HIV TRANSMISSION · Population genetic modelling and analysis of HIV transmission histories
FP6 — Marie Curie Actions (Human Resources and Mobility)
- Duration
- 2007-01-01 → 2007-10-31
- EU contribution
- €158,480
- Participants
- 1
- Scheme
- EIF
Lines connect the coordinator with its partners.
Results in brief
Final Activity Report Summary - HIV transmission (Population genetic modelling and analysis of HIV transmission histories)
We developed a model that allowed us to characterise the human immunodeficiency virus (HIV) transmission dynamics. Parameters of the transmission chain model could be inferred using Bayesian statistical inference from genetic data. The model accommodated population size changes between and within infected individuals, thus allowing for an accurate quantification of the genetic bottleneck during transmission. We implemented this model in Bayesian statistical inference software (BEAST), therefore allowing for flexible parameter estimation from serially sampled gene sequences. We also generated an unprecedented amount of viral sequence data from a known HIV transmission chain. In particular, we obtained clonal sequences from multiple samples per patient taken at different time points. This data was analysed using the transmission chain model by the time of the project completion. In addition to the transmission chain work, we developed novel methods to estimate absolute rates of synonymous and non-synonymous substitution rates and identify recombinant sequences.
Data: CORDIS, © European Union
Project objective
We propose to develop a model that unites viral population genetics and phylogenetics to investigate HIV transmission histories. This genealogy-based population genetic model will accommodate for variable population sizes within and between infected hosts, while taking into account phylogenetic relationships between the patients.It is our objective to implement this model in a recently developed, highly flexible Bayesian framework and to validate this method on a comprehensive set of clonal sequences sampled over time from a well-documented HIV transmission chain. We aim to apply our novel approach to at least three well-characterized HIV transmission chains and to extend the application to other rapidly evolving virus populations.This will allow us to estimate the strength and magnitude of the genetic bottleneck associated with viral transmission and to evaluate its impact on evolution at the population level. Thereby, we can address the switching of co-receptor usage within patients and the spread of immune-escape and drug resistance mutations in the HIV infected population. This research will also result in statistical methods that provide a more realistic description of viral evolution with important practical applications in viral epidemiology.
Original text from CORDIS.
Participants
- THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD · OXFORDCoordinatorUnited Kingdom
Links
Data: CORDIS, © European Union