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MBE Advance Access published online on May 29, 2008
Molecular Biology and Evolution, doi:10.1093/molbev/msn123
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© The Author 2008. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

Research Article

A Maximum Likelihood Method for Detecting Directional Evolution in Protein Sequences and its Application to Influenza A Virus

Sergei L. Kosakovsky Pond1, Art F.Y. Poon1, Andrew J. Leigh Brown2 and Simon D.W. Frost1

1 Department of Pathology, University of California San Diego, La Jolla, California, 92093
2 Institute for Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, Scotland

* Corresponding author, Sergei L Kosakovsky Pond, Antiviral Research Center, 150 W Washington St, Ste 100, San Diego, CA, 92103, USA, Tel: +1-619-543-8899, FAX: +1-619-543-5094, e-mail: spond{at}ucsd.edu

Received for publication February 21, 2008. Revision received May 8, 2008. Accepted for publication May 10, 2008.

We develop a model-based phylogenetic maximum likelihood test for evidence of preferential substitution towards a given residue at individual positions of a protein alignment – Directional Evolution of Protein Sequences (DEPS). DEPS can identify both the target residue and sites evolving towards it, help detect selective sweeps and frequency dependent selection – scenarios that confound most existing tests for selection, and achieves good power and accuracy on simulated data. We applied DEPS to alignments representing different genomic regions of Influenza A virus (IAV), sampled from avian hosts (H5N1 serotype) and human hosts (H3N2 serotype) and identified multiple directionally evolving sites in 5/8 genomic segments of H5N1 and H3N2 IAV. We propose a simple descriptive classification of directionally evolving sites into 5 groups based on the temporal distribution of residue frequencies, and document known functional correlates, such as immune escape or host adaptation.

Key Words: Directional selection • evolution of influenza • maximum likelihood • episodic selection


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