Modelling multilocus selection in an individual‐based, spatially‐explicit landscape genetics framework
| Autor: | Amy V. Whipple, Casey C. Day, Andrew J. Shirk, Andrew J. Eckert, Erin L. Landguth, Samuel A. Cushman, Brenna R. Forester, Mitra Menon |
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| Rok vydání: | 2019 |
| Předmět: |
Gene Flow
0106 biological sciences 0301 basic medicine Genetics Multivariate statistics Natural selection Genotype Models Genetic Biology 010603 evolutionary biology 01 natural sciences 03 medical and health sciences Range (mathematics) Individual based Genetics Population 030104 developmental biology Genetic Loci Computer Simulation Selection Genetic Additive model Ecology Evolution Behavior and Systematics Selection (genetic algorithm) Biotechnology |
| Zdroj: | Molecular Ecology Resources. 20:605-615 |
| ISSN: | 1755-0998 1755-098X |
| DOI: | 10.1111/1755-0998.13121 |
| Popis: | We implemented multilocus selection in a spatially-explicit, individual-based framework that enables multivariate environmental gradients to drive selection in many loci as a new module for the landscape genetics programs, CDPOP and CDMetaPOP. Our module simulates multilocus selection using a linear additive model, providing a flexible platform to evaluate a wide range of genotype-environment associations. Importantly, the module allows simulation of selection in any number of loci under the influence of any number of environmental variables. We validated the module with individual-based selection simulations under Wright-Fisher assumptions. We then evaluated results for simulations under a simple landscape selection model. Next, we simulated individual-based multilocus selection across a complex selection landscape with three loci linked to three different environmental variables. Finally, we demonstrated how the program can be used to simulate multilocus selection under varying selection strengths across different levels of gene flow in a landscape genetics framework. This new module provides a valuable addition to the study of landscape genetics, allowing for explicit evaluation of the contributions and interactions between gene flow and selection-driven processes across complex, multivariate environmental and landscape conditions. |
| Databáze: | OpenAIRE |
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