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Treffer: A Relaxed Directional Random Walk Model for Phylogenetic Trait Evolution.

Title:
A Relaxed Directional Random Walk Model for Phylogenetic Trait Evolution.
Authors:
Gill MS; Department of Statistics, Columbia University, New York, NY 10027, USA., Tung Ho LS; Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA., Baele G; Department of Microbiology and Immunology, Rega Institute, KU Leuven, Minderbroedersstaat 10, 3000, Leuven, Belgium., Lemey P; Department of Microbiology and Immunology, Rega Institute, KU Leuven, Minderbroedersstaat 10, 3000, Leuven, Belgium., Suchard MA; Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA.; Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90095, USA.; Department of Human Genetics, David Geffen School of Medicine at UCLA, Universtiy of California, Los Angeles, CA, USA.
Source:
Systematic biology [Syst Biol] 2017 May 01; Vol. 66 (3), pp. 299-319.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Oxford University Press Country of Publication: England NLM ID: 9302532 Publication Model: Print Cited Medium: Internet ISSN: 1076-836X (Electronic) Linking ISSN: 10635157 NLM ISO Abbreviation: Syst Biol Subsets: MEDLINE
Imprint Name(s):
Publication: 2009- : Oxford : Oxford University Press
Original Publication: Washington, D.C., USA : Society of Systematic Biologists, [1992-
MeSH Terms:
Models, Biological* , Phylogeny*, Classification/*methods, Africa ; Bayes Theorem ; HIV Infections/epidemiology ; HIV Infections/immunology ; HIV Infections/virology ; HIV-1/classification ; HIV-1/immunology ; Humans ; Phenotype
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Grant Information:
R01 AI107034 United States AI NIAID NIH HHS; T32 AI007370 United States AI NIAID NIH HHS; R01 HG006139 United States HG NHGRI NIH HHS; R01 LM011247 United States LM NLM NIH HHS; 260864 International ERC_ European Research Council
Entry Date(s):
Date Created: 20161101 Date Completed: 20180129 Latest Revision: 20250530
Update Code:
20250530
PubMed Central ID:
PMC6075548
DOI:
10.1093/sysbio/syw093
PMID:
27798403
Database:
MEDLINE

Weitere Informationen

Understanding the processes that give rise to quantitative measurements associated with molecular sequence data remains an important issue in statistical phylogenetics. Examples of such measurements include geographic coordinates in the context of phylogeography and phenotypic traits in the context of comparative studies. A popular approach is to model the evolution of continuously varying traits as a Brownian diffusion process acting on a phylogenetic tree. However, standard Brownian diffusion is quite restrictive and may not accurately characterize certain trait evolutionary processes. Here, we relax one of the major restrictions of standard Brownian diffusion by incorporating a nontrivial estimable mean into the process. We introduce a relaxed directional random walk (RDRW) model for the evolution of multivariate continuously varying traits along a phylogenetic tree. Notably, the RDRW model accommodates branch-specific variation of directional trends while preserving model identifiability. Furthermore, our development of a computationally efficient dynamic programming approach to compute the data likelihood enables scaling of our method to large data sets frequently encountered in phylogenetic comparative studies and viral evolution. We implement the RDRW model in a Bayesian inference framework to simultaneously reconstruct the evolutionary histories of molecular sequence data and associated multivariate continuous trait data, and provide tools to visualize evolutionary reconstructions. We demonstrate the performance of our model on synthetic data, and we illustrate its utility in two viral examples. First, we examine the spatiotemporal spread of HIV-1 in central Africa and show that the RDRW model uncovers a clearer, more detailed picture of the dynamics of viral dispersal than standard Brownian diffusion. Second, we study antigenic evolution in the context of HIV-1 resistance to three broadly neutralizing antibodies. Our analysis reveals evidence of a continuous drift at the HIV-1 population level towards enhanced resistance to neutralization by the VRC01 monoclonal antibody over the course of the epidemic. [Brownian Motion; Diffusion Processes; Phylodynamics; Phylogenetics; Phylogeography; Trait Evolution.].
(© The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)