MBE Advance Access originally published online on February 1, 2007
Molecular Biology and Evolution 2007 24(4):1025-1031; doi:10.1093/molbev/msm021
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© 2007 The Authors.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Research Articles |
A Model of Directional Selection Applied to the Evolution of Drug Resistance in HIV-1
* Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Rondebosch, South Africa
South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
AIDS Virus Research Unit, National Institute for Communicable Diseases, Johannesburg, South Africa
Dept of Biochemistry & Molecular Biology, University College London, London, United Kingdom
| School of Medicine, Johns Hopkins University, Baltimore, Maryland
¶ Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa
E-mail: cathal.seoighe{at}uct.ac.za.
Accepted for publication January 26, 2007.
Understanding how pathogens acquire resistance to drugs is important for the design of treatment strategies, particularly for rapidly evolving viruses such as HIV-1. Drug treatment can exert strong selective pressures and sites within targeted genes that confer resistance frequently evolve far more rapidly than the neutral rate. Rapid evolution at sites that confer resistance to drugs can be used to help elucidate the mechanisms of evolution of drug resistance and to discover or corroborate novel resistance mutations. We have implemented standard maximum likelihood methods that are used to detect diversifying selection and adapted them for use with serially sampled reverse transcriptase (RT) coding sequences isolated from a group of 300 HIV-1 subtype C–infected women before and after single-dose nevirapine (sdNVP) to prevent mother-to-child transmission. We have also extended the standard models of codon evolution for application to the detection of directional selection. Through simulation, we show that the directional selection model can provide a substantial improvement in sensitivity over models of diversifying selection. Five of the sites within the RT gene that are known to harbor mutations that confer resistance to nevirapine (NVP) strongly supported the directional selection model. There was no evidence that other mutations that are known to confer NVP resistance were selected in this cohort. The directional selection model, applied to serially sampled sequences, also had more power than the diversifying selection model to detect selection resulting from factors other than drug resistance. Because inference of selection from serial samples is unlikely to be adversely affected by recombination, the methods we describe may have general applicability to the analysis of positive selection affecting recombining coding sequences when serially sampled data are available.
Key Words: HIV-1 • nevirapine • drug resistance • positive selection
Edward Holmes, Associate Editor
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