Nene , N R , Mustonen , V & Illingworth , C J R 2018 , ' Evaluating genetic drift in time-series evolutionary analysis ' , Journal of Theoretical Biology , vol. 437 , pp. 51-57 . https://doi.org/10.1016/j.jtbi.2017.09.021
Title: | Evaluating genetic drift in time-series evolutionary analysis |
Author: | Nene, Nuno R.; Mustonen, Ville; Illingworth, Christopher J. R. |
Contributor organization: | Biosciences |
Date: | 2018-01-21 |
Language: | eng |
Number of pages: | 7 |
Belongs to series: | Journal of Theoretical Biology |
ISSN: | 0022-5193 |
DOI: | https://doi.org/10.1016/j.jtbi.2017.09.021 |
URI: | http://hdl.handle.net/10138/229854 |
Abstract: | The Wright-Fisher model is the most popular population model for describing the behaviour of evolutionary systems with a finite population size. Approximations have commonly been used but the model itself has rarely been tested against time-resolved genomic data. Here, we evaluate the extent to which it can be inferred as the correct model under a likelihood framework. Given genome-wide data from an evolutionary experiment, we validate the Wright-Fisher drift model as the better option for describing evolutionary trajectories in a finite population. This was found by evaluating its performance against a Gaussian model of allele frequency propagation. However, we note a range of circumstances under which standard Wright-Fisher drift cannot be correctly identified. (C) 2017 The Author(s). Published by Elsevier Ltd. |
Subject: |
Genetic drift
Time-resolved genome sequence data Wright-Fisher model Experimental evolution EFFECTIVE POPULATION-SIZE GENERAL DIPLOID SELECTION WRIGHT-FISHER MODEL DROSOPHILA-MELANOGASTER FREQUENCY INFERENCE DYNAMICS LINKAGE APPROXIMATION TRANSITION 1182 Biochemistry, cell and molecular biology |
Peer reviewed: | Yes |
Rights: | cc_by |
Usage restriction: | openAccess |
Self-archived version: | publishedVersion |
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