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Identifying predictors of time-inhomogeneous viral evolutionary processes
Filip Bielejec1, Guy Baele1, Allen G Rodrigo2
1Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.
Virus Evolution
|October 25, 2016
Summary
This study introduces a new Bayesian method to analyze viral evolution, revealing significant changes in mutation rates during HIV-1 infections. The findings suggest immune relaxation and increasing replicative fitness influence viral genetic diversity.
Area of Science:
- Virology
- Evolutionary Biology
- Computational Biology
Background:
- Viral evolutionary rates are influenced by replication, selection, and host factors.
- Understanding these dynamics is crucial for managing persistent viral infections.
- Existing models struggle to integrate complex predictors with sparse viral sequence data.
Purpose of the Study:
- To develop a novel Bayesian evolutionary inference method.
- To test the association of clinical, virological, and demographic predictors with viral substitution rates.
- To analyze within-host human immunodeficiency virus type 1 (HIV-1) sequence data.
Main Methods:
- A Bayesian framework integrating multiple predictors.
- Coalescent modeling to infer population size changes.
- Joint analysis of synonymous and non-synonymous substitution rates.
Main Results:
- A significant drop in non-synonymous substitution rates in late-stage HIV-1 infection.
- A gradual increase in synonymous substitution rates during infection.
- Detection of these trends through joint analysis across multiple patients.
Conclusions:
- The developed method effectively links viral evolutionary rates to external factors.
- Observed rate changes align with hypotheses on immune pressure and viral fitness.
- This approach enhances our understanding of viral evolution during persistent infections.
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