Population genomic analysis of ALMS1 in humans reveals a surprisingly complex evolutionary history

Common Treatment, Common Variant: Evolutionary Prediction of Functional Pharmacogenomic Variants

Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new ‘common treatment, common variant’ perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX’s in silico predictions.

Prevalent ALMS1 Pathogenic Variants in Spanish Alström Patients

Alström syndrome (ALMS) is an ultrarare disease with an estimated prevalence lower than 1 in 1,000,000. It is associated with disease-causing mutations in the Alström syndrome 1 (ALMS1) gene, which codifies for a structural protein of the basal body and centrosomes. The symptomatology involves nystagmus, type 2 diabetes mellitus (T2D), obesity, dilated cardiomyopathy (DCM), neurodegenerative disorders and multiorgan fibrosis. We refined the clinical and genetic diagnosis data of 12 patients from 11 families, all of them from Spain. We also studied the allelic frequency of the different variants present in this cohort and performed a haplotype analysis for the most prevalent allele. The genetic analysis revealed 2 novel homozygous variants located in the exon 8, p.(Glu929Ter) and p.(His1808GlufsTer20) in 2 unrelated patients. These 2 novel variants were classified as pathogenic after an in silico experiment (computer analysis). On the other hand, 2 alleles were detected at a high frequency in our cohort: p.(Tyr1714Ter) (25%) and p.(Ser3872TyrfsTer19) (16.7%). The segregation analysis showed that the pathogenic variant p.(Tyr1714Ter) in 3 families is linked to a rare missense polymorphism, p.(Asn1787Asp). In conclusion, 2 novel pathological mutations have been discovered in homozygosis, as well as a probable founder effect in 3 unrelated families.

Genomic evidence for shared common ancestry of East African hunting-gathering populations and insights into local adaptation

Anatomically modern humans arose in Africa ∼300,000 years ago, but the demographic and adaptive histories of African populations are not well-characterized. Here, we have generated a genome-wide dataset from 840 Africans, residing in western, eastern, southern, and northern Africa, belonging to 50 ethnicities, and speaking languages belonging to four language families. In addition to agriculturalists and pastoralists, our study includes 16 populations that practice, or until recently have practiced, a hunting-gathering (HG) lifestyle. We observe that genetic structure in Africa is broadly correlated not only with geography, but to a lesser extent, with linguistic affiliation and subsistence strategy. Four East African HG (EHG) populations that are geographically distant from each other show evidence of common ancestry: the Hadza and Sandawe in Tanzania, who speak languages with clicks classified as Khoisan; the Dahalo in Kenya, whose language has remnant clicks; and the Sabue in Ethiopia, who speak an unclassified language. Additionally, we observed common ancestry between central African rainforest HGs and southern African San, the latter of whom speak languages with clicks classified as Khoisan. With the exception of the EHG, central African rainforest HGs, and San, other HG groups in Africa appear genetically similar to neighboring agriculturalist or pastoralist populations. We additionally demonstrate that infectious disease, immune response, and diet have played important roles in the adaptive landscape of African history. However, while the broad biological processes involved in recent human adaptation in Africa are often consistent across populations, the specific loci affected by selective pressures more often vary across populations.

Recent positive selection has acted on genes encoding proteins with more interactions within the whole human interactome

Genes vary in their likelihood to undergo adaptive evolution. The genomic factors that determine adaptability, however, remain poorly understood. Genes function in the context of molecular networks, with some occupying more important positions than others and thus being likely to be under stronger selective pressures. However, how positive selection distributes across the different parts of molecular networks is still not fully understood. Here, we inferred positive selection using comparative genomics and population genetics approaches through the comparison of 10 mammalian and 270 human genomes, respectively. In agreement with previous results, we found that genes with lower network centralities are more likely to evolve under positive selection (as inferred from divergence data). Surprisingly, polymorphism data yield results in the opposite direction than divergence data: Genes with higher centralities are more likely to have been targeted by recent positive selection during recent human evolution. Our results indicate that the relationship between centrality and the impact of adaptive evolution highly depends on the mode of positive selection and/or the evolutionary time-scale.

Soft shoulders ahead: spurious signatures of soft and partial selective sweeps result from linked hard sweeps

Characterizing the nature of the adaptive process at the genetic level is a central goal for population genetics. In particular, we know little about the sources of adaptive substitution or about the number of adaptive variants currently segregating in nature. Historically, population geneticists have focused attention on the hard-sweep model of adaptation in which a de novo beneficial mutation arises and rapidly fixes in a population. Recently more attention has been given to soft-sweep models, in which alleles that were previously neutral, or nearly so, drift until such a time as the environment shifts and their selection coefficient changes to become beneficial. It remains an active and difficult problem, however, to tease apart the telltale signatures of hard vs. soft sweeps in genomic polymorphism data. Through extensive simulations of hard- and soft-sweep models, here we show that indeed the two might not be separable through the use of simple summary statistics. In particular, it seems that recombination in regions linked to, but distant from, sites of hard sweeps can create patterns of polymorphism that closely mirror what is expected to be found near soft sweeps. We find that a very similar situation arises when using haplotype-based statistics that are aimed at detecting partial or ongoing selective sweeps, such that it is difficult to distinguish the shoulder of a hard sweep from the center of a partial sweep. While knowing the location of the selected site mitigates this problem slightly, we show that stochasticity in signatures of natural selection will frequently cause the signal to reach its zenith far from this site and that this effect is more severe for soft sweeps; thus inferences of the target as well as the mode of positive selection may be inaccurate. In addition, both the time since a sweep ends and biologically realistic levels of allelic gene conversion lead to errors in the classification and identification of selective sweeps. This general problem of "soft shoulders" underscores the difficulty in differentiating soft and partial sweeps from hard-sweep scenarios in molecular population genomics data. The soft-shoulder effect also implies that the more common hard sweeps have been in recent evolutionary history, the more prevalent spurious signatures of soft or partial sweeps may appear in some genome-wide scans.

On detecting incomplete soft or hard selective sweeps using haplotype structure

We present a new haplotype-based statistic (nSL) for detecting both soft and hard sweeps in population genomic data from a single population. We compare our new method with classic single-population haplotype and site frequency spectrum (SFS)-based methods and show that it is more robust, particularly to recombination rate variation. However, all statistics show some sensitivity to the assumptions of the demographic model. Additionally, we show that nSL has at least as much power as other methods under a number of different selection scenarios, most notably in the cases of sweeps from standing variation and incomplete sweeps. This conclusion holds up under a variety of demographic models. In many aspects, our new method is similar to the iHS statistic; however, it is generally more robust and does not require a genetic map. To illustrate the utility of our new method, we apply it to HapMap3 data and show that in the Yoruban population, there is strong evidence of selection on genes relating to lipid metabolism. This observation could be related to the known differences in cholesterol levels, and lipid metabolism more generally, between African Americans and other populations. We propose that the underlying causes for the selection on these genes are pleiotropic effects relating to blood parasites rather than their role in lipid metabolism.

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.

Paleolithic Contingent in Modern Japanese: Estimation and Inference using Genome-wide Data

The genetic origins of Japanese populations have been controversial. Upper Paleolithic Japanese, i.e. Jomon, developed independently in Japanese islands for more than 10,000 years until the isolation was ended with the influxes of continental immigrants about 2,000 years ago. However, the knowledge of origin of Jomon and its contribution to the genetic pool of contemporary Japanese is still limited, albeit the extensive studies using mtDNA and Y chromosomes. In this report, we aimed to infer the origin of Jomon and to estimate its contribution to Japanese by fitting an admixture model with missing data from Jomon to a genome-wide data from 94 worldwide populations. Our results showed that the genetic contributions of Jomon, the Paleolithic contingent in Japanese, are 54.3∼62.3% in Ryukyuans and 23.1∼39.5% in mainland Japanese, respectively. Utilizing inferred allele frequencies of the Jomon population, we further showed the Paleolithic contingent in Japanese had a Northeast Asia origin.

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

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

Investigation of the domestication of common bean (Phaseolus vulgaris) using multilocus sequence data

Multilocus sequence data collected from domesticated and related wild relatives provides a rich source of information on the effect of human selection on the diversity and adaptability of a species to complex environments. To evaluate the domestication history of common bean (Phaseolus vulgaris L.), multilocus sequence data from landraces representing the various races within the Middle American (MA) and Andean gene pools was evaluated. Across 13 loci, nucleotide diversity was similar between landraces and wild germplasm in both gene pools. The diversity data were evaluated using the approximate Bayesian computation approach to test multiple domestication models and estimate population demographic parameters. A model with a single domestication event coupled with bidirectional migration between wild and domesticated genotypes fitted the data better than models consisting of two or three domestication events in each genepool. The effective bottleneck population size was ~50% of the base population in each genepool. The bottleneck began ~8200 and ~8500 years before present and ended at ~6300 and ~7000 years before present in MA and Andean gene pools respectively. Linkage disequilibrium decayed to a greater extent in the MA genepool. Given the (1) geographical adaptation bottleneck in each wild gene pool, (2) a subsequent domestication bottleneck within each gene pool, (3) differentiation into gene-pool specific races and (4) variable extents of linkage disequilibrium, association mapping experiments for common bean would more appropriately be performed within each genepool.

Clusters of adaptive evolution in the human genome

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

A genome-wide metabolic QTL analysis in Europeans implicates two loci shaped by recent positive selection

We have performed a metabolite quantitative trait locus (mQTL) study of the ¹H nuclear magnetic resonance spectroscopy (¹H NMR) metabolome in humans, building on recent targeted knowledge of genetic drivers of metabolic regulation. Urine and plasma samples were collected from two cohorts of individuals of European descent, with one cohort comprised of female twins donating samples longitudinally. Sample metabolite concentrations were quantified by ¹H NMR and tested for association with genome-wide single-nucleotide polymorphisms (SNPs). Four metabolites' concentrations exhibited significant, replicable association with SNP variation (8.6×10⁻¹¹<p<2.8×10⁻²³). Three of these—trimethylamine, 3-amino-isobutyrate, and an N-acetylated compound—were measured in urine. The other—dimethylamine—was measured in plasma. Trimethylamine and dimethylamine mapped to a single genetic region (hence we report a total of three implicated genomic regions). Two of the three hit regions lie within haplotype blocks (at 2p13.1 and 10q24.2) that carry the genetic signature of strong, recent, positive selection in European populations. Genes NAT8 and PYROXD2, both with relatively uncharacterized functional roles, are good candidates for mediating the corresponding mQTL associations. The study's longitudinal twin design allowed detailed variance-components analysis of the sources of population variation in metabolite levels. The mQTLs explained 40%–64% of biological population variation in the corresponding metabolites' concentrations. These effect sizes are stronger than those reported in a recent, targeted mQTL study of metabolites in serum using the targeted-metabolomics Biocrates platform. By re-analysing our plasma samples using the Biocrates platform, we replicated the mQTL findings of the previous study and discovered a previously uncharacterized yet substantial familial component of variation in metabolite levels in addition to the heritability contribution from the corresponding mQTL effects.

Physiological concentrations of metabolites—small molecules involved in biochemical processes in living systems—can be measured and used to diagnose and predict disease states. A common goal is to detect and clinically exploit statistical differences in metabolite concentrations between diseased and healthy individuals. As a basis for the design and interpretation of case-control studies, it is useful to have a characterization of metabolic diversity amongst healthy individuals, some of which stems from inter-individual genetic variation. When a single genetic locus has a sufficiently strong effect on metabolism, its genomic position can be determined by collecting metabolite concentration data and genome-wide genotype data on a set of individuals and searching for associations between the two data sets—a so-called metabolite quantitative trait locus (mQTL) study. By so tracing mQTLs, we can identify the genetic drivers of metabolism, characterize how the nature or quantity of the corresponding expressed protein(s) feeds forward to influence metabolite levels, and specify disease-predictive models that incorporate mutual dependence amongst genetics, environment, and metabolism.

Differing evolutionary histories of WFDC8 (short-term balancing) in Europeans and SPINT4 (incomplete selective sweep) in Africans

The whey acidic protein four-disulfide core (WFDC) gene cluster on human chromosome 20q13, harbors 15 small serine protease inhibitor genes with roles in innate immunity, reproduction, and regulation of endogenous proteases kallikreins. The WFDC cluster has emerged as a prime example of rapid diversification and adaptive evolution in primates. This study sought a better understanding of the evolutionary history of WFDC genes in humans and focused on exploring the adaptive selection signatures found in populations of European (Utah residents with ancestry from northern and western Europe [CEU]) and African (Yoruba from Ibadan, in Nigeria [YRI]) ancestry in a genome-wide scan for putative targets of recent adaptive selection. Our approach included resequencing coding and noncoding regions of WFDC6, EPPIN, and WFDC8 in 20 CEU and of SPINT4 in 20 YRI individuals. We generated 302 kb and 60 kb of high-quality sequence data from CEU and of YRI populations, respectively, enabling the identification of 72 single nucleotide polymorphisms. Using classic neutrality tests, empirical and haplotype-based analysis, we pinpointed WFDC8 and SPINT4 as the likely targets of short-term balancing selection in the CEU population, and recent positive selection (incomplete selective sweep) in the YRI population. Putative candidate variants targeted by selection include 44A (rs7273669A) for WFDC8, which may downregulate gene expression by abolishing the binding site of two transcription factors; and a haplotype configuration [Ser73+98A] (rs6017667A-rs6032474A) for SPINT4, which may simultaneously affect protein function and gene regulation. We propose that the evolution of WFDC8 and SPINT4 has been shaped by complex selective scenarios due to the interdependence of variant fitness and ecological variables.

Alström syndrome: genetics and clinical overview

Alström syndrome is a rare autosomal recessive genetic disorder characterized by cone-rod dystrophy, hearing loss, childhood truncal obesity, insulin resistance and hyperinsulinemia, type 2 diabetes, hypertriglyceridemia, short stature in adulthood, cardiomyopathy, and progressive pulmonary, hepatic, and renal dysfunction. Symptoms first appear in infancy and progressive development of multi-organ pathology leads to a reduced life expectancy. Variability in age of onset and severity of clinical symptoms, even within families, is likely due to genetic background.Alström syndrome is caused by mutations in ALMS1, a large gene comprised of 23 exons and coding for a protein of 4,169 amino acids. In general, ALMS1 gene defects include insertions, deletions, and nonsense mutations leading to protein truncations and found primarily in exons 8, 10 and 16. Multiple alternate splice forms exist. ALMS1 protein is found in centrosomes, basal bodies, and cytosol of all tissues affected by the disease. The identification of ALMS1 as a ciliary protein explains the range of observed phenotypes and their similarity to those of other ciliopathies such as Bardet-Biedl syndrome.Studies involving murine and cellular models of Alström syndrome have provided insight into the pathogenic mechanisms underlying obesity and type 2 diabetes, and other clinical problems. Ultimately, research into the pathogenesis of Alström syndrome should lead to better management and treatments for individuals, and have potentially important ramifications for other rare ciliopathies, as well as more common causes of obesity and diabetes, and other conditions common in the general population.

The emergence of human-evolutionary medical genomics

In this review, I describe how evolutionary genomics is uniquely suited to spearhead advances in understanding human disease risk, owing to the privileged position of genes as fundamental causes of phenotypic variation, and the ability of population genetic and phylogenetic methods to robustly infer processes of natural selection, drift, and mutation from genetic variation at the levels of family, population, species, and clade. I first provide an overview of models for the origins and maintenance of genetically based disease risk in humans. I then discuss how analyses of genetic disease risk can be dovetailed with studies of positive and balancing selection, to evaluate the degree to which the 'genes that make us human' also represent the genes that mediate risk of polygenic disease. Finally, I present four basic principles for the nascent field of human evolutionary medical genomics, each of which represents a process that is nonintuitive from a proximate perspective. Joint consideration of these principles compels novel forms of interdisciplinary analyses, most notably studies that (i) analyze tradeoffs at the level of molecular genetics, and (ii) identify genetic variants that are derived in the human lineage or in specific populations, and then compare individuals with derived versus ancestral alleles.

The effect of recurrent mutation on the linkage disequilibrium under a selective sweep

A selective sweep describes the reduction of diversity due to strong positive selection. If the mutation rate to a selectively beneficial allele is sufficiently high, Pennings and Hermisson (Mol Biol Evol 23(5):1076-1084, 2006a) have shown, that it becomes likely, that a selective sweep is caused by several individuals. Such an event is called a soft sweep and the complementary event of a single origin of the beneficial allele, the classical case, a hard sweep. We give analytical expressions for the linkage disequilibrium (LD) between two neutral loci linked to the selected locus, depending on the recurrent mutation to the beneficial allele, measured by D and ̂σ(2)(D), a quantity introduced by Ohta and Kimura (Genetics 63(1):229-238, 1969), and conclude that the LD-pattern of a soft sweep differs substantially from that of a hard sweep due to haplotype structure. The analytical results are compared with simulations.

The genetics of human adaptation: hard sweeps, soft sweeps, and polygenic adaptation

There has long been interest in understanding the genetic basis of human adaptation. To what extent are phenotypic differences among human populations driven by natural selection? With the recent arrival of large genome-wide data sets on human variation, there is now unprecedented opportunity for progress on this type of question. Several lines of evidence argue for an important role of positive selection in shaping human variation and differences among populations. These include studies of comparative morphology and physiology, as well as population genetic studies of candidate loci and genome-wide data. However, the data also suggest that it is unusual for strong selection to drive new mutations rapidly to fixation in particular populations (the 'hard sweep' model). We argue, instead, for alternatives to the hard sweep model: in particular, polygenic adaptation could allow rapid adaptation while not producing classical signatures of selective sweeps. We close by discussing some of the likely opportunities for progress in the field.

Haplotype structure and divergence at human and chimpanzee serotonin transporter and receptor genes: implications for behavioral disorder association analyses

Genetic variation in the human serotonin system has long-been studied because of its functional consequences and links to various behavior-related disorders and it being routinely targeted in research and development for drug therapy. However, aside from clinical studies, little is known about this genetic diversity and how it differs within and between human populations with respect to haplotype structure, which can greatly impact phenotype association studies. In addition, no evolutionary approach among humans and other primates has examined how long- and short-term selective pressures explain existing serotonin variation. Here, we examine DNA sequence variation in natural population samples of 192 human and 40 chimpanzee chromosome sequences for the most commonly implicated approximately 38-kb serotonin transporter (SLC6A4) and approximately 63-kb serotonin 2A receptor (HTR2A) genes. Our comparative population genetic analyses find significant linkage disequilibrium associated with functionally relevant variants in humans, as well as geographic variation for these haplotypes, at both loci. In addition, although amino acid divergence is consistent with purifying selection, promoter and untranslated regions exhibit significantly high divergence in both species lineages. These evolutionary analyses imply that the serotonin system may have accumulated significant regulatory variation over both recent and ancient periods of time in both humans and chimpanzees. We discuss the implications of this variation for disease association studies and for the evolution of behavior-related phenotypes during the divergence of humans and our closest primate relatives.

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

Identifying targets of positive selection in humans has, until recently, been frustratingly slow, relying on the analysis of individual candidate genes. Genomics, however, has provided the necessary resources to systematically interrogate the entire genome for signatures of natural selection. To date, 21 genome-wide scans for recent or ongoing positive selection have been performed in humans. A key challenge is to begin synthesizing these newly constructed maps of positive selection into a coherent narrative of human evolutionary history and derive a deeper mechanistic understanding of how natural populations evolve. Here, I chronicle the recent history of the burgeoning field of human population genomics, critically assess genome-wide scans for positive selection in humans, identify important gaps in knowledge, and discuss both short- and long-term strategies for traversing the path from the low-resolution, incomplete, and error-prone maps of selection today to the ultimate goal of a detailed molecular, mechanistic, phenotypic, and population genetics characterization of adaptive alleles.

Population differentiation as an indicator of recent positive selection in humans: an empirical evaluation

We have evaluated the extent to which SNPs identified by genomewide surveys as showing unusually high levels of population differentiation in humans have experienced recent positive selection, starting from a set of 32 nonsynonymous SNPs in 27 genes highlighted by the HapMap1 project. These SNPs were genotyped again in the HapMap samples and in the Human Genome Diversity Project-Centre d'Etude du Polymorphisme Humain (HGDP-CEPH) panel of 52 populations representing worldwide diversity; extended haplotype homozygosity was investigated around all of them, and full resequence data were examined for 9 genes (5 from public sources and 4 from new data sets). For 7 of the genes, genotyping errors were responsible for an artifactual signal of high population differentiation and for 2, the population differentiation did not exceed our significance threshold. For the 18 genes with confirmed high population differentiation, 3 showed evidence of positive selection as measured by unusually extended haplotypes within a population, and 7 more did in between-population analyses. The 9 genes with resequence data included 7 with high population differentiation, and 5 showed evidence of positive selection on the haplotype carrying the nonsynonymous SNP from skewed allele frequency spectra; in addition, 2 showed evidence of positive selection on unrelated haplotypes. Thus, in humans, high population differentiation is (apart from technical artifacts) an effective way of enriching for recently selected genes, but is not an infallible pointer to recent positive selection supported by other lines of evidence.