald-Kreitman and Ka/Ks tests, showing that as many as 347 genes may have been under positive selection.

CONCLUSIONS

Desiccation stress, a common challenge to many organisms inhabiting dry environments, proves to be a very potent selecting factor having a big impact on genome diversity.