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Dellicour S, Bastide P, Rocu P, Fargette D, Hardy OJ, Suchard MA, Guindon S, Lemey P. How fast are viruses spreading in the wild? BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588821. [PMID: 38645268 PMCID: PMC11030353 DOI: 10.1101/2024.04.10.588821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Genomic data collected from viral outbreaks can be exploited to reconstruct the dispersal history of viral lineages in a two-dimensional space using continuous phylogeographic inference. These spatially explicit reconstructions can subsequently be used to estimate dispersal metrics allowing to unveil the dispersal dynamics and evaluate the capacity to spread among hosts. Heterogeneous sampling intensity of genomic sequences can however impact the accuracy of dispersal insights gained through phylogeographic inference. In our study, we implement a simulation framework to evaluate the robustness of three dispersal metrics - a lineage dispersal velocity, a diffusion coefficient, and an isolation-by-distance signal metric - to the sampling effort. Our results reveal that both the diffusion coefficient and isolation-by-distance signal metrics appear to be robust to the number of samples considered for the phylogeographic reconstruction. We then use these two dispersal metrics to compare the dispersal pattern and capacity of various viruses spreading in animal populations. Our comparative analysis reveals a broad range of isolation-by-distance patterns and diffusion coefficients mostly reflecting the dispersal capacity of the main infected host species but also, in some cases, the likely signature of rapid and/or long-distance dispersal events driven by human-mediated movements through animal trade. Overall, our study provides key recommendations for the lineage dispersal metrics to consider in future studies and illustrates their application to compare the spread of viruses in various settings.
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Revell LJ. phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things). PeerJ 2024; 12:e16505. [PMID: 38192598 PMCID: PMC10773453 DOI: 10.7717/peerj.16505] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 10/31/2023] [Indexed: 01/10/2024] Open
Abstract
Phylogenetic comparative methods comprise the general endeavor of using an estimated phylogenetic tree (or set of trees) to make secondary inferences: about trait evolution, diversification dynamics, biogeography, community ecology, and a wide range of other phenomena or processes. Over the past ten years or so, the phytools R package has grown to become an important research tool for phylogenetic comparative analysis. phytools is a diverse contributed R library now consisting of hundreds of different functions covering a variety of methods and purposes in phylogenetic biology. As of the time of writing, phytools included functionality for fitting models of trait evolution, for reconstructing ancestral states, for studying diversification on trees, and for visualizing phylogenies, comparative data, and fitted models, as well numerous other tasks related to phylogenetic biology. Here, I describe some significant features of and recent updates to phytools, while also illustrating several popular workflows of the phytools computational software.
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Affiliation(s)
- Liam J. Revell
- Department of Biology, University of Massachusetts Boston, Boston, MA, USA
- Facultad de Ciencias, Universidad Católica de la Santísima Concepción, Concepción, Chile
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Van Borm S, Dellicour S, Martin DP, Lemey P, Agianniotaki EI, Chondrokouki ED, Vidanovic D, Vaskovic N, Petroviċ T, Laziċ S, Koleci X, Vodica A, Djadjovski I, Krstevski K, Vandenbussche F, Haegeman A, De Clercq K, Mathijs E. Complete genome reconstruction of the global and European regional dispersal history of the lumpy skin disease virus. J Virol 2023; 97:e0139423. [PMID: 37905838 PMCID: PMC10688313 DOI: 10.1128/jvi.01394-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 10/02/2023] [Indexed: 11/02/2023] Open
Abstract
IMPORTANCE Lumpy skin disease virus (LSDV) has a complex epidemiology involving multiple strains, recombination, and vaccination. Its DNA genome provides limited genetic variation to trace outbreaks in space and time. Sequencing of LSDV whole genomes has also been patchy at global and regional scales. Here, we provide the first fine-grained whole genome sequence sampling of a constrained LSDV outbreak (southeastern Europe, 2015-2017), which we analyze along with global publicly available genomes. We formally evaluate the past occurrence of recombination events as well as the temporal signal that is required for calibrating molecular clock models and subsequently conduct a time-calibrated spatially explicit phylogeographic reconstruction. Our study further illustrates the importance of accounting for recombination events before reconstructing global and regional dynamics of DNA viruses. More LSDV whole genomes from endemic areas are needed to obtain a comprehensive understanding of global LSDV dispersal dynamics.
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Affiliation(s)
- Steven Van Borm
- Scientific Directorate Animal Infectious Diseases, Sciensano, Brussels, Belgium
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
- Laboratory for Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Darren P. Martin
- Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Philippe Lemey
- Laboratory for Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Eirini I. Agianniotaki
- National Reference Laboratory for Capripoxviruses, Department of Molecular Diagnostics, FMD, Virological, Rickettsial and Exotic Diseases, Directorate of Athens Veterinary Center, Ministry of Rural Development and Food, Athens, Greece
| | - Eleni D. Chondrokouki
- National Reference Laboratory for Capripoxviruses, Department of Molecular Diagnostics, FMD, Virological, Rickettsial and Exotic Diseases, Directorate of Athens Veterinary Center, Ministry of Rural Development and Food, Athens, Greece
| | - Dejan Vidanovic
- Department for laboratory diagnostics, Veterinary Specialized Institute, Kraljevo, Serbia
| | - Nikola Vaskovic
- Department for laboratory diagnostics, Veterinary Specialized Institute, Kraljevo, Serbia
| | - Tamaš Petroviċ
- Department for Virology, Scientific Veterinary Institute, Novi Sad, Serbia
| | - Sava Laziċ
- Department for Virology, Scientific Veterinary Institute, Novi Sad, Serbia
| | - Xhelil Koleci
- Faculty of Veterinary Medicine, The Agricultural University of Tirana, Tirana, Albania
| | - Ani Vodica
- Animal Health Department, Food Safety and Veterinary Institute, Tirana, Albania
| | - Igor Djadjovski
- Faculty of Veterinary Medicine, Ss. Cyril and Methodius University in Skopje, Skopje, Macedonia
| | - Kiril Krstevski
- Faculty of Veterinary Medicine, Ss. Cyril and Methodius University in Skopje, Skopje, Macedonia
| | - Frank Vandenbussche
- Scientific Directorate Animal Infectious Diseases, Sciensano, Brussels, Belgium
| | - Andy Haegeman
- Scientific Directorate Animal Infectious Diseases, Sciensano, Brussels, Belgium
| | - Kris De Clercq
- Scientific Directorate Animal Infectious Diseases, Sciensano, Brussels, Belgium
| | - Elisabeth Mathijs
- Scientific Directorate Animal Infectious Diseases, Sciensano, Brussels, Belgium
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