Journal
PLOS GENETICS
Volume 8, Issue 7, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pgen.1002764
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Categories
Funding
- National Institutes of Health [AI47745, AI57167, AI74621, GM093939, AI43638]
- DMS [NSF-0714991]
- NIGMS Mathematical Biology Initiative [NSF-0714991]
- University of California San Diego Center for AIDS Research (UCSD CFAR)/NIAID Developmental Award [AI36214]
- Bioinformatics, Statistical Analysis, and Evolutionary Core of the UCSD CFAR
- National Research Foundation of South Africa
- European Commission [SANTE/2007/147-790]
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The imprint of natural selection on protein coding genes is often difficult to identify because selection is frequently transient or episodic, i.e. it affects only a subset of lineages. Existing computational techniques, which are designed to identify sites subject to pervasive selection, may fail to recognize sites where selection is episodic: a large proportion of positively selected sites. We present a mixed effects model of evolution (MEME) that is capable of identifying instances of both episodic and pervasive positive selection at the level of an individual site. Using empirical and simulated data, we demonstrate the superior performance of MEME over older models under a broad range of scenarios. We find that episodic selection is widespread and conclude that the number of sites experiencing positive selection may have been vastly underestimated.
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