MetaPopGen 2.0: A multilocus genetic simulator to model populations of large size

Type Article
Date 2021-02
Language English
Author(s) Andrello Marco1, Noirot Christelle2, Débarre Florence3, Manel Stéphanie2
Affiliation(s) 1 : MARBEC Univ Montpellier CNRS Sète, France
2 : CEFE Univ Montpellier CNRS EPHE‐PSL University IRD Univ Paul Valéry Montpellier 3 Montpellier ,France
3 : Sorbonne Université CNRS INRAE UPEC Univ. de Paris Institut d’Ecologie et des Sciences de l’Environnement de Paris (iEES‐Paris) Paris, France
Source Molecular Ecology Resources (1755-098X) (Wiley), 2021-02 , Vol. 21 , N. 2 , P. 596-608
DOI 10.1111/1755-0998.13270
Keyword(s) adaptation, connectivity, dispersal, genetic simulator, landscape genetics

Multi‐locus genetic processes in subdivided populations can be complex and difficult to interpret using theoretical population genetics models. Genetic simulators offer a valid alternative to study multi‐locus genetic processes in arbitrarily complex scenarios. However, the use of forward‐in‐time simulators in realistic scenarios involving high numbers of individuals distributed in multiple local populations is limited by computation time and memory requirements. These limitations increase with the number of simulated individuals. We developed a genetic simulator, MetaPopGen 2.0, to model multi‐locus population genetic processes in subdivided populations of arbitrarily large size. It allows for spatial and temporal variation in demographic parameters, age structure, adult and propagule dispersal, variable mutation rates and selection on survival and fecundity. We developed MetaPopGen 2.0 in the R environment to facilitate its use by non‐modeler ecologists and evolutionary biologists. We illustrate the capabilities of MetaPopGen 2.0 for studying adaptation to water salinity in the striped red mullet Mullus surmuletus.

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