The IICR and the non-stationary structured coalescent: towards demographic inference with arbitrary changes in population structure

Exact calculation of the expected SFS in structured populations

The Site Frequency Spectrum (SFS), summary statistic of the distribution of derived allele frequencies in a sample of DNA sequences, provides information about genetic variation and can be used to make population inferences. The exact calculation of the expected SFS in a panmictic population under the infinite-site model of mutation has been known in the Markovian coalescent theory for decades, but its generalization to the structured coalescent is hampered by the almost exponential growth of the states space. We show here how to obtain this expected SFS as the solution of a linear system. More precisely, we propose a complete algorithmic procedure, from how to build a suitable state space and sort it, to how to take advantage of the sparsity of the rate matrix and to solve numerically the linear system using an iterative method. We then build a specialization for the simplest case of the symmetrical n-island model to arrive at a ready-to-use software called SISiFS from which a demographic parameters inference framework could easily be developed.

Global spatiotemporal patterns of demographic fluctuations in terrestrial vertebrates during the Late Pleistocene

Demographic fluctuations are crucial for assessing species' threat levels, yet their global spatiotemporal patterns and historical drivers remain unknown. Here, we used single whole-genome sequence data for 527 extant and widespread terrestrial vertebrates to investigate their demographic fluctuations during the Late Pleistocene. Effective population size (Ne) simulations indicated that all taxa experienced a population decline from the Last Interglacial to the Last Glacial Maximum (LGM). After the LGM, birds and amphibians underwent population expansion, whereas mammals and reptiles' populations declined. Regions with high Ne shifted from Neotropical to Afrotropical and to Palearctic, some overlapping with recognized glacial refugia and biodiversity hotspots. In addition, climate-related factors exerted long-term effects on Ne, while human disturbances might confine to specific regions around the Pleistocene-Holocene boundary. This study underscores the significance of quantifying vertebrate genetic vulnerability to guide biodiversity conservation in response to environmental changes.

Can genomic analysis actually estimate past population size?

Genomic data can be used to reconstruct population size over thousands of generations, using a new class of algorithms [sequentially Markovian coalescent (SMC) methods]. These analyses often show a recent decline in Ne (effective size), which at face value implies a conservation or demographic crisis: a population crash and loss of genetic diversity. This interpretation is frequently mistaken. Here we outline how SMC methods work, why they generate this misleading signal, and suggest simple approaches for exploiting the rich information produced by these algorithms. In most species, genomic patterns reflect major changes in the species' range and subdivision over tens or hundreds of thousands of years. Consequently, collaboration between geneticists, palaeoecologists, palaeoclimatologists, and geologists is crucial for evaluating the outputs of SMC algorithms.

Ignoring population structure in hominin evolutionary models can lead to the inference of spurious admixture events

Genomic and ancient DNA data have revolutionized palaeoanthropology and our vision of human evolution, with indisputable landmarks like the sequencing of Neanderthal and Denisovan genomes. Yet, using genetic data to identify, date and quantify evolutionary events-such as ancient bottlenecks or admixture-is not straightforward, as inferences may depend on model assumptions. In the last two decades, the idea that Neanderthals and members of the Homo sapiens lineage interbred has gained momentum. From the status of unlikely theory, it has reached consensus among human evolutionary biologists. This theory is mainly supported by statistical approaches that depend on demographic models minimizing or ignoring population structure, despite its widespread occurrence and the fact that, when ignored, population structure can lead to the inference of spurious demographic events. We simulated genomic data under a structured and admixture-free model of human evolution, and found that all the tested admixture approaches identified long Neanderthal fragments in our simulated genomes and an admixture event that never took place. We also observed that several published admixture models failed to predict important empirical diversity or admixture statistics, and that we could identify several scenarios from our structured model that better predicted these statistics jointly. Using a simulated time series of ancient DNA, the structured scenarios could also predict the trajectory of the empirical D statistics. Our results suggest that models accounting for population structure are fundamental to improve our understanding of human evolution, and that admixture between Neanderthals and H. sapiens needs to be re-evaluated in the light of structured models. Beyond the Neanderthal case, we argue that ancient hybridization events, which are increasingly documented in many species, including with other hominins, may also benefit from such re-evaluation.

Next-generation phylogeography reveals unanticipated population history and climate and human impacts on the endangered floodplain bitterling (Acheilognathus longipinnis)

BACKGROUND

Floodplains harbor highly biodiverse ecosystems, which have been strongly affected by both past climate change and by recent human activities, resulting in a high prevalence of many endangered species in these habitats. Understanding the history of floodplain species over a wide range of timescales can contribute to effective conservation planning. We reconstructed the population formation history of the Itasenpara bitterling Acheilognathus longipinnis, an endangered floodplain fish species in Japan, over a broad timescale based on phylogenetic analysis, demographic modeling, and historical demographic analysis using mitogenome and whole-genome sequences. A genome sequence was newly assembled as a reference for the resequencing analysis. This bitterling is distributed in three plains separated by high mountain ranges and exhibits ecological characteristics well adapted to floodplain environments.

RESULTS

Our analyses revealed an unexpected population branching pattern, gene flow, and timing of the differentiation that occurred within a few hundred thousand years, i.e., long after the mountain uplift that was assumed to be the primary geological cause of the population differentiation. The analyses also showed that all local populations experienced a severe decline during the last glacial and post-glacial periods.

CONCLUSIONS

Our results suggest that the floodplain bitterling was able to disperse through unknown routes after mountain uplift and that its populations were strongly influenced by climatic and geographic changes in glacial-interglacial cycles and subsequent human activities, probably related to its floodplain-dependent ecology. The genomic data highlight the unanticipated distribution process of this species and the magnitude of the impact of human activities, with important implications for its conservation.

Improved inference of population histories by integrating genomic and epigenomic data

With the availability of high-quality full genome polymorphism (SNPs) data, it becomes feasible to study the past demographic and selective history of populations in exquisite detail. However, such inferences still suffer from a lack of statistical resolution for recent, for example bottlenecks, events, and/or for populations with small nucleotide diversity. Additional heritable (epi)genetic markers, such as indels, transposable elements, microsatellites, or cytosine methylation, may provide further, yet untapped, information on the recent past population history. We extend the Sequential Markovian Coalescent (SMC) framework to jointly use SNPs and other hyper-mutable markers. We are able to (1) improve the accuracy of demographic inference in recent times, (2) uncover past demographic events hidden to SNP-based inference methods, and (3) infer the hyper-mutable marker mutation rates under a finite site model. As a proof of principle, we focus on demographic inference in Arabidopsis thaliana using DNA methylation diversity data from 10 European natural accessions. We demonstrate that segregating single methylated polymorphisms (SMPs) satisfy the modeling assumptions of the SMC framework, while differentially methylated regions (DMRs) are not suitable as their length exceeds that of the genomic distance between two recombination events. Combining SNPs and SMPs while accounting for site- and region-level epimutation processes, we provide new estimates of the glacial age bottleneck and post-glacial population expansion of the European A. thaliana population. Our SMC framework readily accounts for a wide range of heritable genomic markers, thus paving the way for next-generation inference of evolutionary history by combining information from several genetic and epigenetic markers.

Impact of population structure in the estimation of recent historical effective population size by the software GONE

BACKGROUND

Effective population size (Ne) is a crucial parameter in conservation genetics and animal breeding. A recent method, implemented by the software GONE, has been shown to be rather accurate in estimating recent historical changes in Ne from a single sample of individuals. However, GONE estimations assume that the population being studied has remained isolated for a period of time, that is, without migration or confluence of other populations. If this occurs, the estimates of Ne can be heavily biased. In this paper, we evaluate the impact of migration and admixture on the estimates of historical Ne provided by GONE through a series of computer simulations considering several scenarios: (a) the mixture of two or more ancestral populations; (b) subpopulations that continuously exchange individuals through migration; (c) populations receiving migrants from a large source; and (d) populations with balanced systems of chromosomal inversions, which also generate genetic structure.

RESULTS

Our results indicate that the estimates of historical Ne provided by GONE may be substantially biased when there has been a recent mixture of populations that were previously separated for a long period of time. Similarly, biases may occur when the rate of continued migration between populations is low, or when chromosomal inversions are present at high frequencies. However, some biases due to population structuring can be eliminated by conducting population structure analyses and restricting the estimation to the differentiated groups. In addition, disregarding the genomic regions that are involved in inversions can also remove biases in the estimates of Ne.

CONCLUSIONS

Different kinds of deviations from isolation and panmixia of the populations can generate biases in the recent historical estimates of Ne. Therefore, estimation of past demography could benefit from performing population structure analyses beforehand, by mitigating the impact of these biases on historical Ne estimates.

Reduced representation approaches produce similar results to whole genome sequencing for some common phylogeographic analyses

When designing phylogeographic investigations researchers can choose to collect many different types of molecular markers, including mitochondrial genes or genomes, SNPs from reduced representation protocols, large sequence capture data sets, and even whole genomes. Given that the statistical power and accuracy of various analyses are expected to differ depending on both the type of marker and the amount of data collected, an exploration of the variance across methodological results as a function of marker type should provide valuable information to researchers. Here we collect mitochondrial Cytochrome b sequences, whole mitochondrial genomes, single nucleotide polymorphisms (SNP)s isolated using a genotype by sequencing (GBS) protocol, sequences from ultraconserved elements, and low-coverage nuclear genomes from the North American water vole (Microtus richardsoni). We estimate genetic distances, population genetic structure, and historical demography using data from each of these datasets and compare the results across markers. As anticipated, the results exhibit differences across marker types, particularly in terms of the resolution offered by different analyses. A cost-benefit analysis indicates that SNPs collected using a GBS protocol are the most cost-effective molecular marker, with inferences that mirror those collected from the whole genome data at a fraction of the cost per sample.

The revolution that still isn't: The origins of behavioral complexity in Homo sapiens

The behavioral origins of Homo sapiens can be traced back to the first material culture produced by our species in Africa, the Middle Stone Age (MSA). Beyond this broad consensus, the origins, patterns, and causes of behavioral complexity in modern humans remain debated. Here, we consider whether recent findings continue to support popular scenarios of: (1) a modern human 'package,' (2) a gradual and 'pan-African' emergence of behavioral complexity, and (3) a direct connection to changes in the human brain. Our geographically structured review shows that decades of scientific research have continuously failed to find a discrete threshold for a complete 'modernity package' and that the concept is theoretically obsolete. Instead of a continent-wide, gradual accumulation of complex material culture, the record exhibits a predominantly asynchronous presence and duration of many innovations across different regions of Africa. The emerging pattern of behavioral complexity from the MSA conforms to an intricate mosaic characterized by spatially discrete, temporally variable, and historically contingent trajectories. This archaeological record bears no direct relation to a simplistic shift in the human brain but rather reflects similar cognitive capacities that are variably manifested. The interaction of multiple causal factors constitutes the most parsimonious explanation driving the variable expression of complex behaviors, with demographic processes such as population structure, size, and connectivity playing a key role. While much emphasis has been given to innovation and variability in the MSA record, long periods of stasis and a lack of cumulative developments argue further against a strictly gradualistic nature in the record. Instead, we are confronted with humanity's deep, variegated roots in Africa, and a dynamic metapopulation that took many millennia to reach the critical mass capable of producing the ratchet effect commonly used to define contemporary human culture. Finally, we note a weakening link between 'modern' human biology and behavior from around 300 ka ago.

Like a rolling stone: Colonization and migration dynamics of the gray reef shark (Carcharhinus amblyrhynchos)

Designing appropriate management plans requires knowledge of both the dispersal ability and what has shaped the current distribution of the species under consideration. Here, we investigated the evolutionary history of the endangered gray reef shark (Carcharhinus amblyrhynchos) across its range by sequencing thousands of RADseq loci in 173 individuals in the Indo-Pacific (IP). We first bring evidence of the occurrence of a range expansion (RE) originating close to the Indo-Australian Archipelago (IAA) where two stepping-stone waves (east and westward) colonized almost the entire IP. Coalescent modeling additionally highlighted a homogenous connectivity (Nm ~ 10 per generation) throughout the range, and isolation by distance model suggested the absence of barriers to dispersal despite the affinity of C. amblyrhynchos to coral reefs. This coincides with long-distance swims previously recorded, suggesting that the strong genetic structure at the IP scale (F ST ~ 0.56 between its ends) is the consequence of its broad current distribution and organization in a large number of demes. Our results strongly suggest that management plans for the gray reef shark should be designed on a range-wide rather than a local scale due to its continuous genetic structure. We further contrasted these results with those obtained previously for the sympatric but strictly lagoon-associated Carcharhinus melanopterus, known for its restricted dispersal ability. Carcharhinus melanopterus exhibits a similar RE dynamic but is characterized by a stronger genetic structure and a nonhomogeneous connectivity largely dependent on local coral reefs availability. This sheds new light on shark evolution, emphasizing the roles of IAA as source of biodiversity and of life-history traits in shaping the extent of genetic structure and diversity.

Rates of convergence in the two-island and isolation-with-migration models

A number of powerful demographic inference methods have been developed in recent years, with the goal of fitting rich evolutionary models to genetic data obtained from many populations. In this paper we investigate the statistical performance of these methods in the specific case where there is continuous migration between populations. Compared with earlier work, migration significantly complicates the theoretical analysis and requires new techniques. We employ the theories of phase-type distributions and concentration of measure in order to study the two-island and isolation-with-migration models, resulting in both upper and lower bounds on rates of convergence for parametric estimators in migration models. For the upper bounds, we consider inferring rates of coalescent and migration on the basis of directly observing pairwise coalescent times, and, more realistically, when (conditionally) Poisson-distributed mutations dropped on latent trees are observed. We complement these upper bounds with information-theoretic lower bounds which establish a limit, in terms of sample size, below which inference is effectively impossible.

Heterogeneity in effective size across the genome: effects on the inverse instantaneous coalescence rate (IICR) and implications for demographic inference under linked selection

The relative contribution of selection and neutrality in shaping species genetic diversity is one of the most central and controversial questions in evolutionary theory. Genomic data provide growing evidence that linked selection, i.e. the modification of genetic diversity at neutral sites through linkage with selected sites, might be pervasive over the genome. Several studies proposed that linked selection could be modeled as first approximation by a local reduction (e.g. purifying selection, selective sweeps) or increase (e.g. balancing selection) of effective population size (Ne). At the genome-wide scale, this leads to variations of Ne from one region to another, reflecting the heterogeneity of selective constraints and recombination rates between regions. We investigate here the consequences of such genomic variations of Ne on the genome-wide distribution of coalescence times. The underlying motivation concerns the impact of linked selection on demographic inference, because the distribution of coalescence times is at the heart of several important demographic inference approaches. Using the concept of inverse instantaneous coalescence rate, we demonstrate that in a panmictic population, linked selection always results in a spurious apparent decrease of Ne along time. Balancing selection has a particularly large effect, even when it concerns a very small part of the genome. We also study more general models including genuine population size changes, population structure or transient selection and find that the effect of linked selection can be significantly reduced by that of population structure. The models and conclusions presented here are also relevant to the study of other biological processes generating apparent variations of Ne along the genome.

Coalescence times, life history traits and conservation concerns: An example from four coastal shark species from the Indo-Pacific

Dispersal abilities play a crucial role in shaping the extent of population genetic structure, with more mobile species being panmictic over large geographical ranges and less mobile ones organized in metapopulations exchanging migrants to different degrees. In turn, population structure directly influences the coalescence pattern of the sampled lineages, but the consequences on the estimated variation of the effective population size (N_e ) over time obtained by means of unstructured demographic models remain poorly understood. However, this knowledge is crucial for biologically interpreting the observed N_e trajectory and further devising conservation strategies in endangered species. Here we investigated the demographic history of four shark species (Carharhinus melanopterus, Carharhinus limbatus, Carharhinus amblyrhynchos, Galeocerdo cuvier) with different degrees of endangered status and life history traits related to dispersal distributed in the Indo-Pacific and sampled off New Caledonia. We compared several evolutionary scenarios representing both structured (metapopulation) and unstructured models and then inferred the N_e variation through time. By performing extensive coalescent simulations, we provided a general framework relating the underlying population structure and the observed N_e dynamics. On this basis, we concluded that the recent decline observed in three out of the four considered species when assuming unstructured demographic models can be explained by the presence of population structure. Furthermore, we also demonstrated the limits of the inferences based on the sole site frequency spectrum and warn that statistics based on linkage disequilibrium will be needed to exclude recent demographic events affecting meta-populations.

An overview of current population genomics methods for the analysis of whole-genome resequencing data in eukaryotes

Characterizing the population history of a species and identifying loci underlying local adaptation is crucial in functional ecology, evolutionary biology, conservation and agronomy. The constant improvement of high-throughput sequencing techniques has facilitated the production of whole genome data in a wide range of species. Population genomics now provides tools to better integrate selection into a historical framework, and take into account selection when reconstructing demographic history. However, this improvement has come with a profusion of analytical tools that can confuse and discourage users. Such confusion limits the amount of information effectively retrieved from complex genomic data sets, and impairs the diffusion of the most recent analytical tools into fields such as conservation biology. It may also lead to redundancy among methods. To address these isssues, we propose an overview of more than 100 state-of-the-art methods that can deal with whole genome data. We summarize the strategies they use to infer demographic history and selection, and discuss some of their limitations. A website listing these methods is available at www.methodspopgen.com.

Limits and convergence properties of the sequentially Markovian coalescent

Several methods based on the sequentially Markovian coalescent (SMC) make use of full genome sequence data from samples to infer population demographic history including past changes in population size, admixture, migration events and population structure. More recently, the original theoretical framework has been extended to allow the simultaneous estimation of population size changes along with other life history traits such as selfing or seed banking. The latter developments enhance the applicability of SMC methods to nonmodel species. Although convergence proofs have been given using simulated data in a few specific cases, an in-depth investigation of the limitations of SMC methods is lacking. In order to explore such limits, we first develop a tool inferring the best case convergence of SMC methods assuming the true underlying coalescent genealogies are known. This tool can be used to quantify the amount and type of information that can be confidently retrieved from given data sets prior to the analysis of the real data. Second, we assess the inference accuracy when the assumptions of SMC approaches are violated due to departures from the model, namely the presence of transposable elements, variable recombination and mutation rates along the sequence, and SNP calling errors. Third, we deliver a new interpretation of SMC methods by highlighting the importance of the transition matrix, which we argue can be used as a set of summary statistics in other statistical inference methods, uncoupling the SMC from hidden Markov models (HMMs). We finally offer recommendations to better apply SMC methods and build adequate data sets under budget constraints.

Inferring number of populations and changes in connectivity under the n-island model

Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

One panel to rule them all: DArTcap genotyping for population structure, historical demography, and kinship analyses, and its application to a threatened shark

With recent advances in sequencing technology, genomic data are changing how important conservation management decisions are made. Applications such as Close-Kin Mark-Recapture demand large amounts of data to estimate population size and structure, and their full potential can only be realised through ongoing improvements in genotyping strategies. Here we introduce DArTcap, a cost-efficient method that combines DArTseq and sequence capture, and illustrate its use in a high resolution population analysis of Glyphis garricki, a rare, poorly known and threatened euryhaline shark. Clustering analyses and spatial distribution of kin pairs from four different regions across northern Australia and one in Papua New Guinea, representing its entire known range, revealed that each region hosts at least one distinct population. Further structuring is likely within Van Diemen Gulf, the region that included the most rivers sampled, suggesting additional population structuring would be found if other rivers were sampled. Coalescent analyses and spatially explicit modelling suggest that G. garricki experienced a recent range expansion during the opening of the Gulf of Carpentaria following the conclusion of the Last Glacial Maximum. The low migration rates between neighbouring populations of a species that is found only in restricted coastal and riverine habitats show the importance of managing each population separately, including careful monitoring of local and remote anthropogenic activities that may affect their environments. Overall we demonstrated how a carefully chosen SNP panel combined with DArTcap can provide highly accurate kinship inference and also support population structure and historical demography analyses, therefore maximising cost-effectiveness.

Cryptic Patterns of Speciation in Cryptic Primates: Microendemic Mouse Lemurs and the Multispecies Coalescent

Mouse lemurs (Microcebus) are a radiation of morphologically cryptic primates distributed throughout Madagascar for which the number of recognized species has exploded in the past two decades. This taxonomic revision has prompted understandable concern that there has been substantial oversplitting in the mouse lemur clade. Here, we investigate mouse lemur diversity in a region in northeastern Madagascar with high levels of microendemism and predicted habitat loss. We analyzed RADseq data with multispecies coalescent (MSC) species delimitation methods for two pairs of sister lineages that include three named species and an undescribed lineage previously identified to have divergent mtDNA. Marked differences in effective population sizes, levels of gene flow, patterns of isolation-by-distance, and species delimitation results were found among the two pairs of lineages. Whereas all tests support the recognition of the presently undescribed lineage as a separate species, the species-level distinction of two previously described species, M. mittermeieri and M. lehilahytsara is not supported-a result that is particularly striking when using the genealogical discordance index (gdi). Nonsister lineages occur sympatrically in two of the localities sampled for this study, despite an estimated divergence time of less than 1 Ma. This suggests rapid evolution of reproductive isolation in the focal lineages and in the mouse lemur clade generally. The divergence time estimates reported here are based on the MSC calibrated with pedigree-based mutation rates and are considerably more recent than previously published fossil-calibrated relaxed-clock estimates. We discuss the possible explanations for this discrepancy, noting that there are theoretical justifications for preferring the MSC estimates in this case. [Cryptic species; effective population size; microendemism; multispecies coalescent; speciation; species delimitation.].

Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data

Several methods based on the Sequential Markovian coalescence (SMC) have been developed that make use of genome sequence data to uncover population demographic history, which is of interest in its own right and is a key requirement to generate a null model for selection tests. While these methods can be applied to all possible kind of species, the underlying assumptions are sexual reproduction in each generation and non-overlapping generations. However, in many plants, invertebrates, fungi and other taxa, those assumptions are often violated due to different ecological and life history traits, such as self-fertilization or long term dormant structures (seed or egg-banking). We develop a novel SMC-based method to infer 1) the rates/parameters of dormancy and of self-fertilization, and 2) the populations' past demographic history. Using simulated data sets, we demonstrate the accuracy of our method for a wide range of demographic scenarios and for sequence lengths from one to 30 Mb using four sampled genomes. Finally, we apply our method to a Swedish and a German population of Arabidopsis thaliana demonstrating a selfing rate of ca. 0.87 and the absence of any detectable seed-bank. In contrast, we show that the water flea Daphnia pulex exhibits a long lived egg-bank of three to 18 generations. In conclusion, we here present a novel method to infer accurate demographies and life-history traits for species with selfing and/or seed/egg-banks. Finally, we provide recommendations for the use of SMC-based methods for non-model organisms, highlighting the importance of the per site and the effective ratios of recombination over mutation.

Urbanization without isolation: the absence of genetic structure among cities and forests in the tiny acorn ant Temnothorax nylanderi

Urban alteration of neutral and adaptive evolutionary processes is still underexplored. Using a genome-wide SNP dataset, we investigated (i) urban-induced modifications of population demography, genetic diversity and population structure and (ii) signature of divergent selection between urban and forest populations in the ant species, Temnothorax nylanderi. Our results did not reveal an impact of urbanization on neutral processes since we observed: (i) analogous genetic diversity among paired urban/forest sites and two control populations; (ii) weak population genetic structure explained neither by habitat (urban versus forest) nor by geography; (iii) a remarkably similar demographic history across populations with an ancestral growth followed by a recent decline, regardless of their current habitat or geographical location. The micro-geographical home range of ants may explain their resilience to urbanization. Finally, we detected 19 candidate loci discriminating urban/forest populations and associated with core cellular components, molecular function or biological process. Two of these loci were associated with a gene ontology term that was previously found to belong to a module of co-expressed genes related to caste phenotype. These results call for transcriptomics analyses to identify genes associated with ant social traits and to infer their potential role in urban adaptation.

Statistical tools for seed bank detection

We derive statistical tools to analyze the patterns of genetic variability produced by models related to seed banks; in particular the Kingman coalescent, its time-changed counterpart describing so-called weak seed banks, the strong seed bank coalescent, and the two-island structured coalescent. As (strong) seed banks stratify a population, we expect them to produce a signal comparable to population structure. We present tractable formulas for Wright's F_ST and the expected site frequency spectrum for these models, and show that they can distinguish between some models for certain ranges of parameters. We then use pseudo-marginal MCMC to show that the full likelihood can reliably distinguish between all models in the presence of parameter uncertainty under moderate stratification, and point out statistical pitfalls arising from stratification that is either too strong or too weak. We further show that it is possible to infer parameters, and in particular determine whether mutation is taking place in the (strong) seed bank.