Neutral genomic signatures of host-parasite coevolution.

BACKGROUND: Coevolution is a selective process of reciprocal adaptation in hosts and parasites or in mutualistic symbionts. Classic population genetics theory predicts the signatures of selection at the interacting loci of both species, but not the neutral genome-wide polymorphism patterns. To bridge this gap, we build an eco-evolutionary model, where neutral genomic changes over time are driven by a single selected locus in hosts and parasites via a simple biallelic gene-for-gene or matching-allele interaction. This coevolutionary process may lead to cyclic changes in the sizes of the interacting populations. RESULTS: We investigate if and when these changes can be observed in the site frequency spectrum of neutral polymorphisms from host and parasite full genome data. We show that changes of the host population size are too smooth to be observable in its polymorphism pattern over the course of time. Conversely, the parasite population may undergo a series of strong bottlenecks occurring on a slower relative time scale, which may lead to observable changes in a time series sample. We also extend our results to cases with 1) several parasites per host accelerating relative time, and 2) multiple parasite generations per host generation slowing down rescaled time. CONCLUSIONS: Our results show that time series sampling of host and parasite populations with full genome data are crucial to understand if and how coevolution occurs. This model provides therefore a framework to interpret and draw inference from genome-wide polymorphism data of interacting species.

Effects of population- and seed bank size fluctuations on neutral evolution and efficacy of natural selection.

Population genetics models typically consider a fixed population size and a unique selection coefficient. However, population dynamics inherently generate fluctuations in numbers of individuals and selection acts on various components of the individuals' fitness. In plant species with seed banks, the size of both the above- and below-ground compartments induce fluctuations depending on seed production and the state of the seed bank. We investigate if this fluctuation has consequences on (1) the rate of genetic drift, and (2) the efficacy of selection. We consider four variants of two-allele Moran-type models defined by combinations of presence and absence of fluctuations in the population size in above-ground and seed bank compartments. Time scale analysis and dimension reduction methods allow us to reduce the corresponding Fokker-Planck equations to one-dimensional diffusion approximations of a Moran model. We first show that if the fluctuations of above-ground population size classically affect the rate of genetic drift, fluctuations of below-ground population size reduce the diversity storage effect of the seed bank. Second, we consider that selection can act on four different components of the plant fitness: plant or seed death rate, seed production or seed germination. Our striking result is that the efficacy of selection for seed death rate or germination rate is reduced by fluctuations in the seed bank size, whereas selection occurring on plant death rate or seed production is not affected. We derive the expected site-frequency spectrum reflecting this heterogeneity in selection efficacy between genes underpinning different plant fitness components. Our results highlight the importance to consider the effect of ecological noise to predict the impact of seed banks on neutral and selective evolution.

A genome-wide scan for genes under balancing selection in Drosophila melanogaster.

BACKGROUND: In the history of population genetics balancing selection has been considered as an important evolutionary force, yet until today little is known about its abundance and its effect on patterns of genetic diversity. Several well-known examples of balancing selection have been reported from humans, mice, plants, and parasites. However, only very few systematic studies have been carried out to detect genes under balancing selection. We performed a genome scan in Drosophila melanogaster to find signatures of balancing selection in a derived (European) and an ancestral (African) population. We screened a total of 34 genomes searching for regions of high genetic diversity and an excess of SNPs with intermediate frequency. RESULTS: In total, we found 183 candidate genes: 141 in the European population and 45 in the African one, with only three genes shared between both populations. Most differences between both populations were observed on the X chromosome, though this might be partly due to false positives. Functionally, we find an overrepresentation of genes involved in neuronal development and circadian rhythm. Furthermore, some of the top genes we identified are involved in innate immunity. CONCLUSION: Our results revealed evidence of genes under balancing selection in European and African populations. More candidate genes have been found in the European population. They are involved in several different functions.

Fisher-Wright model with deterministic seed bank and selection.

Seed banks are common characteristics to many plant species, which allow storage of genetic diversity in the soil as dormant seeds for various periods of time. We investigate an above-ground population following a Fisher-Wright model with selection coupled with a deterministic seed bank assuming the length of the seed bank is kept constant and the number of seeds is large. To assess the combined impact of seed banks and selection on genetic diversity, we derive a general diffusion model. The applied techniques outline a path of approximating a stochastic delay differential equation by an appropriately rescaled stochastic differential equation. We compute the equilibrium solution of the site-frequency spectrum and derive the times to fixation of an allele with and without selection. Finally, it is demonstrated that seed banks enhance the effect of selection onto the site-frequency spectrum while slowing down the time until the mutation-selection equilibrium is reached.

Methylome evolution in plants.

Despite major progress in dissecting the molecular pathways that control DNA methylation patterns in plants, little is known about the mechanisms that shape plant methylomes over evolutionary time. Drawing on recent intra- and interspecific epigenomic studies, we show that methylome evolution over long timescales is largely a byproduct of genomic changes. By contrast, methylome evolution over short timescales appears to be driven mainly by spontaneous epimutational events. We argue that novel methods based on analyses of the methylation site frequency spectrum (mSFS) of natural populations can provide deeper insights into the evolutionary forces that act at each timescale.

Balancing selection on immunity genes: review of the current literature and new analysis in Drosophila melanogaster.

Balancing selection has been widely assumed to be an important evolutionary force, yet even today little is known about its abundance and its impact on the patterns of genetic diversity. Several studies have shown examples of balancing selection in humans, plants or parasites, and many genes under balancing selection are involved in immunity. It has been proposed that host-parasite coevolution is one of the main forces driving immune genes to evolve under balancing selection. In this paper, we review the literature on balancing selection on immunity genes in several organisms, including Drosophila. Furthermore, we performed a genome scan for balancing selection in an African population of Drosophila melanogaster using coalescent simulations of a demographic model with and without selection. We find very few genes under balancing selection and only one novel candidate gene related to immunity. Finally, we discuss the possible causes of the low number of genes under balancing selection.

Transition Densities and Sample Frequency Spectra of Diffusion Processes with Selection and Variable Population Size.

Advances in empirical population genetics have made apparent the need for models that simultaneously account for selection and demography. To address this need, we here study the Wright-Fisher diffusion under selection and variable effective population size. In the case of genic selection and piecewise-constant effective population sizes, we obtain the transition density by extending a recently developed method for computing an accurate spectral representation for a constant population size. Utilizing this extension, we show how to compute the sample frequency spectrum in the presence of genic selection and an arbitrary number of instantaneous changes in the effective population size. We also develop an alternate, efficient algorithm for computing the sample frequency spectrum using a moment-based approach. We apply these methods to answer the following questions: If neutrality is incorrectly assumed when there is selection, what effects does it have on demographic parameter estimation? Can the impact of negative selection be observed in populations that undergo strong exponential growth?

SweeD: likelihood-based detection of selective sweeps in thousands of genomes.

The advent of modern DNA sequencing technology is the driving force in obtaining complete intra-specific genomes that can be used to detect loci that have been subject to positive selection in the recent past. Based on selective sweep theory, beneficial loci can be detected by examining the single nucleotide polymorphism patterns in intraspecific genome alignments. In the last decade, a plethora of algorithms for identifying selective sweeps have been developed. However, the majority of these algorithms have not been designed for analyzing whole-genome data. We present SweeD (Sweep Detector), an open-source tool for the rapid detection of selective sweeps in whole genomes. It analyzes site frequency spectra and represents a substantial extension of the widely used SweepFinder program. The sequential version of SweeD is up to 22 times faster than SweepFinder and, more importantly, is able to analyze thousands of sequences. We also provide a parallel implementation of SweeD for multi-core processors. Furthermore, we implemented a checkpointing mechanism that allows to deploy SweeD on cluster systems with queue execution time restrictions, as well as to resume long-running analyses after processor failures. In addition, the user can specify various demographic models via the command-line to calculate their theoretically expected site frequency spectra. Therefore, (in contrast to SweepFinder) the neutral site frequencies can optionally be directly calculated from a given demographic model. We show that an increase of sample size results in more precise detection of positive selection. Thus, the ability to analyze substantially larger sample sizes by using SweeD leads to more accurate sweep detection. We validate SweeD via simulations and by scanning the first chromosome from the 1000 human Genomes project for selective sweeps. We compare SweeD results with results from a linkage-disequilibrium-based approach and identify common outliers.

Demographic inference reveals African and European admixture in the North American Drosophila melanogaster population.

Drosophila melanogaster spread from sub-Saharan Africa to the rest of the world colonizing new environments. Here, we modeled the joint demography of African (Zimbabwe), European (The Netherlands), and North American (North Carolina) populations using an approximate Bayesian computation (ABC) approach. By testing different models (including scenarios with continuous migration), we found that admixture between Africa and Europe most likely generated the North American population, with an estimated proportion of African ancestry of 15%. We also revisited the demography of the ancestral population (Africa) and found-in contrast to previous work-that a bottleneck fits the history of the population of Zimbabwe better than expansion. Finally, we compared the site-frequency spectrum of the ancestral population to analytical predictions under the estimated bottleneck model.

Germ banks affect the inference of past demographic events.

Continuous progress in empirical population genetics based on the whole-genome polymorphism data requires the theoretical analysis of refined models in order to interpret the evolutionary history of populations with adequate accuracy. Recent studies focus prevalently on the aspects of demography and adaptation, whereas age structure (for example, in plants via the maintenance of seed banks) has attracted less attention. Germ banking, that is, seed or egg dormancy, is a prevalent and important life-history trait in plants and invertebrates, which buffers against environmental variability and modulates species extinction in fragmented habitats. Within this study, we investigate the combined effect of germ banking and time-varying population size on the neutral coalescent and particularly derive the allele frequency spectrum under some simplifying assumptions. We then perform an ABC analysis using two simple demographic scenarios-a population expansion and an instantaneous decline. We demonstrate the appreciable influence of seed banks on the estimation of demographic parameters depending on the germination rate with biases scaled by the square of the germination rate. In the more complex case of a population bottleneck, which comprises an instantaneous decline and an expansion phase, ignoring information on the germination rate denies reliable estimates of the bottleneck parameters via the allelic spectrum. In particular, when seeds remain in the bank over several generations, recent expansions may remain invisible in the frequency spectrum, whereas ancient declines leave signatures much longer than in the absence of seed bank.

Analytical results on the neutral non-equilibrium allele frequency spectrum based on diffusion theory.

The allele frequency spectrum has attracted considerable interest for the simultaneous inference of the demographic and adaptive history of populations. In a recent study, Evans et al. (2007) developed a forward diffusion equation describing the allele frequency spectrum, when the population is subject to size changes, selection and mutation. From the diffusion equation, the authors derived a system of ordinary differential equations (ODEs) for the moments in a Wright-Fisher diffusion with varying population size and constant selection. Here, we present an explicit solution for this system of ODEs with variable population size, but without selection, and apply this result to derive the expected spectrum of a sample for time-varying population size. We use this forward-in-time-solution of the allele frequency spectrum to obtain the backward-in-time-solution previously derived via coalescent theory by Griffiths and Tavaré (1998). Finally, we discuss the applicability of the theoretical results to the analysis of nucleotide polymorphism data.

Second-order moments of segregating sites under variable population size.

The identification of genomic regions that have been exposed to positive selection is a major challenge in population genetics. Since selective sweeps are expected to occur during environmental changes or when populations are colonizing a new habitat, statistical tests constructed on the assumption of constant population size are biased by the co-occurrence of population size changes and selection. To delimit this problem and gain better insights into demographic factors, theoretical results regarding the second-order moments of segregating sites, such as the variance of segregating sites, have been derived. Driven by emerging genomewide surveys, which allow the estimation of demographic parameters, a generalized version of Tajima's D has been derived that takes into account a previously estimated demographic scenario to test single loci for traces of selection against the null hypothesis of neutral evolution under variable population size.

Identification of selective sweeps using a dynamically adjusted number of linked microsatellites.

There is currently large interest in distinguishing the signatures of genetic variation produced by demographic events from those produced by natural selection. We propose a simple multilocus statistical test to identify candidate sites of selective sweeps with high power. The test is based on the variability profile measured in an array of linked microsatellites. We also show that the analysis of flanking markers drastically reduces the number of false positives among the candidates that are identified in a genomewide survey of unlinked loci and find that this property is maintained in many population-bottleneck scenarios. However, for a certain range of intermediately severe population bottlenecks we find genomic signatures that are very similar to those produced by a selective sweep. While in these worst-case scenarios the power of the proposed test remains high, the false-positive rate reaches values close to 50%. Hence, selective sweeps may be hard to identify even if multiple linked loci are analyzed. Nevertheless, the integration of information from multiple linked loci always leads to a considerable reduction of the false-positive rate compared to a genome scan of unlinked loci. We discuss the application of this test to experimental data from Drosophila melanogaster.