Journal article
A population genetics-phylogenetics approach to inferring natural selection in coding sequences.
- Abstract:
- Through an analysis of polymorphism within and divergence between species, we can hope to learn about the distribution of selective effects of mutations in the genome, changes in the fitness landscape that occur over time, and the location of sites involved in key adaptations that distinguish modern-day species. We introduce a novel method for the analysis of variation in selection pressures within and between species, spatially along the genome and temporally between lineages. We model codon evolution explicitly using a joint population genetics-phylogenetics approach that we developed for the construction of multiallelic models with mutation, selection, and drift. Our approach has the advantage of performing direct inference on coding sequences, inferring ancestral states probabilistically, utilizing allele frequency information, and generalizing to multiple species. We use a Bayesian sliding window model for intragenic variation in selection coefficients that efficiently combines information across sites and captures spatial clustering within the genome. To demonstrate the utility of the method, we infer selective pressures acting in Drosophila melanogaster and D. simulans from polymorphism and divergence data for 100 X-linked coding regions.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 504.4KB, Terms of use)
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- Publisher copy:
- 10.1371/journal.pgen.1002395
Authors
- Publisher:
- Public Library of Science
- Journal:
- PLoS Genetics More from this journal
- Volume:
- 7
- Issue:
- 12
- Article number:
- e1002395
- Publication date:
- 2011-12-01
- DOI:
- EISSN:
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1553-7404
- ISSN:
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1553-7390
- Language:
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English
- Keywords:
- UUID:
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uuid:a0384a57-d89d-49d9-aef3-f9074159716c
- Local pid:
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pubs:216148
- Source identifiers:
-
216148
- Deposit date:
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2012-12-19
Terms of use
- Copyright holder:
- Wilson et al
- Copyright date:
- 2011
- Notes:
- Copyright 2011 Wilson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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