The Genetics Of Human Adaptation: Hard Sweeps, Soft
Current Biology 20, R208–R215, February 23, 2010 ª2010 Elsevier Ltd All rights reservedDOI 10.1016/j.cub.2009.11.055The Genetics of Human Adaptation: HardReviewSweeps, Soft Sweeps, and Polygenic AdaptationJonathan K. Pritchard1,2,*, Joseph K. Pickrell1,and Graham Coop3There has long been interest in understanding the geneticbasis of human adaptation. To what extent are phenotypicdifferences among human populations driven by naturalselection? With the recent arrival of large genome-widedata sets on human variation, there is now unprecedentedopportunity for progress on this type of question. Severallines of evidence argue for an important role of positiveselection in shaping human variation and differencesamong populations. These include studies of comparativemorphology and physiology, as well as population geneticstudies of candidate loci and genome-wide data. However,the data also suggest that it is unusual for strong selectionto drive new mutations rapidly to fixation in particular populations (the ‘hard sweep’ model). We argue, instead, foralternatives to the hard sweep model: in particular, polygenic adaptation could allow rapid adaptation while notproducing classical signatures of selective sweeps. Weclose by discussing some of the likely opportunities forprogress in the field.IntroductionWithin the past 100,000 years, anatomically modern humanshave spread from sub-Saharan Africa to colonize most of theworld’s land masses (see the other reviews in this specialissue). Human populations live in an extraordinary varietyof different habitats: hot and cold; wet and dry; in forests,grasslands, and tundra. Different human groups feed ona wide variety of food sources. For many populations, dietsshifted further with the development of agriculture in thepast 10,000 years.To what extent have these, and other, factors led togenetic adaptation? If they have, can we identify the typesof genes and phenotypes that have been most affected?With the recent availability of genome-wide single nucleotidepolymorphism (SNP) data for many populations, and with theexpectation that genome-wide sequence data will soon alsobe available for large numbers of individuals, there is nowgreat interest in these questions. There has also been a greatdeal of recent work on methods for using genome-wide datato identify signals of selection. These methods generallymake use of the idea that selective events distort patternsof neutral variation in predictable ways, depending on themodel of selection: for example, reducing haplotype diversity, increasing the fraction of rare alleles and increasingthe extent of allele frequency differences between populations. In this review, we provide a brief overview of some of1Departmentof Human Genetics and 2Howard Hughes MedicalInstitute, The University of Chicago, Room 507, 929 E. 58th St,Chicago, IL 60637, USA. 3Section of Evolution and Ecology andCenter for Population Biology, University of California, Davis, Room2320 Storer Hall, One Shields Avenue, Davis, CA 95616, USA.*E-mail: pritch@uchicago.eduthe key findings thus far, and then focus on what we see assome of the major open questions. A number of other recentreviews discuss either the general principles for detectingselection or summarize the overall results in more detailthan we attempt here [1–6].Recent Human AdaptationsWhile human populations differ in various phenotypes, thereis a considerable burden of proof to show that phenotypicdifferences have a genetic basis and are adaptive. However,we do now have reasonable evidence of differential adaptation of various traits. For example, it has long been knownthat mammals that live in cold climates tend to have larger,rounder bodies (‘Bergmann’s rule’) and shorter limbs(‘Allen’s rule’) than members of the same or closely relatedspecies in warm climates. These patterns — althoughnoisy — do appear to also hold in humans, implying that population movements into colder climates were accompaniedby adaptation to larger, stockier body shape, presumablyto improve thermal efficiency [7]. At the other end of thespectrum is the striking ‘pygmy’ phenotype that has evolvedconvergently in rainforest populations in Africa, South-EastAsia, and South America [8]. It has been suggested that thepygmy phenotype may be an adaptation to food limitations,high humidity or dense forest undergrowth [8].Another impressive example of adaptation is provided byhuman populations living at high altitude, especially in the Himalayas and the Andes [9,10]. Compared to related lowlandpopulations, these high-elevation populations show a suiteof physiological adaptations to low oxygen [11]. These adaptations include markedly increased blood flow and oxygendelivery to the uterus during pregnancy, substantiallyreducing the risk of babies with low birthweight [12]. Currentevidence suggests that these differences are not simply theresult of recent acclimation, but are at least partly genetic,although the relevant loci are not known [9,10,12]. If this isthe case, then the adaptation must have occurred rapidly,because these high altitude regions were settled within thelast 10,000 years, and the adaptation occurred in spite oflikely gene flow from lowland neighbors [10].Skin pigmentation is perhaps the phenotype that variesmost conspicuously among human populations. Dark pigmentation is strongly associated with tropical climates, andthe spread of prehistoric humans into northern latitudeswas accompanied by a shift to lighter skin color [13,14].We now know of at least half a dozen different genes thataffect skin, hair or eye pigmentation, and have stronggenetic signals of selection based on low haplotype diversityor extreme frequency differences between populations[15–21]. There are surely additional selected loci yet to befound. In particular, the evolution of light skin color occurredlargely in parallel in western Eurasia and east Asia, but westill know few of the relevant genes in east Asia [17,18,22].Adaptation to lighter pigmentation may have been drivenby a need to increase UV absorption for vitamin D synthesisat high latitudes or by sexual selection [14].In addition to pigmentation, there are a handful of othergenes for which there are both strong selection signals and
Special IssueR209Enrichment0.6 1.0 1.4A Enrichment of large frequency differences in genic -YRI derived allele frequency0.90.6Fra-PalFra-Han0.3MaximumB No strong differentiation between closely related populations0.000.05Fra-Yor0.10Mean FstYor-Han0.15C High-Fst SNPs lack strong haplotypic patternsSimulation: s 1%Random SNPsDensity0.0 0.2 0.4Figure 1. Conflicting evidence of populationspecific selection.(A) The x-axis shows the signed difference inderived allele frequency between HapMapYoruba and east Asians. The y-axis showsthe fractions of SNPs in each bin of frequencydifferences that are genic, and nongenic,respectively, divided by the total fraction ofSNPs that are genic, and nongenic, respectively. (B) The x-axis shows the mean pairwiseFST between all pairs of HGDP populationswith sample sizes 15 individuals (the valuesof four arbitrary pairs comparing France,Palestine, Han and Yoruba are indicated toprovide a sense of scale). The y-axis showsthe value of the most extreme allele frequencydifference for each population at any of the640,000 genotyped SNPs. (C) The threecurves show the distributions of XP-EHH,a measure of haplotype diversity [34] for (i)random SNPs in east Asians, (ii) SNPs witha frequency difference 90% betweenHapMap Yoruba and east Asians, and (iii)simulated SNPs with a selective advantageof 1% and a frequency difference 90%,assuming a uniform rate of input of favoredmutations. In fact, the middle curve is mostsimilar to data simulated under a neutralmodel, but conditioned on the frequencydifference of 90% (not shown). All three plotsare redrawn from [22].High-FST SNPs–2024XP-EHHCurrent Biologycompelling explanations for their adaptive significance.Several of these are involved in malaria resistance, includingthe Duffy antigen protein (DARC) [23] and Glucose-6-phosphate dehydrogenase (G6PD) [24], as well as rarer mutationsin the a- and b-globin genes that can lead to sickle cellanemia or thalassemias. Another clear example of adaptation is provided by lactase, the enzyme that hydrolyzeslactose, the main sugar in milk. Lactase gene expressionhas evolved repeatedly to continue throughout life in dairyfarming populations in Europe, east Africa, and the MiddleEast [25–27].Genome-Wide DataMoving beyond candidate loci, many researchers have madeuse of the new genome-wide SNP data to scan for signals ofongoing or recently completed selective sweeps. Someglobal trends have emerged that show clear evidence forabundant selection. In particular, various types of signalsare consistently concentrated around genes, as opposedto in intergenic regions. These include signals of partialsweeps [20], reduced diversity at putatively neutral sites[28,29] and an excess of SNPs with extreme population differentiation (high FST) within genes (Figure 1A) [30]. Alsoconsistent with the action of selection, there is reduceddiversity in regions of low recombination, especially ingene-rich regions [28,29,31]. Taken together, these observations are most easily explained by either widespread positiveselection, or possibly by background selection againstmildly deleterious alleles [29,32]. The conclusion that adaptive selection may be widespread is further bolstered bysimilar results for other organisms, especially Drosophila[6], and also by recent estimates that 10-20% of aminoacid replacements on the human lineage have been drivenby positive selection [33].There has also been a great deal of interest in identifyingthe particular loci that have been targets of positive selection. However, in some respects this has proven to be challenging. A recent review lists 21 genome-wide scans, usinga variety of different methods [1]. Although each of thesescans highlights potentially interesting signals, it is currentlydifficult to assess how much confidence should be placed inindividual signals in the absence of further biological or functional information [34,35]. Indeed, there is poor agreementamong the studies, even though many of them actuallyanalyze the same data, frequently genome-wide SNP datafrom HapMap or Perlegen [36,37].Perhaps consistent with some of the challenges of thegenome-wide scans, recent work by Coop et al. [22] foundthat, as described below, some aspects of the human variation data do not show clear signals of widespread, strongselection (Figure 1). The authors studied three million SNPsgenotyped in the Phase II HapMap samples, along witha data set of 640,000 SNPs genotyped in 927 individualsfrom the CEPH-Human Genome Diversity Panel [37,38].They focused primarily on SNPs with high FST values, withthe view that these should be particularly sensitive fordetecting differential selection between populations.Overall, however, the HapMap data show relatively fewfixed or nearly fixed differences between populations fromdifferent continents, implying that new alleles have onlyrarely spread rapidly to fixation within populations, eventhough there has been sufficient time for strongly favoredalleles (selection coefficient, s R 0.5%) to spread from lowto high frequency since these populations separated [22].
Current Biology Vol 20 No 4R210Box 1Glossary.Background selection: refers to a process in which weakly deleterious mutations drift up to low frequencies and are then purged from thepopulation. This causes a reduction in diversity, especially around conserved regions. In some respects, the signals of background selectioncan mimic patterns produced by positive selection [29,32].FST: a classical measure of the amount of allele frequency differentiation between two or more populations. FST can take values between0 and 1, with 0 corresponding to identical allele frequencies in both (all) populations, and 1 corresponding to a fixed difference: i.e., that theallele is absent in one population, and fixed in the other. High FST values for particular SNPs may sometimes provide evidence that thoseSNPs are under selection.Hard sweep: the classical selective sweep model in which a new advantageous mutation arises, and spreads quickly to fixation due to naturalselection [40]. Under this model, neutral variation near to the favored site ‘‘hitch-hikes’’ along with the favored allele. This impacts patterns ofvariation around the selected site in ways that can be detected using a variety of tests of selection [5].Mutational target size: refers to the number of sites at a locus that, if appropriately mutated, could generate a particular favored phenotype.For example, it appears that several mutations in an upstream enhancer of lactase cause lifelong expression of the lactase gene [27,76]. Thesize of the mutational target affects the probability that standing variation will be available to allow rapid evolution following an environmentalchange.Polygenic adaptation: here, we use this term to describe a process in which adaptation occurs by simultaneous selection on variants atmany loci (perhaps tens or hundreds or more). We envisage that a common scenario of polygenic adaptation would be that there is a shift inthe optimal phenotype for a quantitative trait that is affected by hundreds of alleles of small effect. In this case, we can anticipate a responseto selection that is due to small frequency shifts of many alleles. Polygenic adaptation might also occur from new mutations at many loci,following a shift in the optimal phenotype. This latter scenario would be most likely if the newly favored phenotype had previously beenstrongly disfavored.Partial sweep: an event in which a favored allele increases rapidly from low frequency, but has not yet reached fixation (perhaps because thesweep is still in progress, or because the selective advantage of the favored allele has weakened).Selective sweep: an event in which the frequency of a favored allele increases rapidly due to selection. This term is often understood to referto complete hard sweeps, but may also refer to partial sweeps or soft sweeps (see below), depending on the context.Soft sweep: this term was introduced to describe two slightly different scenarios that both contrast with the standard hard sweep model [41].In one scenario, due to a change in selection, an allele that is already segregating in the population (i.e., standing variation) becomesselectively favored, and sweeps up in frequency. It is usually assumed that the allele is neutral or mildly deleterious prior to the change inselection. In the second scenario, multiple independent mutations at a single locus are all favored and all increase in frequencysimultaneously until the sum of the frequencies is 1. If the favored alleles are all similarly advantageous, then typically none of the favoredmutations would fix during the selective event. Both scenarios tend to be more difficult than hard sweeps to detect using standard tests ofselection.Standing variation: variants that are polymorphic in a population. The term is used here in the context of a selective force that is turned on sothat variants that had been drifting (nearly) neutrally suddenly become favored.Nearly all of these rare fixation events have taken placeoutside Africa and, curiously, most are found in the eastAsians, the group that has experienced the strongest geneticdrift of the three HapMap groups [39]. For example, there arejust 13 non-synonymous SNPs in Phase II HapMap witha frequency difference 90% between the Yoruba and eastAsians. Of these, only one is due to a high frequency derivedallele in the Yoruba. Additionally, few of the east Asian fixation events are associated with strong haplotype signals(Figure 1C), as measured by cross-population extendedhaplotype homozygosity (XP-EHH) [34]. This indicates thatfew of these alleles were fixed very rapidly. Instead, theXP-EHH data are more consistent with a steady, slowincrease in frequency during the time since the out-of-Africamigration roughly 60,000 years ago. Finally, these putativelyselected alleles can be grouped in a small number ofgeographic patterns that reflect neutral population structure;these geographical patterns have been described as nonAfrican, West Eurasian and East Asian sweep patterns(Figure 3) [22]. The observation that sweep patterns mimicneutral population structure is not what might have beenexpected if the frequencies of individual alleles were stronglydetermined by environmental factors, such as climate ordiet, that likely vary over different geographic scales. Additionally, looking across all populations, and all SNPs, thereis not a single example of a SNP with very extreme allelefrequency differences between closely related populations(Figure 1B). At the level of individual SNPs, there is thus noclear evidence for extreme differential adaptation betweenclosely related populations.The question, then, is how to make sense of theseapparent discrepancies. On one hand there are examplesof apparent physiological and morphological adaptationsin modern human populations, strong signals of selectionat candidate loci and genome-wide patterns showing cleardifferences between genic and non-genic regions that aredifficult to explain by neutral processes. On the other hand,genome-wide data suggest that there are relatively few fixed(or nearly fixed) differences between HapMap populations,that those that do exist have generally become fixed relatively slowly and that the geographic distributions of putatively selected alleles are strongly influenced by the historicalrelationships among populations.Based in part on the scarcity of high-FST SNPs with stronghaplotype signals, Coop et al. argued that few hard sweeps(i.e., sweeps of new mutations) with selection coefficients
Special IssueR2110.0 0.2 0.4 0.6 0.8 1.0Probability of fixingstanding variationA Probability of a sweep from standing variationL 1000bpL 100bpL 1bp1e-045e-045e-035e-02Selective advantage0.0 0.2 0.4 0.6 0.8 1.0B Probability that a sweep is from standing variation, conditional on a sweepProbability of standingvariation adaptationFigure 2. The probability of sweeps fromstanding variation following an environmentalchange.(A) Probability that a full sweep occurs fromstanding variation, as a function of the mutational target size and the strength of selectionafter the environmental switch. (B) Probabilitythat a sweep occurs from standing variation,conditional on a sweep occurring either fromstanding variation or from new variation thatarises within the first 1000 generations afterthe environmental change. The model is asdescribed in the text and in [41]. Parameters:Prior to the environmental switch, variationis deleterious with 2Nes -10. We assumeNe 10,000 and m 2 x 10-8. All selection isassumed additive. Modified with permissionfrom [41].of more than 1% have swept to fixationin the time since the out-of-Africamigration [22]. A number of possibleexplanations were proposed for theoverall patterns in the data, includingthat most selection on individual allelesmay be relatively weak so that thesealleles have not had time to sweep tofixation within continental populations;1e-04that the strength of selection may varytemporally, and it may be rare for selection to be consistently strong for the10,000 years or more required to drivean allele to near fixation; and thatmuch of human adaptation may proceed by either polygenicadaptation or soft sweeps that can be difficult to detect usingstandard methods.Hard Sweeps, Soft Sweeps and Mutational Target SizeThe standard approaches to detecting selection in population genetic data have been strongly shaped by the classicalhitch-hiking model explored in detail by Maynard Smith andHaigh [40]. In this model, new advantageous mutationsspread rapidly to fixation, purging variation at linked sites
The Genetics of Human Adaptation: Hard Review Sweeps, Soft Sweeps, and Polygenic Adaptation Jonathan K. Pritchard1,2,*, Joseph K. Pickrell1, and Graham Coop3 There has long been interest in understanding the genetic basis of human adaptation. To what extent are phenotypic differences among
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