Rapid detection of inter-clade recombination in SARS-CoV-2 with Bolotie.


Journal

Genetics
ISSN: 1943-2631
Titre abrégé: Genetics
Pays: United States
ID NLM: 0374636

Informations de publication

Date de publication:
14 07 2021
Historique:
received: 16 02 2021
accepted: 19 04 2021
pubmed: 14 5 2021
medline: 15 12 2021
entrez: 13 5 2021
Statut: ppublish

Résumé

The ability to detect recombination in pathogen genomes is crucial to the accuracy of phylogenetic analysis and consequently to forecasting the spread of infectious diseases and to developing therapeutics and public health policies. However, in case of the SARS-CoV-2, the low divergence of near-identical genomes sequenced over a short period of time makes conventional analysis infeasible. Using a novel method, we identified 225 anomalous SARS-CoV-2 genomes of likely recombinant origins out of the first 87,695 genomes to be released, several of which have persisted in the population. Bolotie is specifically designed to perform a rapid search for inter-clade recombination events over extremely large datasets, facilitating analysis of novel isolates in seconds. In cases where raw sequencing data were available, we were able to rule out the possibility that these samples represented co-infections by analyzing the underlying sequence reads. The Bolotie software and other data from our study are available at https://github.com/salzberg-lab/bolotie.

Identifiants

pubmed: 33983397
pii: 6275222
doi: 10.1093/genetics/iyab074
pmc: PMC8194586
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NHGRI NIH HHS
ID : R01 HG006677
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM130151
Pays : United States
Organisme : Fast Grants
Organisme : US National Institutes of Health
ID : R01-AI141009

Commentaires et corrections

Type : UpdateOf

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Auteurs

Ales Varabyou (A)

Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21211, USA.
Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.

Christopher Pockrandt (C)

Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21211, USA.
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.

Steven L Salzberg (SL)

Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21211, USA.
Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA.

Mihaela Pertea (M)

Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21211, USA.
Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.

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Classifications MeSH