Revisiting the historical scenario of a disease dissemination using genetic data and Approximate Bayesian Computation methodology: The case of Pseudocercospora fijiensis invasion in Africa

The reconstruction of geographic and demographic scenarios of dissemination for invasive pathogens of crops is a key step toward improving the management of emerging infectious diseases. Nowadays, the reconstruction of biological invasions typically uses the information of both genetic and historical information to test for different hypotheses of colonization. The Approximate Bayesian Computation framework and its recent Random Forest development (ABC-RF) have been successfully used in evolutionary biology to decipher multiple histories of biological invasions. Yet, for some organisms, typically plant pathogens, historical data may not be reliable notably because of the difficulty to identify the organism and the delay between the introduction and the first mention. We investigated the history of the invasion of Africa by the fungal pathogen of banana Pseudocercospora fijiensis, by testing the historical hypothesis against other plausible hypotheses. We analyzed the genetic structure of eight populations from six eastern and western African countries, using 20 microsatellite markers and tested competing scenarios of population foundation using the ABC-RF methodology. We do find evidence for an invasion front consistent with the historical hypothesis, but also for the existence of another front never mentioned in historical records. We question the historical introduction point of the disease on the continent. Crucially, our results illustrate that even if ABC-RF inferences may sometimes fail to infer a single, well-supported scenario of invasion, they can be helpful in rejecting unlikely scenarios, which can prove much useful to shed light on disease dissemination routes.

Gene Copy Number Variations at the Within-Host Population Level Modulate Gene Expression in a Multipartite Virus

Multipartite viruses have a segmented genome, with each segment encapsidated separately. In all multipartite virus species for which the question has been addressed, the distinct segments reproducibly accumulate at a specific and host-dependent relative frequency, defined as the ‘genome formula’. Here, we test the hypothesis that the multipartite genome organization facilitates the regulation of gene expression via changes of the genome formula and thus via gene copy number variations. In a first experiment, the faba bean necrotic stunt virus (FBNSV), whose genome is composed of eight DNA segments each encoding a single gene, was inoculated into faba bean or alfalfa host plants, and the relative concentrations of the DNA segments and their corresponding messenger RNAs (mRNAs) were monitored. In each of the two host species, our analysis consistently showed that the genome formula variations modulate gene expression, the concentration of each genome segment linearly and positively correlating to that of its cognate mRNA but not of the others. In a second experiment, twenty parallel FBNSV lines were transferred from faba bean to alfalfa plants. Upon host switching, the transcription rate of some genome segments changes, but the genome formula is modified in a way that compensates for these changes and maintains a similar ratio between the various viral mRNAs. Interestingly, a deep-sequencing analysis of these twenty FBNSV lineages demonstrated that the host-related genome formula shift operates independently of DNA-segment sequence mutation. Together, our results indicate that nanoviruses are plastic genetic systems, able to transiently adjust gene expression at the population level in changing environments, by modulating the copy number but not the sequence of each of their genes.

Evolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift

Resurrection studies are a useful tool to measure how phenotypic traits have changed in populations through time. If these trait modifications correlate with the environmental changes that occurred during the time period, it suggests that the phenotypic changes could be a response to selection. Selfing, through its reduction of effective size, could challenge the ability of a population to adapt to environmental changes. Here, we used a resurrection study to test for adaptation in a selfing population of Medicago truncatula, by comparing the genetic composition and flowering times across 22 generations. We found evidence for evolution toward earlier flowering times by about two days and a peculiar genetic structure, typical of highly selfing populations, where some multilocus genotypes (MLGs) are persistent through time. We used the change in frequency of the MLGs through time as a multilocus fitness measure and built a selection gradient that suggests evolution toward earlier flowering times. Yet, a simulation model revealed that the observed change in flowering time could be explained by drift alone, provided the effective size of the population is small enough (<150). These analyses suffer from the difficulty to estimate the effective size in a highly selfing population, where effective recombination is severely reduced.

ƒ-statistics estimation and admixture graph construction with Pool-Seq or allele count data using the R package poolfstat

By capturing various patterns of the structuring of genetic variation across populations, f -statistics have proved highly effective for the inference of demographic history. Such statistics are defined as covariance of SNP allele frequency differences among sets of populations without requiring haplotype information and are hence particularly relevant for the analysis of pooled sequencing (Pool-Seq) data. We here propose a reinterpretation of the F (and D) parameters in terms of probability of gene identity and derive from this unified definition unbiased estimators for both Pool-Seq data and standard allele count data obtained from individual genotypes. We implemented these estimators in a new version of the R package poolfstat, which now includes a wide range of inference methods: (i) three-population test of admixture; (ii) four-population test of treeness; (iii) F4-ratio estimation of admixture rates; and (iv) fitting, visualization and (semi-automatic) construction of admixture graphs. A comprehensive evaluation of the methods implemented in poolfstat on both simulated Pool-Seq (with various sequencing coverages and error rates) and allele count data confirmed the accuracy of these approaches, even for the most cost-effective Pool-Seq design involving relatively low sequencing coverages. We further analyzed a real Pool-Seq data made of 14 populations of the invasive species Drosophila suzukii which allowed refining both the demographic history of native populations and the invasion routes followed by this emblematic pest. Our new package poolfstat provides the community with a user-friendly and efficient all-in-one tool to unravel complex population genetic histories from large-size Pool-Seq or allele count SNP data.

Extending approximate Bayesian computation with supervised machine learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest

Simulation-based methods such as approximate Bayesian computation (ABC) are well-adapted to the analysis of complex scenarios of populations and species genetic history. In this context, supervised machine learning (SML) methods provide attractive statistical solutions to conduct efficient inferences about scenario choice and parameter estimation. The Random Forest methodology (RF) is a powerful ensemble of SML algorithms used for classification or regression problems. Random Forest allows conducting inferences at a low computational cost, without preliminary selection of the relevant components of the ABC summary statistics, and bypassing the derivation of ABC tolerance levels. We have implemented a set of RF algorithms to process inferences using simulated data sets generated from an extended version of the population genetic simulator implemented in DIYABC v2.1.0. The resulting computer package, named DIYABC Random Forest v1.0, integrates two functionalities into a user-friendly interface: the simulation under custom evolutionary scenarios of different types of molecular data (microsatellites, DNA sequences or SNPs) and RF treatments including statistical tools to evaluate the power and accuracy of inferences. We illustrate the functionalities of DIYABC Random Forest v1.0 for both scenario choice and parameter estimation through the analysis of pseudo-observed and real data sets corresponding to pool-sequencing and individual-sequencing SNP data sets. Because of the properties inherent to the implemented RF methods and the large feature vector (including various summary statistics and their linear combinations) available for SNP data, DIYABC Random Forest v1.0 can efficiently contribute to the analysis of large SNP data sets to make inferences about complex population genetic histories.

Preliminary insights into the genetics of bank vole tolerance to Puumala hantavirus in Sweden

Natural reservoirs of zoonotic pathogens generally seem to be capable of tolerating infections. Tolerance and its underlying mechanisms remain difficult to assess using experiments or wildlife surveys. High-throughput sequencing technologies give the opportunity to investigate the genetic bases of tolerance, and the variability of its mechanisms in natural populations. In particular, population genomics may provide preliminary insights into the genes shaping tolerance and potentially influencing epidemiological dynamics. Here, we addressed these questions in the bank vole Myodes glareolus, the specific asymptomatic reservoir host of Puumala hantavirus (PUUV), which causes nephropathia epidemica (NE) in humans. Despite the continuous spatial distribution of M. glareolus in Sweden, NE is endemic to the northern part of the country. Northern bank vole populations in Sweden might exhibit tolerance strategies as a result of coadaptation with PUUV. This may favor the circulation and maintenance of PUUV and lead to high spatial risk of NE in northern Sweden. We performed a genome-scan study to detect signatures of selection potentially correlated with spatial variations in tolerance to PUUV. We analyzed six bank vole populations from Sweden, sampled from northern NE-endemic to southern NE-free areas. We combined candidate gene analyses (Tlr4, Tlr7, and Mx2 genes) and high-throughput sequencing of restriction site-associated DNA (RAD) markers. Outlier loci showed high levels of genetic differentiation and significant associations with environmental data including variations in the regional number of NE human cases. Among the 108 outliers that matched to mouse protein-coding genes, 14 corresponded to immune-related genes. The main biological pathways found to be significantly enriched corresponded to immune processes and responses to hantavirus, including the regulation of cytokine productions, TLR cascades, and IL-7, VEGF, and JAK-STAT signaling. In the future, genome-scan replicates and functional experimentations should enable to assess the role of these biological pathways in M. glareolus tolerance to PUUV.

Identifying genomic hotspots of differentiation and candidate genes involved in the adaptive divergence of pea aphid host races

Identifying the genomic bases of adaptation to novel environments is a long-term objective in evolutionary biology. Because genetic differentiation is expected to increase between locally adapted populations at the genes targeted by selection, scanning the genome for elevated levels of differentiation is a first step towards deciphering the genomic architecture underlying adaptive divergence. The pea aphid Acyrthosiphon pisum is a model of choice to address this question, as it forms a large complex of plant-specialized races and cryptic species, resulting from recent adaptive radiation. Here, we characterized genomewide polymorphisms in three pea aphid races specialized on alfalfa, clover and pea crops, respectively, which we sequenced in pools (poolseq). Using a model-based approach that explicitly accounts for selection, we identified 392 genomic hotspots of differentiation spanning 47.3 Mb and 2,484 genes (respectively, 9.12% of the genome size and 8.10% of its genes). Most of these highly differentiated regions were located on the autosomes, and overall differentiation was weaker on the X chromosome. Within these hotspots, high levels of absolute divergence between races suggest that these regions experienced less gene flow than the rest of the genome, most likely by contributing to reproductive isolation. Moreover, population-specific analyses showed evidence of selection in every host race, depending on the hotspot considered. These hotspots were significantly enriched for candidate gene categories that control host-plant selection and use. These genes encode 48 salivary proteins, 14 gustatory receptors, 10 odorant receptors, five P450 cytochromes and one chemosensory protein, which represent promising candidates for the genetic basis of host-plant specialization and ecological isolation in the pea aphid complex. Altogether, our findings open new research directions towards functional studies, for validating the role of these genes on adaptive phenotypes.

Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time

Rapid phenotypic evolution of quantitative traits can occur within years, but its underlying genetic architecture remains uncharacterized. Here we test the theoretical prediction that genes with intermediate pleiotropy drive adaptive evolution in nature. Through a resurrection experiment, we grew Arabidopsis thaliana accessions collected across an 8-year period in six micro-habitats representative of that local population. We then used genome-wide association mapping to identify the single-nucleotide polymorphisms (SNPs) associated with evolved and unevolved traits in each micro-habitat. Finally, we performed a selection scan by testing for temporal differentiation in these SNPs. Phenotypic evolution was consistent across micro-habitats, but its associated genetic bases were largely distinct. Adaptive evolutionary change was most strongly driven by a small number of quantitative trait loci (QTLs) with intermediate degrees of pleiotropy; this pleiotropy was synergistic with the per-trait effect size of the SNPs, increasing with the degree of pleiotropy. In addition, weak selection was detected for frequent micro-habitat-specific QTLs that shape single traits. In this population, A. thaliana probably responded to local warming and increased competition, in part mediated by central regulators of flowering time. This genetic architecture, which includes both synergistic pleiotropic QTLs and distinct QTLs within particular micro-habitats, enables rapid phenotypic evolution while still maintaining genetic variation in wild populations.

Microevolution of bank voles (Myodes glareolus) at neutral and immune-related genes during multiannual dynamic cycles: Consequences for Puumala hantavirus epidemiology

Understanding how host dynamics, including variations of population size and dispersal, may affect the epidemiology of infectious diseases through ecological and evolutionary processes is an active research area. Here we focus on a bank vole (Myodes glareolus) metapopulation surveyed in Finland between 2005 and 2009. Bank vole is the reservoir of Puumala hantavirus (PUUV), the agent of nephropathia epidemica (NE, a mild form of hemorrhagic fever with renal symptom) in humans. M. glareolus populations experience multiannual density fluctuations that may influence the level of genetic diversity maintained in bank voles, PUUV prevalence and NE occurrence. We examine bank vole metapopulation genetics at presumably neutral markers and immune-related genes involved in susceptibility to PUUV (Tnf-promoter, Tlr4, Tlr7 and Mx2 gene) to investigate the links between population dynamics, microevolutionary processes and PUUV epidemiology. We show that genetic drift slightly and transiently affects neutral and adaptive genetic variability within the metapopulation. Gene flow seems to counterbalance its effects during the multiannual density fluctuations. The low abundance phase may therefore be too short to impact genetic variation in the host, and consequently viral genetic diversity. Environmental heterogeneity does not seem to affect vole gene flow, which might explain the absence of spatial structure previously detected in PUUV in this area. Besides, our results suggest the role of vole dispersal on PUUV circulation through sex-specific and density-dependent movements. We find little evidence of selection acting on immune-related genes within this metapopulation. Footprint of positive selection is detected at Tlr-4 gene in 2008 only. We observe marginally significant associations between Mx2 genotype and PUUV genogroups. These results show that neutral processes seem to be the main factors affecting the evolution of these immune-related genes at a contemporary scale, although the relative effects of neutral and adaptive forces could vary temporally with density fluctuations. Immune related gene polymorphism may in turn partly influence PUUV epidemiology in this metapopulation.

rehh 2.0: a reimplementation of the R package rehh to detect positive selection from haplotype structure

Identifying genomic regions with unusually high local haplotype homozygosity represents a powerful strategy to characterize candidate genes responding to natural or artificial positive selection. To that end, statistics measuring the extent of haplotype homozygosity within (e.g. EHH, iHS) and between (Rsb or XP-EHH) populations have been proposed in the literature. The rehh package for r was previously developed to facilitate genome-wide scans of selection, based on the analysis of long-range haplotypes. However, its performance was not sufficient to cope with the growing size of available data sets. Here, we propose a major upgrade of the rehh package, which includes an improved processing of the input files, a faster algorithm to enumerate haplotypes, as well as multithreading. As illustrated with the analysis of large human haplotype data sets, these improvements decrease the computation time by more than one order of magnitude. This new version of rehh will thus allow performing iHS-, Rsb- or XP-EHH-based scans on large data sets. The package rehh 2.0 is available from the CRAN repository (http://cran.r-project.org/web/packages/rehh/index.html) together with help files and a detailed manual.

Maximum-likelihood inference of population size contractions from microsatellite data

Understanding the demographic history of populations and species is a central issue in evolutionary biology and molecular ecology. In this work, we develop a maximum-likelihood method for the inference of past changes in population size from microsatellite allelic data. Our method is based on importance sampling of gene genealogies, extended for new mutation models, notably the generalized stepwise mutation model (GSM). Using simulations, we test its performance to detect and characterize past reductions in population size. First, we test the estimation precision and confidence intervals coverage properties under ideal conditions, then we compare the accuracy of the estimation with another available method (MSVAR) and we finally test its robustness to misspecification of the mutational model and population structure. We show that our method is very competitive compared with alternative ones. Moreover, our implementation of a GSM allows more accurate analysis of microsatellite data, as we show that the violations of a single step mutation assumption induce very high bias toward false contraction detection rates. However, our simulation tests also showed some limits, which most importantly are large computation times for strong disequilibrium scenarios and a strong influence of some form of unaccounted population structure. This inference method is available in the latest implementation of the MIGRAINE software package.

When history repeats itself: exploring the genetic architecture of host-plant adaptation in two closely related lepidopteran species

The genus Ostrinia includes two allopatric maize pests across Eurasia, namely the European corn borer (ECB, O. nubilalis) and the Asian corn borer (ACB, O. furnacalis). A third species, the Adzuki bean borer (ABB, O. scapulalis), occurs in sympatry with both the ECB and the ACB. The ABB mostly feeds on native dicots, which probably correspond to the ancestral host plant type for the genus Ostrinia. This situation offers the opportunity to characterize the two presumably independent adaptations or preadaptations to maize that occurred in the ECB and ACB. In the present study, we aimed at deciphering the genetic architecture of these two adaptations to maize, a monocot host plant recently introduced into Eurasia. To this end, we performed a genome scan analysis based on 684 AFLP markers in 12 populations of ECB, ACB and ABB. We detected 2 outlier AFLP loci when comparing French populations of the ECB and ABB, and 9 outliers when comparing Chinese populations of the ACB and ABB. These outliers were different in both countries, and we found no evidence of linkage disequilibrium between any two of them. These results suggest that adaptation or preadaptation to maize relies on a different genetic architecture in the ECB and ACB. However, this conclusion must be considered in light of the constraints inherent to genome scan approaches and of the intricate evolution of adaptation and reproductive isolation in the Ostrinia spp. complex.

The joint evolution of dispersal and dormancy in a metapopulation with local extinctions and kin competition

Dispersal and dormancy are two strategies that allow recolonization of empty patches and escape from kin competition. Because they presumably respond to similar evolutionary forces, it is tempting to consider that these strategies may substitute for each other. Yet in order to predict the outcome of the evolution of dispersal and dormancy, and to characterize the emerging covariation between both traits, it is necessary to consider models where dispersal and dormancy evolve jointly. Here, we analyze the evolution of dispersal and dormancy as a function of direct fitness costs, environmental variation, and competition among relatives. We consider two scenarios depending on whether the rates of dormancy for philopatric and dispersed individuals are constrained to be the same (unconditional dormancy) or allowed to be different (conditional dormancy). We show that only philopatric individuals should enter dormancy, at a rate increasing with increasing rates of local extinction and decreasing population sizes. When dormancy and dispersal evolve jointly, we observe a wide range of evolutionary outcomes. In particular, we find that the pattern of covariation between the evolutionarily stable rates of dispersal and dormancy is molded by the rate of extinction and the local population size.

Positive selection of protective variants for type 2 diabetes from the Neolithic onward: a case study in Central Asia

The high prevalence of type 2 diabetes and its uneven distribution among human populations is both a major public health concern and a puzzle in evolutionary biology. Why is this deleterious disease so common, while the associated genetic variants should be removed by natural selection? The 'thrifty genotype' hypothesis proposed that the causal genetic variants were advantageous and selected for during the majority of human evolution. It remains, however, unclear whether genetic data support this scenario. In this study, we characterized patterns of selection at 10 variants associated with type 2 diabetes, contrasting one herder and one farmer population from Central Asia. We aimed at identifying which alleles (risk or protective) are under selection, dating the timing of selective events, and investigating the effect of lifestyle on selective patterns. We did not find any evidence of selection on risk variants, as predicted by the thrifty genotype hypothesis. Instead, we identified clear signatures of selection on protective variants, in both populations, dating from the beginning of the Neolithic, which suggests that this major transition was accompanied by a selective advantage for non-thrifty variants. Combining our results with worldwide data further suggests that East Asia was particularly prone to such recent selection of protective haplotypes. As much effort has been devoted so far to searching for thrifty variants, we argue that more attention should be paid to the evolution of non-thrifty variants.

Genome scans reveal candidate regions involved in the adaptation to host plant in the pea aphid complex

A major goal in evolutionary biology is to uncover the genetic basis of adaptation. Divergent selection exerted on ecological traits may result in adaptive population differentiation and reproductive isolation and affect differentially the level of genetic divergence along the genome. Genome-wide scan of large sets of individuals from multiple populations is a powerful approach to identify loci or genomic regions under ecologically divergent selection. Here, we focused on the pea aphid, a species complex of divergent host races, to explore the organization of the genomic divergence associated with host plant adaptation and ecological speciation. We analysed 390 microsatellite markers located at variable distances from predicted genes in replicate samples of sympatric populations of the pea aphid collected on alfalfa, red clover and pea, which correspond to three common host-adapted races reported in this species complex. Using a method that accounts for the hierarchical structure of our data set, we found a set of 11 outlier loci that show higher genetic differentiation between host races than expected under the null hypothesis of neutral evolution. Two of the outliers are close to olfactory receptor genes and three other nearby genes encoding salivary proteins. The remaining outliers are located in regions with genes of unknown functions, or which functions are unlikely to be involved in interactions with the host plant. This study reveals genetic signatures of divergent selection across the genome and provides an inventory of candidate genes responsible for plant specialization in the pea aphid, thereby setting the stage for future functional studies.

Large-scale candidate gene scan reveals the role of chemoreceptor genes in host plant specialization and speciation in the pea aphid

Understanding the drivers of speciation is critical to interpreting patterns of biodiversity. The identification of the genetic changes underlying adaptation and reproductive isolation is necessary to link barriers to gene flow to the causal origins of divergence. Here, we present a novel approach to the genetics of speciation, which should complement the commonly used approaches of quantitative trait locus mapping and genome-wide scans for selection. We present a large-scale candidate gene approach by means of sequence capture, applied to identifying the genetic changes underlying reproductive isolation in the pea aphid, a model system for the study of ecological speciation. Targeted resequencing enabled us to scale up the candidate gene approach, specifically testing for the role of chemosensory gene families in host plant specialization. Screening for the signature of divergence under selection at 172 candidate and noncandidate loci, we revealed a handful of loci that show high levels of differentiation among host races, which almost all correspond to odorant and gustatory receptor genes. This study offers the first indication that some chemoreceptor genes, often tightly linked together in the genome, could play a key role in local adaptation and reproductive isolation in the pea aphid and potentially other phytophagous insects. Our approach opens a new route toward the functional genomics of ecological speciation.

rehh: an R package to detect footprints of selection in genome-wide SNP data from haplotype structure

With the development of next-generation sequencing and genotyping approaches, large single nucleotide polymorphism haplotype datasets are becoming available in a growing number of both model and non-model species. Identifying genomic regions with unexpectedly high local haplotype homozygosity relatively to neutral expectation represents a powerful strategy to ascertain candidate genes responding to natural or artificial selection. To facilitate genome-wide scans of selection based on the analysis of long-range haplotypes, we developed the R package rehh. It provides a versatile tool to detect the footprints of recent or ongoing selection with several graphical functions that help visual interpretation of the results.

AVAILABILITY AND IMPLEMENTATION

Stable version is available from CRAN: http://cran.r-project.org/. Development version is available from the R-forge repository: http://r-forge.r-project.org/projects/rehh. Both versions can be installed directly from R. Function documentation and example data files are provided within the package and a tutorial is available as Supplementary Material. rehh is distributed under the GNU General Public Licence (GPL ≥ 2).

DETSEL: an R-package to detect marker loci responding to selection

In the new era of population genomics, surveys of genetic polymorphism ("genome scans") offer the opportunity to distinguish locus-specific from genome-wide effects at many loci. Identifying presumably neutral regions of the genome that are assumed to be influenced by genome-wide effects only, and excluding presumably selected regions, is therefore critical to infer population demography and phylogenetic history reliably. Conversely, detecting locus-specific effects may help identify those genes that have been, or still are, targeted by natural selection. The software package DETSEL has been developed to identify markers that show deviation from neutral expectation in pairwise comparisons of diverging populations. Recently, two major improvements have been made: the analysis of dominant markers is now supported, and the estimation of empirical P-values has been implemented. These features, which are described below, have been incorporated into an R package, which replaces the stand-alone DETSEL software package.

Scanning the European corn borer (Ostrinia spp.) genome for adaptive divergence between host-affiliated sibling species

It has recently been shown that the European corn borer, a major pest of maize crops, is actually composed of two genetically differentiated and reproductively isolated taxa, which are found in sympatry over a wide geographical range in Eurasia. Each taxon is adapted to specific host plants: Ostrinia nubilalis feeds mainly on maize, while O. scapulalis feeds mainly on hop or mugwort. Here, we present a genome scan approach as a first step towards an integrated molecular analysis of the adaptive genomic divergence between O. nubilalis and O. scapulalis. We analysed 609 AFLP marker loci in replicate samples of sympatric populations of Ostrinia spp. collected on maize, hop and mugwort, in France. Using two genome scan methods based on the analysis of population differentiation, we found a set of 28 outlier loci that departed from the neutral expectation in one or the other method (of which a subset of 14 loci were common to both methods), which showed a significantly increased differentiation between O. nubilalis and O. scapulalis, when compared to the rest of the genome. A subset of 12 outlier loci were sequenced, of which 7 were successfully re-amplified as target candidate loci. Three of these showed homology with annotated lepidopteran sequences from public nucleotide databases.

Chromosomal inversions, natural selection and adaptation in the malaria vector Anopheles funestus

Chromosomal polymorphisms, such as inversions, are presumably involved in the rapid adaptation of populations to local environmental conditions. Reduced recombination between alternative arrangements in heterozygotes may protect sets of locally adapted genes, promoting ecological divergence and potentially leading to reproductive isolation and speciation. Through a comparative analysis of chromosomal inversions and microsatellite marker polymorphisms, we hereby present biological evidence that strengthens this view in the mosquito Anopheles funestus s.s, one of the most important and widespread malaria vectors in Africa. Specimens were collected across a wide range of geographical, ecological, and climatic conditions in Cameroon. We observed a sharp contrast between population structure measured at neutral microsatellite markers and at chromosomal inversions. Microsatellite data detected only a weak signal for population structuring among geographical zones (F(ST) < 0.013, P < 0.01). By contrast, strong differentiation among ecological zones was revealed by chromosomal inversions (F(ST) > 0.190, P < 0.01). Using standardized estimates of F(ST), we show that inversions behave at odds with neutral expectations strongly suggesting a role of environmental selection in shaping their distribution. We further demonstrate through canonical correspondence analysis that heterogeneity in eco-geographical variables measured at specimen sampling sites explained 89% of chromosomal variance in A. funestus. These results are in agreement with a role of chromosomal inversions in ecotypic adaptation in this species. We argue that this widespread mosquito represents an interesting model system for the study of chromosomal speciation mechanisms and should provide ample opportunity for comparative studies on the evolution of reproductive isolation and speciation in major human malaria vectors.

In the heartland of Eurasia: the multilocus genetic landscape of Central Asian populations

Located in the Eurasian heartland, Central Asia has played a major role in both the early spread of modern humans out of Africa and the more recent settlements of differentiated populations across Eurasia. A detailed knowledge of the peopling in this vast region would therefore greatly improve our understanding of range expansions, colonizations and recurrent migrations, including the impact of the historical expansion of eastern nomadic groups that occurred in Central Asia. However, despite its presumable importance, little is known about the level and the distribution of genetic variation in this region. We genotyped 26 Indo-Iranian- and Turkic-speaking populations, belonging to six different ethnic groups, at 27 autosomal microsatellite loci. The analysis of genetic variation reveals that Central Asian diversity is mainly shaped by linguistic affiliation, with Turkic-speaking populations forming a cluster more closely related to East-Asian populations and Indo-Iranian speakers forming a cluster closer to Western Eurasians. The scattered position of Uzbeks across Turkic- and Indo-Iranian-speaking populations may reflect their origins from the union of different tribes. We propose that the complex genetic landscape of Central Asian populations results from the movements of eastern, Turkic-speaking groups during historical times, into a long-lasting group of settled populations, which may be represented nowadays by Tajiks and Turkmen. Contrary to what is generally thought, our results suggest that the recurrent expansions of eastern nomadic groups did not result in the complete replacement of local populations, but rather into partial admixture.

Limited dispersal in mobile hunter-gatherer Baka Pygmies

Hunter-gatherer Pygmies from Central Africa are described as being extremely mobile. Using neutral genetic markers and population genetics theory, we explored the dispersal behaviour of the Baka Pygmies from Cameroon, one of the largest Pygmy populations in Central Africa. We found a strong correlation between genetic and geographical distances: a pattern of isolation by distance arising from limited parent-offspring dispersal. Our study suggests that mobile hunter-gatherers do not necessarily disperse over wide geographical areas.

Evolution of flowering time in experimental wheat populations: a comprehensive approach to detect genetic signatures of natural selection

In annual plant species, flowering time is a major adaptive trait that synchronizes the initiation of reproduction with favorable environmental conditions. Here, we aimed at studying the evolution of flowering time in three experimental populations of bread wheat, grown in contrasting environments (Northern to Southern France) for 12 generations. By comparing the distribution of phenotypic and presumably neutral variation, we first showed that flowering time responded to selection during the 12 generations of the experiment. To get insight into the genetic architecture of that trait, we then tested whether the distribution of genetic polymorphisms at six candidate genes, presumably involved in the trait expression, departed from neutral expectation. To that end, we focused on the temporal variation during the course of the experiment, and on the spatial differentiation at the end of the experiment, using previously published methods adapted to our experimental design. Only those genes that were strongly associated with flowering time variation were detected as responding to selection. For genes that had low-to-moderate phenotypic effects, or when there was interaction across different genes, we did not find evidence of selection using methods based on the distribution of temporal or spatial variation. In such cases, it might be more informative to consider multilocus and multiallelic combinations across genes, which could be the targets of selection.

In defence of model-based inference in phylogeography

Recent papers have promoted the view that model-based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model-based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model-based inference in population genetics.

Genomic pattern of adaptive divergence in Arabidopsis halleri, a model species for tolerance to heavy metal

Pollution by heavy metals is one of the strongest environmental constraints in human-altered environments that only a handful of species can cope with. Identifying the genes conferring to those species the ability to grow in polluted areas is a first step towards a global understanding of the evolutionary processes involved and will eventually improve phytoremediation practices. We used a genome-scan approach to detect loci under divergent selection among four populations of Arabidopsis halleri growing on either polluted or nonpolluted habitats. Based on a high density of amplified fragment length polymorphism (AFLP) markers (820 AFLP markers, i.e. approximately 1 marker per 0.3Mb), evidence for selection was found for some markers in every sampled population. Four loci departed from neutrality in both metallicolous populations and thus constitute high-quality candidates for general adaptation to pollution. Interestingly, some candidates differed between the two metallicolous populations, suggesting the possibility that different loci may be involved in adaptation in the different metallicolous populations.

Sex-specific genetic structure and social organization in Central Asia: insights from a multi-locus study

In the last two decades, mitochondrial DNA (mtDNA) and the non-recombining portion of the Y chromosome (NRY) have been extensively used in order to measure the maternally and paternally inherited genetic structure of human populations, and to infer sex-specific demography and history. Most studies converge towards the notion that among populations, women are genetically less structured than men. This has been mainly explained by a higher migration rate of women, due to patrilocality, a tendency for men to stay in their birthplace while women move to their husband's house. Yet, since population differentiation depends upon the product of the effective number of individuals within each deme and the migration rate among demes, differences in male and female effective numbers and sex-biased dispersal have confounding effects on the comparison of genetic structure as measured by uniparentally inherited markers. In this study, we develop a new multi-locus approach to analyze jointly autosomal and X-linked markers in order to aid the understanding of sex-specific contributions to population differentiation. We show that in patrilineal herder groups of Central Asia, in contrast to bilineal agriculturalists, the effective number of women is higher than that of men. We interpret this result, which could not be obtained by the analysis of mtDNA and NRY alone, as the consequence of the social organization of patrilineal populations, in which genetically related men (but not women) tend to cluster together. This study suggests that differences in sex-specific migration rates may not be the only cause of contrasting male and female differentiation in humans, and that differences in effective numbers do matter.

Human evolutionary history has been investigated mainly through the prism of genetic variation of the Y chromosome and mitochondrial DNA. These two uniparentally inherited markers reflect the demographic history of males and females, respectively. Their contrasting patterns of genetic differentiation reveal that women are more mobile than men among populations, which might be due to specific marriage rules. However, these two markers provide only a limited understanding of the underlying demographic processes. To obtain an independent picture of sex-specific demography, we developed a new multi-locus approach based on the analysis of markers from the autosomal and X-chromosomal compartments. We applied our method to 21 human populations sampled in Central Asia, with contrasting social organizations and lifestyles. We found that, in patrilineal populations, not only the migration rate but also the number of reproductive individuals is likely to be higher for women. This result does not hold for bilineal populations, for which both the migration rate and the number of reproductive individuals can be equal for both sexes. The social organization of patrilineal populations is the likely cause of this pattern. This study suggests that differences in sex-specific migration rates may not be the only cause of contrasting male and female differentiation in humans, and that differences in effective numbers do matter.

THE EVOLUTION OF DISPERSAL IN A LEVINS' TYPE METAPOPULATION MODEL

We study the evolution of the dispersal rate in a metapopulation model with extinction and colonization dynamics, akin to the model as originally described by Levins. To do so we extend the metapopulation model with a description of the within patch dynamics. By means of a separation of time scales we analytically derive a fitness expression from first principles for this model. The fitness function can be written as an inclusive fitness equation (Hamilton's rule). By recasting this equation in a form that emphasizes the effects of competition we show the effect of the local competition and the local population size on the evolution of dispersal. We find that the evolution of dispersal cannot be easily interpreted in terms of avoidance of kin competition, but rather that increased dispersal reduces the competitive ability. Our model also yields a testable prediction in term of relatedness and life-history parameters.

When Genes Go to Sleep: The Population Genetic Consequences of Seed Dormancy and Monocarpic Perenniality

In many annual plant populations, seeds may be dormant for several seasons before they germinate. Here, we investigate the consequences of both conditional (dispersed seeds cannot enter a dormant stage) and unconditional seed dormancy on the amount and the distribution of neutral genetic diversity within and among populations. We present joint demographic and population genetics models for single and subdivided populations and derive the effective size and population differentiation at both local and metapopulation scales. We suggest that a Wahlund effect is unlikely to result from age structure alone. Furthermore, the differentiation among populations is decreased by the presence of seed banks. We also extend these models to describe monocarpic (semelparous) perennial life cycle, where the nonreproductive stages are vegetative rosettes instead of dormant seeds. The main difference between the models relies in the way the density-dependent regulation is acting. The effective size of monocarpic perennial species may be less than the census number of individuals, and among-population differentiation is always larger than in annual species. We discuss our results in the light of recent population genetics surveys of annual plants with seed banks.

DetSel 1.0: A Computer Program to Detect Markers Responding to Selection

Estimating population parameters from polymorphism frequency data requires neutral genetic markers. Any departure from neutrality may invalidate the inferences drawn from such analyses. We recently discussed the possibility of identifying markers that show deviation from neutral expectations in pairwise comparisons of diverging populations. We are now releasing a user-friendly software package that implements all the necessary steps to identify the signature of selection among molecular markers in a set of polymorphism data. This software can be downloaded free of charge at http://www.univ-montp2.fr/~genetix/detsel/detsel.html.

Multilocus genetic structure at contrasted spatial scales of the endangered water fern Marsilea strigosa Willd. (Marsileaceae, Pteridophyta)

Marsilea strigosa (Marsileaceae, Pterydophyta) is a rare water fern found in the Mediterranean basin, in temporary flooded habitats only. We analyzed the level and the distribution of genetic variation at seven microsatellite loci, both at the Mediterranean scale and at a narrower scale within a highly fragmented French metapopulation. Genetic diversity among individuals within each pond suggests that M. strigosa reproduces predominantly through selfing. The very high population differentiation at the Mediterranean scale indicates that gene flow (if any) is highly restricted. Similar differentiation is also found at the scale of a single metapopulation. The distribution of multilocus genotypes suggests that the genetic variation in this species is maintained mainly through the interplay of mutation and low recombination.

Sex-specific genetic differentiation and coalescence times: estimating sex-biased dispersal rates

I derive the equilibrium values of sex-specific FST parameters, in an island model for a dioecious species with sex-biased dispersal and binomial distribution of family size before dispersal (as assumed in a Wright-Fisher population). I show that FST may take different values among males and among females whenever dispersal is a trait conditioned on gender. This has not always been recognized, because some models assumed that genes are sampled before dispersal. In particular, the ratios of sex-specific FST parameters evaluated after dispersal over FST evaluated before dispersal are simple functions of sex-specific dispersal rates. Therefore, a simple moment-based estimator of sex-specific dispersal rate is proposed. This method is based on the comparison of FST estimated before and after dispersal and assumes equilibrium between migration and drift. I evaluate this method through stochastic simulations for a range of sex-specific dispersal rates and sampling effort (sample size, number of loci scored).

Interpretation of variation across marker loci as evidence of selection

Population structure and history have similar effects on the genetic diversity at all neutral loci. However, some marker loci may also have been strongly influenced by natural selection. Selection shapes genetic diversity in a locus-specific manner. If we could identify those loci that have responded to selection during the divergence of populations, then we may obtain better estimates of the parameters of population history by excluding these loci. Previous attempts were made to identify outlier loci from the distribution of sample statistics under neutral models of population structure and history. Unfortunately these methods depend on assumptions about population structure and history that usually cannot be verified. In this article, we define new population-specific parameters of population divergence and construct sample statistics that are estimators of these parameters. We then use the joint distribution of these estimators to identify outlier loci that may be subject to selection. We found that outlier loci are easier to recognize when this joint distribution is conditioned on the total number of allelic states represented in the pooled sample at each locus. This is so because the conditional distribution is less sensitive to the values of nuisance parameters.

Two-locus identity probabilities and identity disequilibrium in a partially selfing subdivided population

Measures of association of genes at different loci (linkage disequilibrium) are widely used to determine whether the structure of natural populations is clonal or not, to map genes from population data, or to test for the homogeneity of response of molecular markers to background selection, for example. However, the usual definitions of parameters for gametic associations may not be suitable for all these purposes. In this paper, we derive the recursion equations for one- and two-locus identity probabilities in an infinite island model. We study the role of drift, gene flow, partial selfing and mutation model on the expected association of genes across loci. We define the 'within-subpopulation identity disequilibrium' as the difference between the joint two-locus probability of identity in state and the expected product of one-locus identity probabilities. We evaluate this parameter as a function of recombination rate, effective size, gene flow and selfing rate. Within-subpopulation identity disequilibrium attains maximum values for intermediate immigration rates, whatever the selfing rate. Moreover, identity disequilibrium may be very small, even for high selfing rates. We discuss the implications of these findings for the analysis of data from natural populations.

Estimation of effective population size and migration rate from one- and two-locus identity measures

Standard methods for inferring demographic parameters from genetic data are based mainly on one-locus theory. However, the association of genes at different loci (e.g., two-locus identity disequilibrium) may also contain some information about demographic parameters of populations. In this article, we define one- and two-locus parameters of population structure as functions of one- and two-locus probabilities for the identity in state of genes. Since these parameters are known functions of demographic parameters in an infinite island model, we develop moment-based estimators of effective population size and immigration rate from one- and two-locus parameters. We evaluate this method through simulation. Although variance and bias may be quite large, increasing the number of loci on which the estimates are derived improves the method. We simulate an infinite allele model and a K allele model of mutation. Bias and variance are smaller with increasing numbers of alleles per locus. This is, to our knowledge, the first attempt of a joint estimation of local effective population size and immigration rate.

Relationships between transposable elements based upon the integrase-transposase domains: is there a common ancestor?

The integrase domain of RNA-mediated elements (class I) and the transposase domain of DNA-mediated transposable elements (class II) were compared. A number of elements contain the DDE signature, which plays an important role in their integration. The possible relationships between mariner-Tc1 and IS elements, retrotransposons, and retroviruses were analyzed from an alignment of this region. The mariner-Tc1 superfamily, and LTR retrotransposons and retroviruses were found to be monophyletic groups. However, the IS elements of bacteria were found in several groups. These results were used to propose an evolutionary history that suggests a common ancestor for some integrases and transposases.