The evolutionary rate dynamically tracks changes in HIV-1 epidemics: Application of a simple method for optimizing the evolutionary rate in phylogenetic trees with longitudinal data

Abstract Large-sequence datasets provide an opportunity to investigate the dynamics of pathogen epidemics. Thus, a fast method to estimate the evolutionary rate from large and numerous phylogenetic trees becomes necessary. Based on minimizing tip height variances, we optimize the root in a given phy...

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Bibliographic Details
Published in:Epidemics 2009-12, Vol.1 (4), p.230-239
Main Authors: Maljkovic Berry, Irina, Athreya, Gayathri, Kothari, Moulik, Daniels, Marcus, Bruno, William J, Korber, Bette, Kuiken, Carla, Ribeiro, Ruy M, Leitner, Thomas
Format: Article
Language:English
Subjects:
Antiretroviral Therapy, Highly Active
Computer Simulation
Ethiopia - epidemiology
Europe - epidemiology
Evolution, Molecular
HIV Infections - drug therapy
HIV Infections - epidemiology
HIV Infections - genetics
HIV-1 - classification
HIV-1 - genetics
Humans
Infectious Disease
Internal Medicine
Longitudinal Studies
Medicin och hälsovetenskap
Molecular epidemiology
Monte Carlo Method
Phylogeny
TreeRate
United States - epidemiology
Viral evolution
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Summary:Abstract Large-sequence datasets provide an opportunity to investigate the dynamics of pathogen epidemics. Thus, a fast method to estimate the evolutionary rate from large and numerous phylogenetic trees becomes necessary. Based on minimizing tip height variances, we optimize the root in a given phylogenetic tree to estimate the most homogenous evolutionary rate between samples from at least two different time points. Simulations showed that the method had no bias in the estimation of evolutionary rates and that it was robust to tree rooting and topological errors. We show that the evolutionary rates of HIV-1 subtype B and C epidemics have changed over time, with the rate of evolution inversely correlated to the rate of virus spread. For subtype B, the evolutionary rate slowed down and tracked the start of the HAART era in 1996. Subtype C in Ethiopia showed an increase in the evolutionary rate when the prevalence increase markedly slowed down in 1995. Thus, we show that the evolutionary rate of HIV-1 on the population level dynamically tracks epidemic events.
ISSN:1755-4365
1878-0067
1878-0067
DOI:10.1016/j.epidem.2009.10.003