Fluctuations In Allele Frequencies Research Articles

Range expansions across landscapes with quenched noise

When biological populations expand into new territory, the evolutionary outcomes can be strongly influenced by genetic drift, the random fluctuations in allele frequencies. Meanwhile, spatial variability in the environment can also significantly influence the competition between subpopulations vying for space. Little is known about the interplay of these intrinsic and extrinsic sources of noise in population dynamics: When does environmental heterogeneity dominate over genetic drift or vice versa, and what distinguishes their population genetics signatures? Here, in the context of neutral evolution, we examine the interplay between a population's intrinsic, demographic noise and an extrinsic, quenched random noise provided by a heterogeneous environment. Using a multispecies Eden model, we simulate a population expanding over a landscape with random variations in local growth rates and measure how this variability affects genealogical tree structure, and thus genetic diversity. We find that, for strong heterogeneity, the genetic makeup of the expansion front is to a great extent predetermined by the set of fastest paths through the environment. The landscape-dependent statistics of these optimal paths then supersede those of the population's intrinsic noise as the main determinant of evolutionary dynamics. Remarkably, the statistics for coalescence of genealogical lineages, derived from those deterministic paths, strongly resemble the statistics emerging from demographic noise alone in uniform landscapes. This cautions interpretations of coalescence statistics and raises new challenges for inferring past population dynamics.

Genetic Diversity and Reproduction Trends of Phytophthora infestans in Estonia: EU_41_A2 Detected without an Indication of Clonal Reproduction.

This study explores the population dynamics of Phytophthora infestans in Estonia from 2005 to 2022, focusing on genetic diversity and potential shifts in reproductive strategies. In total, 153 P. infestans isolates were collected throughout Estonia over ten growing seasons. Genotyping revealed considerable genetic diversity, with most isolates not corresponding to known multilocus genotypes (MLGs). Still, instances of invasive clonal lineages were observed, notably EU_41_A2. The data indicate the likelihood of random mating rather than clonal reproduction in all the analyzed years. The principal coordinate analysis (PCoA) results revealed no distinct clustering among the sampling years. Statistical analysis and the minimum spanning network (MSN) indicated low genetic differentiation between years with minimal fluctuations in allele frequencies. The continuous monitoring of P. infestans populations is essential for detecting any changes from the current evolutionary trajectory and implement effective disease management strategies, especially considering the recent emergence of EU_41_A2 in the Nordics and the potential impacts of climate change.

Modeling the genetic footprint of fluctuating balancing selection: from the local to the genomic scale.

Natural selection not only affects the actual loci under selection but also leaves "footprints" in patterns of genetic variation in linked genetic regions. This offers exciting opportunities for inferring selection and for understanding the processes shaping levels of genetic variation in natural populations. Here, we develop analytical approximations based on coalescent theory to characterize the genetic footprint of a complex, but potentially common type of natural selection: balancing selection with seasonally fluctuating allele frequencies. As we show analytically and confirm with stochastic simulations, seasonal allele frequency fluctuations can have important (and partly unexpected) consequences for the genetic footprint of balancing selection. Fluctuating balancing selection generally leads to an increase in genetic diversity close to the selected site, the effect of balancing selection, but reduces diversity further away from the selected site, which is a consequence of the allele-frequency fluctuations effectively producing recurrent bottlenecks of allelic backgrounds. This medium- and long-range reduction usually outweighs the short-range increase when averaging diversity levels across the entire chromosome. Strong fluctuating balancing selection even induces a loss of genetic variation in unlinked regions, e.g. on different chromosomes. If many loci in the genome are simultaneously under fluctuating balancing selection this can lead to substantial genome-wide reductions in genetic diversity, even when allele-frequency fluctuations are small and local footprints are difficult to detect. Thus, together with genetic drift, selective sweeps and background selection, fluctuating selection could be a major force shaping levels of genetic diversity in natural populations.

Clinal and seasonal changes are correlated in Drosophila melanogaster natural populations.

Spatial and seasonal variations in the environment are ubiquitous. Environmental heterogeneity can affect natural populations and lead to covariation between environment and allele frequencies. Drosophila melanogaster is known to harbor polymorphisms that change both with latitude and seasons. Identifying the role of selection in driving these changes is not trivial, because nonadaptive processes can cause similar patterns. Given the environment changes in similar ways across seasons and along the latitudinal gradient, one promising approach may be to look for parallelism between clinal and seasonal changes. Here, we test whether there is a genome-wide correlation between clinal and seasonal changes, and whether the pattern is consistent with selection. Allele frequency estimates were obtained from pooled samples from seven different locations along the east coast of the United States, and across seasons within Pennsylvania. We show that there is a genome-wide correlation between clinal and seasonal variations, which cannot be explained by linked selection alone. This pattern is stronger in genomic regions with higher functional content, consistent with natural selection. We derive a way to biologically interpret these correlations and show that around 3.7% of the common, autosomal variants could be under parallel seasonal and spatial selection. Our results highlight the contribution of natural selection in driving fluctuations in allele frequencies in natural fly populations and point to a shared genomic basis to climate adaptation that happens over space and time in D. melanogaster.

The Limits to Estimating Population-Genetic Parameters with Temporal Data.

The ability to obtain genome-wide sequences of very large numbers of individuals from natural populations raises questions about optimal sampling designs and the limits to extracting information on key population-genetic parameters from temporal-survey data. Methods are introduced for evaluating whether observed temporal fluctuations in allele frequencies are consistent with the hypothesis of random genetic drift, and expressions for the expected sampling variances for the relevant statistics are given in terms of sample sizes and numbers. Estimation methods and aspects of statistical reliability are also presented for the mean and temporal variance of selection coefficients. For nucleotide sites that pass the test of neutrality, the current effective population size can be estimated by a method of moments, and expressions for its sampling variance provide insight into the degree to which such methodology can yield meaningful results under alternative sampling schemes. Finally, some caveats are raised regarding the use of the temporal covariance of allele-frequency change to infer selection. Taken together, these results provide a statistical view of the limits to population-genetic inference in even the simplest case of a closed population.

Evolution in range expansions with competition at rough boundaries

When a biological population expands into new territory, genetic drift develops an enormous influence on evolution at the propagating front. In such range expansion processes, fluctuations in allele frequencies occur through stochastic spatial wandering of both genetic lineages and the boundaries between genetically segregated sectors. Laboratory experiments on microbial range expansions have shown that this stochastic wandering, transverse to the front, is superdiffusive due to the front’s growing roughness, implying much faster loss of genetic diversity than predicted by simple flat front diffusive models. We study the evolutionary consequences of this superdiffusive wandering using two complementary numerical models of range expansions: the stepping stone model, and a new interpretation of the model of directed paths in random media, in the context of a roughening population front. Through these approaches we compute statistics for the times since common ancestry for pairs of individuals with a given spatial separation at the front, and we explore how environmental heterogeneities can locally suppress these superdiffusive fluctuations.

Searching for signals of recent natural selection in genes of the innate immune response - ancient DNA study

The last decade has seen sharp progress in the field of human evolutionary genetics and a great amount of genetic evidence of natural selection has been provided so far. Since host-pathogen co-evolution is difficult to trace due to the polygenic nature of human susceptibility to microbial diseases, of particular interest is any signal of natural selection in response to the strong selective pressure exerted by pathogens. Analysis of ancient DNA allows for the direct insight into changes of a gene pool content over time and enables monitoring allele frequency fluctuations. Among pathogenic agents, mycobacteria are proved to have remained in an intimate, long-lasting relation with humans, reflected by the current high level of host resistance. Therefore, we aimed to investigate the prevalence of several polymorphisms within innate immune response genes related to susceptibility to mycobacterial diseases (in SLC11A1, MBL2, TLR2, P2RX7, IL10, TNFA) in time series data from North and East Poland (1st–18th century AD, n = 207). The comparison of allele frequencies over time revealed a predominant role of genetic drift in shaping past gene pool of small, probably isolated groups, which was explained by the high level of population differentiation and limited gene flow. However, the trajectory of frequency fluctuations of two SNPs suggested the possibility of their non-neutral evolution and the results of applied forward simulations further strengthened the hypothesis of natural selection acting on those loci. However, we observed an unusual excess of homozygosity in the profile of several SNPs, which pinpoints to the necessity of further research on temporally and spatially diverse samples to support our inference on non-stochastic evolution, ideally employing pathway-based approaches. Nevertheless, our study confirms that time series data could help to decipher very recent human adaptation to life-threatening pathogens and assisting demographic events.

Signatures of co-evolutionary host-pathogen interactions in the genome of the entomopathogenic nematode Steinernema carpocapsae

BackgroundThe entomopathogenic nematode Steinernema carpocapsae has been used worldwide as a biocontrol agent for insect pests, making it an interesting model for understanding parasite-host interactions. Two models propose that these interactions are co-evolutionary processes in such a way that equilibrium is never reached. In one model, known as “arms race”, new alleles in relevant genes are fixed in both host and pathogens by directional positive selection, producing recurrent and alternating selective sweeps. In the other model, known as“trench warfare”, persistent dynamic fluctuations in allele frequencies are sustained by balancing selection. There are some examples of genes evolving according to both models, however, it is not clear to what extent these interactions might alter genome-level evolutionary patterns and intraspecific diversity. Here we investigate some of these aspects by studying genomic variation in S. carpocapsae and other pathogenic and free-living nematodes from phylogenetic clades IV and V.ResultsTo look for signatures of an arms-race dynamic, we conducted massive scans to detect directional positive selection in interspecific data. In free-living nematodes, we detected a significantly higher proportion of genes with sites under positive selection than in parasitic nematodes. However, in these genes, we found more enriched Gene Ontology terms in parasites. To detect possible effects of dynamic polymorphisms interactions we looked for signatures of balancing selection in intraspecific genomic data. The observed distribution of Tajima’s D values in S. carpocapsae was more skewed to positive values and significantly different from the observed distribution in the free-living Caenorhabditis briggsae. Also, the proportion of significant positive values of Tajima’s D was elevated in genes that were differentially expressed after induction with insect tissues as compared to both non-differentially expressed genes and the global scan.ConclusionsOur study provides a first portrait of the effects that lifestyle might have in shaping the patterns of selection at the genomic level. An arms-race between hosts and pathogens seems to be affecting specific genetic functions but not necessarily increasing the number of positively selected genes. Trench warfare dynamics seem to be acting more generally in the genome, likely focusing on genes responding to the interaction, rather than targeting specific genetic functions.

Rapid Genetic Adaptation during the First Four Months of Survival under Resource Exhaustion.

Many bacteria, including the model bacterium Escherichia coli can survive for years within spent media, following resource exhaustion. We carried out evolutionary experiments, followed by whole genome sequencing of hundreds of evolved clones to study the dynamics by which E. coli adapts during the first 4 months of survival under resource exhaustion. Our results reveal that bacteria evolving under resource exhaustion are subject to intense selection, manifesting in rapid mutation accumulation, enrichment in functional mutation categories and extremely convergent adaptation. In the most striking example of convergent adaptation, we found that across five independent populations adaptation to conditions of resource exhaustion occurs through mutations to the three same specific positions of the RNA polymerase core enzyme. Mutations to these three sites are strongly antagonistically pleiotropic, in that they sharply reduce exponential growth rates in fresh media. Such antagonistically pleiotropic mutations, combined with the accumulation of additional mutations, severely reduce the ability of bacteria surviving under resource exhaustion to grow exponentially in fresh media. We further demonstrate that the three positions at which these resource exhaustion mutations occur are conserved for the ancestral E. coli allele, across bacterial phyla, with the exception of nonculturable bacteria that carry the resource exhaustion allele at one of these positions, at very high frequencies. Finally, our results demonstrate that adaptation to resource exhaustion is not limited by mutational input and that bacteria are able to rapidly adapt under resource exhaustion in a temporally precise manner through allele frequency fluctuations.

A possible genetic basis for vulnerability in Euphydryas maturna (Lepidoptera: Nymphalidae)

Nearly all of the known populations of Scarce Fritillary, Euphydryas maturna (Linnaeus, 1758), are declining in Western and Central Europe. In order to identify the possible reasons for its vulnerability we surveyed the population genetics of this butterfly species using multi-locus genotype data. Females of our target species lay lots of eggs in one or two batches only and pre-hibernation caterpillars live and feed gregariously in a nest. As a consequence, a random unfavourable event can eliminate most offspring of a particular female resulting in a strong genetic drift effect combined with inbreeding. Thus, our hypothesis regarding the genetic composition of Scarce Fritillary populations suggests that: (1) there will be random fluctuations in allele frequencies from generation to generation; (2) populations should exhibit small effective sizes and a relatively high level of heterozygote deficiency, and; (3) the majority of the individuals in a population will be composed of the offspring of just a few females. In order to test these hypotheses, fine-scale genetic structure was studied in two subpopulations of a Hungarian Scarce Fritillary population for 4consecutive years (generations) using enzyme polymorphism data. The results supported all of our assumptions. We detected random fluctuation in the frequency of several alleles, small effective population size and the index of heterozygote deficiency (F IS) indicated a considerable level of inbreeding in most samples. Furthermore, average values of relatedness were also fairly high, and we were able to identify 17 putative sib families in total with the two subpopulations based on estimation of individual gametic phases. Thus, the present study suggests that intrinsic factors (e.g. specific life history) might increase the sensitivity of a species to various threatening factors (e.g. habitat loss or fragmentation) and result in the vulnerability of the given species.

When Is Selection Effective?

Deleterious alleles can reach high frequency in small populations because of random fluctuations in allele frequency. This may lead, over time, to reduced average fitness. In this sense, selection is more "effective" in larger populations. Recent studies have considered whether the different demographic histories across human populations have resulted in differences in the number, distribution, and severity of deleterious variants, leading to an animated debate. This article first seeks to clarify some terms of the debate by identifying differences in definitions and assumptions used in recent studies. We argue that variants of Morton, Crow, and Muller's "total mutational damage" provide the soundest and most practical basis for such comparisons. Using simulations, analytical calculations, and 1000 Genomes Project data, we provide an intuitive and quantitative explanation for the observed similarity in genetic load across populations. We show that recent demography has likely modulated the effect of selection and still affects it, but the net result of the accumulated differences is small. Direct observation of differential efficacy of selection for specific allele classes is nevertheless possible with contemporary data sets. By contrast, identifying average genome-wide differences in the efficacy of selection across populations will require many modeling assumptions and is unlikely to provide much biological insight about human populations.

Current status of the brown trout (Salmo trutta) populations within eastern Pyrenees genetic refuges

AbstractSince the end of the 20th century, some headwaters of rivers in the eastern Pyrenees have been designated as genetic refuges to protect remaining native brown trout (Salmo trutta) diversity. The declaration was based on limited or no evidence of genetic impact from released non‐native Atlantic hatchery fish. Hatchery releases were completely banned into the genetic refuges, but pre‐existing fishing activities were maintained. Specific locations in each refuge have been monitored every 2–3 trout generations to update genetic information to accurately assess the contribution of these reservoirs to the preservation of native brown trout gene pools. This work updates genetic information to year 2014 in three of these locations (in Ter, Freser and Flamisell rivers). Previous studies identified hatchery introgressed populations within refuges and suggested discrepancies between the underlying intention of the genetic refuges and the gene pools detected. Therefore, we also examined genetic divergences among locations inside refuge river segments. Combined information at five microsatellite and the lactate dehydrogenase C (LDH‐C*) loci showed reduced but significant temporal native allele frequency fluctuations in some of the above specific locations that did not modify overall levels of local diversity and river divergences. Bayesian clustering analyses confirmed the presence of differentiated native units within each genetic refuge. Some locations of the Freser River within the genetic refuge area showed high hatchery impact of non‐native fish (over 20%). We discuss additional local actions (releases of native fish, selective removals and fishery reinforcement with sterile individuals) to improve the conservation objective of genetic refuges.

A genetic demographic analysis of Lake Malawi rock-dwelling cichlids using spatio-temporal sampling.

We estimated the effective population sizes (Ne ) and tested for short-term temporal demographic stability of populations of two Lake Malawi cichlids: Maylandia benetos, a micro-endemic, and Maylandia zebra, a widespread species found across the lake. We sampled a total of 351 individuals, genotyped them at 13 microsatellite loci and sequenced their mitochondrial D-loop to estimate genetic diversity, population structure, demographic history and effective population sizes. At the microsatellite loci, genetic diversity was high in all populations. Yet, genetic diversity was relatively low for the sequence data. Microsatellites yielded mean Ne estimates of 481 individuals (±99 SD) for M.benetos and between 597 (±106.3 SD) and 1524 (±483.9 SD) individuals for local populations of M.zebra. The microsatellite data indicated no deviations from mutation-drift equilibrium. Maylandia zebra was further found to be in migration-drift equilibrium. Temporal fluctuations in allele frequencies were limited across the sampling period for both species. Bayesian Skyline analyses suggested a recent expansion of M.zebra populations in line with lake-level fluctuations, whereas the demographic history of M.benetos could only be estimated for the very recent past. Divergence time estimates placed the origin of M.benetos within the last 100ka after the refilling of the lake and suggested that it split off the sympatric M.zebra population. Overall, our data indicate that micro-endemics and populations in less favourable habitats have smaller Ne , indicating that drift may play an important role driving their divergence. Yet, despite small population sizes, high genetic variation can be maintained.

Evidence for adaptation from standing genetic variation on an antimicrobial peptide gene in the mussel Mytilus edulis.

Genome scans of population differentiation identify candidate loci for adaptation but provide little information on how selection has influenced the genetic structure of these loci. Following a genome scan, we investigated the nature of the selection responsible for the outlying differentiation observed between populations of the marine mussel Mytilus edulis at a leucine/arginine polymorphism (L31R) in the antimicrobial peptide MGD2. We analysed DNA sequence polymorphisms, allele frequencies and population differentiation of polymorphisms closely linked to L31R, and pairwise and third-order linkage disequilibria. An outlying level of population differentiation was observed at L31R only, while no departure from panmixia was observed at linked loci surrounding L31R, as in most of the genome. Selection therefore seems to affect L31R directly. Three hypotheses can explain the lack of differentiation in the chromosomal region close to L31R: (i) hitchhiking has occurred but migration and recombination subsequently erased the signal, (ii) selection was weak enough and recombination strong enough to limit the hitchhiking effect to a very small chromosomal region or (iii) selection acted on a pre-existing polymorphism (i.e. standing variation) at linkage equilibrium with its background. Linkage equilibrium was observed between L31R and linked polymorphisms in every population analysed, as expected under the three hypotheses. However, linkage disequilibrium was observed in some populations between pairs of loci located upstream and downstream to L31R, generating a complex pattern of third-order linkage disequilibria which is best explained by the hypothesis of selection on a pre-existing polymorphism. We hypothesise that selection could be either balanced, maintaining alleles at different frequencies depending on the pathogen community encountered locally by mussels, or intermittent, resulting in sporadic fluctuations in allele frequency.

Spatial Genetic Structure Patterns of Phenotype-Limited and Boundary-Limited Expanding Populations: A Simulation Study

Range expansions may create a unique spatial genetic pattern characterized by alternate genetically homogeneous domains and allele frequency clines. Previous attempts to model range expansions have mainly focused on the loss of genetic diversity during expansions. Using individual-based models, we examined spatial genetic patterns under two expansion scenarios, boundary-limited range expansions (BLRE) and phenotype-limited range expansions (PhLRE). Our simulation revealed that the genetic diversity within populations lost quickly during the range expansion, while the genetic difference accumulated between populations. Consequently, accompanying the expansions, the overall diversity featured a slow decrease. Specifically, during BLREs, high speed of boundary motion facilitated the maintenance of total genetic diversity and sharpened genetic clines. Very slight constraints on boundary motion of BLREs drastically narrowed the homogeneous domains and increased the allele frequency fluctuations from those levels exhibited by PhLREs. Even stronger constraints, however, surprisingly brought the width of homogeneous domains and the allele frequency fluctuations back to the normal levels of PhLREs. Furthermore, high migration rates maintained a higher total genetic diversity than low ones did during PhLREs. Whereas, the total genetic diversities during BLREs showed a contrary pattern: higher when migration was low than those when migration was high. Besides, the increase of migration rates helped maintain a greater number of homogeneous domains during PhLREs, but their effects on the number of homogeneous domains during BLREs were not monotonous. Previous studies have showed that the homogenous domains can merge to form a few broad domains as the expansion went on, leading to fewer homogeneous domains. Our simulations, meanwhile, revealed that the range expansions could also rebuild homogeneous domains from the clines during the range expansion. It is possible that that the number of homogeneous domains was determined by the interaction of merging and newly emerging homogeneous domains.

Genetic changes during laboratory domestication of an olive fly SIT strain

AbstractEarly attempts to apply the SIT on the olive fly, Bactrocera oleae, were unsuccessful, mainly due to the low competitiveness of the sterile mass‐reared males compared with the wild ones. Recently, new efforts are underway in Israel to develop a vigorous and efficient mass‐reared olive fly laboratory strain. To understand the genetics of the adaptation process and possibly link the corresponding loss of competitiveness to genetic markers, we followed the fluctuation of genotypic frequencies of ten microsatellite markers during the course of 22 generations of the colonization of a wild Israeli population in laboratory conditions. Effective and observed allele number is halved after 11 generations, so is mean heterozygosity. Practically, there is very little change between F0 and F1, there are substantial changes between F1 and F2–F5, and there is a virtual complete adaptation to the new laboratory environment by F11, because no more changes are observed between F11 and F22. If we assume that the loss of allele number and heterozygosity also reflects the loss of the ‘wild’ character of the colonized strain and, possibly, the loss of a substantial part of its natural vigour, our results indicate that there is an apparent need to refresh a mass‐reared colony with wild material at about every five to eight generations. Furthermore, simulation models indicated that while most of the observed allele frequency fluctuations were due to random drift, some alleles were probably under selection.

Inference on Population Histories by Approximating Infinite Alleles Diffusion

Reconstruction of the past is an important task of evolutionary biology. It takes place at different points in a hierarchy of molecular variation, including genes, individuals, populations, and species. Statistical inference about population histories has recently received considerable attention, following the development of computational tools to provide tractable approaches to this very challenging problem. Here, we introduce a likelihood-based approach which generalizes a recently developed model for random fluctuations in allele frequencies based on an approximation to the neutral Wright-Fisher diffusion. Our new framework approximates the infinite alleles Wright-Fisher model and uses an implementation with an adaptive Markov chain Monte Carlo algorithm. The method is especially well suited to data sets harboring large population samples and relatively few loci for which other likelihood-based models are currently computationally intractable. Using our model, we reconstruct the global population history of a major human pathogen, Streptococcus pneumoniae. The results illustrate the potential to reach important biological insights to an evolutionary process by a population genetics approach, which can appropriately accommodate very large population samples.

Inference of Selection Based on Temporal Genetic Differentiation in the Study of Highly Polymorphic Multigene Families

The co-evolutionary arms race between host immune genes and parasite virulence genes is known as Red Queen dynamics. Temporal fluctuations in allele frequencies, or the ‘turnover’ of alleles at immune genes, are concordant with predictions of the Red Queen hypothesis. Such observations are often taken as evidence of host-parasite co-evolution. Here, we use computer simulations of the Major Histocompatibility Complex (MHC) of guppies (Poecilia reticulata) to study the turnover rate of alleles (temporal genetic differentiation, G'ST). Temporal fluctuations in MHC allele frequencies can be ≥≤order of magnitude larger than changes observed at neutral loci. Although such large fluctuations in the MHC are consistent with Red Queen dynamics, simulations show that other demographic and population genetic processes can account for this observation, these include: (1) overdominant selection, (2) fluctuating population size within a metapopulation, and (3) the number of novel MHC alleles introduced by immigrants when there are multiple duplicated genes. Synergy between these forces combined with migration rate and the effective population size can drive the rapid turnover in MHC alleles. We posit that rapid allelic turnover is an inherent property of highly polymorphic multigene families and that it cannot be taken as evidence of Red Queen dynamics. Furthermore, combining temporal samples in spatial FST outlier analysis may obscure the signal of selection.

Post-colonization temporal genetic variation of an introduced fly, Rhagoletis completa

Evolutionary biologists have been puzzled by the success of introduced species: despite founder effects that reduce genetic variability, invasive species are still successful at colonizing new environments. It is possible that the evolutionary processes during the post-colonization period may increase the genetic diversity and gene flow among invasive populations over time, facilitating their long-term success. Therefore, genetic diversity and population structure would be expected to show greater temporal variation for successful introduced populations than for native populations. We studied the population genetics of the walnut husk fly, Rhagoletis completa, which was introduced into California from the Midwestern US in the early 1900s. We used microsatellites and allozymes to genotype current and historic fly populations, providing a rare perspective on temporal variability in population genetic parameters. We found that introduced populations showed greater temporal fluctuations in allele frequencies than native populations. Some introduced populations also showed an increase in genetic diversity over time, indicating multiple introductions had occurred. Population genetic structure decreased in both native and introduced populations over time. Our study demonstrates that introduced species are not at equilibrium and post-colonization processes may be important in ameliorating the loss of genetic diversity associated with biological invasions.

Reconstructing Population Histories from Single Nucleotide Polymorphism Data

Population genetics encompasses a strong theoretical and applied research tradition on the multiple demographic processes that shape genetic variation present within a species. When several distinct populations exist in the current generation, it is often natural to consider the pattern of their divergence from a single ancestral population in terms of a binary tree structure. Inference about such population histories based on molecular data has been an intensive research topic in the recent years. The most common approach uses coalescent theory to model genealogies of individuals sampled from the current populations. Such methods are able to compare several different evolutionary scenarios and to estimate demographic parameters. However, their major limitation is the enormous computational complexity associated with the indirect modeling of the demographies, which limits the application to small data sets. Here, we propose a novel Bayesian method for inferring population histories from unlinked single nucleotide polymorphisms, which is applicable also to data sets harboring large numbers of individuals from distinct populations. We use an approximation to the neutral Wright-Fisher diffusion to model random fluctuations in allele frequencies. The population histories are modeled as binary rooted trees that represent the historical order of divergence of the different populations. A combination of analytical, numerical, and Monte Carlo integration techniques are utilized for the inferences. A particularly important feature of our approach is that it provides intuitive measures of statistical uncertainty related with the estimates computed, which may be entirely lacking for the alternative methods in this context. The potential of our approach is illustrated by analyses of both simulated and real data sets.