Abstract
Insufficient data on the origins of the first introduced propagule and the initial stages of invasion complicate the reconstruction of a species’ invasion history. Phylogeography of the native area profoundly shapes the genomic patterns of the propagules on which subsequent demographic processes of the invasion are based. Thus, a better understanding of this aspect helps to disentangle native and invasive histories. Here, we used genomic data together with clustering methods, explicit admixture tests combined with ABC models and Machine Learning algorithms, to compare patterns of genetic structure and gene flow of native and introduced populations, and infer the most likely invasion pathways of the highly invasive freshwater fish Pseudorasbora parva. This species is the vector of a novel lethal fungal-like pathogen (Sphaerothecum destruens) that is responsible for the decline of several fish species in Europe. We found that the current genetic structuring in the native range of P. parva has been shaped by waves of gene flow from populations in southern and northern China. Furthermore, our results strongly suggest that the genetic diversity of invasive populations results from recurrent global invasion pathways of admixed native populations. Our study also illustrates how the combination of admixture tests, ABC and Machine Learning can be used to detect high-resolution demographic signatures and reconstruct an integrative biological invasion history.
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source populations predicted for the invasive range. a (Native range, Asia) Mean admixture proportions estimated with STRUCTURE in the native range (Asia), for the chosen K = 6. Native sampled sites are pooled into putative demes for subsequent analyses. Pie chart colors correspond to the genetic clusters inferred by STRUCTURE, as in Fig. 1. (Invasive range, Europe & Middle-East) Assignment predictions of invasive individuals to native demes with AssignPOP’s SVM algorithm with a relative posterior probability > 2 (n = 292 for training, n = 100 for predictions). Pie chart colors correspond to the putative demes defined in the native range to which invasive individuals were assigned. b Posterior assignment probabilities to putative native demes estimated with AssignPop. c The demo-genetic scenario that was inferred with Approximate Bayesian Computation demonstrating three independent introductions from three independent admixed source populations. Branch lengths are not scaled. Bottleneck events are represented in thin red lines in branches. Colored branches correspond to invasive demes history
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Acknowledgements
We would like to thank all co-authors of Gozlan et al. 2020 for their help in collecting P. parva samples across the native and invasive range as well as B. Haenfling. We would also like to thank Eric Lombaert for kindly agreeing to discuss the best practices of Approximate Bayesian Computation methods. This study has been conducted in accordance with the relevant animal or human ethics approvals.
Funding
This study is part of the project GENESIS ANR-AF 13-ADAP-0005-001 supported by the Agence Nationale de la Recherche. S.B. was co-funded by the project PROBIS (Biodiversa) and E.C. was funded by an IRD postdoctoral fellowship. R.E.G., A.G., J.F.M. and S.B. received funding for this research from ANR Bioadapt.
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T.B., E.C. performed research, analysed the data. T.B., E.C. and R.E.G. wrote the manuscript; R.E.G., R.J.S.McC., J.F.M., A.G. and S.B. designed research and contributed with data; Y.Z., R.E.G., M.C. contributed with data; R.J.S.McC. assisted with analyses. All authors commented on the manuscript.
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All sequencing data (GBS reads) are publicly-available under the BioProject ID PRJNA799666. The original genetic data yielded by genotyping (in vcf format), additional metadata (e.g. geographical coordinates) and all scripts necessary to reproduce the results presented in the paper are available in a publicly-available Github repository: https://github.com/ThomasBrazier/PseudorasboraGENESIS. Data are available from the authors upon reasonable request.
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Brazier, T., Cherif, E., Martin, JF. et al. The influence of native populations’ genetic history on the reconstruction of invasion routes: the case of a highly invasive aquatic species. Biol Invasions 24, 2399–2420 (2022). https://doi.org/10.1007/s10530-022-02787-6
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DOI: https://doi.org/10.1007/s10530-022-02787-6