Skip Navigation



MBE Advance Access published online on February 1, 2007

Molecular Biology and Evolution, doi:10.1093/molbev/msm021
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrowOA All Versions of this Article:
24/4/1025    most recent
msm021v2
msm021v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Google Scholar
Right arrow Articles by Seoighe, C.
Right arrow Articles by Hide, W.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Seoighe, C.
Right arrow Articles by Hide, W.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© 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 Article

A Model of Directional Selection Applied to the Evolution of Drug Resistance in HIV-1

Cathal Seoighe*,1, Farahnaz Ketwaroo2, Visva Pillay3, Konrad Scheffler1, Natasha Wood1, Rodger Duffet1, Marketa Zvelebil6, Neil Martinson4,5, James McIntyre5, Lynn Morris3 and Winston Hide2

1 Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Rondebosch 7700, South Africa
2 South African National Bioinformatics Institute, University of the Western Cape, Bellville 7535, South Africa
3 AIDS Virus Research Unit, National Institute for Communicable Diseases, Johannesburg, South Africa
4 School of Medicine, Johns Hopkins University, USA
5 Perinatal HIV Research Unit, University of the Witwatersrand, South Africa
6 Dept of Biochemistry & Molecular Biology, University College London, UK

* corresponding author cathal.seoighe{at}uct.ac.za, phone: +27 21 406 6837, fax: +27 21 650 5192

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 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


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
Mol Biol EvolHome page
M. Anisimova and C. Kosiol
Investigating Protein-Coding Sequence Evolution with Probabilistic Codon Substitution Models
Mol. Biol. Evol., February 1, 2009; 26(2): 255 - 271.
[Abstract] [Full Text] [PDF]


Home page
Brief BioinformHome page
W. Delport, K. Scheffler, and C. Seoighe
Models of coding sequence evolution
Brief Bioinform, January 1, 2009; 10(1): 97 - 109.
[Abstract] [Full Text] [PDF]


Home page
Proc R Soc BHome page
S. Kryazhimskiy, G. A Bazykin, J. Plotkin, and J. Dushoff
Directionality in the evolution of influenza A haemagglutinin
Proc R Soc B, November 7, 2008; 275(1650): 2455 - 2464.
[Abstract] [Full Text] [PDF]


Home page
Mol Biol EvolHome page
S. L. Kosakovsky Pond, A. F.Y. Poon, A. J. Leigh Brown, and S. D.W. Frost
A Maximum Likelihood Method for Detecting Directional Evolution in Protein Sequences and Its Application to Influenza A Virus
Mol. Biol. Evol., September 1, 2008; 25(9): 1809 - 1824.
[Abstract] [Full Text] [PDF]



Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.