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Inferring introduction routes of invasive species using approximate Bayesian computation on microsatellite data

Abstract : Determining the routes of introduction provides not only information about the history of an invasion process, but also information about the origin and construction of the genetic composition of the invading population. It remains difficult, however, to infer introduction routes from molecular data because of a lack of appropriate methods. We evaluate here the use of an approximate Bayesian computation (ABC) method for estimating the probabilities of introduction routes of invasive populations based on microsatellite data. We considered the crucial case of a single source population from which two invasive populations originated either serially from a single introduction event or from two independent introduction events. Using simulated datasets, we found that the method gave correct inferences and was robust to many erroneous beliefs. The method was also more efficient than traditional methods based on raw values of statistics such as assignment likelihood or pairwise F(ST). We illustrate some of the features of our ABC method, using real microsatellite datasets obtained for invasive populations of the western corn rootworm, Diabrotica virgifera virgifera. Most computations were performed with the DIYABC program (http://www1.montpellier.inra.fr/CBGP/diyabc/).
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https://hal.inrae.fr/hal-02659220
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Submitted on : Saturday, May 30, 2020 - 1:43:13 PM
Last modification on : Thursday, April 22, 2021 - 3:40:17 PM

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Thomas Guillemaud, M.A. Beaumont, Marc Ciosi, Jean-Marie Cornuet, Arnaud Estoup. Inferring introduction routes of invasive species using approximate Bayesian computation on microsatellite data. Heredity, Nature Publishing Group, 2010, 104 (1), pp.88-99. ⟨10.1038/hdy.2009.92⟩. ⟨hal-02659220⟩

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