Which evolutionary processes influence natural genetic...

For decades, evolutionary biologists have sought to understand the evolutionary forces that influence genetic variation within and among natural populations1,2. At the molecular level, genome-wide studies have documented vast stores of segregating nucleotide polymorphism, and have begun to elucidate the evolutionary processes that shape this variation3. The situation is far less clear, how-ever, for genetic variation that affects phenotypic traits. What are the roles of genetic drift or various forms of natural selection in determining the amount and pattern of phenotypic trait variation? This question has funda-mental implications for our perspective on evolutionary ecology. The underlying polymorphisms might be evolv-ing neutrally, or could be transient variants on their way to being eliminated because they are deleterious, or on their way to fixation because they are beneficial (BOX 1). If deleterious mutant alleles with short persistence times explain much of the segregating variation within populations4–8, as proposed in hypotheses that involve mutation–selection balance, then such variants might be very different from the alleles that are responsible for adaptive evolution9,10. Alternatively, much of this varia-tion could be actively maintained by natural selection (in individual populations by balancing selection or throughout the entire species by local adaptation)11,12.

Progress towards addressing these alternatives has been limited. Although most traits are genetically

variable in most species, the causal molecular polymor-phisms have been identified in only a limited number of cases, and we lack a general understanding of the evolutionary processes that influence phenotypic vari-ation. Inevitably, efforts toward this goal must consider both molecular and phenotypic variation, as well as the causal relationship between genotype and phenotype. Evolutionary interpretation of complex-trait variation is greatly facilitated by identification of the genes that underlie phenotypic variation. In addition, a mecha-nistic understanding of the molecular, biochemical and developmental mechanisms responsible for this variation will enrich our evolutionary inferences, and will contribute to a synthesis of ecology, evolution and molecular biology13.

Here we discuss the progress that has been made so far in understanding the evolutionary processes that lead to phenotypic variation, and examine how future progress will be made in this area. Combined studies of population, quantitative and ecological genetics are beginning to elucidate the evolutionary significance of complex-trait variation. Some of the more notable suc-cesses involve evolutionary analyses of major gene poly-morphisms (for example, refs 14,15) but, as methods for analysing polymorphisms with more subtle effects on traits and fitness improve, it will soon become possible to determine whether similar or different evolutionary

*Department of Biology, BOX 90338, Duke University, Durham, North Carolina 27708, USA. ‡Center for Population Genomics and Pharmacogenetics, Duke Institute for Genomic Sciences and Policy, Duke University Medical Center, BOX 3471, Duke University.Correspondence to T.M.O. e-mail: [email protected]:10.1038/nrg2207

Mutation–selection balanceModels that examine equilibrium levels of genetic variation attributable to mutation, natural selection and genetic drift.

Which evolutionary processes influence natural genetic variation for phenotypic traits?Thomas Mitchell-Olds*, John H. Willis* and David B. Goldstein‡

Abstract | Although many studies provide examples of evolutionary processes such as adaptive evolution, balancing selection, deleterious variation and genetic drift, the relative importance of these selective and stochastic processes for phenotypic variation within and among populations is unclear. Theoretical and empirical studies from humans as well as natural animal and plant populations have made progress in examining the role of these evolutionary forces within species. Tentative generalizations about evolutionary processes across species are beginning to emerge, as well as contrasting patterns that characterize different groups of organisms. Furthermore, recent technical advances now allow the combination of ecological measurements of selection in natural environments with population genetic analysis of cloned QTLs, promising advances in identifying the evolutionary processes that influence natural genetic variation.

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Balancing selectionHistorically, balancing selection refers to evolutionary processes such as frequency-dependent selection or heterozygote advantage that maintain greater than neutral levels of polymorphism within a population. In the era of molecular population genetics, the term balancing selection is often applied to loci showing species-wide levels of nucleotide polymorphism that exceed neutral expectation, regardless of ecological mechanism or levels of variation within populations.

Local adaptationThe situation in which genotypes from different populations have higher fitness in their home environments owing to historical natural selection.

Disruptive selectionOccurs when individuals with extreme phenotypes have higher fitness than those with intermediate trait values.

patterns hold for this type of variation4,9,16. In addition, in the past few years it has become feasible to apply genomic, statistical and ecological approaches to free-living species to study variation at many loci in many individuals, identify the molecular basis of natural phe-notypic variation and investigate the adaptive function of specific variants in natural habitats. These advances are occurring at the same time as human population and quantitative genetics have blossomed, bringing our own species to the forefront of evolutionary genetics, and highlighting the similarity of evolutionary processes in laboratory and ecological models, as well as human populations.

We first provide a brief overview of approaches that can shed light on evolutionary processes by identify-ing loci that have been subject to selection, and the nature of the selection that has acted at these loci. We then review the evidence from a wide range of studies for the contribution of various evolutionary forces that have been suggested to influence genetic variation. We begin by discussing studies that have begun to reveal the overall influence of positive selection, before moving on to look at the role of heterogeneous selection in different populations of the same species, and the scenarios in which balancing selection can contribute to maintaining genetic variation. Finally, we discuss mutation–selection balance models that address the relative importance of deleterious mutations and purifying selection, and the

role of drift in shaping genetic variation. our current knowledge largely derives from particular studies that demonstrate the importance of one evolutionary proc-ess or another, and we therefore present examples that illustrate the diverse evolutionary influences on pheno-typic variation. The challenge for the future is to infer the relative importance of the various evolutionary processes that influence natural genetic variation for phenotypic traits. The focus of this review is on evolutionary inter-pretation, and we do not cover methods for QTl map-ping, association studies or other techniques, which have been discussed elsewhere17–20.

Identifying the relevant loci and processesTo understand the evolutionary forces that act on genetic variation, a major challenge is to identify loci that might have been under selection, and to determine the type of natural selection that has influenced their evolutionary history. Here and in BOX 2 we provide a brief overview of the various approaches to these chal-lenges. more detailed discussion of the limitations and challenges that are posed by each approach can be found in refs 2,3,21–25.

For both quantitative genetic variation and major gene polymorphisms, ‘real-time’ estimates of the mag-nitude and pattern of natural selection can be gained by comparing phenotypes with fitness estimates in natural populations26,27. However, these approaches are effec-tive only with relatively strong selective differences, in the order of 1% or more. The genetic basis of such trait variation can be inferred by QTl mapping or by segregation studies of clearly recognizable phenotypes, such as colour polymorphisms in plants or animals. but even with major genes it is difficult to ascribe fitness effects to particular loci, because tightly linked poly-morphisms can be separated only by molecular analysis (for example, ref. 28).

Advances in evolutionary interpretation become possible when ecologically important polymorphisms are identified at the single-gene level. This level of resolution allows the effects of polymorphism in a particular locus to be separated from variation at tightly linked genes. In addition, patterns of nucleotide polymorphism reveal sequence signatures of adaptive molecular evolution, reflecting historical influences of natural selection. Consequently, historical evolution-ary processes can be inferred from patterns of genetic variation and linkage disequilibrium at loci of inter-est or across the genome. The availability of dense polymorphism data has enabled new methods to detect signatures of selection23,24 (BOX 2).

by themselves, molecular population genetic analy-ses can identify genes that have evolved non-neutrally, but they provide no information about the phenotypic trait that has been targeted by selection. However, when population genetic approaches are combined with infor-mation on molecular function, phenotypic variation and ecological consequences13,29, we might be able to infer which evolutionary processes influence nucleotide poly-morphism at ecologically important genes, as highlighted by examples in later sections of this review.

Box 1 | Evolutionary influences on genetic variation

If nucleotide polymorphisms are neutral, with no effect on fitness, then their allele frequencies will be determined by random genetic drift. This will be true for SNPs that have no effect on phenotype, as well as for phenotypes that have no effect on fitness. Levels of neutral polymorphism will be relatively high when population sizes are large and mutation rates are high.

Recurring deleterious variants are also an important source of genetic variation. Alleles with reduced fitness can be introduced into a population by the immigration of maladapted genes from nearby populations, or from de novo mutations, and may persist transiently in populations until natural selection eliminates them. Among these new mutations, some might disrupt physiologically or ecologically important functions, and are therefore unconditionally deleterious. Alternatively, other mutations might be deleterious in existing environments or genetic backgrounds, but might be advantageous in other ecological or genetic contexts. Levels of polymorphism will be relatively high for very mildly deleterious mutations and when migration or mutation rates are high.

Natural selection can be directional, balancing or occasionally disruptive. Directional selection occurs when a particular allele is favoured as a result of its effect on phenotype. Spatially heterogeneous patterns of directional selection can occur in different populations, which can cause genetic divergence and local adaptation. Alternatively, a favoured allele can sweep towards fixation across the entire species range, with transient polymorphisms that can contribute to segregating genetic variation. Balancing selection is a general term that refers to several different types of selection that actively maintain polymorphism within a population. Examples of these processes include overdominance (when a heterozygote has higher fitness than either homozygote), as well as frequency-dependent selection and temporal or spatial variation in selection. In modern genome-wide studies of nucleotide polymorphisms throughout a species’ geographical range, investigators might also refer to ‘balanced polymorphisms’ when higher than neutral levels of genetic variation are observed, even though it is usually not known whether the elevated polymorphism is due to local adaptation among populations or balancing selection within populations. Hence, it is important to identify the scale at which balancing selection is being discussed.

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Derivedallele

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OverdominanceAn unusual mode of gene action whereby heterozygotes at a given locus have higher fitness than either homozygote.

Positive selectionDirectional selection based on phenotype.

Signatures of selectionPatterns of nucleotide polymorphism, allele frequency and linkage disequilibrium that distinguish selected loci from neutrally evolving genomic regions.

Metapopulations A series of partially isolated conspecific populations that are subject to local extinction and recolonization.

Box 2 | Detecting signatures of selection

MethodsbasedonthesitefrequencyspectrumThese methods are based on the principle that non-neutral evolution leaves a signature of selection in nucleotide polymorphisms. Balancing selection can maintain high levels of variability for long periods of time, hence balanced polymorphisms are expected to have higher levels of variation and more SNPs at intermediate frequency than would occur under neutrality. Selective sweeps occur when an advantageous mutation rises to fixation through positive selection, replacing ancestral alleles and causing reduced levels of genetic variation among the remaining young alleles. In addition, mutations that occur subsequent to the sweep are unusually recent, so swept regions have young polymorphisms, which tend to be rare.

Although it is challenging to relate complex-trait variation to the causal polymorphisms, the degeneracy of the genetic code offers a partial solution for multilocus studies. Because synonymous and non-synonymous mutations differ in functional importance, it is possible to estimate the magnitude and distribution of the functional effects of amino-acid changes based on the level of polymorphism within species and the divergence between species3,5,25,30,101. For example, rapidly evolving genes might show more amino-acid changes than expected under a neutral evolutionary model; similar approaches can be applied to the evolution of non-coding sequences102. However, these approaches entail substantial statistical and population genetic assumptions2,5,103, and more work is needed to understand the consequences of violating these assumptions.

Haplotype-basedmethodsAnother popular approach is to test for extended haplotype homozygosity, which is based on the probability that any two haplotypes that are chosen from a common population will be identical. Such methods exploit the relationship between the extensive linkage disequilibrium that surrounds a new mutation and the time it takes for recombination to degrade it. In the figure, the lengths of haplotypes that flank a particular polymorphism are portrayed for individuals carrying the ancestral (top, coloured blue) or derived (bottom, coloured red) allele at the test SNP. These simulated data show an advantageous derived allele that is rising in frequency owing to natural selection. Old, ancestral alleles have had many generations to accumulate recombinations with flanking polymorphisms; hence, they are carried on relatively short haplotypes. By contrast, when new advantageous mutations rise to a higher frequency, they are relatively young and have had fewer opportunities for recombination with linked polymorphisms; hence, a selective sweep is characterized by unusually long haplotypes.

These tests are well suited for estimating the relative ages of alleles104 that have been subject to directional selection. Nevertheless, although balancing selection on QTL alleles is one of the fundamental hypotheses for the maintenance of quantitative-trait variation, it is unclear whether analyses of extended haplotype homozygosity can detect this mode of natural selection.

softversushardsweepsSignatures of natural selection also depend on whether positive selection favours multiple pre-existing allelic variants (‘soft sweep’) or a single new advantageous mutation (‘hard sweep’)105. These two selective processes leave contrasting signatures of selection, which can be recognizable in patterns of sequence variation106,107. Positive selection on pre-existing allelic variants leaves a distinctive signature on patterns of linkage disequilibrium, and selection on new mutations influences nucleotide polymorphism and the site frequency spectrum. Therefore, with proper experimental design and analysis, both soft and hard sweeps can be identified by comparison to a genome-wide null distribution at many loci (for example, ref. 108).

theinfluenceofdemographicfactorsAlthough simple population and quantitative genetics theory enables predictions of neutral or selected variation, populations in the real world violate many assumptions of these models. For example, many organisms occur in metapopulations consisting of partially isolated finite local populations that are subject to extinction, recolonization, fluctuations in size over time and limited gene flow109. In addition, many organisms mate with relatives or self-fertilize, rather than mating at random as is assumed by many models110.

To account for such demographic influences, population genomic studies in humans and other model organisms have examined patterns of genetic variation at hundreds of loci that have been sampled genome-wide5,30,108. Such analyses will become increasingly feasible in many species as sequencing costs decline. These genome-wide patterns of variation enable inferences about population structure and demographic history, and provide a multilocus null distribution of variation across the genome. In comparison, we can ask whether focal genes that might influence phenotypic variation display a nucleotide signature of non-neutrality41.

Figure modified with permission from ref. 24 (2006) Public Library of Science.

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Selective sweepDirectional selection that fixes an advantageous mutation in a population.

Site frequency spectrumstatistical tests in population genetics use information on the numbers of sNPs that are rare or common, and the frequency of ancestral and derived alleles in order to infer demographic history and possible natural selection. One widely-used statistic is Tajima’s D.

Antagonistic pleiotropyThe situation in which allelic variation at a locus has phenotypic effects on two or more separate traits, or on the same trait expressed in two or more environments.

Clinal variationA gradual change in trait value or gene frequency across a geographical area.

AdmixtureThe pattern of genetic variation that results when a population is derived from founders that originated from more than one ancestral population.

Positive selectionuntil recently, it was difficult to determine the overall influence of positive selection in shaping genetic varia-tion, but rapidly accumulating dense polymorphism data in various species, combined with advances in methods for analysing such data (BOX 2), is now making this pos-sible. Comparison between Drosophila species indicates that 40–95% of amino-acid replacements might reflect adaptive evolution25,30. However, the selection coefficients that influence most of these amino-acid changes are low (<10–4) (ref. 25) — far below the detection limit for real-time measurements of fitness effects, making it difficult to investigate how individual replacements might contribute to adaptive trait divergence. Such high rates of adaptive changes between Drosophila species suggest that many advantageous polymorphisms are approaching fixation at all times, with adaptive substitutions occurring at inter-vals of roughly 10–50 years10. These polymorphisms are likely to have greater effects on particular quantitative traits than on fitness itself, so it is plausible that alleles experiencing ongoing selective sweeps might be important contributors to phenotypic variation in nature.

Several recent studies have considered evidence for positive selection in human genes3,21, suggesting that up to 10% of our genome has been affected by proxim-ity to a selective sweep. voight, et al.24 used a modified extended haplotype homozygosity test to rank all sites in the human genome for the level of extended haplo-type homozygosity, and identified a number of genomic regions as having been subject to positive selection. Several aspects of these analyses strongly suggest that real evidence of selection is being detected. For exam-ple, there is a highly significant enrichment of selection scores in gene regions. moreover, extreme haplotype sta-tistics occur in regions that also show evidence of selec-tion according to measures based on the site frequency spectrum. Comparison of African, Asian and European populations suggests that most detectable selection is restricted to a single population, although there is overlap

between populations for some chromosome regions. When both African and European populations show evidence of selection in overlapping genomic regions, this suggests the action of independent selection in dif-ferent populations (for example, ref. 31), because selec-tion before the emergence from Africa is unlikely to be detectable with these data.

Although the current work on selection suggests that a signal of past selection is detectable in the genome, it is still too early to tell whether these approaches will help to identify the causal SnPs that are responsible for trait variation. For example, although signals of selection sur-rounding well-characterized systems such as the lactase (LCT) and glucose-6-phosphate dehydrogenase (G6PD) genes31,32 show concordant evidence between molecular population genetics and known biochemical function, it is still unclear whether haplotype-based tests of selec-tion can identify the actual SnP that is under selection, as opposed to broad genomic regions. These are the next natural questions for genome-wide assessments of selection, which will benefit greatly from ongoing, large-scale studies in human populations that attempt to link particular SnPs to phenotypic variation.

Heterogeneous selection causes local adaptationForces that influence local adaptation. most species are not distributed homogeneously throughout their geographical range, but are instead subdivided into populations that experience local ecological conditions. Evolutionary models predict that low levels of gene flow between populations and strong, heterogeneous selec-tion at different sites will favour local adaptation among populations33. nevertheless, the genetic basis of local adaptation remains unclear.

For genes of ecological importance, local adaptation can result from genetic trade-offs (that is, antagonistic pleiotropy, in which alleles at a locus change rank fitness across environments) (fIG. 1a). However, changes in the rank of alleles at individual genes are not necessary for local adaptation to occur at the population level; it can also occur when the fitness of alleles differs in magni-tude but not direction across environments34 (fIG. 1b). However, only changes in rank fitness of alleles can main-tain polymorphism at a locus11. QTls that show changes in phenotypic rank across environments have been found in crop plants (for example, ref. 35), but exam-ples from natural populations are few36–38. many such studies find QTl–environment interactions in which alleles differ in magnitude across environments, but not in direction39 (fIG. 1b). However, we are not aware of any QTl studies involving reciprocal transplants between the parental environments, which are essential to deter-mine the genetic basis of local adaptation17,40,41. Such studies are perhaps the best example of ‘low-hanging fruit’ — these experiments are now straightforward and feasible in several ecological models.

Which ecological situations result in fitness trade-offs between the alleles underlying local adaptation? local adaptation is often inferred in studies of clinal variation in traits across geographical or environmental gradi-ents, although non-selective factors, such as admixture

Figure 1 |thefitnesseffectsofallelesdifferbetweenenvironments.Thefitnesses of two QTL alleles (A1 and A2) measured in two environments, E1 and E2. Genotype–environment interaction occurs in both examples, because the two genotypes respond differently to these environments. Panel a shows antagonistic pleiotropy, in which the rank fitness of genotypes changes between E1 and E2. In panel b, the A2 genotype is favoured in both environments; hence, there is no change in fitness ranking between environments.

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Population structureThe distribution of individuals in partially isolated populations. A metapopulation is one example of a population structure, and includes local extinction and recolonization.

EpistasisOccurs when two or more polymorphic loci interact to determine phenotype.

and historical population structure, must be ruled out by additional experiments or observations (see Table 1 of ref. 41). numerous studies have documented latitudinal clines in life-history traits, enzyme alleles and chromo-somal inversions in Drosophila melanogaster, although the selective and ecological causes of this geographical variation are often unclear. one possible exception is the classic latitudinal cline at the Alcohol dehydrogenase (Adh) locus seen in northern and Southern hemispheres. recent work has shown that this cline has shifted about 4o in latitude over the past 20 years in eastern Australia in a manner that is consistent with evolution in response to climate change42.

latitudinal clines are also common for reproduc-tive diapause; for example, diapausing D. melanogaster are found at high frequencies in northern populations in eastern north America but are relatively rare in southern populations43. recently, Schmidt and Conde conducted experimental laboratory studies suggesting that the diapausing phenotype is selectively favoured in cold, winter conditions but disfavoured in benign condi-tions44. besides perhaps explaining the latitudinal clines, this pattern of selective trade-offs might also maintain polymorphisms in populations owing to temporally varying selection. Indeed, the frequency of diapausing genotypes in seasonal populations increases in the winter but declines in the summer season, whereas diapausing genotypes are rare in urban environments.

recently, natural genetic variation at a circadian clock gene has been shown to control a geographical cline in the frequency of diapause in European D. melanogaster 45. A derived allele at the timeless locus has increased in frequency over about 10,000 years, and displays poly-morphisms that are incompatible with simple models of neutral evolution. In the pitcher-plant mosquito, Wyeomyia smithii, QTls controlling a latitudinal cline in diapause and the photoperiodic response are evidently under strong geographically variable selection46. In addi-tion, latitudinal clines in life-history traits and associated genes have also been reported in Arabdiopsis thaliana. For example, the photoreceptor locus PHYTOCHROME C has two naturally occurring haplotype groups that affect flow-ering time and seedling growth. These functionally distinct alleles show greater clinal variation with latitude than a set of SnPs that are distributed throughout the genome, sug-gesting that local selection and not historical population demography might be responsible for the cline47.

local adaptation together with complex interactions involving epistasis, genotype–environment interaction, temporal fluctuation in fitness and the effects of migra-tion could be important factors in maintaining genetic variation in natural populations (for example, ref. 48). one case that exemplifies the complexity of evolutionary processes that are likely to have an impact on ecologi-cally important traits is a flower-colour polymorphism in Linanthus parryae49,50 (fIG. 2). In this species, selection on flower colour shows temporal and spatial variation in both magnitude and direction, influenced in part by dif-ferences in spring precipitation. In this system and others, immigration of maladapted alleles from neighbouring populations might contribute to the maintenance of

genetic variation within populations (for example, ref. 51). In some circumstances, gene flow might be an important source of locally deleterious alleles, which might be of a similar or greater magnitude than new mutations9.

Although the studies reviewed above provide evidence for a role of local adaptation in maintaining genetic vari-ation in species, it is striking that none involves fitness assays of known alleles in natural populations. Tests of local adaptation at the molecular level using approaches similar to classic reciprocal transplant experiments are clearly needed. As ecological model systems such as Arabidopsis, Boechera, Mimulus, Daphnia, sticklebacks and mice14,41,52–57 become more widely used, genetic experiments in natural populations provide one of the main opportunities for future progress.

The molecular basis of local adaptation. Several recent experiments have identified the molecular basis of local adaptation in humans, mice, A. thaliana, sticklebacks and cave fish54,56–61. For example, Storz et al. present evidence for local adaptation of haemoglobin alleles to oxygen availability across an elevation gradient in mice54. Five amino-acid changes in strong linkage dis-equilibrium show allele frequency changes from low to high elevation (fIG. 3), and are predicted to change the oxygen affinity of α-globin. This genic region also has an elevated level of neutral polymorphism and a significant excess of replacement changes, suggesting the presence of an old, balanced polymorphism. Physiological studies have also shown that biochemical differences in protein function may favour alternative allelic forms at high versus low elevation.

Another recent study of local adaptation in mice14 showed that a derived amino-acid change influences adaptive changes in the coat colour of beach mice. In vitro assays showed that biochemical differences in melanocortin 1 receptor (Mc1r) allelic function might control pigmentation differences. Further experiments62 have found epistatic interactions with the chromosomal region that contains the Agouti candidate gene, which encodes the ligand of mC1r. unlike the amino-acid differences between Mc1r alleles, Agouti alleles differ

Figure 2 |colourpolymorphisminLinanthus parryae.Image courtesy of P. Bierzychudek, Lewis & Clark College, Portland, USA, and D. Schemske, Michigan State University, East Lansing, USA.

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in expression levels but not in amino-acid sequence. Taken together, these results support the suggestion that both regulatory and protein changes contribute to adaptive evolution63 and can be maintained within species by local adaptation. Finally, the genetic basis of light coloration (which provides cryptic coloration on light-coloured beach sand (fIG. 4) has evolved inde-pendently in different parts of the species range, and is controlled by variation at different loci. These results emphasize the fact that similar phenotypes can reflect underlying changes at different loci — a fundamental tenet of quantitative genetics.

Local adaptation in human populations. Genome-wide polymorphism studies have also inferred local adaptation among human populations. most recently, Williamson et al.3 examined human polymorphism data for selective sweeps using methods that account for demography, variable recombination and SnP ascertain-ment. Especially prominent are instances of local selec-tive sweeps in European and/or Chinese subpopulations,

suggesting adaptation to local environments following emigration from Africa. In some cases, the selectively favoured traits might be clear (for example, lactase per-sistence31,64,65), whereas other examples identify a chro-mosome region that might have evolved non-neutrally, although the selected trait is unknown.

Balancing selection within populationsbalancing selection can maintain allelic polymorphisms in populations or species. Some of the most striking exam-ples of balancing selection have evidently maintained allelic diversity for millions of years. Well-known exam-ples include the self-incompatibility system in plants12, colour vision in new World monkeys66 and the major histocompatibility complex (MHC) loci in mammals.

Although previous studies have documented ancient balancing selection at the MHC locus in primates (for example, ref. 67), it has remained unclear how current var-iation at this locus within and among human populations is influenced by demographic factors versus recent natu-ral selection. A recent comparison of MHC variation to

Figure 3 |Molecularbasisoflocaladaptationtooxygenavailabilityindeermice.Allele frequencies at three locations, which vary in elevation and therefore oxygen availability, are shown for five polymorphisms that lead to amino-acid replacements in the α-globin protein in deer mice. Amino-acid positions are indicated on the molecular model of α-globin (bottom left); pie charts show derived allele frequencies (represented as darker segments) for these numbered amino-acid positions. Modified with permission from ref. 54 (2007) Public Library of Science.

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Frequency-dependent selectionOccurs when rare alleles have higher fitness than common alleles. This process can maintain genetic variation within populations.

putatively neutral markers68 found a significant influ-ence of demographic history, with variability in MHC loci being predicted by dispersal distance from the East-African site of human origin. MHC loci differ significantly from neutral markers for the distribution of allele frequencies in populations. However, the pos-sible influences of geographically heterogeneous natural selection in different human populations remain unclear, and more research is needed on population-specific pathogen pressures.

on the basis of a genome-wide scan of nucleotide polymorphism in humans, bubb et al.69 suggest that (except for HLA and the blood group locus (ABO)) the human genome shows little evidence for the per-sistence of ancient balanced polymorphisms over mil-lions of years. Some allelic polymorphisms might be maintained by short-term balancing selection following rapid environmental change, such as the maintenance of the sickle-cell HbS polymorphism due to the rise of malaria following the spread of agriculture (BOX 3). In the long term, however, balanced polymorphisms may be replaced by better-adapted mutations (such as the positively selected HbC β-globin mutation), or by gene duplications. This progression from balancing selec-tion at single-copy genes to tandem duplications, which allow both sequences to be maintained in homozygotes

(so called ‘fixed heterozygosity’), might also occur in clus-ters of disease-resistance genes in plants, in which evidence of balancing selection is observed at many loci, but very old polymorphisms are uncommon70. The widespread occurrence of tandemly duplicated disease-resistance genes, with an elevated number of amino-acid differences between loci indicating adaptive evolution71, might reflect this same progression from balanced polymorphism to fixed heterozygosity.

Although the precise nature of the balancing selection that is detected in genome scans is usually unknown, specific well-studied examples indicate that frequency-dependent selection might often be the selective mechanism under-lying balanced polymorphisms. Frequency-dependent selection usually favours alleles when they are rare, and can thus maintain balanced genetic polymorphisms within populations. Examples include flower colour in morning glories72 and orchids73, and a recent study of a major locus that controls larval foraging behaviour in D. melanogaster74. The foraging locus encodes a cGmP-dependent protein kinase for which there are two allelic classes — ‘rover’ and ‘sitter’ — which differ in rates of larval movement. For larvae raised in low-nutrition envi-ronments, both genotypes have the highest fitness when they are rare, thus maintaining this major behavioural polymorphism within populations. These experiments

Figure 4 | Molecularbasisoflocalvariationinthecoatcolourofbeachmice.Pie charts show frequencies of the light and dark alleles of the melanocortin 1 receptor (Mc1r) coat-colour locus (represented as light and dark segments, respectively) in coastal beach mouse populations, with typical coloration for each subspecies. Mc1r polymorphism controls coat-colour differences between western populations, but not on the east coast of Florida. Modified with permission from ref. 14 (2006) American Association for the Advancement of Science.

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Directional selectionThis form of selection favours a particular allele because of its effect on phenotype.

used transgenics to verify that behavioural and fitness differences are attributable to the foraging locus itself, rather than to flanking polymorphisms. It is striking that this polymorphism, which provided one of the best examples of major gene control of complex traits before the era of QTl cloning75, now provides strong evidence for balancing selection on complex-trait variation.

Some of the clearest examples of balancing selection come from plant genes that control resistance to micro-bial pathogens. Some forms of species-wide balancing selection (perhaps frequency-dependent selection within populations or local adaptation between popula-tions) maintain high levels of nucleotide polymorphism at an intermediate frequency, reflecting the evolutionary interaction between resistance genes in host plants and pathogenicity factors in microbial pathogens76. These ecological interactions that lead to balancing selection have been labelled “trench warfare”70, in contrast to sequential bouts of directional selection in a coevolution-ary ‘arms race’ interaction between host and pathogen, in which a change in the host is followed by a counteracting change in the pathogen through one selective sweep after the other. A recent study of nucleotide polymorphism at 27 disease-resistance loci (R genes) in A. thaliana found widespread balancing selection, but little evidence

for selective sweeps in a coevolutionary arms race70. Although one landmark study has clearly shown a fitness cost of resistance15, in most plant–pathogen interactions, we do not know whether polymorphism is maintained within populations by frequency-dependent selection, or whether populations might be locally adapted to pathogens (and genetically monomorphic) owing to differential directional selection among populations.

Although most known examples of balancing selec-tion involve major gene polymorphisms, recent studies of growth rate in A. thaliana16 and pleiotropic variation in D. melanogaster77 have shown that balancing selection can maintain an elevated level of nucleotide polymorphism at the genes that underlie quantitative-trait variation. For example, the Catsup locus controls dopamine syn-thesis in D. melanogaster, and also has pleiotropic effects on longevity, locomotion and sensory-bristle number. most functional variants at this locus are low-frequency amino-acid polymorphisms. most intriguingly, this locus displays an evolutionary signature of balancing selec-tion, in accordance with balancing-selection models of complex-trait variation. However, the actual selective forces (which could involve epistasis, genotype–environment interaction, or frequency-dependent selection) remain to be determined. Thus, although functional roles and

Box 3 | Resistance to malaria

Several lines of evidence111,112 suggest that malaria became a widespread human disease roughly 10,000 years ago, coincident with the rise of agriculture and the establishment of high-density populations of human hosts for mosquito vectors (see figure). This disease has left evidence of natural selection at several human genes112.

Malaria illustrates many of the complications that are typical of complex-trait variation, with influences from multiple loci, epistatic interactions and fitness consequences that depend on environment. The gene encoding glucose-6-phosphate dehydrogenase (G6PD) has been subject to recent strong directional selection in African populations owing to strong selection for resistance to malaria32, whereas this locus experiences purifying selection to maintain enzyme activity in human populations that are not subject to malaria, and also in chimpanzees113.

The sickle-cell polymorphism at the β-globin locus is one of the few examples of overdominance, and causes balancing selection in many African populations. Before modern medical care, sickle-cell heterozygotes (HbAHbS) had the highest fitness, because they have a lower susceptibility to malaria and to sickle-cell anaemia than do the corresponding homozygotes. The HbS haplotype shows linkage disequilibrium that is indicative of recent strong selection114, but this variant is apparently too young to show the elevated levels of nucleotide polymorphism that are predicted for a balanced polymorphism115. The situation is further complicated, however, because another allele (HbC) provides protection against malaria without the deleterious consequences that are experienced by HbSHbS homozygotes. Evidently, the HbC allele arose more recently than HbS, and population genetic analyses116 project that it should increase in frequency in populations that are exposed to malaria.

Although sickle-cell anaemia and α-thalassaemia provide well-known examples of Mendelian diseases, resistance to malaria is a complex trait that is under polygenic control117. Heritability of malaria incidence is approximately 25% in African and Sri Lankan populations, and the β-globin and α-thalassaemia loci are each responsible for only a few percent of the phenotypic variance for incidence of malaria. Furthermore, these two loci show negative epistatic interactions such that the protection against malaria that is experienced by HbAHbS heterozygotes is reduced by epistasis with the locus that is responsible for α-thalassaemia118. In summary, resistance to malaria entails local adaptation caused by heterogeneous directional selection in different populations, balancing selection for HbAHbS heterozygotes, directional selection favouring the HbC allele, negative epistasis with the α-thalassemia locus, and substantial variation attributable to other loci and to environmental factors.

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http://www.ncbi.nlm.nih.gov/entrez/dispomim.cgi?id=603903


Genetic architectureThe number, magnitude and frequencies of QTL alleles, as well as their patterns of epistasis and genotype–environment interaction.

population genetic processes have been identified, the ecological significance of this balanced polymorphism remains unclear — as is true for most QTls.

Deleterious variationHow much do deleterious changes contribute to phe-notypic variation? In addition to balancing selection and local adaptation, deleterious variation is one of the fundamental evolutionary processes that can influence quantitative variation for ecologically and biomedically important traits. With a continual influx of new, delete-rious mutations, some will segregate transiently within populations, resulting in a mutation–selection balance that is influenced by population size and the magnitude of allelic effects on fitness. However, the contribution of these deleterious variants to quantitative-trait variation generally remains ambiguous.

Genetic studies of human diseases provide clear evi-dence for the influence of deleterious polymorphisms within populations. Three recent studies using diverse approaches and several large data sets all conclude that roughly 20% of new non-synonymous mutations have substantial detrimental fitness consequences5,8,78. In many organisms, non-synonymous SnPs segregate at a lower average frequency than do synonymous ones5,30,79, indicating that many amino-acid polymor-phisms have weakly deleterious effects on individual fitness. In D. melanogaster, for example, it has recently been estimated that about 70% of amino-acid polymor-phisms are mildly deleterious25. The fact that standing molecular variation in D. melanogaster largely seems to reflect a balance between purifying selection and recur-rent mutation is perhaps not unexpected, given the high estimated rate of spontaneous deleterious mutation in this species80. Deleterious variation might be even more significant in species with small population sizes, in which natural selection is less effective and stochastic variation is more important. Finally, individuals sampled from phenotypic extremes or patient groups might be enriched for a heterogeneous collection of low-frequency non-synonymous polymorphisms8,81,82, which presum-ably reflect the low-frequency deleterious alleles that are predicted under mutation–selection balance.

Deleterious polymorphisms can be studied by statisti-cal analysis of many loci10, or by detailed examination of rare mendelian polymorphisms. both approaches have been applied in human biomedical genetics, but the latter approach is uncommon in natural populations of plants or animals. one exception is a study of rare genotypes with albino flowers in Delphinium nelsonii83. These geno-types have reduced fitness because they are discriminated against by hummingbird pollinators. However, they do not suffer from a physiological reduction of fitness — as they display normal fecundity when hand pollinated — and might become advantageous within a different polli-nator community. It is difficult to evaluate the importance of deleterious variation in natural populations, because this hypothesis is rarely considered in ecological studies.

many theoretical studies have examined the possible role of mutation–selection balance as a broadly applicable explanation for heritable variation6. In recent years, these

models have become increasingly more realistic and complex, incorporating pleiotropic mutations, indirect selection on polymorphisms and partial dominance. However, most empirical studies provide little insight into the relative importance of deleterious mutation–selection balance versus weak balancing selection for the maintenance of genetic variation in populations4,11,12. nonetheless, some studies suggest that the quantitative genetic variation that has been identified in populations is incompatible with simple mutation–selection balance models, such as analyses of variation for flower size and fitness components in Mimulus guttatus84,85, female fecundity in D. melanogaster 86 and variation for flight speed in D. melanogaster, a trait that shows a substantial evolutionary response continuing for more than 100 gen-erations of artificial selection without deleterious fitness consequences87. Taken together, these results show that genetic variation at ecologically important complex traits is incompatible with simple mutation–selection balance models, although complex models of deleterious vari-ation6,85 as well as balanced polymorphisms74,77 remain plausible. Indeed, both deleterious and balanced polymor-phisms undoubtedly contribute to quantitative-trait vari-ation, and the real question is the relative importance of these two factors. Importantly, the relative significance of deleterious and adaptive variants might be greatly influenced by demographic factors: species with small effective-population sizes (like humans and inbreeding plant species) can be strongly influenced by segregating deleterious polymorphisms, whereas species with large populations (like D. melanogaster and pine trees) offer greater potential for adaptive evolution10,88.

As mentioned earlier in this review, a major role for deleterious alleles that affect ecologically important traits would imply a fundamental disconnect between ecologi-cal and evolutionary importance — although ecological processes might cause purifying selection on heritable variation, much of this variation might be an evolu-tionary dead end, with little possibility to contribute to long-term evolutionary change.

A central role for common alleles. The contribution of common alleles to complex disease provides a funda-mental justification for the current interest in association studies in human populations89. recent examples (for example, ref. 90) suggest that disease-susceptibility alle-les at intermediate frequency contribute to some com-mon human diseases, although other studies also have identified rare deleterious polymorphisms that influence quantitative-trait variation8,81,82.

Common alleles also provide one of the few oppor-tunities to distinguish between balancing selection or mutation–selection balance models for the maintenance of complex-trait variation, because the expected genetic architecture of complex-trait variation differs between these models4,11. In ideal, equilibrium populations, mutation–selection balance models predict that most trait variation is attributable to rare deleterious alle-les, whereas alleles that are under balancing selection may occur at intermediate frequency4,11. This contrast might also apply to molecular population genetics data

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Ascertainment biasA biased estimation of population genetic parameters when the studied individuals are a non-random sample of a reference population. for example, association studies are biased towards the detection of common polymorphisms.

from non-ideal, real-world populations, in which non- synonymous polymorphisms occur at a lower frequency than synonymous ones5,30,79. These contrasting predic-tions offer an experimental test for neutral, deleterious or balanced polymorphisms that influence quantitative- trait variation4,11. For neutrally evolving traits, QTl alleles may occur at rare or intermediate frequencies. by contrast, when natural selection operates on a QTl, then deleterious alleles are predicted to be rare, whereas balanced polymorphisms may occur at intermedi-ate frequency, and may show a molecular signature of balancing selection (for example, ref. 16).

Thus, testing the deleterious versus balanced hypotheses has several steps. First, equilibrium popula-tions with heritable variation must be identified. Then, natural selection on genetically tractable traits must be demonstrated, followed by cloning of the causal locus that underlies a selectively important QTl. The final step is to estimate the magnitude and frequency of QTl alleles that segregate within populations. This approach requires multiple QTl mapping populations, positional cloning of the genes that underlie QTls, and natural populations that approximate the ideal popula-tions that are considered in mutation–selection balance models. Although this is a substantial undertaking, it is far simpler in ecological model organisms than the whole-genome association studies that are now starting to elucidate the genetic basis of complex human diseases. These experiments can now be carried out in several ecological model systems with strong genomic resources and relatively intact natural populations52,53,56,57,91,92.

ConclusionsInformation about the genetic architecture of QTl alleles is essential for inferring the evolutionary processes that shape the genetic variation that exists for complex traits. For decades, biologists have debated about the evolu-tionary forces that influence natural genetic variation. Great progress has been made towards understanding the evolutionary significance of major gene variants and protein polymorphisms, and quantitative genetic stud-ies can measure selection on complex-trait variation93. However, quantitative genetic and coarse QTl mapping studies are blind to the alleles that underlie complex-trait variation. only when we can recognize frequency and linkage-disequilibrium signatures of deleterious or advantageous polymorphisms as well as heterogeneous origins of particular phenotypes, and determine allelic history as well as geography, can we infer which evo-lutionary processes influence the nucleotide polymor-phisms that control quantitative-trait variation4,9,11,23. Progress has been made toward these goals for some major gene polymorphisms (such as resistance to HIv infection94,95), and comparable studies of the genes that underlie QTls are now becoming feasible.

Several approaches will contribute to our under-standing of evolutionary influences on molecular and phenotypic variation, although each of these approaches has limitations and biases. First, genome-wide analyses of nucleotide polymorphism can estimate small selec-tive effects across thousands of genes. Analyses that

examine heterogeneous selection pressures in different populations will be particularly important for a realistic understanding of natural selection3. However, these approaches entail substantial statistical and population genetic assumptions5,25, and they provide no informa-tion about the phenotypic consequences of these poly-morphisms. Second, association studies in humans and plants (for example, refs 19,90) have begun to identify intermediate-frequency polymorphisms that influence complex-trait variation. However, it is difficult to infer the selective importance of these variants using popu-lation genetic approaches, because the loci that can be detected by association studies have atypical allele fre-quencies and patterns of linkage disequilibrium96,97 that differ from genome-wide neutral patterns because of ascertainment bias. For all of these approaches, follow-up studies using independent evidence will be needed to provide further information on the selective importance of such polymorphisms (for example, refs 31,98).

most importantly, fine mapping (and ultimately cloning) of QTls in multiple or complex mapping populations can begin to elucidate the genetic archi-tecture of quantitative-trait variation (for example, refs 53,57,91,99,100), and can identify sequence signa-tures of selective history. This approach is feasible only when phenotypic effects are moderately large, but it can provide information on QTls with representative pat-terns of frequency and linkage disequilibrium, and can be combined with detailed biochemical, ecological and evolutionary analyses (for example, refs 13,15). Several analyses in laboratory and ecological model organisms are needed so that we can begin to recognize generaliza-tions about the compatibility of balancing selection or mutation–selection balance models with well-studied molecular polymorphisms that control quantitative-trait variation. For the foreseeable future, QTls of small effect will remain difficult to study and to understand, except in unusual cases (for example, ref. 16).

We have considered various selective and demo-graphic processes that can influence patterns of genetic variation for ecologically important traits and complex diseases. These processes are not mutually exclusive, and there is good evidence for each of them having an influ-ence in a broad range of species. nevertheless, we have little understanding of their relative importance, and sev-eral key questions remain to be addressed. For example, is most within-population trait variation attributable to deleterious polymorphisms with short residence times and little evolutionary potential? In species with small effective-population sizes, is adaptive evolution limited by the availability of mutations with sufficiently large effects to overcome random genetic drift? Does local adaptation explain most of the nucleotide variation that appears as ‘balanced polymorphisms’ in species-wide surveys? Are interacting effects such as epistasis and genotype– environment interaction important contributors to genetic variation within and between populations? With the increased availability of genomic tools in non-model organisms, and with the developing synthesis of human population genetics with plant and animal studies, we should soon begin to tackle many of these questions.

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AcknowledgementsWe thank D. Lowry, A. Manzaneda, J. Modliszewski, M. Rausher, C. Wu and three anonymous reviewers for helpful comments and discussion. We are grateful to P. Bierzychudek and D. Schemske for unpublished photos of Linanthus par-ryae, and to H. Hoekstra and J. Storz for permission to reprint figures from their publications. This work was sup-ported by the US National Science Foundation, US National Institutes of Health and Duke University, Durham, USA.

DATABASESEntrez Gene: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=geneAdh | α-globin | β-globin | Catsup | foraging | G6PD | LCT | Mc1r | PHYTOCHROME C | timelessOMIM: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIMα-thalassaemia | sickle-cell anaemia

FURTHER INFORMATIONThomas Mitchell-Olds’s homepage: http://fds.duke.edu/db/aas/Biology/faculty/tmoJohn H. Willis’s homepage: http://fds.duke.edu/db/aas/Biology/faculty/jwillisDavid B. Goldstein’s homepage: http://www.genome.duke.edu/people/faculty/goldstein

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http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene

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http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=OMIM



http://fds.duke.edu/db/aas/Biology/faculty/tmo

http://fds.duke.edu/db/aas/Biology/faculty/jwillis

http://www.genome.duke.edu/people/faculty/goldstein

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