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Evaluating genetic drift in time-series evolutionary analysis.

Published version
Peer-reviewed

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Authors

R Nené, Nuno 
J R Illingworth, Christopher 

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.

Description

Keywords

Experimental evolution, Genetic drift, Time-resolved genome sequence data, Wright–Fisher model, Algorithms, Animals, Computer Simulation, Evolution, Molecular, Gene Frequency, Genetic Drift, Genetics, Population, Genome, Humans, Models, Genetic, Population Density, Time Factors

Journal Title

J Theor Biol

Conference Name

Journal ISSN

0022-5193
1095-8541

Volume Title

437

Publisher

Elsevier BV
Sponsorship
Wellcome Trust (101239/Z/13/Z)