A method to infer positive selection from marker dynamics in an asexual population

Illingworth, C. J.R. and Mustonen, V. (2013) A method to infer positive selection from marker dynamics in an asexual population. Bioinformatics, 28(6), pp. 831-837. (doi: 10.1093/bioinformatics/btr722) (PMID:22223745) (PMCID:PMC3307107)

Abstract

Motivation: The observation of positive selection acting on a mutant indicates that the corresponding mutation has some form of functional relevance. Determining the fitness effects of mutations thus has relevance to many interesting biological questions. One means of identifying beneficial mutations in an asexual population is to observe changes in the frequency of marked subsets of the population. We here describe a method to estimate the establishment times and fitnesses of beneficial mutations from neutral marker frequency data. Results: The method accurately reproduces complex marker frequency trajectories. In simulations for which positive selection is close to 5% per generation, we obtain correlations upwards of 0.91 between correct and inferred haplotype establishment times. Where mutation selection coefficients are exponentially distributed, the inferred distribution of haplotype fitnesses is close to being correct. Applied to data from a bacterial evolution experiment, our method reproduces an observed correlation between evolvability and initial fitness defect. Availability: A C++ implementation of the inference tool is available under GNU GPL license (http://www.sanger.ac.uk/resources/software/optimist/).

• Item Type: Articles
• Additional Information: We would like to acknowledge the Welcome Trust for support under grant reference 098051. This research was also supported in part by the National Science Foundation under Grant No. NSF PHY05-51164 during a visit at the Kavli Institute of Theoretical Physics (KITP, Santa Barbara, CA).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Illingworth, Dr Chris
• Authors: Illingworth, C. J.R., and Mustonen, V.
• College/School: College of Medical Veterinary and Life Sciences > School of Infection & Immunity; College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Virus Research
• Journal Name: Bioinformatics
• Publisher: Oxford University Press
• ISSN: 1367-4803
• ISSN (Online): 1460-2059
• Copyright Holders: Copyright © 2012 The Authors
• First Published: First published in Bioinformatics 28(6):831-837
• Publisher Policy: Reproduced under a Creative Commons License