Genomic surveillance and phylodynamic analyses reveal emergence of novel mutation and co-mutation patterns within SARS-CoV2 variants prevalent in India

  1. Nupur Biswas
  2. Priyanka Mallick
  3. Sujay Krishna Maity
  4. Debaleena Bhowmik
  5. Arpita Ghosh Mitra
  6. Soumen Saha
  7. Aviral Roy
  8. Partha Chakrabarti
  9. Sandip Paul
  10. Saikat Chakrabarti

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Abstract

Emergence of distinct viral clades has been observed in SARS-CoV2 variants across the world and India. Identification of the genomic diversity and the phylodynamic profiles of the prevalent strains of the country are critical to understand the evolution and spread of the variants. We performed whole-genome sequencing of 54 SARS-CoV2 strains collected from COVID-19 patients in Kolkata, West Bengal during August to October 2020. Phylogeographic and phylodynamic analyses were performed using these 54 and other sequences from India and abroad available in GISAID database. Spatio-temporal evolutionary dynamics of the pathogen across various regions and states of India over three different time periods in the year 2020 were analyzed. We estimated the clade dynamics of the Indian strains and compared the clade specific mutations and the co-mutation patterns across states and union territories of India over the time course. We observed that GR, GH and G (GISAID) or 20B and 20A (Nextstrain) clades were the prevalent clades in India during middle and later half of the year 2020. However, frequent mutations and co-mutations observed within the major clades across time periods do not show much overlap, indicating emergence of newer mutations in the viral population prevailing in the country. Further, we explored the possible association of specific mutations and co-mutations with the infection outcomes manifested within the Indian patients.

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    SciScore for 10.1101/2021.03.25.436930: (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
    All samples were then pooled together and ligated with sequencing adapters, purified samples were finally quantified using Qubit 4.0 Fluorometer (Invitrogen), followed by loading of 15ng of pooled barcoded material and sequencing on MinION flow cells.
    MinION
    suggested: (MinION, RRID:SCR_017985)
    All reads from both the platforms were checked for their quality using FastQC (20).
    FastQC
    suggested: (FastQC, RRID:SCR_014583)
    Pilon (25) was used for polishing and generation of final consensus sequences.
    Pilon
    suggested: (Pilon , RRID:SCR_014731)
    Python (version 3.4) codes were used for extracting mutations and further analysis.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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

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  2. Version published to 10.1101/2021.03.25.436930 on bioRxiv