Genetic structure and invasion history of the house mouse (Mus musculus domesticus) in Senegal, West Africa: a legacy of colonial and contemporary times.

Knowledge of the genetic make-up and demographic history of invasive populations is critical to understand invasion mechanisms. Commensal rodents are ideal models to study whether complex invasion histories are typical of introductions involving human activities. The house mouse Mus musculus domesticus is a major invasive synanthropic rodent originating from South-West Asia. It has been largely studied in Europe and on several remote islands, but the genetic structure and invasion history of this taxon have been little investigated in several continental areas, including West Africa. In this study, we focussed on invasive populations of M. m. domesticus in Senegal. In this focal area for European settlers, the distribution area and invasion spread of the house mouse is documented by decades of data on commensal rodent communities. Genetic variation at one mitochondrial locus and 16 nuclear microsatellite markers was analysed from individuals sampled in 36 sites distributed across the country. A combination of phylogeographic and population genetics methods showed that there was a single introduction event on the northern coast of Senegal, from an exogenous (probably West European) source, followed by a secondary introduction from northern Senegal into a coastal site further south. The geographic locations of these introduction sites were consistent with the colonial history of Senegal. Overall, the marked microsatellite genetic structure observed in Senegal, even between sites located close together, revealed a complex interplay of different demographic processes occurring during house mouse spatial expansion, including sequential founder effects and stratified dispersal due to human transport along major roads.

Invasion genetics of a human commensal rodent: the black rat Rattus rattus in Madagascar.

Studies focusing on geographical genetic patterns of commensal species and on human history complement each other and provide proxies to trace common colonization events. On Madagascar, the unintentional introduction and spread of the commensal species Rattus rattus by people may have left a living clue of human colonization patterns and history. In this study, we addressed this question by characterizing the genetic structure of natural populations of R. rattus using both microsatellites and mitochondrial sequences, on an extensive sampling across the island. Such data sets were analysed by a combination of methods using population genetics, phylogeography and approximate Bayesian computation. Our results indicated two introduction events to Madagascar from the same ancestral source of R. rattus, one in the extreme north of the island and the other further south. The latter was the source of a large spatial expansion, which may have initially started from an original point located on the southern coast. The inferred timing of introduction events-several centuries ago-is temporally congruent with the Arabian trade network in the Indian Ocean, which was flourishing from the middle of the first millennium.

|SE|S|AM|E| Barcode: NGS-oriented software for amplicon characterization--application to species and environmental barcoding.

Progress in NGS technologies has opened up new opportunities for characterizing biodiversity, both for individual specimen identification and for environmental barcoding. Although the amount of data available to biologist is increasing, user-friendly tools to facilitate data analysis have yet to be developed. Our aim, with |SE|S|AM|E| Barcode, is to provide such support through a unified platform. The sequences are analysed through a pipeline that (i) processes NGS amplicon runs, filtering markers and samples, (ii) builds reference libraries and finally (iii) identifies (barcodes) the sequences in each amplicon from the reference library. We use a simulated data set for specimen identification and a recently published data set for environmental barcoding to validate the method. The results obtained are consistent with the expected characterizations (in silico and previously published, respectively). |SE|S|AM|E| Barcode and its documentation are freely available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported Licence for Windows and Linux from http://www1.montpellier.inra.fr/CBGP/NGS/.

Do outbreaks affect genetic population structure? A worldwide survey in Locusta migratoria, a pest plagued by microsatellite null alleles.

An understanding of the role of factors intrinsic to a species' life history in structuring contemporary genetic variation is a fundamental, but understudied, aspect of evolutionary biology. Here, we assessed the influence of the propensity to outbreak in shaping worldwide genetic variation in Locusta migratoria, a cosmopolitan pest well known for its expression of density-dependent phase polyphenism. We scored 14 microsatellites in nine subspecies from 25 populations distributed over most of the species' range in regions that vary in the historical frequency and extent of their outbreaks. We rejected the hypothesis that L. migratoria consists of two genetically distinct clusters adapted to habitats either rarely (nonoutbreaking) or cyclically (outbreaking) favourable to increases in population density. We also invalidated the current subspecific taxonomic classification based on morphometrics. Bayesian inferences indicated evidence of a homogenizing effect of outbreaks on L. migratoria population structure. Geographical and ecological barriers to gene flow in conjunction with historical events can also explain the observed patterns. By systematically assessing the effects of null alleles using computer simulations, we also provide a template for the analysis of microsatellite data sets characterized by a high prevalence of null alleles.

GENECLASS2: a software for genetic assignment and first-generation migrant detection.

GENECLASS2 is a software that computes various genetic assignment criteria to assign or exclude reference populations as the origin of diploid or haploid individuals, as well as of groups of individuals, on the basis of multilocus genotype data. In addition to traditional assignment aims, the program allows the specific task of first-generation migrant detection. It includes several Monte Carlo resampling algorithms that compute for each individual its probability of belonging to each reference population or to be a resident (i.e., not a first-generation migrant) in the population where it was sampled. A user-friendly interface facilitates the treatment of large datasets.

Analytical bayesian approach for assigning individuals to populations.

We propose a general formulation of the Bayesian method for assigning individuals to a population among a predetermined set of reference populations using molecular marker information. Compared to previously published methods, ours allows us to consider different types of prior information about allele frequencies by using a Dirichlet prior probability distribution. It also makes it possible to assign a set of individuals assumed to belong to the same population with increased accuracy using their pooled genotype data. The efficiency of the method is illustrated by application to a group of closely related coconut populations. An interesting feature of the Bayesian procedure is the way it handles imprecise information. With a poor or even incomplete dataset, assignment is still be possible and gives valid results: poor data quality is reflected in an ambiguous result rather than in a false conclusion.

New methods employing multilocus genotypes to select or exclude populations as origins of individuals.

A new method for assigning individuals of unknown origin to populations, based on the genetic distance between individuals and populations, was compared to two existing methods based on the likelihood of multilocus genotypes. The distribution of the assignment criterion (genetic distance or genotype likelihood) for individuals of a given population was used to define the probability that an individual belongs to the population. Using this definition, it becomes possible to exclude a population as the origin of an individual, a useful extension of the currently available assignment methods. Using simulated data based on the coalescent process, the different methods were evaluated, varying the time of divergence of populations, the mutation model, the sample size, and the number of loci. Likelihood-based methods (especially the Bayesian method) always performed better than distance methods. Other things being equal, genetic markers were always more efficient when evolving under the infinite allele model than under the stepwise mutation model, even for equal values of the differentiation parameter F(st). Using the Bayesian method, a 100% correct assignment rate can be achieved by scoring ca. 10 microsatellite loci (H approximately 0.6) on 30-50 individuals from each of 10 populations when the F(st) is near 0.1.