Modeling the velocity of evolving lineages and predicting dispersal patterns

Accurate estimation of the dispersal velocity or speed of evolving organisms is no mean feat. In fact, existing probabilistic models in phylogeography or spatial population genetics generally do not provide an adequate framework to define velocity in a relevant manner. For instance, the very concept of instantaneous speed simply does not exist under one of the most popular approaches that models the evolution of spatial coordinates as Brownian trajectories running along a phylogeny. Here, we introduce a family of models-the so-called Phylogenetic Integrated Velocity (PIV) models-that use Gaussian processes to explicitly model the velocity of evolving lineages instead of focusing on the fluctuation of spatial coordinates over time. We describe the properties of these models and show an increased accuracy of velocity estimates compared to previous approaches. Analyses of West Nile virus data in the United States indicate that PIV models provide sensible predictions of the dispersal of evolving pathogens at a one-year time horizon. These results demonstrate the feasibility and relevance of predictive phylogeography in monitoring epidemics in time and space.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2024-11-15
DOI
https://doi.org/10.1073/pnas.2411582121
Citations
6
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
1.40

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article

Modeling the velocity of evolving lineages and predicting dispersal patterns

Johannes Wirtz, Philippe Lemey, Marc A. Suchard, Gabriel W. Hassler et al.
6 citations
Proceedings of the National Academy of Sciences
Genomics and Phylogenetic Studies
1.40
article

Modeling the velocity of evolving lineages and predicting dispersal patterns

Johannes Wirtz, Philippe Lemey, Marc A. Suchard, Gabriel W. Hassler, Denis Fargette, Simon Dellicour, François Chevenet, Stéphane Guindon, Paul Bastide, Pauline Rocu
article en
6 citations

Abstract

Accurate estimation of the dispersal velocity or speed of evolving organisms is no mean feat. In fact, existing probabilistic models in phylogeography or spatial population genetics generally do not provide an adequate framework to define velocity in a relevant manner. For instance, the very concept of instantaneous speed simply does not exist under one of the most popular approaches that models the evolution of spatial coordinates as Brownian trajectories running along a phylogeny. Here, we introduce a family of models-the so-called Phylogenetic Integrated Velocity (PIV) models-that use Gaussian processes to explicitly model the velocity of evolving lineages instead of focusing on the fluctuation of spatial coordinates over time. We describe the properties of these models and show an increased accuracy of velocity estimates compared to previous approaches. Analyses of West Nile virus data in the United States indicate that PIV models provide sensible predictions of the dispersal of evolving pathogens at a one-year time horizon. These results demonstrate the feasibility and relevance of predictive phylogeography in monitoring epidemics in time and space.

Proceedings of the National Academy of SciencesVol. 121(47)
Centre National de la Recherche Scientifique (FR), RAND Corporation (US), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR), Université Libre de Bruxelles (BE), École Pratique des Hautes Études (FR), University of California, Los Angeles (US), Université de Montpellier (FR), Université Paris Cité (FR), Rega Institute for Medical Research (BE), Maladies Infectieuses et Vecteurs: Écologie, Génétique, Évolution et Contrôle (FR), Centre d'Écologie Fonctionnelle et Évolutive (FR), Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier (FR), Institut de Recherche pour le Développement (FR), Mathématiques Appliquées à Paris 5 (FR), KU Leuven (BE)
Horizon 2020 Framework Programme, National Institute of Allergy and Infectious Diseases
Good health and well-being
Openalex Percentile: Top 18%
Genomics and Phylogenetic Studies
1.40
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