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Genetics, Vol. 167, 1059-1068, July 2004, Copyright © 2004
doi:10.1534/genetics.104.026666
The Molecular Population Genetics of HIV-1 Group O
Philippe Lemey*,1,
Oliver G. Pybus
,
Andrew Rambaut,
Alexei J. Drummond,
David L. Robertson
,
Pierre Roques
,**,
Michael Worobey and
Anne-Mieke Vandamme*
* Rega Institute for Medical Research, KULeuven, B-3000 Leuven, Belgium
Department of Zoology, University of Oxford, Oxford OX1 3PS, United Kingdom
School of Biological Sciences, University of Manchester, Manchester M13 9PT, United Kingdom
Service de Neurovirologie, CEA, 92260 Fontenay-aux-Roses, France
** Service de Neurovirologie, CIRMF, BP 769 Franceville, Gabon
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson Arizona 85721
1 Corresponding author: Rega Institute for Medical Research, Minderbroedersstraat 10, B-3000 Leuven, Belgium.
E-mail: philippe.lemey{at}uz.kuleuven.ac.be
HIV-1 group O originated through cross-species transmission of SIV from chimpanzees to humans and has established a relatively low prevalence in Central Africa. Here, we infer the population genetics and epidemic history of HIV-1 group O from viral gene sequence data and evaluate the effect of variable evolutionary rates and recombination on our estimates. First, model selection tools were used to specify suitable evolutionary and coalescent models for HIV group O. Second, divergence times and population genetic parameters were estimated in a Bayesian framework using Markov chain Monte Carlo sampling, under both strict and relaxed molecular clock methods. Our results date the origin of the group O radiation to around 1920 (1890–1940), a time frame similar to that estimated for HIV-1 group M. However, group O infections, which remain almost wholly restricted to Cameroon, show a slower rate of exponential growth during the twentieth century, explaining their lower current prevalence. To explore the effect of recombination, the Bayesian framework is extended to incorporate multiple unlinked loci. Although recombination can bias estimates of the time to the most recent common ancestor, this effect does not appear to be important for HIV-1 group O. In addition, we show that evolutionary rate estimates for different HIV genes accurately reflect differential selective constraints along the HIV genome.
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