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

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 mutation...

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Detalles Bibliográficos
Autores principales: Illingworth, Christopher J. R., Mustonen, Ville
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3307107/
https://www.ncbi.nlm.nih.gov/pubmed/22223745
http://dx.doi.org/10.1093/bioinformatics/btr722
Descripción
Sumario: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/). Contact: vm5@sanger.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.