MetaPopGen 2.0: A multilocus genetic simulator to model populations of large size
| Autor: | Christelle Noirot, Marco Andrello, Florence Débarre, Stéphanie Manel |
|---|---|
| Přispěvatelé: | Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris ), Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0106 biological sciences
0301 basic medicine Mutation rate Salinity [SDV]Life Sciences [q-bio] Population Population genetics adaptation genetic simulator Biology 010603 evolutionary biology 01 natural sciences 03 medical and health sciences Propagule Genetics Animals Computer Simulation education dispersal ComputingMilieux_MISCELLANEOUS Ecology Evolution Behavior and Systematics Selection (genetic algorithm) Simulation Population Density education.field_of_study Models Genetic Genetic Variation landscape genetics Adaptation Physiological Biological Evolution Smegmamorpha Arbitrarily large 030104 developmental biology Genetics Population connectivity Biological dispersal Adaptation Software Biotechnology |
| Zdroj: | Molecular Ecology Resources (1755-098X) (Wiley), 2021-02, Vol. 21, N. 2, P. 596-608 Molecular Ecology Resources Molecular Ecology Resources, Wiley/Blackwell, 2020, ⟨10.1111/1755-0998.13270⟩ |
| ISSN: | 1755-098X 1755-0998 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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