Comprehensive analysis of genomic diversity of SARS-CoV-2 in different geographic regions of India: An endeavour to classify Indian SARS-CoV-2 strains on the basis of co-existing mutations

  1. Rakesh Sarkar
  2. Suvrotoa Mitra
  3. Pritam Chandra
  4. Priyanka Saha
  5. Anindita Banerjee
  6. Shanta Dutta
  7. Mamta Chawla-Sarkar

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Abstract

Accumulation of mutations within the genome is the primary driving force for viral evolution within an endemic setting. This inherent feature often leads to altered virulence, infectivity and transmissibility as well as antigenic shift to escape host immunity, which might compromise the efficacy of vaccines and antiviral drugs. Therefore, we aimed at genome-wide analyses of circulating SARS-CoV-2 viruses for the emergence of novel co-existing mutations and trace their spatial distribution within India. Comprehensive analysis of whole genome sequences of 441 Indian SARS-CoV-2 strains revealed the occurrence of 33 different mutations, 21 being distinctive to India. Emergence of novel mutations were observed in S glycoprotein (7/33), NSP3 (6/33), RdRp/NSP12 (4/33), NSP2 (2/33) and N (2/33). Non-synonymous mutations were found to be 3.4 times more prevalent than synonymous mutations. We classified the Indian isolates into 22 groups based on the co-existing mutations. Phylogenetic analyses revealed that representative strain of each group divided themselves into various sub-clades within their respective clades, based on the presence of unique co-existing mutations. India was dominated by A2a clade (55.60%) followed by A3 (37.38%) and B (7%), but exhibited heterogeneous distribution among various geographical regions. The A2a clade mostly predominated in East India, Western India and Central India, whereas A3 clade prevailed in South and North India. In conclusion, this study highlights the divergent evolution of SARS-CoV-2 strains and co-circulation of multiple clades in India. Monitoring of the emerging mutations would pave ways for vaccine formulation and designing of antiviral drugs.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.14.203463: (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
    MUSCLE v3.8.31 was used for multiple sequence alignment.
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)

    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.

  2. Version published to 10.1101/2020.07.14.203463 on bioRxiv