Natural selection in the water: freshwater invasion and adaptation by water colour in the Amazonian pufferfish

Natural selection and ecological adaptation are ultimately responsible for much of the origin of biodiversity. Yet, the identification of divergent natural selection has been hindered by the spatial complexity of natural systems, the difficulty in identifying genes under selection and their relationship to environment, and the confounding genomic effects of time. Here, we employed genome scans, population genetics and sequence-based phylogeographic methods to identify divergent natural selection on population boundaries in a freshwater invader, the Amazonian pufferfish, Colomesus asellus. We sampled extensively across markedly different hydrochemical settings in the Amazon Basin and use 'water colour' to test for ecological isolation. We distinguish the relative contribution of natural selection across hydrochemical gradients from biogeographic history in the origin and maintenance of population boundaries within a single species and across a complex ecosystem. We show that spatially distinct population structure generated by multiple forces (i.e. water colour and vicariant biogeographic history) can be identified if the confounding effects of genetic drift have not accumulated between selective populations. Our findings have repercussions for studies aimed at identifying engines of biodiversity and assessing their temporal progression in understudied and ecologically complex tropical ecosystems.     

Disentangling the effects of demography and selection in human history

Demographic events affect all genes in a genome, whereas natural selection has only local effects. Using publicly available data from 151 loci sequenced in both European-American and African-American populations, we attempt to distinguish the effects of demography and selection. To analyze large sets of population genetic data such as this one, we introduce "Perlymorphism," a Unix-based suite of analysis tools. Our analyses show that the demographic histories of human populations can account for a large proportion of effects on the level and frequency of variation across the genome. The African-American population shows both a higher level of nucleotide diversity and more negative values of Tajima's D statistic than does a European-American population. Using coalescent simulations, we show that the significantly negative values of the D statistic in African-Americans and the positive values in European-Americans are well explained by relatively simple models of population admixture and bottleneck, respectively. Working within these nonequilibrium frameworks, we are still able to show deviations from neutral expectations at a number of loci, including ABO and TRPV6. In addition, we show that the frequency spectrum of mutations--corrected for levels of polymorphism--is correlated with recombination rate only in European-Americans. These results are consistent with repeated selective sweeps in non-African populations, in agreement with recent reports using microsatellite data.     

Nuclear gene genealogies reveal historical,demographic and selective factors associated with speciation in field crickets

Population genetics theory predicts that genetic drift should eliminate shared polymorphism, leading to monophyly or exclusivity of populations, when the elapsed time between lineage-splitting events is large relative to effective population size. We examined patterns of nucleotide variation in introns at four nuclear loci to relate processes affecting the history of genes to patterns of divergence among natural populations and species. Ancestral polymorphisms were shared among three recognized species, Gryllus firmus, G. pennsylvanicus, and G. ovisopis, and genealogical patterns suggest that successive speciation events occurred recently and rapidly relative to effective population size. High levels of shared polymorphism among these morphologically, behaviorally, and ecologically distinct species indicate that only a small fraction of the genome needs to become differentiated for speciation to occur. Among the four nuclear gene loci there was a 10-fold range in nucleotide diversity, and patterns of polymorphism and divergence suggest that natural selection has acted to maintain or eliminate variation at some loci. While nuclear gene genealogies may have limited applications in phylogeography or other approaches dependent on population monophyly, they provide important insights into the historical, demographic, and selective forces that shape speciation.     

Population Genomic Analysis Reveals a Rich Speciation and Demographic History of Orang-utans (Pongo pygmaeus and Pongo abelii)

To gain insights into evolutionary forces that have shaped the history of Bornean and Sumatran populations of orang-utans, we compare patterns of variation across more than 11 million single nucleotide polymorphisms found by previous mitochondrial and autosomal genome sequencing of 10 wild-caught orang-utans. Our analysis of the mitochondrial data yields a far more ancient split time between the two populations (∼3.4 million years ago) than estimates based on autosomal data (0.4 million years ago), suggesting a complex speciation process with moderate levels of primarily male migration. We find that the distribution of selection coefficients consistent with the observed frequency spectrum of autosomal non-synonymous polymorphisms in orang-utans is similar to the distribution in humans. Our analysis indicates that 35% of genes have evolved under detectable negative selection. Overall, our findings suggest that purifying natural selection, genetic drift, and a complex demographic history are the dominant drivers of genome evolution for the two orang-utan populations.     

Inferring population history and demography using microsatellites, mitochondrial DNA, and major histocompatibility complex (MHC) genes

Microsatellites and mitochondrial DNA (mtDNA) have traditionally been used in population genetics because of their variability and presumed neutrality, whereas genes of the major histocompatibility complex (MHC) are increasingly of interest because strong selective pressures shape their standing variation. Despite the potential for MHC genes, microsatellites, and mtDNA sequences to complement one another in deciphering population history and demography, the three are rarely used in tandem. Here we report on MHC, microsatellite, and mtDNA variability in a single large population of the eastern tiger salamander (Ambystoma tigrinum tigrinum). We use the mtDNA mismatch distribution and, on microsatellite data, the imbalance index and bottleneck tests to infer aspects of population history and demography. Haplotype and allelic variation was high at all loci surveyed, and heterozygosity was high at the nuclear loci. We find concordance among neutral molecular markers that suggests our study population originated from post-Pleistocene expansions of multiple, fragmented sources that shared few migrants. Differences in N(e) estimates derived from haploid and diploid genetic markers are potentially attributable to secondary contact among source populations that experienced rapid mtDNA divergence and comparatively low levels of nuclear DNA divergence. We find strong evidence of natural selection acting on MHC genes and estimate long-term effective population sizes (N(e)) that are very large, making small selection intensities significant evolutionary forces in this population.     

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

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

Impact of demography on linked selection in two outcrossing Brassicaceae species

Genetic diversity is shaped by mutation, genetic drift, gene flow, recombination, and selection. The dynamics and interactions of these forces shape genetic diversity across different parts of the genome, between populations and species. Here, we have studied the effects of linked selection on nucleotide diversity in outcrossing populations of two Brassicaceae species, Arabidopsis lyrata and Capsella grandiflora, with contrasting demographic history. In agreement with previous estimates, we found evidence for a modest population size expansion thousands of generations ago, as well as efficient purifying selection in C. grandiflora. In contrast, the A. lyrata population exhibited evidence for very recent strong population size decline and weaker efficacy of purifying selection. Using multiple regression analyses with recombination rate and other genomic covariates as explanatory variables, we can explain 47% of the variance in neutral diversity in the C. grandiflora population, while in the A. lyrata population, only 11% of the variance was explained by the model. Recombination rate had a significant positive effect on neutral diversity in both species, suggesting that selection at linked sites has an effect on patterns of neutral variation. In line with this finding, we also found reduced neutral diversity in the vicinity of genes in the C. grandiflora population. However, in A. lyrata no such reduction in diversity was evident, a finding that is consistent with expectations of the impact of a recent bottleneck on patterns of neutral diversity near genes. This study thus empirically demonstrates how differences in demographic history modulate the impact of selection at linked sites in natural populations.     

A hierarchical Bayesian model for next-generation population genomics

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

The Counteracting Effects of Demography on Functional Genomic Variation: The Roma Paradigm

Demographic history plays a major role in shaping the distribution of genomic variation. Yet the interaction between different demographic forces and their effects in the genomes is not fully resolved in human populations. Here, we focus on the Roma population, the largest transnational ethnic minority in Europe. They have a South Asian origin and their demographic history is characterized by recent dispersals, multiple founder events, and extensive gene flow from non-Roma groups. Through the analyses of new high-coverage whole exome sequences and genome-wide array data for 89 Iberian Roma individuals together with forward simulations, we show that founder effects have reduced their genetic diversity and proportion of rare variants, gene flow has counteracted the increase in mutational load, runs of homozygosity show ancestry-specific patterns of accumulation of deleterious homozygotes, and selection signals primarily derive from preadmixture adaptation in the Roma population sources. The present study shows how two demographic forces, bottlenecks and admixture, act in opposite directions and have long-term balancing effects on the Roma genomes. Understanding how demography and gene flow shape the genome of an admixed population provides an opportunity to elucidate how genomic variation is modeled in human populations.     

Fractional populations in multiple gene inheritance

MOTIVATION: With complete knowledge of the human genome sequence, one of the most interesting tasks remaining is to understand the functions of individual genes and how they communicate. Using the information about genes (locus, allele, mutation rate, fitness, etc.), we attempt to explain population demographic data. This population evolution study could complement and enhance biologists' understanding about genes. RESULTS: We present a general approach to study population genetics in complex situations. In the present approach, multiple allele inheritance, multiple loci inheritance, natural selection and mutations are allowed simultaneously in order to consider a more realistic situation. A simulation program is presented so that readers can readily carry out studies with their own parameters. It is shown that the multiplicity of the loci greatly affects the demographic results of fractional population ratios. Furthermore, the study indicates that some high infant mortality rates due to congenital anomalies can be attributed to multiple loci inheritance. AVAILABILITY: The simulation program can be downloaded from http://won.hongik.ac.kr/~mhchung/index_files/yapop.htm. In order to run this program, one needs Visual Studio.NET platform, which can be downloaded from http://msdn.microsoft.com/netframework/downloads/default.asp.     

Duplication and population dynamics shape historic patterns of selection and genetic variation at the major histocompatibility complex in rodents

Genetic variation at the major histocompatibility complex (MHC) is vitally important for wildlife populations to respond to pathogen threats. As natural populations can fluctuate greatly in size, a key issue concerns how population cycles and bottlenecks that could reduce genetic diversity will influence MHC genes. Using 454 sequencing, we characterized genetic diversity at the DRB Class II locus in montane voles (Microtus montanus), a North American rodent that regularly undergoes high‐amplitude fluctuations in population size. We tested for evidence of historic balancing selection, recombination, and gene duplication to identify mechanisms maintaining allelic diversity. Counter to our expectations, we found strong evidence of purifying selection acting on the DRB locus in montane voles. We speculate that the interplay between population fluctuations and gene duplication might be responsible for the weak evidence of historic balancing selection and strong evidence of purifying selection detected. To further explore this idea, we conducted a phylogenetically controlled comparative analysis across 16 rodent species with varying demographic histories and MHC duplication events (based on the maximum number of alleles detected per individual). On the basis of phylogenetic generalized linear model‐averaging, we found evidence that the estimated number of duplicated loci was positively related to allelic diversity and, surprisingly, to the strength of purifying selection at the DRB locus. Our analyses also revealed that species that had undergone population bottlenecks had lower allelic richness than stable species. This study highlights the need to consider demographic history and genetic structure alongside patterns of natural selection to understand resulting patterns of genetic variation at the MHC.     

Assessing the evolutionary impact of amino acid mutations in the human genome

Quantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population with non-stationary demographic history (such as that of modern humans). Application of our method to 47,576 coding SNPs found by direct resequencing of 11,404 protein coding-genes in 35 individuals (20 European Americans and 15 African Americans) allows us to assess the relative contribution of demographic and selective effects to patterning amino acid variation in the human genome. We find evidence of an ancient population expansion in the sample with African ancestry and a relatively recent bottleneck in the sample with European ancestry. After accounting for these demographic effects, we find strong evidence for great variability in the selective effects of new amino acid replacing mutations. In both populations, the patterns of variation are consistent with a leptokurtic distribution of selection coefficients (e.g., gamma or log-normal) peaked near neutrality. Specifically, we predict 27–29% of amino acid changing (nonsynonymous) mutations are neutral or nearly neutral (|s|<0.01%), 30–42% are moderately deleterious (0.01%<|s|<1%), and nearly all the remainder are highly deleterious or lethal (|s|>1%). Our results are consistent with 10–20% of amino acid differences between humans and chimpanzees having been fixed by positive selection with the remainder of differences being neutral or nearly neutral. Our analysis also predicts that many of the alleles identified via whole-genome association mapping may be selectively neutral or (formerly) positively selected, implying that deleterious genetic variation affecting disease phenotype may be missed by this widely used approach for mapping genes underlying complex traits.     

Alzheimer disease susceptibility loci: evidence for a protein network under natural selection

Recent genome-wide association studies have identified a number of susceptibility loci for Alzheimer disease (AD). To understand the functional consequences and potential interactions of the associated loci, we explored large-scale data sets interrogating the human genome for evidence of positive natural selection. Our findings provide significant evidence for signatures of recent positive selection acting on several haplotypes carrying AD susceptibility alleles; interestingly, the genes found in these selected haplotypes can be assembled, independently, into a molecular complex via a protein-protein interaction (PPI) network approach. These results suggest a possible coevolution of genes encoding physically-interacting proteins that underlie AD susceptibility and are coexpressed in different tissues. In particular, PICALM, BIN1, CD2AP, and EPHA1 are interconnected through multiple interacting proteins and appear to have coordinated evidence of selection in the same human population, suggesting that they may be involved in the execution of a shared molecular function. This observation may be AD-specific, as the 12 loci associated with Parkinson disease do not demonstrate excess evidence of natural selection. The context for selection is probably unrelated to AD itself; it is likely that these genes interact in another context, such as in immune cells, where we observe cis-regulatory effects at several of the selected AD loci.     

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

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

DNA水平上检测正选择方法的研究进展

达尔文的自然选择学说指出, 自然选择作用是物种进化的主要因素。而1968年Kimura提出的中性进化学说认为中性突变和随机漂变才是进化的主要动力。在接下来的30多年时间中, 人们尝试从各种角度来检测自然选择是否存在。随着DNA测序技术的发展, 大量的DNA序列信息为检验自然选择提供了丰富的数据。因为自然选择会影响DNA变异模式, 所以可以通过分析现有的DNA样本来推断过去是否发生了自然选择。另一方面, 种群历史等因素也会影响到DNA变异模式, 因此会对自然选择的检测产生干扰。文章主要介绍了中性检验基本的概念, 全面回顾了一些经典的检验方法, 并着重介绍了近几年新发展出的研究方向。     

Signatures of demographic history and natural selection in the human major histocompatibility complex Loci

Many lines of evidence show that several HLA loci have experienced balancing selection. However, distinguishing among demographic and selective explanations for patterns of variation observed with HLA genes remains a challenge. In this study we address this issue using data from a diverse set of human populations at six classical HLA loci and, employing a comparative genomics approach, contrast results for HLA loci to those for non-HLA markers. Using a variety of analytic methods, we confirm and extend evidence for selection acting on several HLA loci. We find that allele frequency distributions for four of the six HLA loci deviate from neutral expectations and show that this is unlikely to be explained solely by demographic factors. Other features of HLA variation are explained in part by demographic history, including decreased heterozygosity and increased LD for populations at greater distances from Africa and a similar apportionment of genetic variation for HLA loci compared to putatively neutral non-HLA loci. On the basis of contrasts among different HLA loci and between HLA and non-HLA loci, we conclude that HLA loci bear detectable signatures of both natural selection and demographic history.     

Localizing recent adaptive evolution in the human genome

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

Genome-wide scans provide evidence for positive selection of genes implicated in Lassa fever

Rapidly evolving viruses and other pathogens can have an immense impact on human evolution as natural selection acts to increase the prevalence of genetic variants providing resistance to disease. With the emergence of large datasets of human genetic variation, we can search for signatures of natural selection in the human genome driven by such disease-causing microorganisms. Based on this approach, we have previously hypothesized that Lassa virus (LASV) may have been a driver of natural selection in West African populations where Lassa haemorrhagic fever is endemic. In this study, we provide further evidence for this notion. By applying tests for selection to genome-wide data from the International Haplotype Map Consortium and the 1000 Genomes Consortium, we demonstrate evidence for positive selection in LARGE and interleukin 21 (IL21), two genes implicated in LASV infectivity and immunity. We further localized the signals of selection, using the recently developed composite of multiple signals method, to introns and putative regulatory regions of those genes. Our results suggest that natural selection may have targeted variants giving rise to alternative splicing or differential gene expression of LARGE and IL21. Overall, our study supports the hypothesis that selective pressures imposed by LASV may have led to the emergence of particular alleles conferring resistance to Lassa fever, and opens up new avenues of research pursuit.     

Sex-biased evolutionary forces shape genomic patterns of human diversity

Comparisons of levels of variability on the autosomes and X chromosome can be used to test hypotheses about factors influencing patterns of genomic variation. While a tremendous amount of nucleotide sequence data from across the genome is now available for multiple human populations, there has been no systematic effort to examine relative levels of neutral polymorphism on the X chromosome versus autosomes. We analyzed ~210 kb of DNA sequencing data representing 40 independent noncoding regions on the autosomes and X chromosome from each of 90 humans from six geographically diverse populations. We correct for differences in mutation rates between males and females by considering the ratio of within-human diversity to human-orangutan divergence. We find that relative levels of genetic variation are higher than expected on the X chromosome in all six human populations. We test a number of alternative hypotheses to explain the excess polymorphism on the X chromosome, including models of background selection, changes in population size, and sex-specific migration in a structured population. While each of these processes may have a small effect on the relative ratio of X-linked to autosomal diversity, our results point to a systematic difference between the sexes in the variance in reproductive success; namely, the widespread effects of polygyny in human populations. We conclude that factors leading to a lower male versus female effective population size must be considered as important demographic variables in efforts to construct models of human demographic history and for understanding the forces shaping patterns of human genomic variability.     

Deep Learning for Population Genetic Inference

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.