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Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest.

Antoine Fraimout 1 Vincent Debat 1 Simon Fellous 2 Ruth A Hufbauer 3 Julien Foucaud 4, 5 Pierre Pudlo 6 Jean-Michel Marin 7 Donald K Price 8 Julien Cattel 9 Xiao Chen 10 Marindia Deprá 11 Pierre-François Duyck 12 Christelle Guedot 13 Marc Kenis 14 Masahito T Kimura 15 Gregory Loeb 16 Anne Loiseau 2 Isabel Martinez-Sañudo 17 Marta Pascual 18 Maxi Polihronakis Richmond 19 Peter Shearer 20 Nadia Singh 21 Koichiro Tamura 22 Anne Xuéreb 2 Jinping Zhang 23 Arnaud Estoup 2
Abstract : Deciphering invasion routes from molecular data is crucial to understanding biological invasions, including identifying bottlenecks in population size and admixture among distinct populations. Here, we unravel the invasion routes of the invasive pest Drosophila suzukii using a multi-locus microsatellite dataset (25 loci on 23 worldwide sampling locations). To do this, we use approximate Bayesian computation (ABC), which has improved the reconstruction of invasion routes, but can be computationally expensive. We use our study to illustrate the use of a new, more efficient, ABC method, ABC random forest (ABC-RF) and compare it to a standard ABC method (ABC-LDA). We find that Japan emerges as the most probable source of the earliest recorded invasion into Hawaii. Southeast China and Hawaii together are the most probable sources of populations in western North America, which then in turn served as sources for those in eastern North America. European populations are genetically more homogeneous than North American populations, and their most probable source is northeast China, with evidence of limited gene flow from the eastern US as well. All introduced populations passed through bottlenecks, and analyses reveal five distinct admixture events. These findings can inform hypotheses concerning how this species evolved between different and independent source and invasive populations. Methodological comparisons indicate that ABC-RF and ABC-LDA show concordant results if ABC-LDA is based on a large number of simulated datasets but that ABC-RF out-performs ABC-LDA when using a comparable and more manageable number of simulated datasets, especially when analyzing complex introduction scenarios.
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Antoine Fraimout, Vincent Debat, Simon Fellous, Ruth A Hufbauer, Julien Foucaud, et al.. Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest.. Molecular Biology and Evolution, Oxford University Press (OUP), 2017, 34 (4), pp.980 - 996. ⟨10.1093/molbev/msx050⟩. ⟨hal-01582586⟩



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