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

Authors
  • Varabyou, Ales1, 2
  • Pockrandt, Christopher1, 3
  • Salzberg, Steven L1, 2, 3, 4
  • Pertea, Mihaela1, 2, 3
  • 1 Center for Computational Biology, Johns Hopkins University, Baltimore, MD, 21211, USA.
  • 2 Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA.
  • 3 Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
  • 4 Department of Biostatistics, Johns Hopkins University, Baltimore, MD, 21205, USA.
Type
Published Article
Journal
Genetics
Publisher
The Genetics Society of America
Publication Date
May 13, 2021
Identifiers
DOI: 10.1093/genetics/iyab074
PMID: 33983397
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

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 was 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. © The Author(s) 2021. Published by Oxford University Press on behalf of the Genetics Society of America. All rights reserved. For permissions, please email: [email protected]

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