Population genetics of polymorphism and divergence under fluctuating selection

Models of Fluctuating Selection Between Generations: A Solution for the Theoretical Inconsistency

The theory of selection fluctuation between generations has been a topic with much activities in population genetics and molecular evolution in 1970's. Most studies suggested that, as the result of fluctuating selection between generations, the frequency of an (on average) neutral mutation may fluctuate around 0.5 during the long-term evolution before it was ultimately fixed or lost. However, this pattern can only be derived from a specific type Wright-Fisher additive model, coined by the Nei-Yokoyama puzzle. In this commentary, I revisited this issue and figured out a theoretical assumption that has never been claimed explicitly, the notion of reference phenotype. Consider one locus with two-alleles: A is the wildtype allele and A' is the mutation. The fluctuating selection model actually requires a constraint that one of three genotypes (AA, AA', or A'A') must maintain a constant fitness without fluctuating between generations. It appears that the balancing selection at a frequency of 0.5 emerges only when the heterozygote (AA') is the reference genotype. Because it is difficult to determine which genotype could be the reference genotype in a real population, a desirable population genetics model should take all three possibilities into account. To this end, I propose a mixture model, where each genotype has a certain chance to be the reference genotype. My analysis showed that the emergence of balancing selection depends on the relative proportions of three different reference genotypes.

The genome-wide signature of short-term temporal selection

Despite evolutionary biology's obsession with natural selection, few studies have evaluated multigenerational series of patterns of selection on a genome-wide scale in natural populations. Here, we report on a 10-y population-genomic survey of the microcrustacean Daphnia pulex. The genome sequences of [Formula: see text]800 isolates provide insights into patterns of selection that cannot be obtained from long-term molecular-evolution studies, including the following: the pervasiveness of near quasi-neutrality across the genome (mean net selection coefficients near zero, but with significant temporal variance about the mean, and little evidence of positive covariance of selection across time intervals); the preponderance of weak positive selection operating on minor alleles; and a genome-wide distribution of numerous small linkage islands of observable selection influencing levels of nucleotide diversity. These results suggest that interannual fluctuating selection is a major determinant of standing levels of variation in natural populations, challenge the conventional paradigm for interpreting patterns of nucleotide diversity and divergence, and motivate the need for the further development of theoretical expressions for the interpretation of population-genomic data.

The Genome-wide Signature of Short-term Temporal Selection

Despite evolutionary biology's obsession with natural selection, few studies have evaluated multi-generational series of patterns of selection on a genome-wide scale in natural populations. Here, we report on a nine-year population-genomic survey of the microcrustacean Daphnia pulex. The genome-sequences of > 800 isolates provide insights into patterns of selection that cannot be obtained from long-term molecular-evolution studies, including the pervasiveness of near quasi-neutrality across the genome (mean net selection coefficients near zero, but with significant temporal variance about the mean, and little evidence of positive covariance of selection across time intervals), the preponderance of weak negative selection operating on minor alleles, and a genome-wide distribution of numerous small linkage islands of observable selection influencing levels of nucleotide diversity. These results suggest that fluctuating selection is a major determinant of standing levels of variation in natural populations, challenge the conventional paradigm for interpreting patterns of nucleotide diversity and divergence, and motivate the need for the development of new theoretical expressions for the interpretation of population-genomic data.

Interpreting the pervasive observation of U-shaped Site Frequency Spectra

The standard neutral model of molecular evolution has traditionally been used as the null model for population genomics. We gathered a collection of 45 genome-wide site frequency spectra from a diverse set of species, most of which display an excess of low and high frequency variants compared to the expectation of the standard neutral model, resulting in U-shaped spectra. We show that multiple merger coalescent models often provide a better fit to these observations than the standard Kingman coalescent. Hence, in many circumstances these under-utilized models may serve as the more appropriate reference for genomic analyses. We further discuss the underlying evolutionary processes that may result in the widespread U-shape of frequency spectra.

Fluctuating selection and the determinants of genetic variation

Recent studies of cosmopolitan Drosophila populations have found hundreds to thousands of genetic loci with seasonally fluctuating allele frequencies, bringing temporally fluctuating selection to the forefront of the historical debate surrounding the maintenance of genetic variation in natural populations. Numerous mechanisms have been explored in this longstanding area of research, but these exciting empirical findings have prompted several recent theoretical and experimental studies that seek to better understand the drivers, dynamics, and genome-wide influence of fluctuating selection. In this review, we evaluate the latest evidence for multilocus fluctuating selection in Drosophila and other taxa, highlighting the role of potential genetic and ecological mechanisms in maintaining these loci and their impacts on neutral genetic variation.

Evolution in fluctuating environments: A generic modular approach

Evolutionary processes take place in fluctuating environments, where carrying capacities and selective forces vary over time. The fate of a mutant type and the persistence time of polymorphic states were studied in some specific cases of varying environments, but a generic methodology is still lacking. Here, we present such a general analytic framework. We first identify a set of elementary building blocks, a few basic demographic processes like logistic or exponential growth, competition at equilibrium, sudden decline, and so on. For each of these elementary blocks, we evaluate the mean and the variance of the changes in the frequency of the mutant population. Finally, we show how to find the relevant terms of the diffusion equation for each arbitrary combination of these blocks. Armed with this technique one may calculate easily the quantities that govern the evolutionary dynamics, like the chance of ultimate fixation, the time to absorption, and the time to fixation.

Joint effect of changing selection and demography on the site frequency spectrum

The site frequency spectrum (SFS) is an important statistic that summarizes the molecular variation in a population, and is used to estimate population-genetic parameters and detect natural selection. Here, we study the SFS in a randomly mating, diploid population in which both the population size and selection coefficient vary periodically with time using a diffusion theory approach, and derive simple analytical expressions for the time-averaged SFS in slowly and rapidly changing environments. We show that for strong selection and in slowly changing environments where the population experiences both positive and negative cycles of the selection coefficient, the time-averaged SFS differs significantly from the equilibrium SFS in a constant environment. The deviation is found to depend on the time spent by the population in the deleterious part of the selection cycle and the phase difference between the selection coefficient and population size, and can be captured by an effective population size.

How the storage effect and the number of temporal niches affect biodiversity in stochastic and seasonal environments

Temporal environmental variations affect diversity in communities of competing populations. In particular, the covariance between competition and environment is known to facilitate invasions of rare species via the storage effect. Here we present a quantitative study of the effects of temporal variations in two-species and in diverse communities. Four scenarios are compared: environmental variations may be either periodic (seasonal) or stochastic, and the dynamics may support the storage effect (global competition) or not (local competition). In two-species communities, coexistence is quantified via the mean time to absorption, and we show that stochastic variations yield shorter persistence time because they allow for rare sequences of bad years. In diverse communities, where the steady-state reflects a colonization-extinction equilibrium, the actual number of temporal niches is shown to play a crucial role. When this number is large, the same trends hold: storage effect and periodic variations increase both species richness and the evenness of the community. Surprisingly, when the number of temporal niches is small global competition acts to decrease species richness and evenness, as it focuses the competition to specific periods, thus increasing the effective fitness differences.

One of the major challenges of community ecology and population genetics is the understanding of the factors that protect biodiversity. Surprisingly, in many generic cases temporal environmental variations (and the abundance fluctuations associated with it) promote the coexistence of competing species and facilitate genetic polymorphism. Here we present a detailed and quantitative comparison between the stabilizing (and the destabilizing) effects of periodic (seasonal) and stochastic temporal variations. When the number of species is small, we show that persistence times under periodic variations are much longer than the persistence times in a stochastic environment. However, environmental variations facilitate coexistence only when the number of temporal niches is larger than the number of species, whereas in the opposite case the same mechanism acts to increase competition and to decrease species richness. Since it is reasonable to expect the number of temporal niches under seasonal variations to be typically smaller than the corresponding number in stochastic environments, stochastic variations provide a more plausible explanation for the apparent stability of high-diversity assemblages.

Taming the diffusion approximation through a controlling-factor WKB method

The diffusion approximation (DA) is widely used in the analysis of stochastic population dynamics, from population genetics to ecology and evolution. The DA is an uncontrolled approximation that assumes the smoothness of the calculated quantity over the relevant state space and fails when this property is not satisfied. This failure becomes severe in situations where the direction of selection switches sign. Here we employ the WKB (Wentzel-Kramers-Brillouin) large-deviations method, which requires only the logarithm of a given quantity to be smooth over its state space. Combining the WKB scheme with asymptotic matching techniques, we show how to derive the diffusion approximation in a controlled manner and how to produce better approximations, applicable for much wider regimes of parameters. We also introduce a scalable (independent of population size) WKB-based numerical technique. The method is applied to a central problem in population genetics and evolution, finding the chance of ultimate fixation in a zero-sum, two-types competition.

Gene flow as a simple cause for an excess of high-frequency-derived alleles

Most human populations exhibit an excess of high-frequency variants, leading to a U-shaped site-frequency spectrum (uSFS). This pattern has been generally interpreted as a signature of ongoing episodes of positive selection, or as evidence for a mis-assignment of ancestral/derived allelic states, but uSFS has also been observed in populations receiving gene flow from a ghost population, in structured populations, or after range expansions. In order to better explain the prevalence of high-frequency variants in humans and other populations, we describe here which patterns of gene flow and population demography can lead to uSFS by using extensive coalescent simulations. We find that uSFS can often be observed in a population if gene flow brings a few ancestral alleles from a well-differentiated population. Gene flow can either consist in single pulses of admixture or continuous immigration, but different demographic conditions are necessary to observe uSFS in these two scenarios. Indeed, an extremely low and recent gene flow is required in the case of single admixture events, while with continuous immigration, uSFS occurs only if gene flow started recently at a high rate or if it lasted for a long time at a low rate. Overall, we find that a neutral uSFS occurs under more restrictive conditions in populations having received single pulses of gene flow than in populations exposed to continuous gene flow. We also show that the uSFS observed in human populations from the 1000 Genomes Project can easily be explained by gene flow from surrounding populations without requiring past episodes of positive selection. These results imply that uSFS should be common in non-isolated populations, such as most wild or domesticated plants and animals.

Senescence and entrenchment in evolution of amino acid sites

Amino acid propensities at a site change in the course of protein evolution. This may happen for two reasons. Changes may be triggered by substitutions at epistatically interacting sites elsewhere in the genome. Alternatively, they may arise due to environmental changes that are external to the genome. Here, we design a framework for distinguishing between these alternatives. Using analytical modelling and simulations, we show that they cause opposite dynamics of the fitness of the allele currently occupying the site: it tends to increase with the time since its origin due to epistasis ("entrenchment"), but to decrease due to random environmental fluctuations ("senescence"). By analysing the genomes of vertebrates and insects, we show that the amino acids originating at negatively selected sites experience strong entrenchment. By contrast, the amino acids originating at positively selected sites experience senescence. We propose that senescence of the current allele is a cause of adaptive evolution.

Noncoding regions underpin avian bill shape diversification at macroevolutionary scales

Recent progress has been made in identifying genomic regions implicated in trait evolution on a microevolutionary scale in many species, but whether these are relevant over macroevolutionary time remains unclear. Here, we directly address this fundamental question using bird beak shape, a key evolutionary innovation linked to patterns of resource use, divergence, and speciation, as a model trait. We integrate class-wide geometric-morphometric analyses with evolutionary sequence analyses of 10,322 protein-coding genes as well as 229,001 genomic regions spanning 72 species. We identify 1434 protein-coding genes and 39,806 noncoding regions for which molecular rates were significantly related to rates of bill shape evolution. We show that homologs of the identified protein-coding genes as well as genes in close proximity to the identified noncoding regions are involved in craniofacial embryo development in mammals. They are associated with embryonic stem cell pathways, including BMP and Wnt signaling, both of which have repeatedly been implicated in the morphological development of avian beaks. This suggests that identifying genotype-phenotype association on a genome-wide scale over macroevolutionary time is feasible. Although the coding and noncoding gene sets are associated with similar pathways, the actual genes are highly distinct, with significantly reduced overlap between them and bill-related phenotype associations specific to noncoding loci. Evidence for signatures of recent diversifying selection on our identified noncoding loci in Darwin finch populations further suggests that regulatory rather than coding changes are major drivers of morphological diversification over macroevolutionary times.

Balancing Selection Drives the Maintenance of Genetic Variation in Drosophila Antimicrobial Peptides

Genes involved in immune defense against pathogens provide some of the most well-known examples of both directional and balancing selection. Antimicrobial peptides (AMPs) are innate immune effector genes, playing a key role in pathogen clearance in many species, including Drosophila. Conflicting lines of evidence have suggested that AMPs may be under directional, balancing, or purifying selection. Here, we use both a linear model and control-gene-based approach to show that balancing selection is an important force shaping AMP diversity in Drosophila. In Drosophila melanogaster, this is most clearly observed in ancestral African populations. Furthermore, the signature of balancing selection is even more striking once background selection has been accounted for. Balancing selection also acts on AMPs in Drosophila mauritiana, an isolated island endemic separated from D. melanogaster by about 4 Myr of evolution. This suggests that balancing selection may be broadly acting to maintain adaptive diversity in Drosophila AMPs, as has been found in other taxa.

Partial protection from cyclical selection generates a high level of polymorphism at multiple non-neutral sites

Temporally varying selection is known to maintain genetic polymorphism under certain restricted conditions. However, if part of a population can escape from selective pressure, a condition called the "storage effect" is produced, which greatly promotes balanced polymorphism. We investigate whether seasonally fluctuating selection can maintain polymorphism at multiple loci, if cyclically fluctuating selection is not acting on a subpopulation called a "refuge." A phenotype with a seasonally oscillating optimum is determined by alleles at multiple sites, across which the effects of mutations on phenotype are distributed randomly. This model resulted in long-term polymorphism at multiple sites, during which allele frequencies oscillate heavily, greatly increasing the level of nonneutral polymorphism. The level of polymorphism at linked neutral sites was either higher or lower than expected for unlinked neutral loci. Overall, these results suggest that for a protein-coding sequence, the nonsynonymous-to-synonymous ratio of polymorphism may exceed one. In addition, under randomly perturbed environmental oscillation, different sets of sites may take turns harboring long-term polymorphism, thus making trans-species polymorphism (which has been predicted as a classical signature of balancing selection) less likely.

Haploids, polymorphisms and fluctuating selection

I analyze the joint impact of directional and fluctuating selection with reversible mutation in finite bi-allelic haploid populations using diffusion approximations of the Moran and chemostat models. Results differ dramatically from those of the classic Wright-Fisher diffusion. There, a strong dispersive effect attributable to fluctuating selection dissipates nascent polymorphisms promoted by a relatively weak emergent frequency dependent selective effect. The dispersive effect in the Moran diffusion with fluctuations every birth-death event is trivial. The same frequency dependent selective effect now dominates and polymorphism is promoted. The dispersive effect in the chemostat diffusion with fluctuations every generation is identical to that in the Wright-Fisher diffusion. Nevertheless, polymorphism is again promoted because the emergent frequency dependent effect is doubled, an effect attributable to geometric reproduction within generations. Fluctuating selection in the Moran and chemostat diffusions can also promote bi-allelic polymorphisms when one allele confers a net benefit. Rapid fluctuations within generations are highly effective at promoting polymorphism in large populations. The bi-allelic distribution is approximately Gaussian but becomes uniform and then U-shaped as the frequency of environmental fluctuations decreases to once a generation and then once every multiple generations. Trade-offs (negative correlations in fitness) help promote polymorphisms but are not essential. In all three models the frequency dependent effect raises the probability of ultimate fixation of new alleles, but less effectively in the Wright-Fisher diffusion. Individual-based forward simulations confirm the calculations.

Theory of time-averaged neutral dynamics with environmental stochasticity

Competition is the main driver of population dynamics, which shapes the genetic composition of populations and the assembly of ecological communities. Neutral models assume that all the individuals are equivalent and that the dynamics is governed by demographic (shot) noise, with a steady state species abundance distribution (SAD) that reflects a mutation-extinction equilibrium. Recently, many empirical and theoretical studies emphasized the importance of environmental variations that affect coherently the relative fitness of entire populations. Here we consider two generic time-averaged neutral models; in both the relative fitness of each species fluctuates independently in time but its mean is zero. The first (model A) describes a system with local competition and linear fitness dependence of the birth-death rates, while in the second (model B) the competition is global and the fitness dependence is nonlinear. Due to this nonlinearity, model B admits a noise-induced stabilization mechanism that facilitates the invasion of new mutants. A self-consistent mean-field approach is used to reduce the multispecies problem to two-species dynamics, and the large-N asymptotics of the emerging set of Fokker-Planck equations is presented and solved. Our analytic expressions are shown to fit the SADs obtained from extensive Monte Carlo simulations and from numerical solutions of the corresponding master equations.

Genomic Signatures of Sexual Conflict

Sexual conflict is a specific class of intergenomic conflict that describes the reciprocal sex-specific fitness costs generated by antagonistic reproductive interactions. The potential for sexual conflict is an inherent property of having a shared genome between the sexes and, therefore, is an extreme form of an environment-dependent fitness effect. In this way, many of the predictions from environment-dependent selection can be used to formulate expected patterns of genome evolution under sexual conflict. However, the pleiotropic and transmission constraints inherent to having alleles move across sex-specific backgrounds from generation to generation further modulate the anticipated signatures of selection. We outline methods for detecting candidate sexual conflict loci both across and within populations. Additionally, we consider the ability of genome scans to identify sexually antagonistic loci by modeling allele frequency changes within males and females due to a single generation of selection. In particular, we highlight the need to integrate genotype, phenotype, and functional information to truly distinguish sexual conflict from other forms of sexual differentiation.

Fluctuating Selection in the Moran

Contrary to classical population genetics theory, experiments demonstrate that fluctuating selection can protect a haploid polymorphism in the absence of frequency dependent effects on fitness. Using forward simulations with the Moran model, we confirm our analytical results showing that a fluctuating selection regime, with a mean selection coefficient of zero, promotes polymorphism. We find that increases in heterozygosity over neutral expectations are especially pronounced when fluctuations are rapid, mutation is weak, the population size is large, and the variance in selection is big. Lowering the frequency of fluctuations makes selection more directional, and so heterozygosity declines. We also show that fluctuating selection raises dn /ds ratios for polymorphism, not only by sweeping selected alleles into the population, but also by purging the neutral variants of selected alleles as they undergo repeated bottlenecks. Our analysis shows that randomly fluctuating selection increases the rate of evolution by increasing the probability of fixation. The impact is especially noticeable when the selection is strong and mutation is weak. Simulations show the increase in the rate of evolution declines as the rate of new mutations entering the population increases, an effect attributable to clonal interference. Intriguingly, fluctuating selection increases the dn /ds ratios for divergence more than for polymorphism, a pattern commonly seen in comparative genomics. Our model, which extends the classical neutral model of molecular evolution by incorporating random fluctuations in selection, accommodates a wide variety of observations, both neutral and selected, with economy.

A time transect of exomes from a Native American population before and after European contact

A major factor for the population decline of Native Americans after European contact has been attributed to infectious disease susceptibility. To investigate whether a pre-existing genetic component contributed to this phenomenon, here we analyse 50 exomes of a continuous population from the Northwest Coast of North America, dating from before and after European contact. We model the population collapse after European contact, inferring a 57% reduction in effective population size. We also identify signatures of positive selection on immune-related genes in the ancient but not the modern group, with the strongest signal deriving from the human leucocyte antigen (HLA) gene HLA-DQA1. The modern individuals show a marked frequency decrease in the same alleles, likely due to the environmental change associated with European colonization, whereby negative selection may have acted on the same gene after contact. The evident shift in selection pressures correlates to the regional European-borne epidemics of the 1800s.

A First Nation population declined after European contact, likely as a result of infectious disease. Here, researchers partner with indigenous communities to analyse ancient and modern Native American exomes, and find a shift in selection pressure on immune genes, correlated to European-borne epidemics.

Changing preferences: deformation of single position amino acid fitness landscapes and evolution of proteins

The fitness landscape-the function that relates genotypes to fitness-and its role in directing evolution are a central object of evolutionary biology. However, its huge dimensionality precludes understanding of even the basic aspects of its shape. One way to approach it is to ask a simpler question: what are the properties of a function that assigns fitness to each possible variant at just one particular site-a single position fitness landscape-and how does it change in the course of evolution? Analyses of genomic data from multiple species and multiple individuals within a species have proved beyond reasonable doubt that fitness functions of positions throughout the genome do themselves change with time, thus shaping protein evolution. Here, I will briefly review the literature that addresses these dynamics, focusing on recent genome-scale analyses of fitness functions of amino acid sites, i.e. vectors of fitnesses of 20 individual amino acid variants at a given position of a protein. The set of amino acids that confer high fitness at a particular position changes with time, and the rate of this change is comparable with the rate at which a position evolves, implying that this process plays a major role in evolutionary dynamics. However, the causes of these changes remain largely unclear.

PReFerSim: fast simulation of demography and selection under the Poisson Random Field model

The Poisson Random Field (PRF) model has become an important tool in population genetics to study weakly deleterious genetic variation under complicated demographic scenarios. Currently, there are no freely available software applications that allow simulation of genetic variation data under this model. Here we present PReFerSim, an ANSI C program that performs forward simulations under the PRF model. PReFerSim models changes in population size, arbitrary amounts of inbreeding, dominance and distributions of selective effects. Users can track summaries of genetic variation over time and output trajectories of selected alleles.

AVAILABILITY AND IMPLEMENTATION

PReFerSim is freely available at: https://github.com/LohmuellerLab/PReFerSim CONTACT: klohmueller@ucla.eduSupplementary information: Supplementary data are available at Bioinformatics online.

The landscape of somatic mutations in protein coding genes in apparently benign human tissues carries signatures of relaxed purifying selection

Mutations acquired during development and aging lead to inter- and intra-tissue genetic variations. Evidence linking such mutations to complex traits and diseases is rising. We detected somatic mutations in protein-coding regions in 140 benign tissue samples representing nine tissue-types (bladder, breast, liver, lung, prostate, stomach, thyroid, head and neck) and paired blood from 70 donors. A total of 80% of the samples had 2–39 mutations detectable at tissue-level resolution. Factors such as age and smoking were associated with increased burden of detectable mutations, and tissues carried signatures of distinct mutagenic processes such as oxidative DNA damage and transcription-coupled repair. Using mutational signatures, we predicted that majority of the mutations in blood originated in hematopoietic stem and early progenitor cells. Missense to silent mutations ratio and the persistence of potentially damaging mutations in expressed genes carried signatures of relaxed purifying selection. Our findings have relevance for etiology, diagnosis and treatment of diseases including cancer.

Bayesian inference of selection in a heterogeneous environment from genetic time-series data

Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research programme has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian nonhomogeneous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was nonlinear. Past studies of temporal evolutionary dynamics in laboratory populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible and thereby could help answer fundamental questions about the causes and consequences of evolution in the wild.

Carriers of Mitochondrial DNA Macrohaplogroup N Lineages Reached Australia around 50,000 Years Ago following a Northern Asian Route

Background

The modern human colonization of Eurasia and Australia is mostly explained by a single-out-of-Africa exit following a southern coastal route throughout Arabia and India. However, dispersal across the Levant would better explain the introgression with Neanderthals, and more than one exit would fit better with the different ancient genomic components discovered in indigenous Australians and in ancient Europeans. The existence of an additional Northern route used by modern humans to reach Australia was previously deduced from the phylogeography of mtDNA macrohaplogroup N. Here, we present new mtDNA data and new multidisciplinary information that add more support to this northern route.

Methods

MtDNA hypervariable segments and haplogroup diagnostic coding positions were analyzed in 2,278 Saudi Arabs, from which 1,725 are new samples. Besides, we used 623 published mtDNA genomes belonging to macrohaplogroup N, but not R, to build updated phylogenetic trees to calculate their coalescence ages, and more than 70,000 partial mtDNA sequences were screened to establish their respective geographic ranges.

Results

The Saudi mtDNA profile confirms the absence of autochthonous mtDNA lineages in Arabia with coalescence ages deep enough to support population continuity in the region since the out-of-Africa episode. In contrast to Australia, where N(xR) haplogroups are found in high frequency and with deep coalescence ages, there are not autochthonous N(xR) lineages in India nor N(xR) branches with coalescence ages as deep as those found in Australia. These patterns are at odds with the supposition that Australian colonizers harboring N(xR) lineages used a route involving India as a stage. The most ancient N(xR) lineages in Eurasia are found in China, and inconsistently with the coastal route, N(xR) haplogroups with the southernmost geographical range have all more recent radiations than the Australians.

Conclusions

Apart from a single migration event via a southern route, phylogeny and phylogeography of N(xR) lineages support that people carrying mtDNA N lineages could have reach Australia following a northern route through Asia. Data from other disciplines also support this scenario.

Evolutionary genetic bases of longevity and senescence

Senescence, as a time-dependent developmental process, affects all organisms at every stage in their development and growth. During this process, genetic, epigenetic and environmental factors are known to introduce a wide range of variation for longevity among individuals. As an important life-history trait, longevity shows ontogenetic relationships with other complex traits, and hence may be viewed as a composite trait. Factors that influence the origin and maintenance of diversity of life are ultimately governed by Darwinian processes. Here we review evolutionary genetic mechanisms underlying longevity and senescence in humans from a life-history and genotype-epigenetic-phenotype (G-E-P) map prospective. We suggest that synergistic and cascading effects of cis-ruptive mechanisms in the genome, and epigenetic disruptive processes in relation to environmental factors may lead to sequential slippage in the G-E-P space. These mechanisms accompany age, stage and individual specific senescent processes, influenced by positive pleiotropy of certain genes, superior genome integrity, negative-frequency dependent selection and other factors that universally regulate rarity in nature. Finally we interpret life span as an inherent property of self-organizing systems that, accordingly, maintain species-specific limits for the entire complex of fitness traits. We conclude that Darwinian approaches provide unique opportunities to discover the biological bases of longevity as well as devise individual specific medical or other interventions toward improving health span.

Effects of new mutations on fitness: insights from models and data

The rates and properties of new mutations affecting fitness have implications for a number of outstanding questions in evolutionary biology. Obtaining estimates of mutation rates and effects has historically been challenging, and little theory has been available for predicting the distribution of fitness effects (DFE); however, there have been recent advances on both fronts. Extreme-value theory predicts the DFE of beneficial mutations in well-adapted populations, while phenotypic fitness landscape models make predictions for the DFE of all mutations as a function of the initial level of adaptation and the strength of stabilizing selection on traits underlying fitness. Direct experimental evidence confirms predictions on the DFE of beneficial mutations and favors distributions that are roughly exponential but bounded on the right. A growing number of studies infer the DFE using genomic patterns of polymorphism and divergence, recovering a wide range of DFE. Future work should be aimed at identifying factors driving the observed variation in the DFE. We emphasize the need for further theory explicitly incorporating the effects of partial pleiotropy and heterogeneity in the environment on the expected DFE.

Fluctuating selection models and McDonald-Kreitman type analyses

It is likely that the strength of selection acting upon a mutation varies through time due to changes in the environment. However, most population genetic theory assumes that the strength of selection remains constant. Here we investigate the consequences of fluctuating selection pressures on the quantification of adaptive evolution using McDonald-Kreitman (MK) style approaches. In agreement with previous work, we show that fluctuating selection can generate evidence of adaptive evolution even when the expected strength of selection on a mutation is zero. However, we also find that the mutations, which contribute to both polymorphism and divergence tend, on average, to be positively selected during their lifetime, under fluctuating selection models. This is because mutations that fluctuate, by chance, to positive selected values, tend to reach higher frequencies in the population than those that fluctuate towards negative values. Hence the evidence of positive adaptive evolution detected under a fluctuating selection model by MK type approaches is genuine since fixed mutations tend to be advantageous on average during their lifetime. Never-the-less we show that methods tend to underestimate the rate of adaptive evolution when selection fluctuates.

The characteristic trajectory of a fixing allele: a consequence of fictitious selection that arises from conditioning

This work is concerned with the historical progression, to fixation, of an allele in a finite population. This progression is characterized by the average frequency trajectory of alleles that achieve fixation before a given time, T. Under a diffusion analysis, the average trajectory, conditional on fixation by time T, is shown to be equivalent to the average trajectory in an unconditioned problem involving additional selection. We call this additional selection "fictitious selection"; it plays the role of a selective force in the unconditioned problem but does not exist in reality. It is a consequence of conditioning on fixation. The fictitious selection is frequency dependent and can be very large compared with any real selection that is acting. We derive an approximation for the characteristic trajectory of a fixing allele, when subject to real additive selection, from an unconditioned problem, where the total selection is a combination of real and fictitious selection. Trying to reproduce the characteristic trajectory from the action of additive selection, in an infinite population, can lead to estimates of the strength of the selection that deviate from the real selection by >1000% or have the opposite sign. Strong evolutionary forces may be invoked in problems where conditioning has been carried out, but these forces may largely be an outcome of the conditioning and hence may not have a real existence. The work presented here clarifies these issues and provides two useful tools for future analyses: the characteristic trajectory of a fixing allele and the force that primarily drives this, namely fictitious selection. These should prove useful in a number of areas of interest including coalescence with selection, experimental evolution, time series analyses of ancient DNA, game theory in finite populations, and the historical dynamics of selected alleles in wild populations.

Random fluctuation of selection coefficients and the extent of nucleotide variation in human populations

It is well known that the selection coefficient of a mutant allele varies from generation to generation, and the effect of this factor on genetic variation has been studied by many theoreticians. However, no consensus has been reached. One group of investigators believes that fluctuating selection has an effect of enhancing genetic variation, whereas the other group contends that it has a diversity-reducing effect. In recent years, it has become possible to study this problem by using single nucleotide polymorphisms (SNPs) as well as exome sequence data. In this article we present the theoretical distributions of mutant nucleotide frequencies for the two models of fluctuating selection and then compare the distributions with the empirical distributions obtained from SNP and exome sequence data in human populations. Interestingly, both SNP and exome sequence data showed that the neutral mutation model fits the empirical distribution quite well. Furthermore, the mathematical models with diversity-enhancing and diversity-reducing effects also fit the empirical distribution reasonably well. This result implies that there is no need of distinguishing between the diversity-enhancing and diversity-reducing models of fluctuating selection and the nucleotide polymorphism in human populations can be explained largely by neutral mutations when long-term evolution is considered.

Modeling the effect of changing selective pressures on polymorphism and divergence

The most common models of sequence evolution used to make inferences about adaptation rely on the assumption that selective pressures at a site remain constant through time. Instead, one might plausibly imagine that a change in the environment renders an allele beneficial and that when it fixes, the site is now constrained-until another change in the environment occurs that affects the selective pressures at that site. With this view in mind, we introduce a simple dynamic model for the evolution of coding regions, in which non-synonymous sites alternate between being fixed for the favored allele and being neutral with respect to other alleles. We use the pruning algorithm to derive closed forms for observable patterns of polymorphism and divergence in terms of the model parameters. Using our model, estimates of the fraction of beneficial substitutions α would remain similar to those obtained from existing approaches. In this framework, however, it becomes natural to ask how often adaptive substitutions originate from previously constrained or previously neutral sites, i.e., about the source of adaptive substitutions. We show that counts of coding sites that are both polymorphic in a sample from one species and divergent between two others carry information about this parameter. We also extend the basic model to include the effects of weakly deleterious mutations and discuss the importance of assumptions about the distribution of deleterious mutations among constrained non-synonymous sites. Finally, we derive a likelihood function for the parameters and apply it to a toy example, variation data for coding regions from chromosome 2 of the Drosophila melanogaster subgroup. This modeling work underscores how restrictive assumptions about adaptation have been to date, and how further work in this area will help to reveal unexplored and yet basic characteristics of adaptation.

Recombination is associated with the evolution of genome structure and worker behavior in honey bees

The rise of insect societies, marked by the formation of reproductive and sterile castes, represents a major unsolved mystery in evolution. Across several independent origins of sociality, the genomes of social hymenopterans share two peculiar attributes: high recombination and low but heterogeneous GC content. For example, the genome of the honey bee, Apis mellifera, represents a mosaic of GC-poor and GC-rich regions with rates of recombination an order of magnitude higher than in humans. However, it is unclear how heterogeneity in GC content arises, and how it relates to the expression and evolution of worker traits. Using population genetic analyses, we demonstrate a bias in the allele frequency and fixation rate of derived C or G mutations in high-recombination regions, consistent with recombination's causal influence on GC-content evolution via biased gene conversion. We also show that recombination and biased gene conversion actively maintain the heterogeneous GC content of the honey bee genome despite an overall A/T mutation bias. Further, we found that GC-rich genes and intergenic regions have higher levels of genetic diversity and divergence relative to GC-poor regions, also consistent with recombination's causal influence on the rate of molecular evolution. Finally, we found that genes associated with behavior and those with worker-biased expression are found in GC-rich regions of the bee genome and also experience high rates of molecular evolution. Taken together, these findings suggest that recombination acts to maintain a genetically diverse and dynamic part of the genome where genes underlying worker behavior evolve more quickly.

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.

Weighing the evidence for adaptation at the molecular level

The abundance of genome polymorphism and divergence data has provided unprecedented insight into how mutation, drift and natural selection shape genome evolution. Application of the McDonald-Kreitman (MK) test to such data indicates a pervasive influence of positive selection, particularly in Drosophila species. However, evidence for positive selection in other species ranging from yeast to humans is often weak or absent. Although evidence for positive selection could be obscured in some species, there is also reason to believe that the frequency of adaptive substitutions could be overestimated as a result of epistatic fitness effects or hitchhiking of deleterious mutations. Based on these considerations it is argued that the common assumption of independence among sites must be relaxed before abandoning the neutral theory of molecular evolution.

A unified treatment of the probability of fixation when population size and the strength of selection change over time

The fixation probability is determined when population size and selection change over time and differs from Kimura's result, with long-term implications for a population. It is found that changes in population size are not equivalent to the corresponding changes in selection and can result in less drift than anticipated.

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.

Population genetic inference from genomic sequence variation

Population genetics has evolved from a theory-driven field with little empirical data into a data-driven discipline in which genome-scale data sets test the limits of available models and computational analysis methods. In humans and a few model organisms, analyses of whole-genome sequence polymorphism data are currently under way. And in light of the falling costs of next-generation sequencing technologies, such studies will soon become common in many other organisms as well. Here, we assess the challenges to analyzing whole-genome sequence polymorphism data, and we discuss the potential of these data to yield new insights concerning population history and the genomic prevalence of natural selection.

An adaptive walk by human immunodeficiency virus type 1 through a fluctuating fitness landscape

The mutational landscape model of adaptive sequence evolution has been used to explain an unexpected strong positive linear relationship between marginal fitness and mean site-specific amino acid frequency in the functionally important HIV-1 gp120 V3 protein region. The model predicts a positive linear relationship between the probability that a particular beneficial allele, among several, is the next to spread to fixation during an adaptive walk, its transition probability, and the allele's selection coefficient. Here, stochastic simulation is used to confirm the intuition that the linear relationship between transition probabilities and selection coefficients, predicted by the model, should, under fluctuating selection, produce a linear relationship between allele frequency, averaged across populations, and fitness. In addition, these relationships hold for the effective population size and mutation rate of HIV-1 and for the moderately strong selection observed for V3. A survey of the strength of mutation for diverse organisms suggests that these relationships may be widely applicable.

XML-based approaches for the integration of heterogeneous bio-molecular data

Background

The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing.

Results

In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML.

Conclusion

XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

Estimating the rate of adaptive molecular evolution in the presence of slightly deleterious mutations and population size change

The prevalence of adaptive evolution relative to genetic drift is a central problem in molecular evolution. Methods to estimate the fraction of adaptive nucleotide substitutions (alpha) have been developed, based on the McDonald-Kreitman test, that contrast polymorphism and divergence between selectively and neutrally evolving sites. However, these methods are expected to give downwardly biased estimates of alpha if there are slightly deleterious mutations, because these inflate polymorphism relative to divergence. Here, we estimate alpha by simultaneously estimating the distribution of fitness effects of new mutations at selected sites from the site frequency spectrum and the number of adaptive substitutions. We test the method using simulations. If data meet the assumptions of the analysis model, estimates of alpha show little bias, even when there is little or no recombination. However, population size differences between the divergence and polymorphism phases may cause alpha to be over or underestimated by a predictable factor that depends on the magnitude of the population size change and the shape of the distribution of effects of deleterious mutations. We analyze several data sets of protein-coding genes and noncoding regions from hominids and Drosophila. In Drosophila genes, we estimate that approximately 50% of amino acid substitutions and approximately 20% of substitutions in introns are adaptive. In protein-coding and noncoding data sets of humans, comparison to macaque sequences reveals little evidence for adaptive substitutions. However, the true frequency of adaptive substitutions in human-coding DNA could be as high as 40%, because estimates based on current polymorphism may be strongly downwardly biased by a decrease in the effective population size along the human lineage.

From fitness landscapes to seascapes: non-equilibrium dynamics of selection and adaptation

Evolution is a quest for innovation. Organisms adapt to changing natural selection by evolving new phenotypes. Can we read this dynamics in their genomes? Not every mutation under positive selection responds to a change in selection: beneficial changes also occur at evolutionary equilibrium, repairing previous deleterious changes and restoring existing functions. Adaptation, by contrast, is viewed here as a non-equilibrium phenomenon: the genomic response to time-dependent selection. Our approach extends the static concept of fitness landscapes to dynamic fitness seascapes. It shows that adaptation requires a surplus of beneficial substitutions over deleterious ones. Here, we focus on the evolution of yeast and Drosophila genomes, providing examples where adaptive evolution can and cannot be inferred, despite the presence of positive selection.

A stochastic version of the Price equation reveals the interplay of deterministic and stochastic processes in evolution

Background

Evolution involves both deterministic and random processes, both of which are known to contribute to directional evolutionary change. A number of studies have shown that when fitness is treated as a random variable, meaning that each individual has a distribution of possible fitness values, then both the mean and variance of individual fitness distributions contribute to directional evolution. Unfortunately the most general mathematical description of evolution that we have, the Price equation, is derived under the assumption that both fitness and offspring phenotype are fixed values that are known exactly. The Price equation is thus poorly equipped to study an important class of evolutionary processes.

Results

I present a general equation for directional evolutionary change that incorporates both deterministic and stochastic processes and applies to any evolving system. This is essentially a stochastic version of the Price equation, but it is derived independently and contains terms with no analog in Price's formulation. This equation shows that the effects of selection are actually amplified by random variation in fitness. It also generalizes the known tendency of populations to be pulled towards phenotypes with minimum variance in fitness, and shows that this is matched by a tendency to be pulled towards phenotypes with maximum positive asymmetry in fitness. This equation also contains a term, having no analog in the Price equation, that captures cases in which the fitness of parents has a direct effect on the phenotype of their offspring.

Conclusion

Directional evolution is influenced by the entire distribution of individual fitness, not just the mean and variance. Though all moments of individuals' fitness distributions contribute to evolutionary change, the ways that they do so follow some general rules. These rules are invisible to the Price equation because it describes evolution retrospectively. An equally general prospective evolution equation compliments the Price equation and shows that the influence of stochastic processes on directional evolution is more diverse than has generally been recognized.