Recombination rate and selection strength in HIV intra-patient evolution.

PLoS Computational Biology
R A Neher, Thomas Leitner

Abstract

The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Yet, little is known about the distribution of selection differentials between individual viruses and the impact of single polymorphisms on viral fitness. Here, we estimate the rate of recombination and the distribution of selection coefficients from time series sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be rho = 1.4+/-0.6 x 10(...Continue Reading

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Datasets Mentioned

BETA
AY449806
AY450055
AY450056
AY450257

Software Mentioned

SciPy
MUSCLE
Matplotlib
NumPy

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