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virDTL: Viral Recombination Analysis Through Phylogenetic Reconciliation and Its Application to Sarbecoviruses and SARS-CoV-2.
Zaman, Sumaira; Sledzieski, Samuel; Berger, Bonnie; Wu, Yi-Chieh; Bansal, Mukul S.
  • Zaman S; Department of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, USA.
  • Sledzieski S; Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
  • Berger B; Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
  • Wu YC; Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
  • Bansal MS; Department of Computer Science, Harvey Mudd College, Claremont, California, USA.
J Comput Biol ; 2022 Sep 20.
Article in English | MEDLINE | ID: covidwho-2246666
ABSTRACT
An accurate understanding of the evolutionary history of rapidly-evolving viruses like SARS-CoV-2, responsible for the COVID-19 pandemic, is crucial to tracking and preventing the spread of emerging pathogens. However, viruses undergo frequent recombination, which makes it difficult to trace their evolutionary history using traditional phylogenetic methods. In this study, we present a phylogenetic workflow, virDTL, for analyzing viral evolution in the presence of recombination. Our approach leverages reconciliation methods developed for inferring horizontal gene transfer in prokaryotes and, compared to existing tools, is uniquely able to identify ancestral recombinations while accounting for several sources of inference uncertainty, including in the construction of a strain tree, estimation and rooting of gene family trees, and reconciliation itself. We apply this workflow to the Sarbecovirus subgenus and demonstrate how a principled analysis of predicted recombination gives insight into the evolution of SARS-CoV-2. In addition to providing confirming evidence for the horseshoe bat as its zoonotic origin, we identify several ancestral recombination events that merit further study.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal subject: Molecular Biology / Medical Informatics Year: 2022 Document Type: Article Affiliation country: Cmb.2021.0507

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal subject: Molecular Biology / Medical Informatics Year: 2022 Document Type: Article Affiliation country: Cmb.2021.0507