Polymorphism and divergence for island-model species

Isolating selective from non-selective forces using site frequency ratios

A new method is introduced for estimating the distribution of mutation fitness effects using site frequency spectra. Unlike previous methods, which make assumptions about non-selective factors, or that try to incorporate such factors into the underlying model, this new method mostly avoids non-selective effects by working with the ratios of counts of selected sites to neutral sites. An expression for the likelihood of a set of selected/neutral ratios is found by treating the ratio of two Poisson random variables as the ratio of two gaussian random variables. This approach also avoids the need to estimate the relative mutation rates of selected and neutral sites. Simulations over a wide range of demographic models, with linked selection effects show that the new SFRatios method performs well for statistical tests of selection, and it performs well for estimating the distribution of selection effects. Performance was better with weak selection models and for expansion and structured demographic models than for bottleneck models. Applications to two populations of Drosophila melanogaster reveal clear but very weak selection on synonymous sites. For nonsynonymous sites, selection was found to be consistent with previous estimates and stronger for an African population than for one from North Carolina.

Stochastic viability in an island model with partial dispersal: Approximation by a diffusion process in the limit of a large number of islands

In this paper, we investigate a finite population undergoing evolution through an island model with partial dispersal and without mutation, where generations are discrete and non-overlapping. The population is structured into D demes, each containing N individuals of two possible types, A and B, whose viability coefficients, sA and sB, respectively, vary randomly from one generation to the next. We assume that the means, variances and covariance of the viability coefficients are inversely proportional to the number of demes D, while higher-order moments are negligible in comparison to 1/D. We use a discrete-time Markov chain with two timescales to model the evolutionary process, and we demonstrate that as the number of demes D approaches infinity, the accelerated Markov chain converges to a diffusion process for any deme size N≥2. This diffusion process allows us to evaluate the fixation probability of type A following its introduction as a single mutant in a population that was fixed for type B. We explore the impact of increasing the variability in the viability coefficients on this fixation probability. At least when N is large enough, it is shown that increasing this variability for type B or decreasing it for type A leads to an increase in the fixation probability of a single A. The effect of the population-scaled variances, σA2 and σB2, can even cancel the effects of the population-scaled means, μA and μB. We also show that the fixation probability of a single A increases as the deme-scaled migration rate increases. Moreover, this probability is higher for type A than for type B if the population-scaled geometric mean viability coefficient is higher for type A than for type B, which means that μA-σA2/2>μB-σB2/2.

Fixation times of de novo and standing beneficial variants in subdivided populations

The rate at which beneficial alleles fix in a population depends on the probability of and time to fixation of such alleles. Both of these quantities can be significantly impacted by population subdivision and limited gene flow. Here, we investigate how limited dispersal influences the rate of fixation of beneficial de novo mutations, as well as fixation time from standing genetic variation. We investigate this for a population structured according to the island model of dispersal allowing us to use the diffusion approximation, which we complement with simulations. We find that fixation may take on average fewer generations under limited dispersal than under panmixia when selection is moderate. This is especially the case if adaptation occurs from de novo recessive mutations, and dispersal is not too limited (such that approximately FST<0.2). The reason is that mildly limited dispersal leads to only a moderate increase in effective population size (which slows down fixation), but is sufficient to cause a relative excess of homozygosity due to inbreeding, thereby exposing rare recessive alleles to selection (which accelerates fixation). We also explore the effect of metapopulation dynamics through local extinction followed by recolonization, finding that such dynamics always accelerate fixation from standing genetic variation, while de novo mutations show faster fixation interspersed with longer waiting times. Finally, we discuss the implications of our results for the detection of sweeps, suggesting that limited dispersal mitigates the expected differences between the genetic signatures of sweeps involving recessive and dominant alleles.

The fitness consequences of genetic divergence between polymorphic gene arrangements

Inversions restrict recombination when heterozygous with standard arrangements, but often have few noticeable phenotypic effects. Nevertheless, there are several examples of inversions that can be maintained polymorphic by strong selection under laboratory conditions. A long-standing model for the source of such selection is divergence between arrangements with respect to recessive or partially recessive deleterious mutations, resulting in a selective advantage to heterokaryotypic individuals over homokaryotypes. This paper uses a combination of analytical and numerical methods to investigate this model, for the simple case of an autosomal inversion with multiple independent nucleotide sites subject to mildly deleterious mutations. A complete lack of recombination in heterokaryotypes is assumed, as well as constancy of the frequency of the inversion over space and time. It is shown that a significantly higher mutational load will develop for the less frequent arrangement. A selective advantage to heterokaryotypes is only expected when the two alternative arrangements are nearly equal in frequency, so that their mutational loads are very similar in size. The effects of some Drosophila pseudoobscura polymorphic inversions on fitness traits seem to be too large to be explained by this process, although it may contribute to some of the observed effects. Several population genomic statistics can provide evidence for signatures of a reduced efficacy of selection associated with the rarer of two arrangements, but there is currently little published data that are relevant to the theoretical predictions.

The role of migration in mutant dynamics in fragmented populations

Mutant dynamics in fragmented populations have been studied extensively in evolutionary biology. Yet, open questions remain, both experimentally and theoretically. Some of the fundamental properties predicted by models still need to be addressed experimentally. We contribute to this by using a combination of experiments and theory to investigate the role of migration in mutant distribution. In the case of neutral mutants, while the mean frequency of mutants is not influenced by migration, the probability distribution is. To address this empirically, we performed in vitro experiments, where mixtures of GFP-labelled ("mutant") and non-labelled ("wid-type") murine cells were grown in wells (demes), and migration was mimicked via cell transfer from well to well. In the presence of migration, we observed a change in the skewedness of the distribution of the mutant frequencies in the wells, consistent with previous and our own model predictions. In the presence of de novo mutant production, we used modelling to investigate the level at which disadvantageous mutants are predicted to exist, which has implications for the adaptive potential of the population in case of an environmental change. In panmictic populations, disadvantageous mutants can persist around a steady state, determined by the rate of mutant production and the selective disadvantage (selection-mutation balance). In a fragmented system that consists of demes connected by migration, a steady-state persistence of disadvantageous mutants is also observed, which, however, is fundamentally different from the mutation-selection balance and characterized by higher mutant levels. The increase in mutant frequencies above the selection-mutation balance can be maintained in small ( N < N c ) demes as long as the migration rate is sufficiently small. The migration rate above which the mutants approach the selection-mutation balance decays exponentially with N / N c . The observed increase in the mutant numbers is not explained by the change in the effective population size. Implications for evolutionary processes in diseases are discussed, where the pre-existence of disadvantageous drug-resistant mutant cells or pathogens drives the response of the disease to treatments.

Metacommunities, fitness and gradual evolution

We analyze the evolution of a multidimensional quantitative trait in a class-structured focal species interacting with other species in a wider metacommunity. The evolutionary dynamics in the focal species as well as the ecological dynamics of the whole metacommunity is described as a continuous-time process with birth, physiological development, dispersal, and death given as rates that can depend on the state of the whole metacommunity. This can accommodate complex local community and global metacommunity environmental feedbacks owing to inter- and intra-specific interactions, as well as local environmental stochastic fluctuations. For the focal species, we derive a fitness measure for a mutant allele affecting class-specific trait expression. Using classical results from geometric singular perturbation theory, we provide a detailed proof that if the effect of the mutation on phenotypic expression is small ("weak selection"), the large system of dynamical equations needed to describe selection on the mutant allele in the metacommunity can be reduced to a single ordinary differential equation on the arithmetic mean mutant allele frequency that is of constant sign. This invariance on allele frequency entails the mutant either dies out or will out-compete the ancestral resident (or wild) type. Moreover, the directional selection coefficient driving arithmetic mean allele frequency can be expressed as an inclusive fitness effect calculated from the resident metacommunity alone, and depends, as expected, on individual fitness differentials, relatedness, and reproductive values. This formalizes the Darwinian process of gradual evolution driven by random mutation and natural selection in spatially and physiologically class-structured metacommunities.

Inferring the distribution of selective effects from a time inhomogeneous model

We have developed a Poisson random field model for estimating the distribution of selective effects of newly arisen nonsynonymous mutations that could be observed as polymorphism or divergence in samples of two related species under the assumption that the two species populations are not at mutation-selection-drift equilibrium. The model is applied to 91Drosophila genes by comparing levels of polymorphism in an African population of D. melanogaster with divergence to a reference strain of D. simulans. Based on the difference of gene expression level between testes and ovaries, the 91 genes were classified as 33 male-biased, 28 female-biased, and 30 sex-unbiased genes. Under a Bayesian framework, Markov chain Monte Carlo simulations are implemented to the model in which the distribution of selective effects is assumed to be Gaussian with a mean that may differ from one gene to the other to sample key parameters. Based on our estimates, the majority of newly-arisen nonsynonymous mutations that could contribute to polymorphism or divergence in Drosophila species are mildly deleterious with a mean scaled selection coefficient of -2.81, while almost 86% of the fixed differences between species are driven by positive selection. There are only 16.6% of the nonsynonymous mutations observed in sex-unbiased genes that are under positive selection in comparison to 30% of male-biased and 46% of female-biased genes that are beneficial. We also estimated that D. melanogaster and D. simulans may have diverged 1.72 million years ago.

Population Genomic Analysis of North American Eastern Wolves (Canis lycaon) Supports Their Conservation Priority Status

The threatened eastern wolf is found predominantly in protected areas of central Ontario and has an evolutionary history obscured by interbreeding with coyotes and gray wolves, which challenges its conservation status and subsequent management. Here, we used a population genomics approach to uncover spatial patterns of variation in 281 canids in central Ontario and the Great Lakes region. This represents the first genome-wide single nucleotide polymorphism (SNP) dataset with substantial sample sizes of representative populations. Although they comprise their own genetic cluster, we found evidence of eastern wolf dispersal outside of the boundaries of protected areas, in that the frequency of eastern wolf genetic variation decreases with increasing distance from provincial parks. We detected eastern wolf alleles in admixed coyotes along the northeastern regions of Lake Huron and Lake Ontario. Our analyses confirm the unique genomic composition of eastern wolves, which are mostly restricted to small fragmented patches of protected habitat in central Ontario. We hope this work will encourage an innovative discussion regarding a plan for managed introgression, which could conserve eastern wolf genetic material in any genome regardless of their potential mosaic ancestry composition and the habitats that promote them.

Forensic genetic analyses in isolated populations with examples of central European Valachs and Roma

Isolated populations present a constant threat to the correctness of forensic genetic casework. In this review article we present several examples of how analyzing samples from isolated populations can bias the results of the forensic statistics and analyses. We select our examples from isolated populations from central and southeastern Europe, namely the Valachs and the European Roma. We also provide the reader with general strategies and principles to improve the laboratory practice (best practice) and reporting of samples from supposedly isolated populations. These include reporting the precise population data used for computing the forensic statistics, using the appropriate θ correction factor for calculating allele frequencies, typing ancestry informative markers in samples of unknown or uncertain ethnicity and establishing ethnic-specific forensic databases.

Recurrence Equations for the Probability Distribution of Sample Configurations in Exact Population Genetics Models

Recurrence equations for the number of types and the frequency of each type in a random sample drawn from a finite population undergoing discrete, nonoverlapping generations and reproducing according to the Cannings exchangeable model are deduced under the assumption of a mutation scheme with infinitely many types. The case of overlapping generations in discrete time is also considered. The equations are developed for the Wright-Fisher model and the Moran model, and extended to the case of the limit coalescent with nonrecurrent mutation as the population size goes to ∞ and the mutation rate to 0. Computations of the total variation distance for the distribution of the number of types in the sample suggest that the exact Moran model provides a better approximation for the sampling formula under the exact Wright-Fisher model than the Ewens sampling formula in the limit of the Kingman coalescent with nonrecurrent mutation. On the other hand, this model seems to provide a good approximation for a Λ-coalescent with nonrecurrent mutation as long as the probability of multiple mergers and the mutation rate are small enough.

Effects of Interference Between Selected Loci on the Mutation Load, Inbreeding Depression, and Heterosis

A classical prediction from single-locus models is that inbreeding increases the efficiency of selection against partially recessive deleterious alleles (purging), thereby decreasing the mutation load and level of inbreeding depression. However, previous multilocus simulation studies found that increasing the rate of self-fertilization of individuals may not lead to purging and argued that selective interference among loci causes this effect. In this article, I derive simple analytical approximations for the mutation load and inbreeding depression, taking into account the effects of interference between pairs of loci. I consider two classical scenarios of nonrandomly mating populations: a single population undergoing partial selfing and a subdivided population with limited dispersal. In the first case, correlations in homozygosity between loci tend to reduce mean fitness and increase inbreeding depression. These effects are stronger when deleterious alleles are more recessive, but only weakly depend on the strength of selection against deleterious alleles and on recombination rates. In subdivided populations, interference increases inbreeding depression within demes, but decreases heterosis between demes. Comparisons with multilocus, individual-based simulations show that these analytical approximations are accurate as long as the effects of interference stay moderate, but fail for high deleterious mutation rates and low dominance coefficients of deleterious alleles.

Social evolution and genetic interactions in the short and long term

The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W.D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks capture both weak and strong effects of social payoffs in a manner difficult to replicate with the short-term approach. Together, the results from the short and long-term approaches suggest both how Hamilton's insight may be robust in unexpected ways and how current analytical approaches can expand our understanding of social evolution far beyond Hamilton's original work.

Robust estimates of divergence times and selection with a poisson random field model: a case study of comparative phylogeographic data

Mutation frequencies can be modeled as a Poisson random field (PRF) to estimate speciation times and the degree of selection on newly arisen mutations. This approach provides a quantitative theory for comparing intraspecific polymorphism with interspecific divergence in the presence of selection and can be used to estimate population genetic parameters. Although the original PRF model has been extended to more general biological settings to make statistical inference about selection and divergence among model organisms, it has not been incorporated into phylogeographic studies that focus on estimating population genetic parameters for nonmodel organisms. Here, we modified a recently developed time-dependent PRF model to independently estimate genetic parameters from a nuclear and mitochondrial DNA data set of 22 sister pairs of birds that have diverged across a biogeographic barrier. We found that species that inhabit humid habitats had more recent divergence times and larger effective population sizes than those that inhabit drier habitats, and divergence time estimated from the PRF model were similar to estimates from a coalescent species-tree approach. Selection coefficients were higher in sister pairs that inhabited drier habitats than in those in humid habitats, but overall the mitochondrial DNA was under weak selection. Our study indicates that PRF models are useful for estimating various population genetic parameters and serve as a framework for incorporating estimates of selection into comparative phylogeographic studies.

Statistical inference of selection and divergence from a time-dependent Poisson random field model

We apply a recently developed time-dependent Poisson random field model to aligned DNA sequences from two related biological species to estimate selection coefficients and divergence time. We use Markov chain Monte Carlo methods to estimate species divergence time and selection coefficients for each locus. The model assumes that the selective effects of non-synonymous mutations are normally distributed across genetic loci but constant within loci, and synonymous mutations are selectively neutral. In contrast with previous models, we do not assume that the individual species are at population equilibrium after divergence. Using a data set of 91 genes in two Drosophila species, D. melanogaster and D. simulans, we estimate the species divergence time (or 1.68 million years, assuming the haploid effective population size years) and a mean selection coefficient per generation . Although the average selection coefficient is positive, the magnitude of the selection is quite small. Results from numerical simulations are also presented as an accuracy check for the time-dependent model.

The relation between the neutrality index for mitochondrial genes and the distribution of mutational effects on fitness

We explore factors affecting patterns of polymorphism and divergence (as captured by the neutrality index) at mammalian mitochondrial loci. To do this, we develop a population genetic model that incorporates a fraction of neutral amino acid sites, mutational bias, and a probability distribution of selection coefficients against new nonsynonymous mutations. We confirm, by reanalyzing publicly available datasets, that the mitochondrial cyt-b gene shows a broad range of neutrality indices across mammalian taxa, and explore the biological factors that can explain this observation. We find that observed patterns of differences in the neutrality index, polymorphism, and divergence are not caused by differences in mutational bias. They can, however, be explained by a combination of a small fraction of neutral amino acid sites, weak selection acting on most amino acid mutations, and differences in effective population size among taxa.

Evolutionary games in deme structured, finite populations

We describe a fairly general model for the evolutionary dynamics in a sub-divided (or deme structured) population with migration and mutation. The number and size of demes are finite and fixed. The fitness of each individual is determined by pairwise interactions with other members of the same deme. The dynamics within demes can be modeled according to a broad range of evolutionary processes. With a probability proportional to fitness, individuals migrate to another deme. Mutations occur randomly. In the limit of few migrations and even rarer mutations we derive a simple analytic condition for selection to favor one strategic type over another. In particular, we show that the Pareto efficient type is favored when competition within demes is sufficiently weak. We then apply the general results to the prisoner's dilemma game and discuss selected dynamics and the conditions for cooperation to prevail.

The population genomics of plant adaptation

There has been an enormous increase in the amount of data on DNA sequence polymorphism available for many organisms in the last decade. New sequencing technologies provide great potential for investigating natural selection in plants using population genomic approaches. However, plant populations frequently show significant departures from the assumptions of standard models used to detect selection and many forms of directional selection do not fit with classical population genetics theory. Here, we explore the extent to which plant populations show departures from standard model assumptions, and the implications this has for detecting selection on molecular variation. A growing number of multilocus studies of nucleotide variation suggest that changes in population size, particularly bottlenecks, and strong subdivision may be common in plants. This demographic variation presents important challenges for models used to infer selection. In addition, selection from standing genetic variation and multiple independent adaptive substitutions can further complicate efforts to understand the nature of selection. We discuss emerging patterns from plant studies and propose that, rather than treating population history as a nuisance variable when testing for selection, the interaction between demography and selection is of fundamental importance for evolutionary studies of plant populations using molecular data.

Shifts in the intensity of purifying selection: an analysis of genome-wide polymorphism data from two closely related yeast species

How much does the intensity of purifying selection vary among populations and species? How uniform are the shifts in selective pressures across the genome? To address these questions, we took advantage of a recent, whole-genome polymorphism data set from two closely related species of yeast, Saccharomyces cerevisiae and S. paradoxus, paying close attention to the population structure within these species. We found that the average intensity of purifying selection on amino acid sites varies markedly among populations and between species. As expected in the presence of extensive weakly deleterious mutations, the effect of purifying selection is substantially weaker on single nucleotide polymorphisms (SNPs) segregating within populations than on SNPs fixed between population samples. Also in accordance with a Nearly Neutral model, the variation in the intensity of purifying selection across populations corresponds almost perfectly to simple measures of their effective size. As a first step toward understanding the processes generating these patterns, we sought to tease apart the relative importance of systematic, genome-wide changes in the efficacy of selection, such as those expected from demographic processes and of gene-specific changes, which may be expected after a shift in selective pressures. For that purpose, we developed a new model for the evolution of purifying selection between populations and inferred its parameters from the genome-wide data using a likelihood approach. We found that most, but not all changes seem to be explained by systematic shifts in the efficacy of selection. One population, the sake-derived strains of S. cerevisiae, however, also shows extensive gene-specific changes, plausibly associated with domestication. These findings have important implications for our understanding of purifying selection as well as for estimates of the rate of molecular adaptation in yeast and in other species.

Recurrence Equations for the Probability Distribution of Sample Configurations in Exact Population Genetics Models

Recurrence equations for the number of types and the frequency of each type in a random sample drawn from a finite population undergoing discrete, nonoverlapping generations and reproducing according to the Cannings exchangeable model are deduced under the assumption of a mutation scheme with infinitely many types. The case of overlapping generations in discrete time is also considered. The equations are developed for the Wright-Fisher model and the Moran model, and extended to the case of the limit coalescent with nonrecurrent mutation as the population size goes to ∞ and the mutation rate to 0. Computations of the total variation distance for the distribution of the number of types in the sample suggest that the exact Moran model provides a better approximation for the sampling formula under the exact Wright-Fisher model than the Ewens sampling formula in the limit of the Kingman coalescent with nonrecurrent mutation. On the other hand, this model seems to provide a good approximation for a Λ-coalescent with nonrecurrent mutation as long as the probability of multiple mergers and the mutation rate are small enough.

The genealogical consequences of fecundity variance polymorphism

The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules.

Fixation probability of beneficial mutations in a fluctuating population

We compute an accurate approximation to the probability of fixation for a beneficial mutation in a population fluctuating with a stationary distribution of population size. The population dynamics are described by the theta-logistic model with environmental variance, assuming that the population size is large enough to ignore demographic variance. We show that stochastic fluctuations of population size reduce the probability of fixation. However, it is not the magnitude of the population fluctuations per se that creates this reduction. Only the environmental variance has a substantial effect on the probability of fixation. The strength of density dependence (or expected return time to equilibrium) and the functional form of density-regulation, given by the parameter theta in the theta-logistic model, have little effect on the fixation probability. Effective population size based on harmonic mean population size will therefore underestimate the expected fixation rate of beneficial mutations in fluctuating populations.

Diffusion approximations for one-locus multi-allele kin selection, mutation and random drift in group-structured populations: a unifying approach to selection models in population genetics

Diffusion approximations are ascertained from a two-time-scale argument in the case of a group-structured diploid population with scaled viability parameters depending on the individual genotype and the group type at a single multi-allelic locus under recurrent mutation, and applied to the case of random pairwise interactions within groups. The main step consists in proving global and uniform convergence of the distribution of the group types in an infinite population in the absence of selection and mutation, using a coalescent approach. An inclusive fitness formulation with coefficient of relatedness between a focal individual J affecting the reproductive success of an individual I, defined as the expected fraction of genes in I that are identical by descent to one or more genes in J in a neutral infinite population, given that J is allozygous or autozygous, yields the correct selection drift functions. These are analogous to the selection drift functions obtained with pure viability selection in a population with inbreeding. They give the changes of the allele frequencies in an infinite population without mutation that correspond to the replicator equation with fitness matrix expressed as a linear combination of a symmetric matrix for allozygous individuals and a rank-one matrix for autozygous individuals. In the case of no inbreeding, the mean inclusive fitness is a strict Lyapunov function with respect to this deterministic dynamics. Connections are made between dispersal with exact replacement (proportional dispersal), uniform dispersal, and local extinction and recolonization. The timing of dispersal (before or after selection, before or after mating) is shown to have an effect on group competition and the effective population size.

Population frequencies of transposable elements in selfing and outcrossing Caenorhabditis nematodes

Population genetics theory predicts that differences in breeding systems should be an important factor in the dynamics of selfish genetic elements, because of different intensities of selection on both hosts and elements. We examined population frequencies of transposable elements (TEs) in natural populations of the self-fertilizing nematode Caenorhabditis elegans and its outcrossing relative Caenorhabditis remanei. We identified a Tc1-like class of elements in the C. remanei genome with homology to the terminal inverted repeats of the C. elegans Tc1 transposon, which we name mTcre1. We measured levels of insertion polymorphism for all 32 Tc1 elements present in the genome sequence of the C. elegans N2 strain, and 16 mTcre1 elements from the genome sequence of the C. remanei PB4641 strain. We show that transposons are less polymorphic and segregate at higher frequencies in C. elegans compared with C. remanei. Estimates of the intensity of selection based on the population frequencies of polymorphic elements suggest that transposons are selectively neutral in C. elegans, but subject to purifying selection in C. remanei. These results are consistent with a reduced efficacy of natural selection against TEs in selfing populations, but may in part be explained by non-equilibrium TE dynamics.

The polymorphism frequency spectrum of finitely many sites under selection

The distribution of genetic polymorphisms in a population contains information about evolutionary processes. The Poisson random field (PRF) model uses the polymorphism frequency spectrum to infer the mutation rate and the strength of directional selection. The PRF model relies on an infinite-sites approximation that is reasonable for most eukaryotic populations, but that becomes problematic when is large ( greater, similar 0.05). Here, we show that at large mutation rates characteristic of microbes and viruses the infinite-sites approximation of the PRF model induces systematic biases that lead it to underestimate negative selection pressures and mutation rates and erroneously infer positive selection. We introduce two new methods that extend our ability to infer selection pressures and mutation rates at large : a finite-site modification of the PRF model and a new technique based on diffusion theory. Our methods can be used to infer not only a "weighted average" of selection pressures acting on a gene sequence, but also the distribution of selection pressures across sites. We evaluate the accuracy of our methods, as well that of the original PRF approach, by comparison with Wright-Fisher simulations.

Population genetics of speciation in two closely related wild tomatoes (Solanum section Lycopersicon)

We present a multilocus sequencing study to assess patterns of polymorphism and divergence in the closely related wild tomato species, Solanum peruvianum and S. chilense (Solanum section Lycopersicon, Solanaceae). The data set comprises seven mapped nuclear loci (approximately 9.3 kb of analyzed sequence across loci) and four local population samples per species that cover much of the species' range (between 80 and 88 sequenced alleles across both species). We employ the analytical framework of divergence population genetics (DPG) in evaluating the utility of the "isolation" model of speciation to explain observed patterns of polymorphism and divergence. Whereas the isolation model is not rejected by goodness-of-fit criteria established via coalescent simulations, patterns of intragenic linkage disequilibrium provide evidence for postdivergence gene flow at two of the seven loci. These results suggest that speciation occurred under residual gene flow, implying that natural selection is one of the evolutionary forces driving the divergence of these tomato species. This inference is fully consistent with their recent divergence, conservatively estimated to be <or=0.55 million years. We discuss possible biases in the demographic parameter estimates due to the current restriction of DPG algorithms to panmictic species.

Identification of human T cell targets recognized during Chlamydia trachomatis genital infection

The specificity of the human T cell response to Chlamydia trachomatis was investigated by stimulating lymphocytes from 16 case patients with urogenital infection by use of a size-fractionated serovar D lysate. Considerable heterogeneity was found among case patients, and multiple protein fractions were recognized in each specimen. Mass spectrometry analysis of the 30-42-kDa T cell-stimulating region identified 10 C. trachomatis proteins. Of these, CT583, CT603, and CT610 were identified as strong antigens that induced significantly higher levels of IFN- gamma secretion in PBMCs from case patients, compared with PBMCs from control donors. All 3 proteins were recognized in specimens from case patients infected with serovars D-F, the most prevalent serovars. McDonald-Kreitman and Tajima's D tests involving clinical isolates from the same samples showed evidence for frequency-dependent selection on ct583. We predict that CT583 is a target of acquired protective immune responses in humans.

An exact sampling formula for the Wright-Fisher model and a solution to a conjecture about the finite-island model

An exact sampling formula for a Wright-Fisher population of fixed size N under the infinitely many neutral alleles model is deduced. This extends the Ewens formula for the configuration of a random sample to the case where the sample is drawn from a population of small size, that is, without the usual large-N and small-mutation-rate assumption. The formula is used to prove a conjecture ascertaining the validity of a diffusion approximation for the frequency of a mutant-type allele under weak selection in segregation with a wild-type allele in the limit finite-island model, namely, a population that is subdivided into a finite number of demes of size N and that receives an expected fraction m of migrants from a common migrant pool each generation, as the number of demes goes to infinity. This is done by applying the formula to the migrant ancestors of a single deme and sampling their types at random. The proof of the conjecture confirms an analogy between the island model and a random-mating population, but with a different timescale that has implications for estimation procedures.

Microbial diversity--insights from population genetics

Although many environmental microbial populations are large and genetically diverse, both the level of diversity and the extent to which it is ecologically relevant remain enigmatic. Because the effective (or long-term) population size, N(e), is one of the parameters that determines population genetic diversity, tests and simulations that assume selectively neutral mutations may help to identify the processes that have shaped microbial diversity. Using ecologically important genes, tests of selective neutrality suggest that adaptive as well as non-adaptive types of selection act and that departure from neutrality may be widespread or restricted to small groups of genotypes. Population genetic simulations using population sizes between 10(3) and 10(7) suggest extremely high levels of microbial diversity in environments that sustain large populations. However, census and effective population sizes may differ considerably, and because we know nothing of the evolutionary history of environmental microbial populations, we also have no idea what N(e) of environmental populations is. On the one hand, this reflects our ignorance of the microbial world. On the other hand, the tests and simulations illustrate interactions between microbial diversity and microbial population genetics that should inform our thinking in microbial ecology. Because of the different views on microbial diversity across these disciplines, such interactions are crucial if we are to understand the role of genes in microbial communities.

Fixation probability for a beneficial allele and a mutant strategy in a linear game under weak selection in a finite island model

The effect of population structure on the probability of fixation of a newly introduced mutant under weak selection is studied using a coalescent approach. Wright's island model in a framework of a finite number of demes is assumed and two selection regimes are considered: a beneficial allele model and a linear game among offspring. A first-order approximation of the fixation probability for a single mutant with respect to the intensity of selection is deduced. The approximation requires the calculation of expected coalescence times, under neutrality, for lineages starting from two or three sampled individuals. The results are obtained in a general setting without assumptions on the number of demes, the deme size or the migration rate, which allows for simultaneous coalescence or migration events in the genealogy of the sampled individuals. Comparisons are made with limit cases as the deme size or the number of demes goes to infinity or the migration rate goes to zero for which a diffusion approximation approach is possible. Conditions for selection to favor a mutant strategy replacing a resident strategy in the context of a linear game in a finite island population are addressed.

Selection on protein-coding genes of natural cyanobacterial populations

We examined the distribution of synonymous and non-synonymous changes in 12 protein-coding genes of natural populations of cyanobacteria to infer changes in gene functionality. By comparing mutation distributions within and across species using the McDonald-Kreitman test, we found data sets to contain evidence for purifying selection (hetR of Trichodesmium, nifH of Cylindrospermopsis raceborskii and rpoC1 of Anabaena lemmermannii) and positive selection (kaiC of Microcoleus chthonoplastes and rbcX of Anabaena and Aphanizomenon sp.). Other genes from the same set of clonal isolates (petB and rbcL in M. chthonoplastes and Anabaena/Aphanizomenon, respectively) did not harbour evidence for either form of selection. The results of branch models of codon evolution agreed fully with the results of the McDonald-Kreitman test in terms of significance and absolute value of the dN/dS estimates. The high frequency of gene-specific mutation patterns and their association with branches that separate closely related cyanobacterial genera suggest that evolutionary tests are suited to uncover gene-specific selective differentiation in cyanobacterial genomes. At the same time, given the lack of information about the history of cyanobacteria, analysis of larger numbers of protein-coding genes of clonal cyanobacterial isolates will produce more detailed pictures of the effects of natural selection.

Recurrent positive selection at bgcn, a key determinant of germ line differentiation, does not appear to be driven by simple coevolution with its partner protein bam

Surveys of nucleotide sequence polymorphism in Drosophila melanogaster and Drosophila simulans were performed at 2 interacting loci crucial for gametogenesis: bag-of-marbles (bam) and benign gonial cell neoplasm (bgcn). At the polymorphism level, both loci appear to be evolving under the expectations of the neutral theory. However, ratios of polymorphism and divergence for synonymous and nonsynonymous mutations depart significantly from neutral expectations for both loci consistent with a previous observation of positive selection at bam. The deviations suggest either an excess of synonymous polymorphisms or an excess of nonsynonymous fixations at both loci. Synonymous evolution appears to conform to neutrality at bam. At bgcn, there is evidence of positive selection affecting preferred synonymous mutations along the D. simulans lineage. However, there is also a significantly higher rate of nonsynonymous fixations at bgcn within D. simulans. Thus, the deviation from neutrality detected by the McDonald-Kreitman test at these 2 loci is likely due to the selective acceleration of nonsynonymous fixations. Differences in the pattern of amino acid fixations between these 2 interacting proteins suggest that the detected positive selection is not due to a simple model of coevolution.

Weak selection and recent mutational changes influence polymorphic synonymous mutations in humans

Recent large-scale genomic and evolutionary studies have revealed the small but detectable signature of weak selection on synonymous mutations during mammalian evolution, likely acting at the level of translational efficacy (i.e., translational selection). To investigate whether weak selection, and translational selection in particular, plays any role in shaping the fate of synonymous mutations that are present today in human populations, we studied genetic variation at the polymorphic level and patterns of evolution in the human lineage after human-chimpanzee separation. We find evidence that neutral mechanisms are influencing the frequency of polymorphic mutations in humans. Our results suggest a recent increase in mutational tendencies toward AT, observed in all isochores, that is responsible for AT mutations segregating at lower frequencies than GC mutations. In all, however, changes in mutational tendencies and other neutral scenarios are not sufficient to explain a difference between synonymous and noncoding mutations or a difference between synonymous mutations potentially advantageous or deleterious under a translational selection model. Furthermore, several estimates of selection intensity on synonymous mutations all suggest a detectable influence of weak selection acting at the level of translational selection. Thus, random genetic drift, recent changes in mutational tendencies, and weak selection influence the fate of synonymous mutations that are present today as polymorphisms. All of these features, neutral and selective, should be taken into account in evolutionary analyses that often assume constancy of mutational tendencies and complete neutrality of synonymous mutations.

Effect of population structure on the amount of polymorphism and the fixation probability under overdominant selection

Under overdominant selection, mutants substantially contribute to increase the amount of polymorphism. It is also known that under neutrality as the migration rates among demes decrease in a subdivided population, the amount of polymorphism increases along with the increase of the effective population size, N(e). In this study, under overdominant selection the effect of population subdivision on the amount of polymorphism was investigated using the diffusion approximation and the low migration approximation. It was shown that if selection is medium or strong (e.g., N(T)s > 1, where N(T) is the population size and s is the selective advantage of heterozygotes), the nucleotide diversity, pi, decreases along with the decrease of Nm against the increase of N(e), where N is the size of demes and m is the migration rate per deme. In addition, the ratio of the nucleotide diversity to the evolutionary rate also decreases along with the decrease of Nm. In some cases the ratio becomes smaller than that expected under neutrality as Nm decreases.

Separation of time scales, fixation probabilities and convergence to evolutionarily stable states under isolation by distance

To a first order of approximation, selection is frequency independent in a wide range of family structured models and in populations following an island model of dispersal, provided the number of families or demes is large and the population is haploid or diploid but allelic effects on phenotype are semidominant. This result underlies the way the evolutionary stability of traits is computed in games with continuous strategy sets. In this paper similar results are derived under isolation by distance. The first-order effect on expected change in allele frequency is given in terms of a measure of local genetic diversity, and of measures of genetic structure which are almost independent of allele frequency in the total population when the number of demes is large. Hence, when the number of demes increases the response to selection becomes of constant sign. This result holds because the relevant neutral measures of population structure converge to equilibrium at a rate faster than the rate of allele frequency changes in the total population. In the same conditions and in the absence of demographic fluctuations, the results also provide a simple way to compute the fixation probability of mutants affecting various ecological traits, such as sex ratio, dispersal, life-history, or cooperation, under isolation by distance. This result is illustrated and tested against simulations for mutants affecting the dispersal probability under a stepping-stone model.

Inbreeding Depression and the Evolution of Dispersal Rates: A Multilocus Model

Inbreeding depression is one of the possible reasons organisms disperse. In this article, we present a two-locus model for the evolution of dispersal in the presence of inbreeding depression. The first locus codes for a modifier of the migration rate, while the second locus is a selected locus generating inbreeding depression. We express the change in frequency of the migration modifier as a function of allele frequencies and genetic associations and then use a quasi-equilibrium assumption to express genetic associations as functions of allele frequencies. Our model disentangles two effects of inbreeding depression: it gives an advantage to migrant individuals because their offspring are on average less homozygous, but it also decreases the degree of population structure, thus decreasing the strength of kin selection for dispersal. We then extend our model to include an infinite number of selected loci. When the cost of dispersal is not too high, the model predictions are confirmed by multilocus simulation results and show that inbreeding depression can have a substantial effect on the dispersal rate. For high costs of dispersal, we observe discrepancies between the model and the simulations, probably caused by associations among selected loci, which are neglected in the analysis.

Multiple signatures of positive selection downstream of notch on the X chromosome in Drosophila melanogaster

To identify genomic regions affected by the rapid fixation of beneficial mutations (selective sweeps), we performed a scan of microsatellite variability across the Notch locus region of Drosophila melanogaster. Nine microsatellites spanning 60 kb of the X chromosome were surveyed for variation in one African and three non-African populations of this species. The microsatellites identified an approximately 14-kb window for which we observed relatively low levels of variability and/or a skew in the frequency spectrum toward rare alleles, patterns predicted at regions linked to a selective sweep. DNA sequence polymorphism data were subsequently collected within this 14-kb region for three of the D. melanogaster populations. The sequence data strongly support the initial microsatellite findings; in the non-African populations there is evidence of a recent selective sweep downstream of the Notch locus near or within the open reading frames CG18508 and Fcp3C. In addition, we observe a significant McDonald-Kreitman test result suggesting too many amino acid fixations species wide, presumably due to positive selection, at the unannotated open reading frame CG18508. Thus, we observe within this small genomic region evidence for both recent (skew toward rare alleles in non-African populations) and recurring (amino acid evolution at CG18508) episodes of positive selection.

A composite-likelihood approach for detecting directional selection from DNA sequence data

We present a novel composite-likelihood-ratio test (CLRT) for detecting genes and genomic regions that are subject to recurrent natural selection (either positive or negative). The method uses the likelihood functions of Hartl et al. (1994) for inference in a Wright-Fisher genic selection model and corrects for nonindependence among sites by application of coalescent simulations with recombination. Here, we (1) characterize the distribution of the CLRT statistic (Lambda) as a function of the population recombination rate (R=4Ner); (2) explore the effects of bias in estimation of R on the size (type I error) of the CLRT; (3) explore the robustness of the model to population growth, bottlenecks, and migration; (4) explore the power of the CLRT under varying levels of mutation, selection, and recombination; (5) explore the discriminatory power of the test in distinguishing negative selection from population growth; and (6) evaluate the performance of maximum composite-likelihood estimation (MCLE) of the selection coefficient. We find that the test has excellent power to detect weak negative selection and moderate power to detect positive selection. Moreover, the test is quite robust to bias in the estimate of local recombination rate, but not to certain demographic scenarios such as population growth or a recent bottleneck. Last, we demonstrate that the MCLE of the selection parameter has little bias for weak negative selection and has downward bias for positively selected mutations.

Germline bottlenecks, biparental inheritance and selection on mitochondrial variants: a two-level selection model

Selection on mitochondrial mutations potentially occurs at different levels: at the mitochondria, cell, and organism levels. Several factors affect the strength of selection at these different levels; in particular, mitochondrial bottlenecks during germline development and reduced paternal transmission decrease the genetic variance within cells, while they increase the variance between cells and between organisms, thus decreasing the strength of selection within cells and increasing the strength of selection between cells and organisms. However, bottlenecks and paternal transmission also affect the effective mitochondrial population size, thus affecting genetic drift. In this article, we use a simple model of a unicellular life cycle to investigate the effects of bottlenecks and paternal transmission on the probability of fixation of mitochondrial mutants and their frequency at mutation-selection equilibrium. We find that bottlenecks and reduced paternal transmission decrease the mean frequency of alleles with sm>sc (approximately), where sm and sc are the strengths of selection for an allele within and between cells, respectively, and increase the frequency of alleles with sm<sc. Effects on fixation probabilities are different; for example, bottlenecks reduce the fixation probability of mutants with sm>0 (unless sm is very small relative to sc) and increase the fixation probability of mutants with sm<0.

Distinguishing between selective sweeps and demography using DNA polymorphism data

In 2002 Kim and Stephan proposed a promising composite-likelihood method for localizing and estimating the fitness advantage of a recently fixed beneficial mutation. Here, we demonstrate that their composite-likelihood-ratio (CLR) test comparing selective and neutral hypotheses is not robust to undetected population structure or a recent bottleneck, with some parameter combinations resulting in a false positive rate of nearly 90%. We also propose a goodness-of-fit test for discriminating rejections due to directional selection (true positive) from those due to population and demographic forces (false positives) and demonstrate that the new method has high sensitivity to differentiate the two classes of rejections.

Joint effects of self-fertilization and population structure on mutation load, inbreeding depression and heterosis

Both the spatial distribution of organisms and their mode of reproduction have important effects on the change in allele frequencies within populations. In this article, we study the combined effect of population structure and the rate of partial selfing of organisms on the efficiency of selection against recurrent deleterious mutations. Assuming an island model of population structure and weak selection, we express the mutation load, the within- and between-deme inbreeding depression, and heterosis as functions of the frequency of deleterious mutants in the metapopulation; we then use a diffusion model to calculate an expression for the equilibrium probability distribution of this frequency of deleterious mutants. This allows us to derive approximations for the average mutant frequency, mutation load, inbreeding depression, and heterosis, the simplest ones being Equations 35-39 in the text. We find that population structure can help to purge recessive deleterious mutations and reduce the load for some parameter values (in particular when the dominance coefficient of these mutations is <0.2-0.3), but that this effect is reversed when the selfing rate is above a given value. Conversely, within-deme inbreeding depression always decreases, while heterosis always increases, with the degree of population subdivision, for all selfing rates.