Altered Subgenomic RNA Expression in SARS-CoV-2 B.1.1.7 Infections

  1. Matthew D Parker
  2. Benjamin B. Lindsey
  3. Dhruv R Shah
  4. Sharon Hsu
  5. Alexander J Keeley
  6. David G Partridge
  7. Shay Leary
  8. Alison Cope
  9. Amy State
  10. Katie Johnson
  11. Nasar Ali
  12. Rasha Raghei
  13. Joe Heffer
  14. Nikki Smith
  15. Peijun Zhang
  16. Marta Gallis
  17. Stavroula F Louka
  18. Hailey R Hornsby
  19. Max Whiteley
  20. Benjamin H Foulkes
  21. Stella Christou
  22. Paige Wolverson
  23. Manoj Pohare
  24. Samantha E Hansford
  25. Luke R Green
  26. Cariad Evans
  27. Mohammad Raza
  28. Dennis Wang
  29. Silvana Gaudieri
  30. Simon Mallal
  31. The COVID-19 Genomics UK (COG-UK) consortium
  32. Thushan I. de Silva

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

SARS-CoV-2 lineage B.1.1.7 viruses are more transmissible, may lead to greater clinical severity, and result in modest reductions in antibody neutralization. subgenomic RNA (sgRNA) is produced by discontinuous transcription of the SARS-CoV-2 genome and is a crucial step in the SARS-CoV-2 life cycle. Applying our tool (periscope) to ARTIC Network Oxford Nanopore genomic sequencing data from 4400 SARS-CoV-2 positive clinical samples, we show that normalised sgRNA expression profiles are significantly increased in B.1.1.7 infections (n=879). This increase is seen over the previous dominant circulating lineage in the UK, B.1.177 (n=943), which is independent of genomic reads, E gene cycle threshold and days since symptom onset at sampling. A noncanonical sgRNA which could represent ORF9b is found in 98.4% of B.1.1.7 SARS-CoV-2 infections compared with only 13.8% of other lineages, with a 16-fold increase in median expression. We hypothesise that this is a direct consequence of a triple nucleotide mutation in nucleocapsid (28280:GAT>CAT, D3L) creating a transcription regulatory-like sequence complementary to a region 3’ of the genomic leader. These findings provide a unique insight into the biology of B.1.1.7 and support monitoring of sgRNA profiles in sequence data to evaluate emerging potential variants of concern.

One Sentence Summary

The recently emerged and more transmissible SARS-CoV-2 lineage B.1.1.7 shows greater subgenomic RNA expression in clinical infections and enhanced expression of a noncanonical subgenomic RNA near ORF9b.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.03.02.433156: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationFirst by randomly selecting one sequence per country per epi week followed by random sampling of the remaining sequences to generate a sample of 4000 sequences.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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.

    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 10.1101/2021.03.02.433156v2 on bioRxiv
  3. Version published to 10.1101/2021.03.02.433156v1 on bioRxiv