ArticleMicrobial genomics2016
Bayesian codon substitution modelling to identify sources of pathogen evolutionary rate variation.
Article in Microbial genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Detecting Evolutionary Change-Points with Branch-Specific Substitution Models and Shrinkage Priors.ArXiv · 2025Article
- Detecting Evolutionary Change-Points with Branch-Specific Substitution Models and Shrinkage Priors.Research square · 2025Article
- Higher HIV-1 evolutionary rate is associated with cytotoxic T lymphocyte escape mutations in infants.Journal of virology · 2024Article
- Next-generation development and application of codon model in evolution.Frontiers in genetics · 2023Review
- Divergence dating using mixed effects clock modelling: An application to HIV-1.Virus evolution · 2019Article
- Evolution of HIV-1 within untreated individuals and at the population scale in Uganda.PLoS pathogens · 2018Article
- Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10.Virus evolution · 2018Article
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Authors and funding
4 authors.
Funding
Abstract
Phylodynamic reconstructions rely on a measurable molecular footprint of epidemic processes in pathogen genomes. Identifying the factors that govern the tempo and mode by which these processes leave a footprint in pathogen genomes represents an important goal towards understanding infectious disease evolution. Discriminating between synonymous and non-synonymous substitution rates is crucial for testing hypotheses about the sources of evolutionary rate variation. Here, we implement a codon substitution model in a Bayesian statistical framework to estimate absolute rates of synonymous and non-synonymous substitution in unknown evolutionary histories. To demonstrate how this model can provide critical insights into pathogen evolutionary dynamics, we adopt hierarchical phylogenetic modelling with fixed effects and apply it to two viral examples. Using within-host HIV-1 data from patients with different host genetic background and different disease progression rates, we show that viral populations undergo faster absolute synonymous substitution rates in patients with faster disease progression, probably reflecting faster replication rates. We also re-analyse rabies data from different bat species in the Americas to demonstrate that climate predicts absolute synonymous substitution rates, which can be attributed to climate-associated bat activity and viral transmission dynamics. In conclusion, our model to estimate absolute rates of synonymous and non-synonymous substitution can provide a powerful approach to investigate how host ecology can shape the tempo of pathogen evolution.
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