Using human immunodeficiency virus type 1 sequences to infer historical features of the acquired immune deficiency syndrome epidemic and human immunodeficiency virus evolution

Author:

Yusim Karina12,Peeters Martine3,Pybus Oliver G.4,Bhattacharya Tanmoy1,Delaporte Eric5,Mulanga Claire3,Muldoon Mark6,Theiler James1,Korber Bette12

Affiliation:

1. Los Alamos National Laboratory, Los Alamos, PO Box 1663, MM 87545, USA

2. Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, MM 87501, USA

3. Laboratoire Retrovirus, Institut de Recherche pour le Developpement, 911 avenue AgroPolis, BP 5045, 34032, Montpdlier, France

4. Department of Zoology, University of Oxford, South Parks Road, Oxford 0X1 3PS, UK

5. Centre Hospitaller Universitaire (CHU), Gui de Chauliac, 2 avenue Bertin Sans, 34295 Montpdlier, France

6. University of Manchester Institute of Science and Technology, PO Box 88, Manchester M60 1QD, UK

Abstract

In earlier work, human immunodeficiency virus type 1 (HIV–1) sequences were analysed to estimate the timing of the ancestral sequence of the main group of HIV–1, the virus that is responsible for the acquired immune deficiency syndrome pandemic, yielding a best estimate of 1931 (95% confidence interval of 1915–1941). That work will be briefly reviewed, outlining how phylogenetic tools were extended to incorporate improved evolutionary models, how the molecular clock model was adapted to incorporate variable periods of latency, and how the approach was validated by correctly estimating the timing of two historically documented dates. The advantages, limitations, and assumptions of the approach will be summarized, with particular consideration of the implications of branch length uncertainty and recombination. We have recently undertaken new phylogenetic analysis of an extremely diverse set of human immunodeficiency virus envelope sequences from the Democratic Republic of the Congo (the DRC, formerly Zaire). This analysis both corroborates and extends the conclusions of our original study. Coalescent methods were used to infer the demographic history of the HIV–1 epidemic in the DRC, and the results suggest an increase in the exponential growth rate of the infected population through time.

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

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