Identifying recent adaptations in large-scale genomic data

Detecting recent positive selection with high accuracy and reliability by conditional coalescent tree

Studies of natural selection, followed by functional validation, are shedding light on understanding of genetic mechanisms underlying human evolution and adaptation. Classic methods for detecting selection, such as the integrated haplotype score (iHS) and Fay and Wu's H statistic, are useful for candidate gene searching underlying positive selection. These methods, however, have limited capability to localize causal variants in selection target regions. In this study, we developed a novel method based on conditional coalescent tree to detect recent positive selection by counting unbalanced mutations on coalescent gene genealogies. Extensive simulation studies revealed that our method is more robust than many other approaches against biases due to various demographic effects, including population bottleneck, expansion, or stratification, while not sacrificing its power. Furthermore, our method demonstrated its superiority in localizing causal variants from massive linked genetic variants. The rate of successful localization was about 20-40% higher than that of other state-of-the-art methods on simulated data sets. On empirical data, validated functional causal variants of four well-known positive selected genes were all successfully localized by our method, such as ADH1B, MCM6, APOL1, and HBB. Finally, the computational efficiency of this new method was much higher than that of iHS implementations, that is, 24-66 times faster than the REHH package, and more than 10,000 times faster than the original iHS implementation. These magnitudes make our method suitable for applying on large sequencing data sets. Software can be downloaded from https://github.com/wavefancy/scct.

Human genomic regions with exceptionally high levels of population differentiation identified from 911 whole-genome sequences

BACKGROUND

Population differentiation has proved to be effective for identifying loci under geographically localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes.

RESULTS

We demonstrate that while sites with low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively.

CONCLUSIONS

We identify known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.

Evolutionary analysis identifies an MX2 haplotype associated with natural resistance to HIV-1 infection

The protein product of the myxovirus resistance 2 (MX2) gene restricts HIV-1 and simian retroviruses. We demonstrate that MX2 evolved adaptively in mammals with distinct sites representing selection targets in distinct branches; selection mainly involved residues in loop 4, previously shown to carry antiviral determinants. Modeling data indicated that positively selected sites form a continuous surface on loop 4, which folds into two antiparallel α-helices protruding from the stalk domain. A population genetics-phylogenetics approach indicated that the coding region of MX2 mainly evolved under negative selection in the human lineage. Nonetheless, population genetic analyses demonstrated that natural selection operated on MX2 during the recent history of human populations: distinct selective events drove the frequency increase of two haplotypes in the populations of Asian and European ancestry. The Asian haplotype carries a susceptibility allele for melanoma; the European haplotype is tagged by rs2074560, an intronic variant. Analyses performed on three independent European cohorts of HIV-1-exposed seronegative individuals with different geographic origin and distinct exposure route showed that the ancestral (G) allele of rs2074560 protects from HIV-1 infection with a recessive effect (combined P = 1.55 × 10(-4)). The same allele is associated with lower in vitro HIV-1 replication and increases MX2 expression levels in response to IFN-α. Data herein exploit evolutionary information to identify a novel host determinant of HIV-1 infection susceptibility.

Demography-adjusted tests of neutrality based on genome-wide SNP data

Tests of the neutral evolution hypothesis are usually built on the standard null model which assumes that mutations are neutral and the population size remains constant over time. However, it is unclear how such tests are affected if the last assumption is dropped. Here, we extend the unifying framework for tests based on the site frequency spectrum, introduced by Achaz and Ferretti, to populations of varying size. Key ingredients are the first two moments of the site frequency spectrum. We show how these moments can be computed analytically if a population has experienced two instantaneous size changes in the past. We apply our method to data from ten human populations gathered in the 1000 genomes project, estimate their demographies and define demography-adjusted versions of Tajima's D, Fay & Wu's H, and Zeng's E. Our results show that demography-adjusted test statistics facilitate the direct comparison between populations and that most of the differences among populations seen in the original unadjusted tests can be explained by their underlying demographies. Upon carrying out whole-genome screens for deviations from neutrality, we identify candidate regions of recent positive selection. We provide track files with values of the adjusted and unadjusted tests for upload to the UCSC genome browser.

The human condition-a molecular approach

Research into when and where modern humans originated and how they differ from, and interacted with, other now-extinct forms of human has so far been the realm of archaeologists and paleoanthropologists. However, over the past decade, molecular geneticists have begun to study genomes of extinct humans. Here, I discuss where we stand today with respect to understanding how modern humans came to differ from Neandertals and other human forms that existed until about 30,000 years ago.

Genomics meets proteomics: identifying the culprits in disease

Genome-wide association studies (GWAS) revealed genomic risk loci that potentially have an impact on disease and phenotypic traits. This extensive resource holds great promise in providing novel directions for personalized medicine, including disease risk prediction, prevention and targeted medication. One of the major challenges that researchers face on the path between the initial identification of an association and precision treatment of patients is the comprehension of the biological mechanisms that underlie these associations. Currently, the focus to solve these questions lies on the integrative analysis of system-wide data on global genome variation, gene expression, transcription factor binding, epigenetic profiles and chromatin conformation. The generation of this data mainly relies on next-generation sequencing. However, due to multiple recent developments, mass spectrometry-based proteomics now offers additional, by the GWAS field so far hardly recognized possibilities for the identification of functional genome variants and, in particular, for the identification and characterization of (differentially) bound protein complexes as well as physiological target genes. In this review, we introduce these proteomics advances and suggest how they might be integrated in post-GWAS workflows. We argue that the combination of highly complementary techniques is powerful and can provide an unbiased, detailed picture of GWAS loci and their mechanistic involvement in disease.

Human genome variability, natural selection and infectious diseases

The recent availability of large-scale sequencing DNA data allowed researchers to investigate how genomic variation is distributed among populations. While demographic factors explain genome-wide population genetic diversity levels, scans for signatures of natural selection pinpointed several regions under non-neutral evolution. Recent studies found an enrichment of immune-related genes subjected to natural selection, suggesting that pathogens and infectious diseases have imposed a strong selective pressure throughout human history. Pathogen-mediated selection often targeted regulatory sites of genes belonging to the same biological pathway. Results from these studies have the potential to identify mutations that modulate infection susceptibility by integrating a population genomic approach with molecular immunology data and large-scale functional annotations.

Private haplotypes can reveal local adaptation

BACKGROUND

Genome-wide scans for regions that demonstrate deviating patterns of genetic variation have become common approaches for finding genes targeted by selection. Several genomic patterns have been utilized for this purpose, including deviations in haplotype homozygosity, frequency spectra and genetic differentiation between populations.

RESULTS

We describe a novel approach based on the Maximum Frequency of Private Haplotypes--MFPH--to search for signals of recent population-specific selection. The MFPH statistic is straightforward to compute for phased SNP- and sequence-data. Using both simulated and empirical data, we show that MFPH can be a powerful statistic to detect recent population-specific selection, that it performs at the same level as other commonly used summary statistics (e.g. FST, iHS and XP-EHH), and that MFPH in some cases capture signals of selection that are missed by other statistics. For instance, in the Maasai, MFPH reveals a strong signal of selection in a region where other investigated statistics fail to pick up a clear signal that contains the genes DOCK3, MAPKAPK3 and CISH. This region has been suggested to affect height in many populations based on phenotype-genotype association studies. It has specifically been suggested to be targeted by selection in Pygmy groups, which are on the opposite end of the human height spectrum compared to the Maasai.

CONCLUSIONS

From the analysis of both simulated and publicly available empirical data, we show that MFPH represents a summary statistic that can provide further insight concerning population-specific adaptation.

Heritability and genomics of gene expression in peripheral blood

We assessed gene expression profiles in 2,752 twins, using a classic twin design to quantify expression heritability and quantitative trait loci (eQTLs) in peripheral blood. The most highly heritable genes (∼777) were grouped into distinct expression clusters, enriched in gene-poor regions, associated with specific gene function or ontology classes, and strongly associated with disease designation. The design enabled a comparison of twin-based heritability to estimates based on dizygotic identity-by-descent sharing and distant genetic relatedness. Consideration of sampling variation suggests that previous heritability estimates have been upwardly biased. Genotyping of 2,494 twins enabled powerful identification of eQTLs, which we further examined in a replication set of 1,895 unrelated subjects. A large number of non-redundant local eQTLs (6,756) met replication criteria, whereas a relatively small number of distant eQTLs (165) met quality control and replication standards. Our results provide a new resource toward understanding the genetic control of transcription.

Natural selection and infectious disease in human populations

Infectious pathogens are among the strongest selective forces that shape the human genome. Migrations and cultural changes in the past 100,000 years exposed populations to dangerous new pathogens.

Host genetics influences susceptibility to infectious disease. Evolutionary adaptations for resistance and symbiosis may underlie common immune-mediated diseases.

Signatures of selection and methods to detect them vary with the age, geographical spread and virulence of the pathogen.

A history of selection on a trait adds power to association studies by driving the emergence of common alleles of strong effect. Combining selection and association metrics can further increase power.

Genome-wide association studies (GWASs) of susceptibility to pathogens that are moderately old (1,000–50,000 years ago), geographically limited in history and exerted strong positive selective pressure will have the most power if GWASs can be done in the historically affected population.

An understanding of host–pathogen interactions can inform the development of new therapies for both infectious diseases and common immune-mediated diseases.

The impact of various infectious agents on human survival and reproduction over thousands of years has exerted selective pressure on numerous regions of the human genome. This Review describes how such signatures of selection can be detected and integrated with data from complementary approaches, such as genome-wide association studies, to provide biological insights into host–pathogen interactions.

The ancient biological 'arms race' between microbial pathogens and humans has shaped genetic variation in modern populations, and this has important implications for the growing field of medical genomics. As humans migrated throughout the world, populations encountered distinct pathogens, and natural selection increased the prevalence of alleles that are advantageous in the new ecosystems in both host and pathogens. This ancient history now influences human infectious disease susceptibility and microbiome homeostasis, and contributes to common diseases that show geographical disparities, such as autoimmune and metabolic disorders. Using new high-throughput technologies, analytical methods and expanding public data resources, the investigation of natural selection is leading to new insights into the function and dysfunction of human biology.

Genomic diversity and admixture differs for Stone-Age Scandinavian foragers and farmers

Prehistoric population structure associated with the transition to an agricultural lifestyle in Europe remains a contentious idea. Population-genomic data from 11 Scandinavian Stone Age human remains suggest that hunter-gatherers had lower genetic diversity than that of farmers. Despite their close geographical proximity, the genetic differentiation between the two Stone Age groups was greater than that observed among extant European populations. Additionally, the Scandinavian Neolithic farmers exhibited a greater degree of hunter-gatherer-related admixture than that of the Tyrolean Iceman, who also originated from a farming context. In contrast, Scandinavian hunter-gatherers displayed no significant evidence of introgression from farmers. Our findings suggest that Stone Age foraging groups were historically in low numbers, likely owing to oscillating living conditions or restricted carrying capacity, and that they were partially incorporated into expanding farming groups.

Defining functional DNA elements in the human genome

With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease.

Detecting natural selection in genomic data

The past fifty years have seen the development and application of numerous statistical methods to identify genomic regions that appear to be shaped by natural selection. These methods have been used to investigate the macro- and microevolution of a broad range of organisms, including humans. Here, we provide a comprehensive outline of these methods, explaining their conceptual motivations and statistical interpretations. We highlight areas of recent and future development in evolutionary genomics methods and discuss ongoing challenges for researchers employing such tests. In particular, we emphasize the importance of functional follow-up studies to characterize putative selected alleles and the use of selection scans as hypothesis-generating tools for investigating evolutionary histories.

Neanderthal ancestry drives evolution of lipid catabolism in contemporary Europeans

Although Neanderthals are extinct, fragments of their genomes persist in contemporary humans. Here we show that while the genome-wide frequency of Neanderthal-like sites is approximately constant across all contemporary out-of-Africa populations, genes involved in lipid catabolism contain more than threefold excess of such sites in contemporary humans of European descent. Evolutionally, these genes show significant association with signatures of recent positive selection in the contemporary European, but not Asian or African populations. Functionally, the excess of Neanderthal-like sites in lipid catabolism genes can be linked with a greater divergence of lipid concentrations and enzyme expression levels within this pathway, seen in contemporary Europeans, but not in the other populations. We conclude that sequence variants that evolved in Neanderthals may have given a selective advantage to anatomically modern humans that settled in the same geographical areas.

Modern human genomes contain Neanderthal sequences, but it is unclear whether these were selected. Here, Khrameeva et al. show that Neanderthal sequences associated with lipid catabolism are three times more frequent in Europe, suggesting that these sequences might have been beneficial to Europeans.

Exploring the occurrence of classic selective sweeps in humans using whole-genome sequencing data sets

Genome-wide scans for selection have identified multiple regions of the human genome as being targeted by positive selection. However, only a small proportion has been replicated across studies, and the prevalence of positive selection as a mechanism of adaptive change in humans remains controversial. Here we explore the power of two haplotype-based statistics--the integrated haplotype score (iHS) and the Derived Intraallelic Nucleotide Diversity (DIND) test--in the context of next-generation sequencing data, and evaluate their robustness to demography and other selection modes. We show that these statistics are both powerful for the detection of recent positive selection, regardless of population history, and robust to variation in coverage, with DIND being insensitive to very low coverage. We apply these statistics to whole-genome sequence data sets from the 1000 Genomes Project and Complete Genomics. We found that putative targets of selection were highly significantly enriched in genic and nonsynonymous single nucleotide polymorphisms, and that DIND was more powerful than iHS in the context of small sample sizes, low-quality genotype calling, or poor coverage. As we excluded genomic confounders and alternative selection models, such as background selection, the observed enrichment attests to the action of recent, strong positive selection. Further support to the adaptive significance of these genomic regions came from their enrichment in functional variants detected by genome-wide association studies, informing the relationship between past selection and current benign and disease-related phenotypic variation. Our results indicate that hard sweeps targeting low-frequency standing variation have played a moderate, albeit significant, role in recent human evolution.

An evolutionary analysis of antigen processing and presentation across different timescales reveals pervasive selection

The antigenic repertoire presented by MHC molecules is generated by the antigen processing and presentation (APP) pathway. We analyzed the evolutionary history of 45 genes involved in APP at the inter- and intra-species level. Results showed that 11 genes evolved adaptively in mammals. Several positively selected sites involve positions of fundamental importance to the protein function (e.g. the TAP1 peptide-binding domains, the sugar binding interface of langerin, and the CD1D trafficking signal region). In CYBB, all selected sites cluster in two loops protruding into the endosomal lumen; analysis of missense mutations responsible for chronic granulomatous disease (CGD) showed the action of different selective forces on the very same gene region, as most CGD substitutions involve aminoacid positions that are conserved in all mammals. As for ERAP2, different computational methods indicated that positive selection has driven the recurrent appearance of protein-destabilizing variants during mammalian evolution. Application of a population-genetics phylogenetics approach showed that purifying selection represented a major force acting on some APP components (e.g. immunoproteasome subunits and chaperones) and allowed identification of positive selection events in the human lineage.

We also investigated the evolutionary history of APP genes in human populations by developing a new approach that uses several different tests to identify the selection target, and that integrates low-coverage whole-genome sequencing data with Sanger sequencing. This analysis revealed that 9 APP genes underwent local adaptation in human populations. Most positive selection targets are located within noncoding regions with regulatory function in myeloid cells or act as expression quantitative trait loci. Conversely, balancing selection targeted nonsynonymous variants in TAP1 and CD207 (langerin). Finally, we suggest that selected variants in PSMB10 and CD207 contribute to human phenotypes. Thus, we used evolutionary information to generate experimentally-testable hypotheses and to provide a list of sites to prioritize in follow-up analyses.

Antigen-presenting cells digest intracellular and extracellular proteins and display the resulting antigenic repertoire on cell surface molecules for recognition by T cells. This process initiates cell-mediated immune responses and is essential to detect infections. The antigenic repertoire is generated by the antigen processing and presentation pathway. Because several pathogens evade immune recognition by hampering this process, genes involved in antigen processing and presentation may represent common natural selection targets. Thus, we analyzed the evolutionary history of these genes during mammalian evolution and in the more recent history of human populations. Evolutionary analyses in mammals indicated that positive selection targeted a very high proportion of genes (24%), and revealed that many selected sites affect positions of fundamental importance to the protein function. In humans, we found different signatures of natural selection acting both on regions that are expected to regulate gene expression levels or timing and on coding variants; two human selected polymorphisms may modulate the susceptibility to Crohn's disease and to HIV-1 infection. Therefore, we provide a comprehensive evolutionary analysis of antigen processing and we show that evolutionary studies can provide useful information concerning the location and nature of functional variants, ultimately helping to clarify phenotypic differences between and within species.

Genome-wide signals of positive selection in human evolution

The role of positive selection in human evolution remains controversial. On the one hand, scans for positive selection have identified hundreds of candidate loci, and the genome-wide patterns of polymorphism show signatures consistent with frequent positive selection. On the other hand, recent studies have argued that many of the candidate loci are false positives and that most genome-wide signatures of adaptation are in fact due to reduction of neutral diversity by linked deleterious mutations, known as background selection. Here we analyze human polymorphism data from the 1000 Genomes Project and detect signatures of positive selection once we correct for the effects of background selection. We show that levels of neutral polymorphism are lower near amino acid substitutions, with the strongest reduction observed specifically near functionally consequential amino acid substitutions. Furthermore, amino acid substitutions are associated with signatures of recent adaptation that should not be generated by background selection, such as unusually long and frequent haplotypes and specific distortions in the site frequency spectrum. We use forward simulations to argue that the observed signatures require a high rate of strongly adaptive substitutions near amino acid changes. We further demonstrate that the observed signatures of positive selection correlate better with the presence of regulatory sequences, as predicted by the ENCODE Project Consortium, than with the positions of amino acid substitutions. Our results suggest that adaptation was frequent in human evolution and provide support for the hypothesis of King and Wilson that adaptive divergence is primarily driven by regulatory changes.

Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression

To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.

Information compression exploits patterns of genome composition to discriminate populations and highlight regions of evolutionary interest

Background

Genomic information allows population relatedness to be inferred and selected genes to be identified. Single nucleotide polymorphism microarray (SNP-chip) data, a proxy for genome composition, contains patterns in allele order and proportion. These patterns can be quantified by compression efficiency (CE). In principle, the composition of an entire genome can be represented by a CE number quantifying allele representation and order.

Results

We applied a compression algorithm (DEFLATE) to genome-wide high-density SNP data from 4,155 human, 1,800 cattle, 1,222 sheep, 81 dogs and 49 mice samples. All human ethnic groups can be clustered by CE and the clusters recover phylogeography based on traditional fixation index (F_ST) analyses. CE analysis of other mammals results in segregation by breed or species, and is sensitive to admixture and past effective population size. This clustering is a consequence of individual patterns such as runs of homozygosity. Intriguingly, a related approach can also be used to identify genomic loci that show population-specific CE segregation. A high resolution CE ‘sliding window’ scan across the human genome, organised at the population level, revealed genes known to be under evolutionary pressure. These include SLC24A5 (European and Gujarati Indian skin pigmentation), HERC2 (European eye color), LCT (European and Maasai milk digestion) and EDAR (Asian hair thickness). We also identified a set of previously unidentified loci with high population-specific CE scores including the chromatin remodeler SCMH1 in Africans and EDA2R in Asians. Closer inspection reveals that these prioritised genomic regions do not correspond to simple runs of homozygosity but rather compositionally complex regions that are shared by many individuals of a given population. Unlike F_ST, CE analyses do not require ab initio population comparisons and are amenable to the hemizygous X chromosome.

Conclusions

We conclude with a discussion of the implications of CE for a complex systems science view of genome evolution. CE allows one to clearly visualise the evolution of individual genomes and populations through a formal, mathematically-rigorous information space. Overall, CE makes a set of biological predictions, some of which are unique and await functional validation.

Genetic dissection of Anopheles gambiae gut epithelial responses to Serratia marcescens

Genetic variation in the mosquito Anopheles gambiae profoundly influences its ability to transmit malaria. Mosquito gut bacteria are shown to influence the outcome of infections with Plasmodium parasites and are also thought to exert a strong drive on genetic variation through natural selection; however, a link between antibacterial effects and genetic variation is yet to emerge. Here, we combined SNP genotyping and expression profiling with phenotypic analyses of candidate genes by RNAi-mediated silencing and 454 pyrosequencing to investigate this intricate biological system. We identified 138 An. gambiae genes to be genetically associated with the outcome of Serratia marcescens infection, including the peptidoglycan recognition receptor PGRPLC that triggers activation of the antibacterial IMD/REL2 pathway and the epidermal growth factor receptor EGFR. Silencing of three genes encoding type III fibronectin domain proteins (FN3Ds) increased the Serratia load and altered the gut microbiota composition in favor of Enterobacteriaceae. These data suggest that natural genetic variation in immune-related genes can shape the bacterial population structure of the mosquito gut with high specificity. Importantly, FN3D2 encodes a homolog of the hypervariable pattern recognition receptor Dscam, suggesting that pathogen-specific recognition may involve a broader family of immune factors. Additionally, we showed that silencing the gene encoding the gustatory receptor Gr9 that is also associated with the Serratia infection phenotype drastically increased Serratia levels. The Gr9 antibacterial activity appears to be related to mosquito feeding behavior and to mostly rely on changes of neuropeptide F expression, together suggesting a behavioral immune response following Serratia infection. Our findings reveal that the mosquito response to oral Serratia infection comprises both an epithelial and a behavioral immune component.

In malaria vector mosquitoes, the presence of bacteria and malaria parasites is tightly linked. Bacteria that are part of the mosquito gut ecosystem are critical modulators of the immune response elicited during infection with malaria parasites. Furthermore, responses against oral bacterial infections can affect malaria parasites. Here, we combined mosquito gut infections with the enterobacterium Serratia marcescens with genome-wide discovery and phenotypic analysis of genes involved in antibacterial responses to characterize molecular processes that control gut bacterial infections thus possibly affecting the mosquito susceptibility to infection by malaria parasites. Our data reveal complex genetic networks controlling the gut bacterial infection load and ecosystem homeostasis. These networks appear to exhibit much higher specificity toward specific classes of bacteria than previously thought and include behavioral response circuits involved in antibacterial immunity.

Screen of whole blood responses to flagellin identifies TLR5 variation associated with outcome in melioidosis

Melioidosis is a severe infection caused by the flagellated bacterium Burkholderia pseudomallei. The nonsense polymorphism TLR51174C>T is associated with improved outcome in Thais with melioidosis. We hypothesized that other TLR5 variants may modulate the host response and determine outcome in melioidosis. We genotyped 12 TLR5 variants selected de novo from the HapMap database and examined the association of each with cytokines induced by flagellin stimulation of whole blood from healthy Thai subjects. We found a blunted cytokine response for three related markers that were in linkage disequilibrium (LD) with a non-synonymous variant, TLR51846T>C. Carriers of TLR51846T>C had broadly impaired cytokine responses induced by flagellin. TLR51846T>C was associated with protection against death in melioidosis patients (odds ratio: 0.62, 95% confidence interval: 0.42-0.93, P=0.021). We observed no impairment in TLR51846C-dependent nuclear factor κB activation, however, suggesting an alternative mechanism for the effect. We found that TLR51846T>C was in strong LD with TLR51174C>T. Many of the blunted cytokine responses observed and the association of TLR51846T>C with survival in melioidosis patients may be attributable to TLR51174C>T, but we could not exclude an independent effect of TLR51846T>C. These data identify novel associations for TLR51846T>C, enhance our understanding of TLR5 genetic architecture in Thais and highlight the role of TLR5 in melioidosis.

Extreme population differences in the human zinc transporter ZIP4 (SLC39A4) are explained by positive selection in Sub-Saharan Africa

Extreme differences in allele frequency between West Africans and Eurasians were observed for a leucine-to-valine substitution (Leu372Val) in the human intestinal zinc uptake transporter, ZIP4, yet no further evidence was found for a selective sweep around the ZIP4 gene (SLC39A4). By interrogating allele frequencies in more than 100 diverse human populations and resequencing Neanderthal DNA, we confirmed the ancestral state of this locus and found a strong geographical gradient for the derived allele (Val372), with near fixation in West Africa. In extensive coalescent simulations, we show that the extreme differences in allele frequency, yet absence of a classical sweep signature, can be explained by the effect of a local recombination hotspot, together with directional selection favoring the Val372 allele in Sub-Saharan Africans. The possible functional effect of the Leu372Val substitution, together with two pathological mutations at the same codon (Leu372Pro and Leu372Arg) that cause acrodermatitis enteropathica (a disease phenotype characterized by extreme zinc deficiency), was investigated by transient overexpression of human ZIP4 protein in HeLa cells. Both acrodermatitis mutations cause absence of the ZIP4 transporter cell surface expression and nearly absent zinc uptake, while the Val372 variant displayed significantly reduced surface protein expression, reduced basal levels of intracellular zinc, and reduced zinc uptake in comparison with the Leu372 variant. We speculate that reduced zinc uptake by the ZIP4-derived Val372 isoform may act by starving certain pathogens of zinc, and hence may have been advantageous in Sub-Saharan Africa. Moreover, these functional results may indicate differences in zinc homeostasis among modern human populations with possible relevance for disease risk.

The role of microhomology in genomic structural variation

Genomic structural variation, which can be defined as differences in the copy number, orientation, or location of relatively large DNA segments, is not only crucial in evolution, but also gives rise to genomic disorders. Whereas the major mechanisms that generate structural variation have been well characterised, insights into additional mechanisms are emerging from the identification of short regions of DNA sequence homology, also known as microhomology, at chromosomal breakpoints. In addition, functional studies are elucidating the characteristics of microhomology-mediated pathways, which are mutagenic. Here, we describe the features and mechanistic models of microhomology-mediated events, discuss their physiological and pathological significance, and highlight recent advances in this rapidly evolving field of research.

Natural selection in a bangladeshi population from the cholera-endemic ganges river delta

As an ancient disease with high fatality, cholera has likely exerted strong selective pressure on affected human populations. We performed a genome-wide study of natural selection in a population from the Ganges River Delta, the historic geographic epicenter of cholera. We identified 305 candidate selected regions using the composite of multiple signals (CMS) method. The regions were enriched for potassium channel genes involved in cyclic adenosine monophosphate-mediated chloride secretion and for components of the innate immune system involved in nuclear factor κB (NF-κB) signaling. We demonstrate that a number of these strongly selected genes are associated with cholera susceptibility in two separate cohorts. We further identify repeated examples of selection and association in an NF-κB/inflammasome-dependent pathway that is activated in vitro by Vibrio cholerae. Our findings shed light on the genetic basis of cholera resistance in a population from the Ganges River Delta and present a promising approach for identifying genetic factors influencing susceptibility to infectious diseases.

Genome-scale analysis of demographic history and adaptive selection

One of the main topics in population genetics is identification of adaptive selection among populations. For this purpose, population history should be correctly inferred to evaluate the effect of random drift and exclude it in selection identification. With the rapid progress in genomics in the past decade, vast genome-scale variations are available for population genetic analysis, which however requires more sophisticated models to infer species' demographic history and robust methods to detect local adaptation. Here we aim to review what have been achieved in the fields of demographic modeling and selection detection. We summarize their rationales, implementations, and some classical applications. We also propose that some widely-used methods can be improved in both theoretical and practical aspects in near future.

Derived immune and ancestral pigmentation alleles in a 7,000-year-old Mesolithic European

Ancient genomic sequences have started to reveal the origin and the demographic impact of farmers from the Neolithic period spreading into Europe. The adoption of farming, stock breeding and sedentary societies during the Neolithic may have resulted in adaptive changes in genes associated with immunity and diet. However, the limited data available from earlier hunter-gatherers preclude an understanding of the selective processes associated with this crucial transition to agriculture in recent human evolution. Here we sequence an approximately 7,000-year-old Mesolithic skeleton discovered at the La Braña-Arintero site in León, Spain, to retrieve a complete pre-agricultural European human genome. Analysis of this genome in the context of other ancient samples suggests the existence of a common ancient genomic signature across western and central Eurasia from the Upper Paleolithic to the Mesolithic. The La Braña individual carries ancestral alleles in several skin pigmentation genes, suggesting that the light skin of modern Europeans was not yet ubiquitous in Mesolithic times. Moreover, we provide evidence that a significant number of derived, putatively adaptive variants associated with pathogen resistance in modern Europeans were already present in this hunter-gatherer.

Genes associated with SLE are targets of recent positive selection

The reasons for the ethnic disparities in the prevalence of systemic lupus erythematosus (SLE) and the relative high frequency of SLE risk alleles in the population are not fully understood. Population genetic factors such as natural selection alter allele frequencies over generations and may help explain the persistence of such common risk variants in the population and the differential risk of SLE. In order to better understand the genetic basis of SLE that might be due to natural selection, a total of 74 genomic regions with compelling evidence for association with SLE were tested for evidence of recent positive selection in the HapMap and HGDP populations, using population differentiation, allele frequency, and haplotype-based tests. Consistent signs of positive selection across different studies and statistical methods were observed at several SLE-associated loci, including PTPN22, TNFSF4, TET3-DGUOK, TNIP1, UHRF1BP1, BLK, and ITGAM genes. This study is the first to evaluate and report that several SLE-associated regions show signs of positive natural selection. These results provide corroborating evidence in support of recent positive selection as one mechanism underlying the elevated population frequency of SLE risk loci and supports future research that integrates signals of natural selection to help identify functional SLE risk alleles.

Toll-like receptor genetic variants and colorectal cancer

Single-nucleotide polymorphisms in Toll-like receptor 5 (TLR5), encoding a sensor for flagellin, have been shown to influence cytokine responses to intestinal bacteria and to be associated with significant alterations in the survival of colorectal carcinoma (CRC) patients. These findings point to a link between TLRs and CRC that may have both therapeutic and prognostic/predictive implications.

dbPSHP: a database of recent positive selection across human populations

The dbPSHP database (http://jjwanglab.org/dbpshp) aims to help researchers to efficiently identify, validate and visualize putative positively selected loci in human evolution and further discover the mechanism governing these natural selections. Recent evolution of human populations at the genomic level reflects the adaptations to the living environments, including climate change and availability and stability of nutrients. Many genetic regions under positive selection have been identified, which assist us to understand how natural selection has shaped population differences. Here, we manually collect recent positive selections in different human populations, consisting of 15,472 loci from 132 publications. We further compiled a database that used 15 statistical terms of different evolutionary attributes for single nucleotide variant sites from the HapMap 3 and 1000 Genomes Project to identify putative regions under positive selection. These attributes include variant allele/genotype properties, variant heterozygosity, within population diversity, long-range haplotypes, pairwise population differentiation and evolutionary conservation. We also provide interactive pages for visualization and annotation of different selective signals. The database is freely available to the public and will be frequently updated.

Low frequency variants, collapsed based on biological knowledge, uncover complexity of population stratification in 1000 genomes project data

Analyses investigating low frequency variants have the potential for explaining additional genetic heritability of many complex human traits. However, the natural frequencies of rare variation between human populations strongly confound genetic analyses. We have applied a novel collapsing method to identify biological features with low frequency variant burden differences in thirteen populations sequenced by the 1000 Genomes Project. Our flexible collapsing tool utilizes expert biological knowledge from multiple publicly available database sources to direct feature selection. Variants were collapsed according to genetically driven features, such as evolutionary conserved regions, regulatory regions genes, and pathways. We have conducted an extensive comparison of low frequency variant burden differences (MAF<0.03) between populations from 1000 Genomes Project Phase I data. We found that on average 26.87% of gene bins, 35.47% of intergenic bins, 42.85% of pathway bins, 14.86% of ORegAnno regulatory bins, and 5.97% of evolutionary conserved regions show statistically significant differences in low frequency variant burden across populations from the 1000 Genomes Project. The proportion of bins with significant differences in low frequency burden depends on the ancestral similarity of the two populations compared and types of features tested. Even closely related populations had notable differences in low frequency burden, but fewer differences than populations from different continents. Furthermore, conserved or functionally relevant regions had fewer significant differences in low frequency burden than regions under less evolutionary constraint. This degree of low frequency variant differentiation across diverse populations and feature elements highlights the critical importance of considering population stratification in the new era of DNA sequencing and low frequency variant genomic analyses.

Low frequency variants are likely to play an important role in uncovering complex trait heritability; however, they are often continent or population specific. This specificity complicates genetic analyses investigating low frequency variants for two reasons: low frequency variant signals in an association test are often difficult to generalize beyond a single population or continental group, and there is an increase in false positive results in association analyses due to underlying population stratification. In order to reveal the magnitude of low frequency population stratification, we performed pairwise population comparisons using the 1000 Genomes Project Phase I data to investigate differences in low frequency variant burden across multiple biological features. We found that low frequency variant confounding is much more prevalent than one might expect, even within continental groups. The proportion of significant differences in low frequency variant burden was also dependent on the region of interest; for example, annotated regulatory regions showed fewer low frequency burden differences between populations than intergenic regions. Knowledge of population structure and the genomic landscape in a region of interest are important factors in determining the extent of confounding due to population stratification in a low frequency genomic analysis.

Recent human adaptation: genomic approaches, interpretation and insights

The recent availability of genomic data has spurred many genome-wide studies of human adaptation in different populations worldwide. Such studies have provided insights into novel candidate genes and pathways that are putatively involved in adaptation to different environments, diets and disease prevalence. However, much work is needed to translate these results into candidate adaptive variants that are biologically interpretable. In this Review, we discuss methods that may help to identify true biological signals of selection and studies that incorporate complementary phenotypic and functional data. We conclude with recommendations for future studies that focus on opportunities to use integrative genomics methodologies in human adaptation studies.

An ABC method for estimating the rate and distribution of effects of beneficial mutations

Determining the distribution of adaptive mutations available to natural selection is a difficult task. These are rare events and most of them are lost by chance. Some theoretical works propose that the distribution of newly arising beneficial mutations should be close to exponential. Empirical data are scarce and do not always support an exponential distribution. Analysis of the dynamics of adaptation in asexual populations of microorganisms has revealed that these can be summarized by two effective parameters, the effective mutation rate, U_e, and the effective selection coefficient of a beneficial mutation, S_e. Here, we show that these effective parameters will not always reflect the rate and mean effect of beneficial mutations, especially when the distribution of arising mutations has high variance, and the mutation rate is high. We propose a method to estimate the distribution of arising beneficial mutations, which is motivated by a common experimental setup. The method, which we call One Biallelic Marker Approximate Bayesian Computation, makes use of experimental data consisting of periodic measures of neutral marker frequencies and mean population fitness. Using simulations, we find that this method allows the discrimination of the shape of the distribution of arising mutations and that it provides reasonable estimates of their rates and mean effects in ranges of the parameter space that may be of biological relevance.

Signatures of natural selection on genetic variants affecting complex human traits

It has recently been hypothesized that polygenic adaptation, resulting in modest allele frequency changes at many loci, could be a major mechanism behind the adaptation of complex phenotypes in human populations. Here we leverage the large number of variants that have been identified through genome-wide association (GWA) studies to comprehensively study signatures of natural selection on genetic variants associated with complex traits. Using population differentiation based methods, such as FST and phylogenetic branch length analyses, we systematically examined nearly 1300 SNPs associated with 38 complex phenotypes. Instead of detecting selection signatures at individual variants, we aimed to identify combined evidence of natural selection by aggregating signals across many trait associated SNPs. Our results have revealed some general features of polygenic selection on complex traits associated variants. First, natural selection acting on standing variants associated with complex traits is a common phenomenon. Second, characteristics of selection for different polygenic traits vary both temporarily and geographically. Third, some studied traits (e.g. height and urate level) could have been the primary targets of selection, as indicated by the significant correlation between the effect sizes and the estimated strength of selection in the trait associated variants; however, for most traits, the allele frequency changes in trait associated variants might have been driven by the selection on other correlated phenotypes. Fourth, the changes in allele frequencies as a result of selection can be highly stochastic, such that, polygenic adaptation may accelerate differentiation in allele frequencies among populations, but generally does not produce predictable directional changes. Fifth, multiple mechanisms (pleiotropy, hitchhiking, etc) may act together to govern the changes in allele frequencies of genetic variants associated with complex traits.

1000 Genomes Selection Browser 1.0: a genome browser dedicated to signatures of natural selection in modern humans

Searching for Darwinian selection in natural populations has been the focus of a multitude of studies over the last decades. Here we present the 1000 Genomes Selection Browser 1.0 (http://hsb.upf.edu) as a resource for signatures of recent natural selection in modern humans. We have implemented and applied a large number of neutrality tests as well as summary statistics informative for the action of selection such as Tajima’s D, CLR, Fay and Wu’s H, Fu and Li’s F* and D*, XPEHH, ΔiHH, iHS, F_ST, ΔDAF and XPCLR among others to low coverage sequencing data from the 1000 genomes project (Phase 1; release April 2012). We have implemented a publicly available genome-wide browser to communicate the results from three different populations of West African, Northern European and East Asian ancestry (YRI, CEU, CHB). Information is provided in UCSC-style format to facilitate the integration with the rich UCSC browser tracks and an access page is provided with instructions and for convenient visualization. We believe that this expandable resource will facilitate the interpretation of signals of selection on different temporal, geographical and genomic scales.

Population Genomics of Human Adaptation

Recent advances in genotyping technologies have facilitated genome-wide scans for natural selection. Identification of targets of natural selection will shed light on processes of human adaptation and evolution and could be important for identifying variation that influences both normal human phenotypic variation as well as disease susceptibility. Here we focus on studies of natural selection in modern humans who originated ~200,000 years go in Africa and migrated across the globe ~50,000 - 100,000 years ago. Movement into new environments, as well as changes in culture and technology including plant and animal domestication, resulted in local adaptation to diverse environments. We summarize statistical approaches for detecting targets of natural selection and for distinguishing the effects of demographic history from natural selection. On a genome-wide scale, immune-related genes appear to be major targets of positive selection. Genes associated with reproduction and fertility also appear to be fast evolving. Additional examples of recent human adaptation include genes associated with lactase persistence, eccrine glands, and response to hypoxia. Lastly, we emphasize the need to supplement scans of selection with functional studies to demonstrate the physiologic impact of candidate loci.

Super-enhancers in the control of cell identity and disease

Super-enhancers are large clusters of transcriptional enhancers that drive expression of genes that define cell identity. Improved understanding of the roles that super-enhancers play in biology would be afforded by knowing the constellation of factors that constitute these domains and by identifying super-enhancers across the spectrum of human cell types. We describe here the population of transcription factors, cofactors, chromatin regulators, and transcription apparatus occupying super-enhancers in embryonic stem cells and evidence that super-enhancers are highly transcribed. We produce a catalog of super-enhancers in a broad range of human cell types and find that super-enhancers associate with genes that control and define the biology of these cells. Interestingly, disease-associated variation is especially enriched in the super-enhancers of disease-relevant cell types. Furthermore, we find that cancer cells generate super-enhancers at oncogenes and other genes important in tumor pathogenesis. Thus, super-enhancers play key roles in human cell identity in health and in disease.

Origin and differential selection of allelic variation at TAS2R16 associated with salicin bitter taste sensitivity in Africa

Bitter taste perception influences human nutrition and health, and the genetic variation underlying this trait may play a role in disease susceptibility. To better understand the genetic architecture and patterns of phenotypic variability of bitter taste perception, we sequenced a 996 bp region, encompassing the coding exon of TAS2R16, a bitter taste receptor gene, in 595 individuals from 74 African populations and in 94 non-Africans from 11 populations. We also performed genotype-phenotype association analyses of threshold levels of sensitivity to salicin, a bitter anti-inflammatory compound, in 296 individuals from Central and East Africa. In addition, we characterized TAS2R16 mutants in vitro to investigate the effects of polymorphic loci identified at this locus on receptor function. Here, we report striking signatures of positive selection, including significant Fay and Wu's H statistics predominantly in East Africa, indicating strong local adaptation and greater genetic structure among African populations than expected under neutrality. Furthermore, we observed a "star-like" phylogeny for haplotypes with the derived allele at polymorphic site 516 associated with increased bitter taste perception that is consistent with a model of selection for "high-sensitivity" variation. In contrast, haplotypes carrying the "low-sensitivity" ancestral allele at site 516 showed evidence of strong purifying selection. We also demonstrated, for the first time, the functional effect of nonsynonymous variation at site 516 on salicin phenotypic variance in vivo in diverse Africans and showed that most other nonsynonymous substitutions have weak or no effect on cell surface expression in vitro, suggesting that one main polymorphism at TAS2R16 influences salicin recognition. Additionally, we detected geographic differences in levels of bitter taste perception in Africa not previously reported and infer an East African origin for high salicin sensitivity in human populations.

Comparative genomics as a tool to understand evolution and disease

When the human genome project started, the major challenge was how to sequence a 3 billion letter code in an organized and cost-effective manner. When completed, the project had laid the foundation for a huge variety of biomedical fields through the production of a complete human genome sequence, but also had driven the development of laboratory and analytical methods that could produce large amounts of sequencing data cheaply. These technological developments made possible the sequencing of many more vertebrate genomes, which have been necessary for the interpretation of the human genome. They have also enabled large-scale studies of vertebrate genome evolution, as well as comparative and human medicine. In this review, we give examples of evolutionary analysis using a wide variety of time frames—from the comparison of populations within a species to the comparison of species separated by at least 300 million years. Furthermore, we anticipate discoveries related to evolutionary mechanisms, adaptation, and disease to quickly accelerate in the coming years.

Visualizing genomic information across chromosomes with PhenoGram

Background

With the abundance of information and analysis results being collected for genetic loci, user-friendly and flexible data visualization approaches can inform and improve the analysis and dissemination of these data. A chromosomal ideogram is an idealized graphic representation of chromosomes. Ideograms can be combined with overlaid points, lines, and/or shapes, to provide summary information from studies of various kinds, such as genome-wide association studies or phenome-wide association studies, coupled with genomic location information. To facilitate visualizing varied data in multiple ways using ideograms, we have developed a flexible software tool called PhenoGram which exists as a web-based tool and also a command-line program.

Results

With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail. We have now used PhenoGram to produce a variety of different plots, and provide these as examples herein. These plots include visualization of the genomic coverage of SNPs from a genotyping array, highlighting the chromosomal coverage of imputed SNPs, copy-number variation region coverage, as well as plots similar to the NHGRI GWA Catalog of genome-wide association results.

Conclusions

PhenoGram is a versatile, user-friendly software tool fostering the exploration and sharing of genomic information. Through visualization of data, researchers can both explore and share complex results, facilitating a greater understanding of these data.

Integrative annotation of variants from 1092 humans: application to cancer genomics

Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations ("ultrasensitive") and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, "motif-breakers"). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.

Global patterns of diversity and selection in human tyrosinase gene

Global variation in skin pigmentation is one of the most striking examples of environmental adaptation in humans. More than two hundred loci have been identified as candidate genes in model organisms and a few tens of these have been found to be significantly associated with human skin pigmentation in genome-wide association studies. However, the evolutionary history of different pigmentation genes is rather complex: some loci have been subjected to strong positive selection, while others evolved under the relaxation of functional constraints in low UV environment. Here we report the results of a global study of the human tyrosinase gene, which is one of the key enzymes in melanin production, to assess the role of its variation in the evolution of skin pigmentation differences among human populations. We observe a higher rate of non-synonymous polymorphisms in the European sample consistent with the relaxation of selective constraints. A similar pattern was previously observed in the MC1R gene and concurs with UV radiation-driven model of skin color evolution by which mutations leading to lower melanin levels and decreased photoprotection are subject to purifying selection at low latitudes while being tolerated or even favored at higher latitudes because they facilitate UV-dependent vitamin D production. Our coalescent date estimates suggest that the non-synonymous variants, which are frequent in Europe and North Africa, are recent and have emerged after the separation of East and West Eurasian populations.

Costimulatory genes: hotspots of conflict between host defense and autoimmunity

To understand the adaptations of costimulatory molecules through mammalian evolution, Forni et al. (Forni et al., 2013) studied evolutionary selection in key costimulatory genes. Their results, presented in this issue of Immunity, suggest that the risk of autoimmmunity is balanced against efficacy of the anti-pathogen immune response.

Different selective pressures shape the evolution of Toll-like receptors in human and African great ape populations

The study of the genetic and selective landscape of immunity genes across primates can provide insight into the existing differences in susceptibility to infection observed between human and non-human primates. Here, we explored how selection has driven the evolution of a key family of innate immunity receptors, the Toll-like receptors (TLRs), in African great ape species. We sequenced the 10 TLRs in various populations of chimpanzees and gorillas, and analysed these data jointly with a human data set. We found that purifying selection has been more pervasive in great apes than in humans. Furthermore, in chimpanzees and gorillas, purifying selection has targeted TLRs irrespectively of whether they are endosomal or cell surface, in contrast to humans where strong selective constraints are restricted to endosomal TLRs. These observations suggest important differences in the relative importance of TLR-mediated pathogen sensing, such as that of recognition of flagellated bacteria by TLR5, between humans and great apes. Lastly, we used a population genetics-phylogenetics method that jointly analyses polymorphism and divergence data to detect fine-scale variation in selection pressures at specific codons within TLR genes. We identified different codons at different TLRs as being under positive selection in each species, highlighting that functional variation at these genes has conferred a selective advantage in immunity to infection to specific primate species. Overall, this study showed that the degree of selection driving the evolution of TLRs has largely differed between human and non-human primates, increasing our knowledge on their respective biological contribution to host defence in the natural setting.

Exploring signatures of positive selection in pigmentation candidate genes in populations of East Asian ancestry

Background

Currently, there is very limited knowledge about the genes involved in normal pigmentation variation in East Asian populations. We carried out a genome-wide scan of signatures of positive selection using the 1000 Genomes Phase I dataset, in order to identify pigmentation genes showing putative signatures of selective sweeps in East Asia. We applied a broad range of methods to detect signatures of selection including: 1) Tests designed to identify deviations of the Site Frequency Spectrum (SFS) from neutral expectations (Tajima’s D, Fay and Wu’s H and Fu and Li’s D* and F*), 2) Tests focused on the identification of high-frequency haplotypes with extended linkage disequilibrium (iHS and Rsb) and 3) Tests based on genetic differentiation between populations (LSBL). Based on the results obtained from a genome wide analysis of 25 kb windows, we constructed an empirical distribution for each statistic across all windows, and identified pigmentation genes that are outliers in the distribution.

Results

Our tests identified twenty genes that are relevant for pigmentation biology. Of these, eight genes (ATRN, EDAR, KLHL7, MITF, OCA2, TH, TMEM33 and TRPM1,) were extreme outliers (top 0.1% of the empirical distribution) for at least one statistic, and twelve genes (ADAM17, BNC2, CTSD, DCT, EGFR, LYST, MC1R, MLPH, OPRM1, PDIA6, PMEL (SILV) and TYRP1) were in the top 1% of the empirical distribution for at least one statistic. Additionally, eight of these genes (BNC2, EGFR, LYST, MC1R, OCA2, OPRM1, PMEL (SILV) and TYRP1) have been associated with pigmentary traits in association studies.

Conclusions

We identified a number of putative pigmentation genes showing extremely unusual patterns of genetic variation in East Asia. Most of these genes are outliers for different tests and/or different populations, and have already been described in previous scans for positive selection, providing strong support to the hypothesis that recent selective sweeps left a signature in these regions. However, it will be necessary to carry out association and functional studies to demonstrate the implication of these genes in normal pigmentation variation.

Selection and adaptation in the human genome

An enduring goal of evolutionary biology is to understand how natural selection has shaped patterns of polymorphism and divergence within and between species and to map the genetic basis of adaptations. The rapid maturation of next-generation sequencing technology has generated a deluge of genomics data from nonhuman primates, extinct hominins, and diverse human populations. These emerging genome data sets have simultaneously broadened our understanding of human evolution and sharply defined existing gaps in knowledge about the mechanistic basis of evolutionary change. In this review, we summarize recent insights into how natural selection has influenced the human genome across different timescales. Although the path to a more comprehensive understanding of selection and adaptation in humans remains arduous, some general insights are beginning to emerge, such as the importance of adaptive regulatory evolution, the absence of pervasive classic selective sweeps, and the potential roles that selection from standing variation and polygenic adaptation have likely played in recent human evolutionary history.

Nutrient-dependent/pheromone-controlled adaptive evolution: a model

BACKGROUND

The prenatal migration of gonadotropin-releasing hormone (GnRH) neurosecretory neurons allows nutrients and human pheromones to alter GnRH pulsatility, which modulates the concurrent maturation of the neuroendocrine, reproductive, and central nervous systems, thus influencing the development of ingestive behavior, reproductive sexual behavior, and other behaviors.

METHODS

THIS MODEL DETAILS HOW CHEMICAL ECOLOGY DRIVES ADAPTIVE EVOLUTION VIA: (1) ecological niche construction, (2) social niche construction, (3) neurogenic niche construction, and (4) socio-cognitive niche construction. This model exemplifies the epigenetic effects of olfactory/pheromonal conditioning, which alters genetically predisposed, nutrient-dependent, hormone-driven mammalian behavior and choices for pheromones that control reproduction via their effects on luteinizing hormone (LH) and systems biology.

RESULTS

Nutrients are metabolized to pheromones that condition behavior in the same way that food odors condition behavior associated with food preferences. The epigenetic effects of olfactory/pheromonal input calibrate and standardize molecular mechanisms for genetically predisposed receptor-mediated changes in intracellular signaling and stochastic gene expression in GnRH neurosecretory neurons of brain tissue. For example, glucose and pheromones alter the hypothalamic secretion of GnRH and LH. A form of GnRH associated with sexual orientation in yeasts links control of the feedback loops and developmental processes required for nutrient acquisition, movement, reproduction, and the diversification of species from microbes to man.

CONCLUSION

An environmental drive evolved from that of nutrient ingestion in unicellular organisms to that of pheromone-controlled socialization in insects. In mammals, food odors and pheromones cause changes in hormones such as LH, which has developmental affects on pheromone-controlled sexual behavior in nutrient-dependent reproductively fit individuals across species of vertebrates.