Evaluating genetic drift in time-series evolutionary analysis

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Pysyväisosoite

http://hdl.handle.net/10138/229854

Lähdeviite

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

Julkaisun nimi: Evaluating genetic drift in time-series evolutionary analysis
Tekijä: Nene, Nuno R.; Mustonen, Ville; Illingworth, Christopher J. R.
Tekijän organisaatio: Biosciences
Päiväys: 2018-01-21
Kieli: eng
Sivumäärä: 7
Kuuluu julkaisusarjaan: Journal of Theoretical Biology
ISSN: 0022-5193
DOI-tunniste: https://doi.org/10.1016/j.jtbi.2017.09.021
URI: http://hdl.handle.net/10138/229854
Tiivistelmä: 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.
Avainsanat: 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
Vertaisarvioitu: Kyllä
Tekijänoikeustiedot: cc_by
Pääsyrajoitteet: openAccess
Rinnakkaistallennettu versio: publishedVersion


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