SARS-CoV-2 Omicron Variant Wave in India: Advent, Phylogeny and Evolution

  1. Urvashi B. Singh
  2. Sushanta Deb
  3. Rama Chaudhry
  4. Kiran Bala
  5. Lata Rani
  6. Ritu Gupta
  7. Lata Kumari
  8. Jawed Ahmed
  9. Sudesh Gaurav
  10. Sowjanya Perumalla
  11. Md. Nizam
  12. Anwita Mishra
  13. J. Stephenraj
  14. Jyoti Shukla
  15. Deepika Bhardwaj
  16. Jamshed Nayer
  17. Praveen Aggarwal
  18. Madhulika Kabra
  19. Vineet Ahuja
  20. Subrata Sinha
  21. Randeep Guleria

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Abstract

SARS-CoV-2 evolution has continued to generate variants, responsible for new pandemic waves locally and globally. Varying disease presentation and severity has been ascribed to inherent variant characteristics and vaccine immunity. This study analyzed genomic data from 305 whole genome sequences from SARS-CoV-2 patients before and through the third wave in India. Delta variant was responsible for disease in patients without comorbidity(97%), while Omicron BA.2 caused disease primarily in those with comorbidity(77%). Tissue adaptation studies brought forth higher propensity of Omicron variants to bronchial tissue than lung, contrary to observation in Delta variants from Delhi. Study of codon usage pattern distinguished the prevalent variants, clustering them separately, Omicron BA.2 isolated in February grouped away from December strains, and all BA.2 after December acquired a new mutation S959P in ORF1b (44.3% of BA.2 in the study) indicating ongoing evolution. Loss of critical spike mutations in Omicron BA.2 and gain of immune evasion mutations including G142D, reported in Delta but absent in BA.1, and S371F instead of S371L in BA.1 could possibly be due to evolutionary trade-off and explain very brief period of BA.1 in December 2021, followed by complete replacement by BA.2.

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  1. ScreenIT

    SciScore for 10.1101/2022.05.14.491911: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The fragment sizes of the pooled libraries were assessed with DNA HS Kit (Agilent Technologies, Santa Clara, USA) on Agilent Bioanalyser.
    Agilent Bioanalyser
    suggested: None
    The pooled library was further normalized to 4nM concentration, denatured and loaded onto a Miseq V3 Flow Cell (150 cycles) to carry out paired end sequencing with a read length of 2×75 on MiSeq platform.
    MiSeq
    suggested: (A5-miseq, RRID:SCR_012148)
    The whole-genome sequences were aligned using were aligned using MAFFT v7.475 12, the aligned sequences were further used as input for IQ-TREE program build in nextstrain pipeline and downstream analysis steps were followed to generate the phylogenetic tree.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Generated tree file were visualized using the FigTree program v1.4.4 (available at: http://tree.bio.ed.ac.uk/software/figtree/).
    FigTree
    suggested: (FigTree, RRID:SCR_008515)
    To determine the phylogenetic clade, isolated SARS-CoV-2 genomes were compared against the global Nextstrain database (https://nextstrain.org/ncov/global) using the combined package of Augur, the MAFFT and the IQ-tree software embedded in Nextstrain pipeline.
    IQ-tree
    suggested: (IQ-TREE, RRID:SCR_017254)

    Results from OddPub: Thank you for sharing your data.

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2022.05.14.491911v1 on bioRxiv