Emergence and expansion of highly infectious spike protein D614G mutant SARS-CoV-2 in central India

  1. Shashi Sharma
  2. Paban Kumar Dash
  3. Sushil Kumar Sharma
  4. Ambuj Srivastava
  5. Jyoti S. Kumar
  6. B. S. Karothia
  7. K. T. Chelvam
  8. Sandeep Singh
  9. Abhaydeep Gupta
  10. Ram Govind Yadav
  11. Ruchi Yadav
  12. T. S. Greeshma
  13. Pramod Kumar Kushwaha
  14. Ravi Bhushan Kumar
  15. D. P. Nagar
  16. Manvendra Nandan
  17. Subodh Kumar
  18. Duraipandian Thavaselvam
  19. Devendra Kumar Dubey

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Abstract

COVID-19 has emerged as global pandemic with largest damage to the public health, economy and human psyche.The genome sequence data obtained during the ongoing pandemic are valuable to understand the virus evolutionary patterns and spread across the globe. Increased availability of genome information of circulating SARS-CoV-2 strains in India will enable the scientific community to understand the emergence of new variants and their impact on human health. The first case of COVID-19 was detected in Chambal region of Madhya Pradesh state in mid of March 2020 followed by multiple introduction events and expansion of cases within next three months. More than 5000 COVID-19 suspected samples referred to Defence Research and Development Establishment, Gwalior, Madhya Pradesh were analyzed during the nation -wide lockdown and unlock period. A total of 136 cases were found positive over a span of three months that included virus introduction to the region and its further spread. Whole genome sequences employing Oxford nanopore technology were generated for 26 SARS-CoV-2 circulating in 10 different districts in Madhya Pradesh state of India. This period witnessed index cases with multiple travel histories responsible for introduction of COVID-19 followed by remarkable expansion of virus. The genome wide substitutions including in important viral proteins were identified. The detailed phylogenetic analysis revealed the circulating SARS-CoV-2 clustered in multiple clades including A2a, A4 and B. The cluster-wise segregation was observed, suggesting multiple introduction links and subsequent evolution of virus in the region. This is the first comprehensive whole genome sequence analysis from central India, which revealed the emergence and evolution of SARS-CoV-2 during thenation-wide lockdown and unlock.

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  1. Version published to 10.1038/s41598-021-95822-w
  2. ScreenIT

    SciScore for 10.1101/2020.09.15.297846: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The Arctic pipeline uses processed reads to align against the available SARS CoV-2 reference genome.
    Arctic
    suggested: (ARCTIC, RRID:SCR_005989)
    Further, variant calling and consensus sequence generation was done using Nanopolish.
    Nanopolish
    suggested: (Nanopolish, RRID:SCR_016157)
    The good quality variants were used for annotation using snpEff tool.
    snpEff
    suggested: (SnpEff, RRID:SCR_005191)
    Genome analysis of SARS-CoV-2: The nucleotide sequences of representative SARS-CoV-2 were retrieved from Global Initiative on Sharing All Influenza Data (GISAID) and NCBI GenBank, edited and analysed employing EditSeq and MegAlign modules of lasergene5 software package (DNASTAR Inc, USA).
    EditSeq
    suggested: None
    Multiple sequence alignment was carried out using MUSCLE alignment method in Bioedit software module.
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    Bioedit
    suggested: (BioEdit, RRID:SCR_007361)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.09.15.297846v2 on bioRxiv
  4. Version published to 10.1101/2020.09.15.297846v1 on bioRxiv