Spatial coalescent connectivity through multi-generation dispersal modelling predicts gene flow across marine phyla

Térence Legrand (), Anne Chenuil, Enrico Ser-Giacomi, Sophie Arnaud-Haond, Nicolas Bierne and Vincent Rossi ()
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Térence Legrand: Aix Marseille University, Universite de Toulon, CNRS, IRD, Mediterranean Institute of Oceanography (UMR 7294)
Anne Chenuil: Aix Marseille Université, Avignon Université, IRD 237, Station marine d’Endoume, Chemin de la Batterie des Lions
Enrico Ser-Giacomi: Massachusetts Institute of Technology, 54-1514 MIT
Sophie Arnaud-Haond: Exploitation and Conservation, UMR 9190) Univ. Montpellier, IFREMER, IRD, CNRS
Nicolas Bierne: ISEM, Univ Montpellier, CNRS, IRD
Vincent Rossi: Aix Marseille University, Universite de Toulon, CNRS, IRD, Mediterranean Institute of Oceanography (UMR 7294)

Nature Communications, 2022, vol. 13, issue 1, 1-12

Abstract: Abstract Gene flow governs the contemporary spatial structure and dynamic of populations as well as their long-term evolution. For species that disperse using atmospheric or oceanic flows, biophysical models allow predicting the migratory component of gene flow, which facilitates the interpretation of broad-scale spatial structure inferred from observed allele frequencies among populations. However, frequent mismatches between dispersal estimates and observed genetic diversity prevent an operational synthesis for eco-evolutionary projections. Here we use an extensive compilation of 58 population genetic studies of 47 phylogenetically divergent marine sedentary species over the Mediterranean basin to assess how genetic differentiation is predicted by Isolation-By-Distance, single-generation dispersal and multi-generation dispersal models. Unlike previous approaches, the latter unveil explicit parents-to-offspring links (filial connectivity) and implicit links among siblings from a common ancestor (coalescent connectivity). We find that almost 70 % of observed variance in genetic differentiation is explained by coalescent connectivity over multiple generations, significantly outperforming other models. Our results offer great promises to untangle the eco-evolutionary forces that shape sedentary population structure and to anticipate climate-driven redistributions, altogether improving spatial conservation planning.

Date: 2022
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DOI: 10.1038/s41467-022-33499-z

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