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Longitudinal phylogenetic tree of within-host viral evolution from noncontemporaneous samples: a distance-based
Fengrong Ren1, Soichi Ogishima, Hiroshi Tanaka
1Department of Bioinformatics, Medical Research Institute, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo, Tokyo 113-8510, Japan.
Gene
|November 8, 2003
Summary
A new distance-based algorithm reconstructs patient-specific viral evolution from noncontemporaneous samples. This method efficiently estimates neutral and adaptive evolution patterns, aiding in understanding viral dynamics.
Area of Science:
- Virology
- Computational Biology
- Evolutionary Biology
Background:
- Reconstructing within-host viral evolution from noncontemporaneous samples is challenging.
- Previous maximum likelihood methods were computationally intensive and difficult to scale.
- Understanding viral evolution dynamics requires robust phylogenetic reconstruction tools.
Purpose of the Study:
- To develop a novel, computationally efficient algorithm for reconstructing longitudinal phylogenetic trees from noncontemporaneous viral samples.
- To estimate both neutral and adaptive evolution patterns during within-host viral evolution.
- To apply the method to human immunodeficiency virus type 1 (HIV-1) env gene data.
Main Methods:
- A distance-based sequential-linking algorithm utilizing the neighbor-joining method.
- Application to a longitudinal dataset of HIV-1 env gene (V3 region) from a single patient over 7 years.
- Comparison with previous maximum likelihood-based approaches.
Main Results:
- The new algorithm successfully reconstructs longitudinal phylogenetic trees from noncontemporaneous viral samples.
- The method operates within a reasonable calculation time, overcoming limitations of previous approaches.
- The reconstructed tree provides insights into the dynamic process of within-host viral evolution.
Conclusions:
- The distance-based sequential-linking algorithm is an effective and efficient tool for within-host viral phylogenetic reconstruction.
- This revised method facilitates the estimation of viral evolution patterns over time.
- The approach is valuable for studying the evolutionary dynamics of viruses like HIV-1 within patients.
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