Literature DB >> 33885735

New framework for recombination and adaptive evolution analysis with application to the novel coronavirus SARS-CoV-2.

Yinghan Wang1, Jinfeng Zeng1, Chi Zhang1, Cai Chen1, Zekai Qiu1, Jiali Pang2, Yutian Xu3, Zhiqi Dong1, Yanxin Song4, Weiying Liu1, Peipei Dong1, Litao Sun1, Yao-Qing Chen1, Yuelong Shu1,5, Xiangjun Du1,5.   

Abstract

The 2019 novel coronavirus (SARS-CoV-2) has spread rapidly worldwide and was declared a pandemic by the WHO in March 2020. The evolution of SARS-CoV-2, either in its natural reservoir or in the human population, is still unclear, but this knowledge is essential for effective prevention and control. We propose a new framework to systematically identify recombination events, excluding those due to noise and convergent evolution. We found that several recombination events occurred for SARS-CoV-2 before its transfer to humans, including a more recent recombination event in the receptor-binding domain. We also constructed a probabilistic mutation network to explore the diversity and evolution of SARS-CoV-2 after human infection. Clustering results show that the novel coronavirus has diverged into several clusters that cocirculate over time in various regions and that several mutations across the genome are fixed during transmission throughout the human population, including D614G in the S gene and two accompanied mutations in ORF1ab. Together, these findings suggest that SARS-CoV-2 experienced a complicated evolution process in the natural environment and point to its continuous adaptation to humans. The new framework proposed in this study can help our understanding of and response to other emerging pathogens.
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  SARS-CoV-2; adaptation; evolution; mutation network; recombination

Year:  2021        PMID: 33885735      PMCID: PMC8083196          DOI: 10.1093/bib/bbab107

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


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4.  Clustering and superspreading potential of SARS-CoV-2 infections in Hong Kong.

Authors:  Dillon C Adam; Peng Wu; Jessica Y Wong; Eric H Y Lau; Tim K Tsang; Simon Cauchemez; Gabriel M Leung; Benjamin J Cowling
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5.  MAFFT multiple sequence alignment software version 7: improvements in performance and usability.

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Journal:  Mol Biol Evol       Date:  2013-01-16       Impact factor: 16.240

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Journal:  Nat Microbiol       Date:  2020-07-28       Impact factor: 17.745

7.  KaKs_Calculator 2.0: a toolkit incorporating gamma-series methods and sliding window strategies.

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8.  Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding.

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Journal:  Lancet       Date:  2020-01-30       Impact factor: 79.321

Review 9.  Recombination in viruses: mechanisms, methods of study, and evolutionary consequences.

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  2 in total

1.  A Standardized Framework for Better Understanding of Phenotypic Differences within Bacterial Phyla Based on Protein Domain.

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2.  Molecular Characterization of Infectious Bronchitis Virus Strain HH06 Isolated in a Poultry Farm in Northeastern China.

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  2 in total

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