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

Abstract

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.

Deciphering the worldwide invasion of the Asian long‐horned beetle: A recurrent invasion process from the native area together with a bridgehead effect

“…The consistency between results based on the core and alternative data sets for all but one analysis, as well as the moderate prior error rates and the large differences in terms of RF votes (Table ), indicates a reasonable level of confidence in the choice of scenarios. Note that high F IS values should not challenge ABC analyses, as demonstrated by Lippens et al ().…”

“…This method makes it possible to take into account complex demographic processes such as changes in effective population size, admixture events and the involvement of unsampled populations (i.e., ghost populations; Estoup & Guillemaud, ). ABC has been used successfully to retrace the invasion routes of numerous alien species (Lesieur et al, ; Lippens et al, ; Lombaert et al, ; Miller et al, ; Pascual et al, ). The number of simulated data sets increases steadily with the number of tested scenarios, which can lead to time‐consuming computations.…”

Interplay between historical and current features of the cityscape in shaping the genetic structure of the house mouse (Mus musculus domesticus) in Dakar (Senegal, West Africa)

“…1). They were chosen to represent different stages of the urban history and different habitats (Table 1 and Coeur district (DAK), which was sampled in 2014 for a previous study (Lippens et al, 2017), according to a standardized protocol described in Dalecky et al (2015). Each sampling site was the focus of one live trapping session of 2 to 5 consecutive days, in order to reach the target sample size of a minimum of 20 captured house mice on a median surface of 0.04 km 2 (min: 0.01, max: 1.51; the maximum value concerned POR).…”

“…Several phylogeographic studies have shown that its colonization history is strongly related to human migration patterns at different timescales (Jones et al, 2013). The house mouse may have been introduced in Dakar as soon as it was settled by Europeans in the middle of the nineteenth century (Lippens et al, 2017). The city has then been continuously growing since European settled at the southern end of the Cap-Vert peninsula.…”

A young age of subspecific divergence in the desert locustSchistocerca gregaria, inferred by ABC Random Forest

“…For model choice, Estoup et al (2018) use the so called posterior predictive error rate which is an error of this type. In this case, some simulated datasets of the reference table close to the observation are selected thanks to an Euclidean distance, then new pseudo-observed datasets are simulated using similar parameters, on which is computed the error (see also Lippens et al, 2017, for a similar approach in a standard ABC framework). However, the main problem of processing this way is the difficulty to specify the size of the area around the observation, especially when the number of summary statistics is large.…”