Constructing genomic maps of positive selection in humans: where do we go from here?

A genome-wide perspective of human diversity and its implications in infectious disease

Progress in genomic technologies, such as DNA arrays and next-generation sequencing, is allowing systematic characterization of the degree of human genetic variation at the scale of individual genomes. Public efforts, such as the International HapMap Project and the 1000 Genomes Project, have provided a realistic picture of the levels of genetic diversity in individuals and populations. These genomic techniques are also making it possible to evaluate the contribution of host genetic diversity to differences in susceptibility to both rare and common infectious diseases. Recent studies have revealed the power of whole-exome sequencing for dissecting the immunological mechanisms underlying the pathogenesis of severe, rare infectious diseases. Likewise, genome-wide association studies on common viral, bacterial, and parasitic infections have shed light on the host genetic basis of susceptibility to infectious diseases and, in some cases, of disease progression and drug responses.

Outlier Loci and Selection Signatures of Simple Sequence Repeats (SSRs) in Flax (Linum usitatissimum L.)

Genomic microsatellites (gSSRs) and expressed sequence tag-derived SSRs (EST-SSRs) have gained wide application for elucidating genetic diversity and population structure in plants. Both marker systems are assumed to be selectively neutral when making demographic inferences, but this assumption is rarely tested. In this study, three neutrality tests were assessed for identifying outlier loci among 150 SSRs (85 gSSRs and 65 EST-SSRs) that likely influence estimates of population structure in three differentiated flax sub-populations (F_ST = 0.19). Moreover, the utility of gSSRs, EST-SSRs, and the combined sets of SSRs was also evaluated in assessing genetic diversity and population structure in flax. Six outlier loci were identified by at least two neutrality tests showing footprints of balancing selection. After removing the outlier loci, the STRUCTURE analysis and the dendrogram topology of EST-SSRs improved. Conversely, gSSRs and combined SSRs results did not change significantly, possibly as a consequence of the higher number of neutral loci assessed. Taken together, the genetic structure analyses established the superiority of gSSRs to determine the genetic relationships among flax accessions, although the combined SSRs produced the best results. Genetic diversity parameters did not differ statistically (P > 0.05) between gSSRs and EST-SSRs, an observation partially explained by the similar number of repeat motifs. Our study provides new insights into the ability of gSSRs and EST-SSRs to measure genetic diversity and structure in flax and confirms the importance of testing for the occurrence of outlier loci to properly assess natural and breeding populations, particularly in studies considering only few loci.

Positive selection in the chromosome 16 VKORC1 genomic region has contributed to the variability of anticoagulant response in humans

VKORC1 (vitamin K epoxide reductase complex subunit 1, 16p11.2) is the main genetic determinant of human response to oral anticoagulants of antivitamin K type (AVK). This gene was recently suggested to be a putative target of positive selection in East Asian populations. In this study, we genotyped the HGDP-CEPH Panel for six VKORC1 SNPs and downloaded chromosome 16 genotypes from the HGDP-CEPH database in order to characterize the geographic distribution of footprints of positive selection within and around this locus. A unique VKORC1 haplotype carrying the promoter mutation associated with AVK sensitivity showed especially high frequencies in all the 17 HGDP-CEPH East Asian population samples. VKORC1 and 24 neighboring genes were found to lie in a 505 kb region of strong linkage disequilibrium in these populations. Patterns of allele frequency differentiation and haplotype structure suggest that this genomic region has been submitted to a near complete selective sweep in all East Asian populations and only in this geographic area. The most extreme scores of the different selection tests are found within a smaller 45 kb region that contains VKORC1 and three other genes (BCKDK, MYST1 (KAT8), and PRSS8) with different functions. Because of the strong linkage disequilibrium, it is not possible to determine if VKORC1 or one of the three other genes is the target of this strong positive selection that could explain present-day differences among human populations in AVK dose requirement. Our results show that the extended region surrounding a presumable single target of positive selection should be analyzed for genetic variation in a wide range of genetically diverse populations in order to account for other neighboring and confounding selective events and the hitchhiking effect.

Screen for Footprints of Selection during Domestication/Captive Breeding of Atlantic Salmon

Domesticated animals provide a unique opportunity to identify genomic targets of artificial selection to the captive environment. Here, we screened three independent domesticated/captive Atlantic salmon (Salmo salar) strains and their wild progenitor populations in an effort to detect potential signals of domestication selection by typing of 261 SNPs and 70 microsatellite loci. By combining information from four different neutrality tests, in total ten genomic regions showed signs of directional selection based on multiple sources of evidence. Most of the identified candidate regions were rather small ranging from zero to a few centimorgans (cM) in the female Atlantic salmon linkage map. We also evaluated how adaptation from standing variation affects adjacent SNP and microsatellite variation along the chromosomes and, by using forward simulations with strong selection, we were able to generate genetic differentiation patterns comparable to the observed data. This study highlights the significance of standing genetic variation during the early stages of adaptation and represents a useful step towards identifying functional variants involved in domestication of Atlantic salmon.

Genetic diversity and the structure of genealogies in rapidly adapting populations

Positive selection distorts the structure of genealogies and hence alters patterns of genetic variation within a population. Most analyses of these distortions focus on the signatures of hitchhiking due to hard or soft selective sweeps at a single genetic locus. However, in linked regions of rapidly adapting genomes, multiple beneficial mutations at different loci can segregate simultaneously within the population, an effect known as clonal interference. This leads to a subtle interplay between hitchhiking and interference effects, which leads to a unique signature of rapid adaptation on genetic variation both at the selected sites and at linked neutral loci. Here, we introduce an effective coalescent theory (a "fitness-class coalescent") that describes how positive selection at many perfectly linked sites alters the structure of genealogies. We use this theory to calculate several simple statistics describing genetic variation within a rapidly adapting population and to implement efficient backward-time coalescent simulations, which can be used to predict how clonal interference alters the expected patterns of molecular evolution.

A high resolution genome-wide scan for significant selective sweeps: an application to pooled sequence data in laying chickens

In most studies aimed at localizing footprints of past selection, outliers at tails of the empirical distribution of a given test statistic are assumed to reflect locus-specific selective forces. Significance cutoffs are subjectively determined, rather than being related to a clear set of hypotheses. Here, we define an empirical p-value for the summary statistic by means of a permutation method that uses the observed SNP structure in the real data. To illustrate the methodology, we applied our approach to a panel of 2.9 million autosomal SNPs identified from re-sequencing a pool of 15 individuals from a brown egg layer line. We scanned the genome for local reductions in heterozygosity, suggestive of selective sweeps. We also employed a modified sliding window approach that accounts for gaps in the sequence and increases scanning resolution by moving the overlapping windows by steps of one SNP only, and suggest to call this a “creeping window” strategy. The approach confirmed selective sweeps in the region of previously described candidate genes, i.e. TSHR, PRL, PRLHR, INSR, LEPR, IGF1, and NRAMP1 when used as positive controls. The genome scan revealed 82 distinct regions with strong evidence of selection (genome-wide p-value<0.001), including genes known to be associated with eggshell structure and immune system such as CALB1 and GAL cluster, respectively. A substantial proportion of signals was found in poor gene content regions including the most extreme signal on chromosome 1. The observation of multiple signals in a highly selected layer line of chicken is consistent with the hypothesis that egg production is a complex trait controlled by many genes.

Human-specific histone methylation signatures at transcription start sites in prefrontal neurons

Cognitive abilities and disorders unique to humans are thought to result from adaptively driven changes in brain transcriptomes, but little is known about the role of cis-regulatory changes affecting transcription start sites (TSS). Here, we mapped in human, chimpanzee, and macaque prefrontal cortex the genome-wide distribution of histone H3 trimethylated at lysine 4 (H3K4me3), an epigenetic mark sharply regulated at TSS, and identified 471 sequences with human-specific enrichment or depletion. Among these were 33 loci selectively methylated in neuronal but not non-neuronal chromatin from children and adults, including TSS at DPP10 (2q14.1), CNTN4 and CHL1 (3p26.3), and other neuropsychiatric susceptibility genes. Regulatory sequences at DPP10 and additional loci carried a strong footprint of hominid adaptation, including elevated nucleotide substitution rates and regulatory motifs absent in other primates (including archaic hominins), with evidence for selective pressures during more recent evolution and adaptive fixations in modern populations. Chromosome conformation capture at two neurodevelopmental disease loci, 2q14.1 and 16p11.2, revealed higher order chromatin structures resulting in physical contact of multiple human-specific H3K4me3 peaks spaced 0.5-1 Mb apart, in conjunction with a novel cis-bound antisense RNA linked to Polycomb repressor proteins and downregulated DPP10 expression. Therefore, coordinated epigenetic regulation via newly derived TSS chromatin could play an important role in the emergence of human-specific gene expression networks in brain that contribute to cognitive functions and neurological disease susceptibility in modern day humans.

The effect of genomic inversions on estimation of population genetic parameters from SNP data

In recent years it has emerged that structural variants have a substantial impact on genomic variation. Inversion polymorphisms represent a significant class of structural variant, and despite the challenges in their detection, data on inversions in the human genome are increasing rapidly. Statistical methods for inferring parameters such as the recombination rate and the selection coefficient have generally been developed without accounting for the presence of inversions. Here we exploit new software for simulating inversions in population genetic data, invertFREGENE, to assess the potential impact of inversions on such methods. Using data simulated by invertFREGENE, as well as real data from several sources, we test whether large inversions have a disruptive effect on widely applied population genetics methods for inferring recombination rates, for detecting selection, and for controlling for population structure in genome-wide association studies (GWAS). We find that recombination rates estimated by LDhat are biased downward at inversion loci relative to the true contemporary recombination rates at the loci but that recombination hotspots are not falsely inferred at inversion breakpoints as may have been expected. We find that the integrated haplotype score (iHS) method for detecting selection appears robust to the presence of inversions. Finally, we observe a strong bias in the genome-wide results of principal components analysis (PCA), used to control for population structure in GWAS, in the presence of even a single large inversion, confirming the necessity to thin SNPs by linkage disequilibrium at large physical distances to obtain unbiased results.

A novel analytical method, Birth Date Selection Mapping, detects response of the Angus (Bos taurus) genome to selection on complex traits

BACKGROUND

Several methods have recently been developed to identify regions of the genome that have been exposed to strong selection. However, recent theoretical and empirical work suggests that polygenic models are required to identify the genomic regions that are more moderately responding to ongoing selection on complex traits. We examine the effects of multi-trait selection on the genome of a population of US registered Angus beef cattle born over a 50-year period representing approximately 10 generations of selection. We present results from the application of a quantitative genetic model, called Birth Date Selection Mapping, to identify signatures of recent ongoing selection.

RESULTS

We show that US Angus cattle have been systematically selected to alter their mean additive genetic merit for most of the 16 production traits routinely recorded by breeders. Using Birth Date Selection Mapping, we estimate the time-dependency of allele frequency for 44,817 SNP loci using genomic best linear unbiased prediction, generalized least squares, and BayesCπ analyses. Finally, we reconstruct the primary phenotypes that have historically been exposed to selection from a genome-wide analysis of the 16 production traits and gene ontology enrichment analysis.

CONCLUSIONS

We demonstrate that Birth Date Selection Mapping utilizing mixed models corrects for time-dependent pedigree sampling effects that lead to spurious SNP associations and reveals genomic signatures of ongoing selection on complex traits. Because multiple traits have historically been selected in concert and most quantitative trait loci have small effects, selection has incrementally altered allele frequencies throughout the genome. Two quantitative trait loci of large effect were not the most strongly selected of the loci due to their antagonistic pleiotropic effects on strongly selected phenotypes. Birth Date Selection Mapping may readily be extended to temporally-stratified human or model organism populations.

Population genomic scan for candidate signatures of balancing selection to guide antigen characterization in malaria parasites

Acquired immunity in vertebrates maintains polymorphisms in endemic pathogens, leading to identifiable signatures of balancing selection. To comprehensively survey for genes under such selection in the human malaria parasite Plasmodium falciparum, we generated paired-end short-read sequences of parasites in clinical isolates from an endemic Gambian population, which were mapped to the 3D7 strain reference genome to yield high-quality genome-wide coding sequence data for 65 isolates. A minority of genes did not map reliably, including the hypervariable var, rifin, and stevor families, but 5,056 genes (90.9% of all in the genome) had >70% sequence coverage with minimum read depth of 5 for at least 50 isolates, of which 2,853 genes contained 3 or more single nucleotide polymorphisms (SNPs) for analysis of polymorphic site frequency spectra. Against an overall background of negatively skewed frequencies, as expected from historical population expansion combined with purifying selection, the outlying minority of genes with signatures indicating exceptionally intermediate frequencies were identified. Comparing genes with different stage-specificity, such signatures were most common in those with peak expression at the merozoite stage that invades erythrocytes. Members of clag, PfMC-2TM, surfin, and msp3-like gene families were highly represented, the strongest signature being in the msp3-like gene PF10_0355. Analysis of msp3-like transcripts in 45 clinical and 11 laboratory adapted isolates grown to merozoite-containing schizont stages revealed surprisingly low expression of PF10_0355. In diverse clonal parasite lines the protein product was expressed in a minority of mature schizonts (<1% in most lines and ∼10% in clone HB3), and eight sub-clones of HB3 cultured separately had an intermediate spectrum of positive frequencies (0.9 to 7.5%), indicating phase variable expression of this polymorphic antigen. This and other identified targets of balancing selection are now prioritized for functional study.

On measures of association among genetic variables

Systems involving many variables are important in population and quantitative genetics, for example, in multi-trait prediction of breeding values and in exploration of multi-locus associations. We studied departures of the joint distribution of sets of genetic variables from independence. New measures of association based on notions of statistical distance between distributions are presented. These are more general than correlations, which are pairwise measures, and lack a clear interpretation beyond the bivariate normal distribution. Our measures are based on logarithmic (Kullback-Leibler) and on relative ‘distances’ between distributions. Indexes of association are developed and illustrated for quantitative genetics settings in which the joint distribution of the variables is either multivariate normal or multivariate-t, and we show how the indexes can be used to study linkage disequilibrium in a two-locus system with multiple alleles and present applications to systems of correlated beta distributions. Two multivariate beta and multivariate beta-binomial processes are examined, and new distributions are introduced: the GMS-Sarmanov multivariate beta and its beta-binomial counterpart.

Microsatellites as targets of natural selection

The ability to survey polymorphism on a genomic scale has enabled genome-wide scans for the targets of natural selection. Theory that connects patterns of genetic variation to evidence of natural selection most often assumes a diallelic locus and no recurrent mutation. Although these assumptions are suitable to selection that targets single nucleotide variants, fundamentally different types of mutation generate abundant polymorphism in genomes. Moreover, recent empirical results suggest that mutationally complex, multiallelic loci including microsatellites and copy number variants are sometimes targeted by natural selection. Given their abundance, the lack of inference methods tailored to the mutational peculiarities of these types of loci represents a notable gap in our ability to interrogate genomes for signatures of natural selection. Previous theoretical investigations of mutation-selection balance at multiallelic loci include assumptions that limit their application to inference from empirical data. Focusing on microsatellites, we assess the dynamics and population-level consequences of selection targeting mutationally complex variants. We develop general models of a multiallelic fitness surface, a realistic model of microsatellite mutation, and an efficient simulation algorithm. Using these tools, we explore mutation-selection-drift equilibrium at microsatellites and investigate the mutational history and selective regime of the microsatellite that causes Friedreich's ataxia. We characterize microsatellite selective events by their duration and cost, note similarities to sweeps from standing point variation, and conclude that it is premature to label microsatellites as ubiquitous agents of efficient adaptive change. Together, our models and simulation algorithm provide a powerful framework for statistical inference, which can be used to test the neutrality of microsatellites and other multiallelic variants.

The genomics of adaptation

The amount and nature of genetic variation available to natural selection affect the rate, course and outcome of evolution. Consequently, the study of the genetic basis of adaptive evolutionary change has occupied biologists for decades, but progress has been hampered by the lack of resolution and the absence of a genome-level perspective. Technological advances in recent years should now allow us to answer many long-standing questions about the nature of adaptation. The data gathered so far are beginning to challenge some widespread views of the way in which natural selection operates at the genomic level. Papers in this Special Feature of Proceedings of the Royal Society B illustrate various aspects of the broad field of adaptation genomics. This introductory article sets up a context and, on the basis of a few selected examples, discusses how genomic data can advance our understanding of the process of adaptation.

Human population admixture in Asia

Genetic admixture in human, the result of inter-marriage among people from different well-differentiated populations, has been extensively studied in the New World, where European colonization brought contact between peoples of Europe, Africa, and Asia and the Amerindian populations. In Asia, genetic admixing has been also prevalent among previously separated human populations. However, studies on admixed populations in Asia have been largely underrepresented in similar efforts in the New World. Here, I will provide an overview of population genomic studies that have been published to date on human admixture in Asia, focusing on population structure and population history.

What is the evidence for heterozygote advantage selection?

Recent genomic data have found that many genes show the signal of selection. How many of these genes are undergoing heterozygote advantage selection is only beginning to be known. Initial genomic surveys have suggested that only a small proportion of loci have polymorphisms maintained by heterozygote advantage and this is consistent with the few examples generated from other approaches within given species. Unless further studies provide large numbers of loci with heterozygote advantage, it appears that loci with heterozygote advantage must be considered only a small minority of all loci in a species. This is not to say that some heterozygote advantage loci do not have important adaptive functions, but that their role in overall evolutionary change might be more of an unusual phenomenon than a major player in adaptation.

Limited evidence for classic selective sweeps in African populations

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

Molecular evolutionary and population genomic analysis of the nine-spined stickleback using a modified restriction-site-associated DNA tag approach

In recent years, the explosion of affordable next generation sequencing technology has provided an unprecedented opportunity to conduct genome-wide studies of adaptive evolution in organisms previously lacking extensive genomic resources. Here, we characterize genome-wide patterns of variability and differentiation using pooled DNA from eight populations of the nine-spined stickleback (Pungitius pungitius L.) from marine, lake and pond environments. We developed a novel genome complexity reduction protocol, defined as paired-end double restriction-site-associated DNA (PE dRAD), to maximize read coverage at sequenced locations. This allowed us to identify over 114,000 short consensus sequences and 15,000 SNPs throughout the genome. A total of 6834 SNPs mapped to a single position on the related three-spined stickleback genome, allowing the detection of genomic regions affected by divergent and balancing selection, both between species and between freshwater and marine populations of the nine-spined stickleback. Gene ontology analysis revealed 15 genomic regions with elevated diversity, enriched for genes involved in functions including immunity, chemical stimulus response, lipid metabolism and signalling pathways. Comparisons of marine and freshwater populations identified nine regions with elevated differentiation related to kidney development, immunity and MAP kinase pathways. In addition, our analysis revealed that a large proportion of the identified SNPs mapping to LG XII is likely to represent alternative alleles from divergent X and Y chromosomes, rather than true autosomal markers following Mendelian segregation. Our work demonstrates how population-wide sequencing and combining inter- and intra-specific RAD analysis can uncover genome-wide patterns of differentiation and adaptations in a non-model species.

Genome patterns of selection and introgression of haplotypes in natural populations of the house mouse (Mus musculus)

General parameters of selection, such as the frequency and strength of positive selection in natural populations or the role of introgression, are still insufficiently understood. The house mouse (Mus musculus) is a particularly well-suited model system to approach such questions, since it has a defined history of splits into subspecies and populations and since extensive genome information is available. We have used high-density single-nucleotide polymorphism (SNP) typing arrays to assess genomic patterns of positive selection and introgression of alleles in two natural populations of each of the subspecies M. m. domesticus and M. m. musculus. Applying different statistical procedures, we find a large number of regions subject to apparent selective sweeps, indicating frequent positive selection on rare alleles or novel mutations. Genes in the regions include well-studied imprinted loci (e.g. Plagl1/Zac1), homologues of human genes involved in adaptations (e.g. alpha-amylase genes) or in genetic diseases (e.g. Huntingtin and Parkin). Haplotype matching between the two subspecies reveals a large number of haplotypes that show patterns of introgression from specific populations of the respective other subspecies, with at least 10% of the genome being affected by partial or full introgression. Using neutral simulations for comparison, we find that the size and the fraction of introgressed haplotypes are not compatible with a pure migration or incomplete lineage sorting model. Hence, it appears that introgressed haplotypes can rise in frequency due to positive selection and thus can contribute to the adaptive genomic landscape of natural populations. Our data support the notion that natural genomes are subject to complex adaptive processes, including the introgression of haplotypes from other differentiated populations or species at a larger scale than previously assumed for animals. This implies that some of the admixture found in inbred strains of mice may also have a natural origin.

Genome-wide patterns of latitudinal differentiation among populations of Drosophila melanogaster from North America

Understanding the genetic underpinnings of adaptive change is a fundamental but largely unresolved problem in evolutionary biology. Drosophila melanogaster, an ancestrally tropical insect that has spread to temperate regions and become cosmopolitan, offers a powerful opportunity for identifying the molecular polymorphisms underlying clinal adaptation. Here, we use genome-wide next-generation sequencing of DNA pools ('pool-seq') from three populations collected along the North American east coast to examine patterns of latitudinal differentiation. Comparing the genomes of these populations is particularly interesting since they exhibit clinal variation in a number of important life history traits. We find extensive latitudinal differentiation, with many of the most strongly differentiated genes involved in major functional pathways such as the insulin/TOR, ecdysone, torso, EGFR, TGFβ/BMP, JAK/STAT, immunity and circadian rhythm pathways. We observe particularly strong differentiation on chromosome 3R, especially within the cosmopolitan inversion In(3R)Payne, which contains a large number of clinally varying genes. While much of the differentiation might be driven by clinal differences in the frequency of In(3R)P, we also identify genes that are likely independent of this inversion. Our results provide genome-wide evidence consistent with pervasive spatially variable selection acting on numerous loci and pathways along the well-known North American cline, with many candidates implicated in life history regulation and exhibiting parallel differentiation along the previously investigated Australian cline.

Evolution and functional impact of rare coding variation from deep sequencing of human exomes

As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111× in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86% with a minor allele frequency less than 0.5%), previously unknown (82%), and population-specific (82%). On average, 2.3% of the 13,595 SNVs each person carried were predicted to affect protein function of ~313 genes per genome, and ~95.7% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.

Comparative studies of gene expression and the evolution of gene regulation

The hypothesis that differences in gene regulation have an important role in speciation and adaptation is more than 40 years old. With the advent of new sequencing technologies, we are able to characterize and study gene expression levels and associated regulatory mechanisms in a large number of individuals and species at an unprecedented resolution and scale. We have thus gained new insights into the evolutionary pressures that shape gene expression levels and have developed an appreciation for the relative importance of evolutionary changes in different regulatory genetic and epigenetic mechanisms. The current challenge is to link gene regulatory changes to adaptive evolution of complex phenotypes. Here we mainly focus on comparative studies in primates and how they are complemented by studies in model organisms.

Human population structure and the adaptive response to pathogen-induced selection pressures

The past few years of research in human evolutionary genetics have provided novel insights and questions regarding how human adaptations to recent selective pressures have taken place. Here, we review the advances most relevant to understanding human evolution in response to pathogen-induced selective pressures. Key insights come from theoretical models of adaptive evolution, particularly those that consider spatially structured populations, and from empirical population genomic studies of adaptive evolution in humans. We also review the CCR5-Δ32 HIV resistance allele as a case study of pathogen resistance in humans. Taken together, the results make clear that the human response to pathogen-induced selection pressures depends on a complex interplay between the age of the pathogen, the genetic basis of potential resistance phenotypes, and how population structure impacts the adaptive process in humans.

Patterns of ancestry, signatures of natural selection, and genetic association with stature in Western African pygmies

African Pygmy groups show a distinctive pattern of phenotypic variation, including short stature, which is thought to reflect past adaptation to a tropical environment. Here, we analyze Illumina 1M SNP array data in three Western Pygmy populations from Cameroon and three neighboring Bantu-speaking agricultural populations with whom they have admixed. We infer genome-wide ancestry, scan for signals of positive selection, and perform targeted genetic association with measured height variation. We identify multiple regions throughout the genome that may have played a role in adaptive evolution, many of which contain loci with roles in growth hormone, insulin, and insulin-like growth factor signaling pathways, as well as immunity and neuroendocrine signaling involved in reproduction and metabolism. The most striking results are found on chromosome 3, which harbors a cluster of selection and association signals between approximately 45 and 60 Mb. This region also includes the positional candidate genes DOCK3, which is known to be associated with height variation in Europeans, and CISH, a negative regulator of cytokine signaling known to inhibit growth hormone-stimulated STAT5 signaling. Finally, pathway analysis for genes near the strongest signals of association with height indicates enrichment for loci involved in insulin and insulin-like growth factor signaling.

Africa is thought to be the location of origin of modern humans within the past 200,000 years and the source of our dispersion across the globe within the past 100,000 years. Africa is also a region of extreme environmental, cultural, linguistic, and phenotypic diversity, and human populations living there show the highest levels of genetic diversity in the world. Yet little is known about the genetic basis of the observed phenotypic variation in Africa or how local adaptation and demography have influenced these patterns in the recent past. Here, we analyze a set of admixing Bantu-speaking agricultural and Western Pygmy hunter-gatherer populations that show extreme differences in stature; Pygmies are ∼17 cm shorter on average than their Bantu neighbors and among the shortest populations globally. Our multifaceted approach identified several genomic regions that may have been targets of natural selection and so may harbor variants underlying the unique anatomy and physiology of Western African Pygmies. One region of chromosome three, in particular, harbors strong signals of natural selection, population differentiation, and association with height. This region also contains a significant association with height in Europeans as well as a candidate gene known to regulate growth hormone signaling.

Loss and gain of function in SERPINB11: an example of a gene under selection on standing variation, with implications for host-pathogen interactions

Serine protease inhibitors (SERPINs) are crucial in the regulation of diverse biological processes including inflammation and immune response. SERPINB11, located in the 18q21 gene cluster, is a polymorphic gene/pseudogene coding for a non-inhibitory SERPIN. In a genome-wide scan for recent selection, SERPINB11 was identified as a potential candidate gene for adaptive evolution in Yoruba. The present study sought a better understanding of the evolutionary history of SERPINB11, with special focus on evaluating its selective signature. Through the resequencing of coding and noncoding regions of SERPINB11 in 20 Yorubans and analyzing primate orthologous sequences, we identified a full-length SERPINB11 variant encoding a non-inhibitory SERPIN as the putative candidate of selection – probably driven to higher frequencies by an adaptive response using preexisting variation. In addition, we detected contrasting evolutionary features of SERPINB11 in primates: While primate phylogeny as a whole is under purifying selection, the human lineage shows evidence of positive selection in a few codons, all associated with the active SERPINB11. Comparative modeling studies suggest that positively selected codons reduce SERPINB11's ability to undergo the conformational changes typical of inhibitory SERPINs – suggesting that it is evolving towards a new non-inhibitory function in humans. Significant correlations between SERPINB11 variants and the environmental variables, pastoralism and pathogen richness, have led us to propose a selective advantage through host-pathogen interactions, possibly linked to an adaptive response combating the emergence of infectious diseases in recent human evolution. This work represents the first description of a resurrected gene in humans, and may well exemplify selection on standing variation triggered by drastic ecological shifts.

Genomic scan of selective sweeps in thin and fat tail sheep breeds for identifying of candidate regions associated with fat deposition

BACKGROUND

Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most important and challenging areas of research in animal genetics. However, currently there are relatively few genomic regions identified that have been subject to positive selection. In this study, a genome-wide scan using ~50,000 Single Nucleotide Polymorphisms (SNPs) was performed in an attempt to identify genomic regions associated with fat deposition in fat-tail breeds. This trait and its modification are very important in those countries grazing these breeds.

RESULTS

Two independent experiments using either Iranian or Ovine HapMap genotyping data contrasted thin and fat tail breeds. Population differentiation using FST in Iranian thin and fat tail breeds revealed seven genomic regions. Almost all of these regions overlapped with QTLs that had previously been identified as affecting fat and carcass yield traits in beef and dairy cattle. Study of selection sweep signatures using FST in thin and fat tail breeds sampled from the Ovine HapMap project confirmed three of these regions located on Chromosomes 5, 7 and X. We found increased homozygosity in these regions in favour of fat tail breeds on chromosome 5 and X and in favour of thin tail breeds on chromosome 7.

CONCLUSIONS

In this study, we were able to identify three novel regions associated with fat deposition in thin and fat tail sheep breeds. Two of these were associated with an increase of homozygosity in the fat tail breeds which would be consistent with selection for mutations affecting fat tail size several thousand years after domestication.

Human evolutionary genomics: ethical and interpretive issues

Genome-wide computational studies can now identify targets of natural selection. The unique information about humans these studies reveal, and the media attention they attract, indicate the need for caution and precision in communicating results. This need is exacerbated by ways in which evolutionary and genetic considerations have been misapplied to support discriminatory policies, by persistent misconceptions of these fields and by the social sensitivity surrounding discussions of racial ancestry. We discuss the foundations, accomplishments and future directions of human evolutionary genomics, attending to ways in which the interpretation of good science can go awry, and offer suggestions for researchers to prevent misapplication of their work.

Population genomic analysis of model and nonmodel organisms using sequenced RAD tags

The evolutionary processes of mutation, migration, genetic drift, and natural selection shape patterns of genetic variation among individuals, populations, and species, and they can do so differentially across genomes. The field of population genomics provides a comprehensive genome-scale view of these processes, even beyond traditional model organisms. Until recently, genome-wide studies of genetic variation have been prohibitively expensive. However, next-generation sequencing (NGS) technologies are revolutionizing the field of population genomics, allowing for genetic analysis at scales not previously possible even in organisms for which few genomic resources presently exist. To speed this revolution in evolutionary genetics, we and colleagues developed Restriction site Associated DNA (RAD) sequencing, a method that uses Illumina NGS to simultaneously type and score tens to hundreds of thousands of single nucleotide polymorphism (SNP) markers in hundreds of individuals for minimal investment of resources. The core molecular protocol is described elsewhere in this volume, which can be modified to suit a diversity of evolutionary genetic questions. In this chapter, we outline the conceptual framework of population genomics, relate genomic patterns of variation to evolutionary processes, and discuss how RAD sequencing can be used to study population genomics. In addition, we discuss bioinformatic considerations that arise from unique aspects of NGS data as compared to traditional marker based approaches, and we outline some general analytical approaches for RAD-seq and similar data, including a computational pipeline that we developed called Stacks. This software can be used for the analysis of RAD-seq data in organisms with and without a reference genome. Nonetheless, the development of analytical tools remains in its infancy, and further work is needed to fully quantify sampling variance and biases in these data types. As data-gathering technology continues to advance, our ability to understand genomic evolution in natural populations will be limited more by conceptual and analytical weaknesses than by the amount of molecular data.

Adaptive genetic variation and population differences

Since the expansion of modern humans (Homo sapiens) from Africa to the rest of the world between 50,000 and 100,000 years ago, the human genome has been shaped not only by demographic history but also by adaptation to local environments, including regional climate, landscape, food sources, culture, and pathogens. Genetic differences among populations interact with environmental factors, such as diet and lifestyle, leading to differences in nutrient metabolism, which translate into differences in susceptibility to a variety of diseases. Individuals from different populations sharing the same environments can exhibit differences in disease risk, as do individuals from the same population living in various regions of the globe. Therefore, it is important to understand how adaptive genetic variations interact with environments to influence health. This knowledge will provide a broad foundation for designing experiments and approaches in nutrigenomics research and strengthening the knowledge base for dietary recommendations for disease prevention. The objectives of this chapter are to (1) understand the methodology employed in examining adaptive genetic variation across populations, (2) establish the importance of adaptive genetic variation to human health, and (3) discuss the implications for nutrigenomics research and disease prevention.

Contrasting signals of positive selection in genes involved in human skin-color variation from tests based on SNP scans and resequencing

Background

Numerous genome-wide scans conducted by genotyping previously ascertained single-nucleotide polymorphisms (SNPs) have provided candidate signatures for positive selection in various regions of the human genome, including in genes involved in pigmentation traits. However, it is unclear how well the signatures discovered by such haplotype-based test statistics can be reproduced in tests based on full resequencing data. Four genes (oculocutaneous albinism II (OCA2), tyrosinase-related protein 1 (TYRP1), dopachrome tautomerase (DCT), and KIT ligand (KITLG)) implicated in human skin-color variation, have shown evidence for positive selection in Europeans and East Asians in previous SNP-scan data. In the current study, we resequenced 4.7 to 6.7 kb of DNA from each of these genes in Africans, Europeans, East Asians, and South Asians.

Results

Applying all commonly used neutrality-test statistics for allele frequency distribution to the newly generated sequence data provided conflicting results regarding evidence for positive selection. Previous haplotype-based findings could not be clearly confirmed. Although some tests were marginally significant for some populations and genes, none of them were significant after multiple-testing correction. Combined P values for each gene-population pair did not improve these results. Application of Approximate Bayesian Computation Markov chain Monte Carlo based to these sequence data using a simple forward simulator revealed broad posterior distributions of the selective parameters for all four genes, providing no support for positive selection. However, when we applied this approach to published sequence data on SLC45A2, another human pigmentation candidate gene, we could readily confirm evidence for positive selection, as previously detected with sequence-based and some haplotype-based tests.

Conclusions

Overall, our data indicate that even genes that are strong biological candidates for positive selection and show reproducible signatures of positive selection in SNP scans do not always show the same replicability of selection signals in other tests, which should be considered in future studies on detecting positive selection in genetic data.

Genome-wide detection of natural selection in African Americans pre- and post-admixture

It is particularly meaningful to investigate natural selection in African Americans (AfA) due to the high mortality their African ancestry has experienced in history. In this study, we examined 491,526 autosomal single nucleotide polymorphisms (SNPs) genotyped in 5210 individuals and conducted a genome-wide search for selection signals in 1890 AfA. Several genomic regions showing an excess of African or European ancestry, which were considered the footprints of selection since population admixture, were detected based on a commonly used approach. However, we also developed a new strategy to detect natural selection both pre- and post-admixture by reconstructing an ancestral African population (AAF) from inferred African components of ancestry in AfA and comparing it with indigenous African populations (IAF). Interestingly, many selection-candidate genes identified by the new approach were associated with AfA-specific high-risk diseases such as prostate cancer and hypertension, suggesting an important role these disease-related genes might have played in adapting to a new environment. CD36 and HBB, whose mutations confer a degree of protection against malaria, were also located in the highly differentiated regions between AAF and IAF. Further analysis showed that the frequencies of alleles protecting against malaria in AAF were lower than those in IAF, which is consistent with the relaxed selection pressure of malaria in the New World. There is no overlap between the top candidate genes detected by the two approaches, indicating the different environmental pressures AfA experienced pre- and post-population admixture. We suggest that the new approach is reasonably powerful and can also be applied to other admixed populations such as Latinos and Uyghurs.

Genetic contributions to behavioural diversity at the gene-environment interface

Recent work on behavioural variation within and between species has furthered our understanding of the genetic architecture of behavioural traits, the identities of relevant genes and the ways in which genetic variants affect neuronal circuits to modify behaviour. Here we review our understanding of the genetics of natural behavioural variation in non-human animals and highlight the implications of these findings for human genetics. We suggest that gene-environment interactions are central to natural genetic variation in behaviour and that genes affecting neuromodulatory pathways and sensory processing are preferred sites of naturally occurring mutations.

Exploration of signals of positive selection derived from genotype-based human genome scans using re-sequencing data

We have investigated whether regions of the genome showing signs of positive selection in scans based on haplotype structure also show evidence of positive selection when sequence-based tests are applied, whether the target of selection can be localized more precisely, and whether such extra evidence can lead to increased biological insights. We used two tools: simulations under neutrality or selection, and experimental investigation of two regions identified by the HapMap2 project as putatively selected in human populations. Simulations suggested that neutral and selected regions should be readily distinguished and that it should be possible to localize the selected variant to within 40 kb at least half of the time. Re-sequencing of two ~300 kb regions (chr4:158Mb and chr10:22Mb) lacking known targets of selection in HapMap CHB individuals provided strong evidence for positive selection within each and suggested the micro-RNA gene hsa-miR-548c as the best candidate target in one region, and changes in regulation of the sperm protein gene SPAG6 in the other.

Recent advances in understanding the role of nutrition in human genome evolution

Dietary transitions in human history have been suggested to play important roles in the evolution of mankind. Genetic variations caused by adaptation to diet during human evolution could have important health consequences in current society. The advance of sequencing technologies and the rapid accumulation of genome information provide an unprecedented opportunity to comprehensively characterize genetic variations in human populations and unravel the genetic basis of human evolution. Series of selection detection methods, based on various theoretical models and exploiting different aspects of selection signatures, have been developed. Their applications at the species and population levels have respectively led to the identification of human specific selection events that distinguish human from nonhuman primates and local adaptation events that contribute to human diversity. Scrutiny of candidate genes has revealed paradigms of adaptations to specific nutritional components and genome-wide selection scans have verified the prevalence of diet-related selection events and provided many more candidates awaiting further investigation. Understanding the role of diet in human evolution is fundamental for the development of evidence-based, genome-informed nutritional practices in the era of personal genomics.

Molecular spandrels: tests of adaptation at the genetic level

Although much progress has been made in identifying the genes (and, in rare cases, mutations) that contribute to phenotypic variation, less is known about the effects that these genes have on fitness. Nonetheless, genes are commonly labelled as 'adaptive' if an allele has been shown to affect a phenotype with known or suspected functional importance or if patterns of nucleotide variation at the locus are consistent with positive selection. In these cases, the 'adaptive' designation may be premature and may lead to incorrect conclusions about the relationships between gene function and fitness. Experiments to test targets and agents of natural selection within a genomic context are necessary for identifying the adaptive consequences of individual alleles.

Evolutionary and functional evidence for positive selection at the human CD5 immune receptor gene

CD5 is a lymphocyte surface coreceptor of still incompletely understood function. Currently available information indicates that CD5 participates not only in cell-to-cell immune interactions through still poorly defined endogenous ligands expressed on hemopoietic and nonhemopoietic cells but also in recognition of exogenous and highly conserved microbial structures such as fungal β-glucans. Preceding single nucleotide polymorphism (SNP) data analysis provided evidence for a recent selective sweep in East Asia and suggested a nonsynonymous substitution at position 471 (A471V; rs2229177) of the cytoplasmatic region of the CD5 receptor as the most plausible target of selection. The present report further investigates the role of natural selection in the CD5 gene by a resequencing approach in 60 individuals representing populations from 3 different continents (20 Africans, 20 Europeans and 20 East Asians) and by functionally assaying the relevance of the A471V replacement on CD5 signaling. The high differentiation pattern found at the nonsynonymous A471V site together with the low diversity, most of the performed neutrality tests (Tajima's D, Fu and Li's F* and D*, and Fu's Fs) and the predominance of a major haplotype in East Asians strongly argue in favor of positive selection for the A471V site. Importantly, anti-CD5 monoclonal antibody cross-linking unveiled significant differences among A471V variants regarding the mitogen-activated protein kinase (MAPK) cascade activation on COS7 and on human peripheral blood mononuclear cells. Similar differences on MAPK activation and IL-8 cytokine release were also observed upon exposure of HEK293 cell transfectants expressing the A471V variants to Zymosan, a β-glucan-rich fungal particle. Taken together, the results provide evidence for the hypothesis of an adaptive role of the A471V substitution to environmental challenges, most likely infectious pathogens, in East Asian populations.

Natural selection affects multiple aspects of genetic variation at putatively neutral sites across the human genome

A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries of genetic variation, like allele frequencies, are also correlated with recombination rate and whether these correlations can be explained solely by negative selection against deleterious mutations or whether positive selection acting on favorable alleles is also required. Here we attempt to address these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations. However, models with strong positive selection on nonsynonymous mutations and little negative selection predict a stronger negative correlation between neutral diversity and nonsynonymous divergence than observed in the actual data, supporting the importance of negative, rather than positive, selection throughout the genome. Further, we show that the widespread presence of weakly deleterious alleles, rather than a small number of strongly positively selected mutations, is responsible for the correlation between neutral genetic diversity and recombination rate. This work suggests that natural selection has affected multiple aspects of linked neutral variation throughout the human genome and that positive selection is not required to explain these observations.

Population genomics of wild and laboratory zebrafish (Danio rerio)

Understanding a wider range of genotype–phenotype associations can be achieved through ecological and evolutionary studies of traditional laboratory models. Here, we conducted the first large-scale geographic analysis of genetic variation within and among wild zebrafish (Danio rerio) populations occurring in Nepal, India, and Bangladesh, and we genetically compared wild populations to several commonly used lab strains. We examined genetic variation at 1832 polymorphic EST-based single nucleotide polymorphisms (SNPs) and the cytb mitochondrial gene in 13 wild populations and three lab strains. Natural populations were subdivided into three major mitochondrial DNA clades with an average among-clade sequence divergence of 5.8%. SNPs revealed five major evolutionarily and genetically distinct groups with an overall F_ST of 0.170 (95% CI 0.105–0.254). These genetic groups corresponded to discrete geographic regions and appear to reflect isolation in refugia during past climate cycles. We detected 71 significantly divergent outlier loci (3.4%) and nine loci (0.5%) with significantly low F_ST values. Valleys of reduced heterozygosity, consistent with selective sweeps, surrounded six of the 71 outliers (8.5%). The lab strains formed two additional groups that were genetically distinct from all wild populations. An additional subset of outlier loci was consistent with domestication selection within lab strains. Substantial genetic variation that exists in zebrafish as a whole is missing from lab strains that we analysed. A combination of laboratory and field studies that incorporates genetic variation from divergent wild populations along with the wealth of molecular information available for this model organism provides an opportunity to advance our understanding of genetic influences on phenotypic variation for a vertebrate species.

The promise and limitations of population exomics for human evolution studies

Exome sequencing is poised to yield substantial insights into human genetic variation and evolutionary history, but there are significant challenges to overcome before this becomes a reality.

Clusters of adaptive evolution in the human genome

Considerable work has been devoted to identifying regions of the human genome that have been subjected to recent positive selection. Although detailed follow-up studies of putatively selected regions are critical for a deeper understanding of human evolutionary history, such studies have received comparably less attention. Recently, we have shown that ALMS1 has been the target of recent positive selection acting on standing variation in Eurasian populations. Here, we describe a careful follow-up analysis of genetic variation across the ALMS1 region, which unexpectedly revealed a cluster of substrates of positive selection. Specifically, through the analysis of SNP data from the HapMap and Human Genome Diversity Project–Centre d’Etude du Polymorphisme Humain samples as well sequence data from the region, we find compelling evidence for three independent and distinct signals of recent positive selection across this 3 Mb region surrounding ALMS1. Moreover, we analyzed the HapMap data to identify other putative clusters of independent selective events and conservatively discovered 19 additional clusters of adaptive evolution. This work has important implications for the interpretation of genome-scans for positive selection in humans and more broadly contributes to a better understanding of how recent positive selection has shaped genetic variation across the human genome.

Genome-wide comparison of African-ancestry populations from CARe and other cohorts reveals signals of natural selection

The study of recent natural selection in human populations has important applications to human history and medicine. Positive natural selection drives the increase in beneficial alleles and plays a role in explaining diversity across human populations. By discovering traits subject to positive selection, we can better understand the population level response to environmental pressures including infectious disease. Our study examines unusual population differentiation between three large data sets to detect natural selection. The populations examined, African Americans, Nigerians, and Gambians, are genetically close to one another (F(ST) < 0.01 for all pairs), allowing us to detect selection even with moderate changes in allele frequency. We also develop a tree-based method to pinpoint the population in which selection occurred, incorporating information across populations. Our genome-wide significant results corroborate loci previously reported to be under selection in Africans including HBB and CD36. At the HLA locus on chromosome 6, results suggest the existence of multiple, independent targets of population-specific selective pressure. In addition, we report a genome-wide significant (p = 1.36 × 10(-11)) signal of selection in the prostate stem cell antigen (PSCA) gene. The most significantly differentiated marker in our analysis, rs2920283, is highly differentiated in both Africa and East Asia and has prior genome-wide significant associations to bladder and gastric cancers.

Copy number variation analysis in the great apes reveals species-specific patterns of structural variation

Copy number variants (CNVs) are increasingly acknowledged as an important source of evolutionary novelties in the human lineage. However, our understanding of their significance is still hindered by the lack of primate CNV data. We performed intraspecific comparative genomic hybridizations to identify loci harboring copy number variants in each of the four great apes: bonobos, chimpanzees, gorillas, and orangutans. For the first time, we could analyze differences in CNV location and frequency in these four species, and compare them with human CNVs and primate segmental duplication (SD) maps. In addition, for bonobo and gorilla, patterns of CNV and nucleotide diversity were studied in the same individuals. We show that CNVs have been subject to different selective pressures in different lineages. Evidence for purifying selection is stronger in gorilla CNVs overlapping genes, while positive selection appears to have driven the fixation of structural variants in the orangutan lineage. In contrast, chimpanzees and bonobos present high levels of common structural polymorphism, which is indicative of relaxed purifying selection together with the higher mutation rates induced by the known burst of segmental duplication in the ancestor of the African apes. Indeed, the impact of the duplication burst is noticeable by the fact that bonobo and chimpanzee share more CNVs with gorilla than expected. Finally, we identified a number of interesting genomic regions that present high-frequency CNVs in all great apes, while containing only very rare or even pathogenic structural variants in humans.

Evidence for hitchhiking of deleterious mutations within the human genome

Deleterious mutations present a significant obstacle to adaptive evolution. Deleterious mutations can inhibit the spread of linked adaptive mutations through a population; conversely, adaptive substitutions can increase the frequency of linked deleterious mutations and even result in their fixation. To assess the impact of adaptive mutations on linked deleterious mutations, we examined the distribution of deleterious and neutral amino acid polymorphism in the human genome. Within genomic regions that show evidence of recent hitchhiking, we find fewer neutral but a similar number of deleterious SNPs compared to other genomic regions. The higher ratio of deleterious to neutral SNPs is consistent with simulated hitchhiking events and implies that positive selection eliminates some deleterious alleles and increases the frequency of others. The distribution of disease-associated alleles is also altered in hitchhiking regions. Disease alleles within hitchhiking regions have been associated with auto-immune disorders, metabolic diseases, cancers, and mental disorders. Our results suggest that positive selection has had a significant impact on deleterious polymorphism and may be partly responsible for the high frequency of certain human disease alleles.