Continued Emergence and Evolution of Omicron in South Africa: New BA.4 and BA.5 lineages

  1. Houriiyah Tegally
  2. Monika Moir
  3. Josie Everatt
  4. Marta Giovanetti
  5. Cathrine Scheepers
  6. Eduan Wilkinson
  7. Kathleen Subramoney
  8. Sikhulile Moyo
  9. Daniel G. Amoako
  10. Cheryl Baxter
  11. Christian L. Althaus
  12. Ugochukwu J. Anyaneji
  13. Dikeledi Kekana
  14. Raquel Viana
  15. Jennifer Giandhari
  16. Richard J. Lessells
  17. Tongai Maponga
  18. Dorcas Maruapula
  19. Wonderful Choga
  20. Mogomotsi Matshaba
  21. Simnikiwe Mayaphi
  22. Nokuzola Mbhele
  23. Mpaphi B. Mbulawa
  24. Nokukhanya Msomi
  25. NGS-SA consortium
  26. Yeshnee Naidoo
  27. Sureshnee Pillay
  28. Tomasz Janusz Sanko
  29. James E. San
  30. Lesley Scott
  31. Lavanya Singh
  32. Nonkululeko A. Magini
  33. Pamela Smith-Lawrence
  34. Wendy Stevens
  35. Graeme Dor
  36. Derek Tshiabuila
  37. Nicole Wolter
  38. Wolfgang Preiser
  39. Florette K. Treurnicht
  40. Marietjie Venter
  41. Michaela Davids
  42. Georginah Chiloane
  43. Adriano Mendes
  44. Caitlyn McIntyre
  45. Aine O’Toole
  46. Christopher Ruis
  47. Thomas P. Peacock
  48. Cornelius Roemer
  49. Carolyn Williamson
  50. Oliver G. Pybus
  51. Jinal Bhiman
  52. Allison Glass
  53. Darren P. Martin
  54. Andrew Rambaut
  55. Simani Gaseitsiwe
  56. Anne von Gottberg
  57. Tulio de Oliveira

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Abstract

South Africa’s fourth COVID-19 wave was driven predominantly by three lineages (BA.1, BA.2 and BA.3) of the SARS-CoV-2 Omicron variant of concern. We have now identified two new lineages, BA.4 and BA.5. The spike proteins of BA.4 and BA.5 are identical, and comparable to BA.2 except for the addition of 69-70del, L452R, F486V and the wild type amino acid at Q493. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure with the TaqPath™ COVID-19 qPCR assay. BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa from the first week of April 2022 onwards. Using a multinomial logistic regression model, we estimate growth advantages for BA.4 and BA.5 of 0.08 (95% CI: 0.07 - 0.09) and 0.12 (95% CI: 0.09 - 0.15) per day respectively over BA.2 in South Africa.

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  1. ScreenIT

    SciScore for 10.1101/2022.05.01.22274406: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    A GridION X5 or MinION sequencing run was initiated using MinKNOW software with the base-call setting switched off.
    MinION
    suggested: (MinION, RRID:SCR_017985)
    MinKNOW
    suggested: None
    TRINITY was used for de novo assembly and the Iterative Refinement Meta-Assembler (IRMA) was used for genome assisted assembly as well as FastQC for quality checks.
    FastQC
    suggested: (FastQC, RRID:SCR_014583)
    For Illumina assembly, the GATK HaploTypeCaller --min-pruning 0 argument was added to increase mutation calling sensitivity near sequencing gaps.
    GATK
    suggested: (GATK, RRID:SCR_001876)
    bam files using Geneious v.
    Geneious
    suggested: (Geneious, RRID:SCR_010519)
    Raw reads from the Illumina COVIDSeq protocol were assembled using the Exatype NGS SARS-CoV-2 pipeline v.
    SARS-CoV-2
    suggested: (Active Motif Cat# 91351, RRID:AB_2847848)
    To resolve this, the raw reads from the IonTorrent platform were assembled using the SARSCoV2 RECoVERY (Reconstruction of Coronavirus Genomes & Rapid Analysis) pipeline implemented in the Galaxy instance ARIES (https://aries.iss.it).
    Galaxy
    suggested: (Galaxy, RRID:SCR_006281)
    These consensus sequences were manually inspected and polished using Aliview v.
    Aliview
    suggested: (AliView, RRID:SCR_002780)
    The pipeline contains several Python scripts that manage the analysis workflow.
    Python
    suggested: (IPython, RRID:SCR_001658)
    We extracted these clusters and constructed a preliminary maximum-likelihood tree with a subset of BA.2 sequences (n=52) in IQ-tree.
    IQ-tree
    suggested: (IQ-TREE, RRID:SCR_017254)
    We inspected this maximum-likelihood tree in TempEst v.
    TempEst
    suggested: (TempEst, RRID:SCR_017304)
    We then estimated time-calibrated phylogenies using the Bayesian software package BEAST v.1.10.432.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)
    As described in ‘Phylogenetic analysis’, MCMC chains were run in duplicate for 10 million generations and sampled every 1,000 steps, with convergence assessed using Tracer v.1.7.1.
    Tracer
    suggested: (Tracer, RRID:SCR_019121)

    Results from OddPub: Thank you for sharing your code and 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.
    • 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.

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

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  2. Version published to 10.1101/2022.05.01.22274406v1 on medRxiv