Hitchhiking mapping reveals a candidate genomic region for natural selection in three-spined stickleback chromosome VIII

Identification of genes and genomic regions under directional natural selection has become one of the major goals in evolutionary genetics, but relatively little work to this end has been done by applying hitchhiking mapping to wild populations. Hitchhiking mapping starts from a genome scan using a randomly spaced set of molecular markers followed by a fine-scale analysis in the flanking regions of the candidate regions under selection. We used the hitchhiking mapping approach to narrow down a selective sweep in the genomic region flanking a candidate locus (Stn90) in chromosome VIII in the three-spined stickleback (Gasterosteus aculeatus). Twenty-four microsatellite markers were screened in an approximately 800-kb region around the candidate locus in three marine and four freshwater populations. The patterns of genetic diversity and differentiation in the candidate region were compared to those of a putatively neutral set of markers. The Bayesian FST-test indicated an elevated genetic differentiation, deviating significantly from neutral expectations, at a continuous region of approximately 20 kb upstream from the candidate locus. Furthermore, a method developed for an array of microsatellite markers rejected neutrality in a region of approximately 90 kb flanking the candidate locus supporting the selective sweep hypothesis. Likewise, the genomewide pattern of genetic diversity differed from the candidate region in a bottleneck analysis suggesting that selection, rather than demography, explains the reduced genetic diversity at the candidate interval. The neutrality tests suggest that the selective sweep had occurred mainly in the Lake Pulmanki population, but the results from bottleneck analyses indicate that selection might have operated in other populations as well. These results suggest that the narrow interval around locus Stn90 has likely been under directional selection, but the region contains several predicted genes, each of which can be the actual targets of selection. Understanding of the functional significance of this genomic region in an ecological context will require a more detailed sequence analysis.     

Genetic analysis of differentiation among breeding ponds reveals a candidate gene for local adaptation in Rana arvalis

One of the main questions in evolutionary and conservation biology is how geographical and environmental features of the landscape shape neutral and adaptive genetic variation in natural populations. The identification of genomic polymorphisms that account for adaptive variation can aid in finding candidate loci for local adaptation. Consequently, a comparison of spatial patterns in neutral markers and loci under selection may help disentangle the effects of gene flow, genetic drift and selection at the landscape scale. Many amphibians breed in wetlands, which differ in environmental conditions and in the degree of isolation, enhancing the potential for local adaptation. We used microsatellite markers to measure genetic differentiation among 17 local populations of Rana arvalis breeding in a network of wetlands. We found that locus RC08604 deviated from neutral expectations, suggesting that it is a good candidate for directional selection. We used a genetic network analysis to show that the allele distribution in this locus is correlated with habitat characteristics, whereas this was not the case at neutral markers that displayed a different allele distribution and population network in the study area. The graph approach illustrated the genomic heterogeneity (neutral loci vs. the candidate locus for directional selection) of gene exchange and genetic divergence among populations under directional selection. Limited gene flow between wetlands was only observed at the candidate genomic region under directional selection. RC08604 is partially located inside an up‐regulated thyroid‐hormone receptor (TRβ) gene coordinating the expression of other genes during metamorphosis and appears to be linked with variation in larval life‐history traits found among R. arvalis populations. We suggest that directional selection on genes coding larval life‐history traits is strong enough to maintain the divergence in these genomic regions, reducing the effective recombination of locally adapted alleles but not in other regions of the genome. Integrating this knowledge into conservation plans at the landscape scale will improve the design of management strategies to preserve adaptive genetic diversity in wetland networks.     

2型糖尿病易感候选基因在世界不同人群中的多样性比较分析

近10年来兴起的全基因组关联分析（Genome-wide association study, GWAS）相关研究结果获得了大量与2型糖尿病相关的候选易感基因,了解这些候选基因在正常人群中的遗传多样性程度以及在不同人群间的遗传差异,不但有助于阐明2型糖尿病的遗传机理,而且对于今后在特定人群中进行2型糖尿病发病机制的深入研究具有指导意义。本研究通过对GWAS数据库和相关文献的搜索和整理确定了170个与2型糖尿病相关的基因或基因区域;随后基于千人基因组计划的全基因组测序数据对这些候选基因在世界范围内14个人群间的遗传多样性进行了比较分析;进一步确定了在人群间存在显著差异的易感基因,并分析了这些基因的多样性特征。在所研究的14个世界人群中,2型糖尿病候选易感基因的遗传多样性与基因组范围的平均水平没有显著差异;但其中8个易感基因IL20RA、RNMTL1-NXN、NOTCH2、ADRA2A-BTBD7P2、TBC1D4、RBM38-HMGB1P1、UBE2E2和PPARD在群体间呈现显著差异,其中最明显的是IL20RA基因 (FST=0.152),该易感基因在非洲人群和非非洲人群间存在显著等位基因频率和单倍型频率差异。14个人群中易感基因遗传结构差异的主要原因是由于非洲人群与非非洲人群之间的群体遗传结构的不同所造成的。进一步比较东西方人群间的2型糖尿病候选基因遗传结构差异,发现在东西方人群中同样存在明显的群体遗传结构差别,其中DGKB-AGMO(FST=0.173)和JAZF1(FST=0.182)是差异最显著的易感基因。本研究通过对群体间2型糖尿病易感基因遗传结构进行比较,鉴别出一些差异特别显著的易感基因,对今后2型糖尿病易感基因与不同人群间发病率和易感性差异的相关研究提供重要参考。     

Scanning the genome for gene single nucleotide polymorphisms involved in adaptive population differentiation in white spruce

Conifers are characterized by a large genome size and a rapid decay of linkage disequilibrium, most often within gene limits. Genome scans based on noncoding markers are less likely to detect molecular adaptation linked to genes in these species. In this study, we assessed the effectiveness of a genome-wide single nucleotide polymorphism (SNP) scan focused on expressed genes in detecting local adaptation in a conifer species. Samples were collected from six natural populations of white spruce ( Picea glauca ) moderately differentiated for several quantitative characters. A total of 534 SNPs representing 345 expressed genes were analysed. Genes potentially under natural selection were identified by estimating the differentiation in SNP frequencies among populations ( F _ST) and identifying outliers, and by estimating local differentiation using a Bayesian approach. Both average expected heterozygosity and population differentiation estimates ( H _E = 0.270 and F _ST = 0.006) were comparable to those obtained with other genetic markers. Of all genes, 5.5% were identified as outliers with F _ST at the 95% confidence level, while 14% were identified as candidates for local adaptation with the Bayesian method. There was some overlap between the two gene sets. More than half of the candidate genes for local adaptation were specific to the warmest population, about 20% to the most arid population, and 15% to the coldest and most humid higher altitude population. These adaptive trends were consistent with the genes' putative functions and the divergence in quantitative traits noted among the populations. The results suggest that an approach separating the locus and population effects is useful to identify genes potentially under selection. These candidates are worth exploring in more details at the physiological and ecological levels.     

Widespread Signals of Convergent Adaptation to High Altitude in Asia and America

Living at high altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean, and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can also be due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP data set from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high-altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.     

Intrapopulation genomics in a model mutualist: Population structure and candidate symbiosis genes under selection in Medicago truncatula

Bottom‐up evolutionary approaches, including geographically explicit population genomic analyses, have the power to reveal the mechanistic basis of adaptation. Here, we conduct a population genomic analysis in the model legume, Medicago truncatula, to characterize population genetic structure and identify symbiosis‐related genes showing evidence of spatially variable selection. Using RAD‐seq, we generated over 26,000 SNPs from 191 accessions from within three regions of the native range in Europe. Results from STRUCTURE analysis identify five distinct genetic clusters with divisions that separate east and west regions in the Mediterranean basin. Much of the genetic variation is maintained within sampling sites, and there is evidence for isolation by distance. Extensive linkage disequilibrium was identified, particularly within populations. We conducted genetic outlier analysis with F_ST‐based genome scans and a Bayesian modeling approach (PCAdapt). There were 70 core outlier loci shared between these distinct methods with one clear candidate symbiosis related gene, DMI1. This work sets that stage for functional experiments to determine the important phenotypes that selection has acted upon and complementary efforts in rhizobium populations.     

Inference with selection,varying population size,and evolving population structure: application of ABC to a forward–backward coalescent process with interactions

Genetic data are often used to infer demographic history and changes or detect genes under selection. Inferential methods are commonly based on models making various strong assumptions: demography and population structures are supposed a priori known, the evolution of the genetic composition of a population does not affect demography nor population structure, and there is no selection nor interaction between and within genetic strains. In this paper, we present a stochastic birth-death model with competitive interactions and asexual reproduction. We develop an inferential procedure for ecological, demographic, and genetic parameters. We first show how genetic diversity and genealogies are related to birth and death rates, and to how individuals compete within and between strains. This leads us to propose an original model of phylogenies, with trait structure and interactions, that allows multiple merging. Second, we develop an Approximate Bayesian Computation framework to use our model for analyzing genetic data. We apply our procedure to simulated data from a toy model, and to real data by analyzing the genetic diversity of microsatellites on Y-chromosomes sampled from Central Asia human populations in order to test whether different social organizations show significantly different fertilities.Subject terms: Genetic variation, Phylogenetics, Ecological genetics     

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.     

A Genomic Portrait of Haplotype Diversity and Signatures of Selection in Indigenous Southern African Populations

We report a study of genome-wide, dense SNP (∼900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region.     

Genetic Variation and Recent Positive Selection in Worldwide Human Populations: Evidence from Nearly 1 Million SNPs

Background

Genome-wide scans of hundreds of thousands of single-nucleotide polymorphisms (SNPs) have resulted in the identification of new susceptibility variants to common diseases and are providing new insights into the genetic structure and relationships of human populations. Moreover, genome-wide data can be used to search for signals of recent positive selection, thereby providing new insights into the genetic adaptations that occurred as modern humans spread out of Africa and around the world.

Methodology

We genotyped approximately 500,000 SNPs in 255 individuals (5 individuals from each of 51 worldwide populations) from the Human Genome Diversity Panel (HGDP-CEPH). When merged with non-overlapping SNPs typed previously in 250 of these same individuals, the resulting data consist of over 950,000 SNPs. We then analyzed the genetic relationships and ancestry of individuals without assigning them to populations, and we also identified candidate regions of recent positive selection at both the population and regional (continental) level.

Conclusions

Our analyses both confirm and extend previous studies; in particular, we highlight the impact of various dispersals, and the role of substructure in Africa, on human genetic diversity. We also identified several novel candidate regions for recent positive selection, and a gene ontology (GO) analysis identified several GO groups that were significantly enriched for such candidate genes, including immunity and defense related genes, sensory perception genes, membrane proteins, signal receptors, lipid binding/metabolism genes, and genes involved in the nervous system. Among the novel candidate genes identified are two genes involved in the thyroid hormone pathway that show signals of selection in African Pygmies that may be related to their short stature.     

Classic Selective Sweeps Revealed by Massive Sequencing in Cattle

Human driven selection during domestication and subsequent breed formation has likely left detectable signatures within the genome of modern cattle. The elucidation of these signatures of selection is of interest from the perspective of evolutionary biology, and for identifying domestication-related genes that ultimately may help to further genetically improve this economically important animal. To this end, we employed a panel of more than 15 million autosomal SNPs identified from re-sequencing of 43 Fleckvieh animals. We mainly applied two somewhat complementary statistics, the integrated Haplotype Homozygosity Score (iHS) reflecting primarily ongoing selection, and the Composite of Likelihood Ratio (CLR) having the most power to detect completed selection after fixation of the advantageous allele. We find 106 candidate selection regions, many of which are harboring genes related to phenotypes relevant in domestication, such as coat coloring pattern, neurobehavioral functioning and sensory perception including KIT, MITF, MC1R, NRG4, Erbb4, TMEM132D and TAS2R16, among others. To further investigate the relationship between genes with signatures of selection and genes identified in QTL mapping studies, we use a sample of 3062 animals to perform four genome-wide association analyses using appearance traits, body size and somatic cell count. We show that regions associated with coat coloring significantly (P<0.0001) overlap with the candidate selection regions, suggesting that the selection signals we identify are associated with traits known to be affected by selection during domestication. Results also provide further evidence regarding the complexity of the genetics underlying coat coloring in cattle. This study illustrates the potential of population genetic approaches for identifying genomic regions affecting domestication-related phenotypes and further helps to identify specific regions targeted by selection during speciation, domestication and breed formation of cattle. We also show that Linkage Disequilibrium (LD) decays in cattle at a much faster rate than previously thought.     

Efficiently Tracking Selection in a Multiparental Population: The Case of Earliness in Wheat

Multiparental populations are innovative tools for fine mapping large numbers of loci. Here we explored the application of a wheat Multiparent Advanced Generation Inter-Cross (MAGIC) population for QTL mapping. This population was created by 12 generations of free recombination among 60 founder lines, following modification of the mating system from strict selfing to strict outcrossing using the ms1b nuclear male sterility gene. Available parents and a subset of 380 SSD lines of the resulting MAGIC population were phenotyped for earliness and genotyped with the 9K i-Select SNP array and additional markers in candidate genes controlling heading date. We demonstrated that 12 generations of strict outcrossing rapidly and drastically reduced linkage disequilibrium to very low levels even at short map distances and also greatly reduced the population structure exhibited among the parents. We developed a Bayesian method, based on allelic frequency, to estimate the contribution of each parent in the evolved population. To detect loci under selection and estimate selective pressure, we also developed a new method comparing shifts in allelic frequency between the initial and the evolved populations due to both selection and genetic drift with expectations under drift only. This evolutionary approach allowed us to identify 26 genomic areas under selection. Using association tests between flowering time and polymorphisms, 6 of these genomic areas appeared to carry flowering time QTL, 1 of which corresponds to Ppd-D1, a major gene involved in the photoperiod sensitivity. Frequency shifts at 4 of 6 areas were consistent with earlier flowering of the evolved population relative to the initial population. The use of this new outcrossing wheat population, mixing numerous initial parental lines through multiple generations of panmixia, is discussed in terms of power to detect genes under selection and association mapping. Furthermore we provide new statistical methods for use in future analyses of multiparental populations.     

Detecting lineage-specific adaptive evolution of brain-expressed genes in human using rhesus macaque as outgroup

Comparative genetic analysis between human and chimpanzee may detect genetic divergences responsible for human-specific characteristics. Previous studies have identified a series of genes that potentially underwent Darwinian positive selection during human evolution. However, without a closely related species as outgroup, it is difficult to identify human-lineage-specific changes, which is critical in delineating the biological uniqueness of humans. In this study, we conducted phylogeny-based analyses of 2633 human brain-expressed genes using rhesus macaque as the outgroup. We identified 47 candidate genes showing strong evidence of positive selection in the human lineage. Genes with maximal expression in the brain showed a higher evolutionary rate in human than in chimpanzee. We observed that many immune-defense-related genes were under strong positive selection, and this trend was more prominent in chimpanzee than in human. We also demonstrated that rhesus macaque performed much better than mouse as an outgroup in identifying lineage-specific selection in humans.     

Evolutionary analysis of genes of two pathways involved in placental malaria infection

Placental malaria is a special form of malaria that causes up to 200,000 maternal and infant deaths every year. Previous studies show that two receptor molecules, hyaluronic acid and chondroitin sulphate A, are mediating the adhesion of parasite-infected erythrocytes in the placenta of patients, which is believed to be a key step in the pathogenesis of the disease. In this study, we aimed at identifying sites of malaria-induced adaptation by scanning for signatures of natural selection in 24 genes in the complete biosynthesis pathway of these two receptor molecules. We analyzed a total of 24 Mb of publicly available polymorphism data from the International HapMap project for three human populations with European, Asian and African ancestry, with the African population from a region of presently and historically high malaria prevalence. Using the methods based on allele frequency distributions, genetic differentiation between populations, and on long-range haplotype structure, we found only limited evidence for malaria-induced genetic adaptation in this set of genes in the African population; however, we identified one candidate gene with clear evidence of selection in the Asian population. Although historical exposure to malaria in this population cannot be ruled out, we speculate that it might be caused by other pathogens, as there is growing evidence that these molecules are important receptors in a variety of host-pathogen interactions. We propose to use the present methods in a systematic way to help identify candidate regions under positive selection as a consequence of malaria. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Geographical variation of genetic and phenotypic traits in the Mexican sailfin mollies, Poecilia velifera and P. petenensis

Comparing the patterns of population divergence using both neutral genetic and phenotypic traits provides an opportunity to examine the relative importance of evolutionary mechanisms in shaping population differences. We used microsatellite markers to examine population genetic structure in the Mexican sailfin mollies Poecilia velifera and P. petenensis. We compared patterns of genetic structure and divergence to that in two types of phenotypic traits: morphological characters and mating behaviours. Populations within each species were genetically distinct, and conformed to a model of isolation by distance, with populations within different geographical regions being more genetically similar to one another than were populations from different regions. Bayesian clustering and barrier analyses provided additional support for population separation, especially between geographical regions. In contrast, none of the phenotypic traits showed any type of geographical pattern, and population divergence in these traits was uncorrelated with that found in neutral markers. There was also a weaker pattern of regional differences among geographical regions compared to neutral genetic divergence. These results suggest that while divergence in neutral traits is likely a product of population history and genetic drift, phenotypic divergence is governed by different mechanisms, such as natural and sexual selection, and arises at spatial scales independent from those of neutral markers.     

Genome-Wide Scan for Signatures of Human Population Differentiation and Their Relationship with Natural Selection,Functional Pathways and Diseases

Genetic differences both between individuals and populations are studied for their evolutionary relevance and for their potential medical applications. Most of the genetic differentiation among populations are caused by random drift that should affect all loci across the genome in a similar manner. When a locus shows extraordinary high or low levels of population differentiation, this may be interpreted as evidence for natural selection. The most used measure of population differentiation was devised by Wright and is known as fixation index, or F_ST. We performed a genome-wide estimation of F_ST on about 4 millions of SNPs from HapMap project data. We demonstrated a heterogeneous distribution of F_ST values between autosomes and heterochromosomes. When we compared the F_ST values obtained in this study with another evolutionary measure obtained by comparative interspecific approach, we found that genes under positive selection appeared to show low levels of population differentiation. We applied a gene set approach, widely used for microarray data analysis, to detect functional pathways under selection. We found that one pathway related to antigen processing and presentation showed low levels of F_ST, while several pathways related to cell signalling, growth and morphogenesis showed high F_ST values. Finally, we detected a signature of selection within genes associated with human complex diseases. These results can help to identify which process occurred during human evolution and adaptation to different environments. They also support the hypothesis that common diseases could have a genetic background shaped by human evolution.     

Extensive linkage disequilibrium and parallel adaptive divergence across threespine stickleback genomes

Population genomic studies are beginning to provide a more comprehensive view of dynamic genome-scale processes in evolution. Patterns of genomic architecture, such as genomic islands of increased divergence, may be important for adaptive population differentiation and speciation. We used next-generation sequencing data to examine the patterns of local and long-distance linkage disequilibrium (LD) across oceanic and freshwater populations of threespine stickleback, a useful model for studies of evolution and speciation. We looked for associations between LD and signatures of divergent selection, and assessed the role of recombination rate variation in generating LD patterns. As predicted under the traditional biogeographic model of unidirectional gene flow from ancestral oceanic to derived freshwater stickleback populations, we found extensive local and long-distance LD in fresh water. Surprisingly, oceanic populations showed similar patterns of elevated LD, notably between large genomic regions previously implicated in adaptation to fresh water. These results support an alternative biogeographic model for the stickleback radiation, one of a metapopulation with appreciable bi-directional gene flow combined with strong divergent selection between oceanic and freshwater populations. As predicted by theory, these processes can maintain LD within and among genomic islands of divergence. These findings suggest that the genomic architecture in oceanic stickleback populations may provide a mechanism for the rapid re-assembly and evolution of multi-locus genotypes in newly colonized freshwater habitats, and may help explain genetic mapping of parallel phenotypic variation to similar loci across independent freshwater populations.     

Identifying Signatures of Natural Selection in Tibetan and Andean Populations Using Dense Genome Scan Data

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary to confirm the role of selection-nominated candidate genes and gene regions in adaptation to altitude.