title: Identifying predictors of time-inhomogeneous viral evolutionary processes.
abstract: Various factors determine the rate at which mutations are generated and fixed in viral genomes. Viral evolutionary rates may vary over the course of a single persistent infection and can reflect changes in replication rates and selective dynamics. Dedicated statistical inference approaches are required to understand how the complex interplay of these processes shapes the genetic diversity and divergence in viral populations. Although evolutionary models accommodating a high degree of complexity can now be formalized, adequately informing these models by potentially sparse data, and assessing the association of the resulting estimates with external predictors, remains a major challenge. In this article, we present a novel Bayesian evolutionary inference method, which integrates multiple potential predictors and tests their association with variation in the absolute rates of synonymous and non-synonymous substitutions along the evolutionary history. We consider clinical and virological measures as predictors, but also changes in population size trajectories that are simultaneously inferred using coalescent modelling. We demonstrate the potential of our method in an application to within-host HIV-1 sequence data sampled throughout the infection of multiple patients. While analyses of individual patient populations lack statistical power, we detect significant evidence for an abrupt drop in non-synonymous rates in late stage infection and a more gradual increase in synonymous rates over the course of infection in a joint analysis across all patients. The former is predicted by the immune relaxation hypothesis while the latter may be in line with increasing replicative fitness during the asymptomatic stage.
authors: Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.
authors: Filip
authors: F
authors: Bielejec
authors: Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.
authors: Guy
authors: G
authors: Baele
authors: Research School of Biology, Australian National University, Canberra, ACT, Australia.
authors: Allen G
authors: AG
authors: Rodrigo
authors: Department of Biomathematics and Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90095, USA; Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA.
authors: Marc A
authors: MA
authors: Suchard
authors: Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium.
authors: Philippe
authors: P
authors: Lemey
keywords: Bayesian phylogenetics; codon substitution models; epoch models; evolutionary rate; generalized linear models; pathogen; virus evolution