Evidence map›Paper›PMID 33743803›Full record

ArticleBioData mining2021

Indels in SARS-CoV-2 occur at template-switching hotspots.

Brianna Sierra Chrisman, Kelley Paskov, Nate Stockham, Kevin Tabatabaei, Jae-Yoon Jung, Peter Washington, Maya Varma, Min Woo Sun, Sepideh Maleki, Dennis P Wall

Open access · goldAbstract read
In one paragraph

Article in BioData mining, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.2field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Hidden Markov models detect recombination and ancestry of SARS-CoV-2.bioRxiv : the preprint server for biology · 2026
    Article
  3. Highly Recurrent Multinucleotide Mutations in SARS-CoV-2.Molecular biology and evolution · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. High-resolution mapping reveals the mechanism and contribution of genome insertions and deletions to RNA virus evolution.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  11. Correlated substitutions reveal SARS-like coronaviruses recombine frequently with a diverse set of structured gene pools.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Brianna Sierra ChrismanDepartment of Bioengineering, Stanford University, Stanford, USA. briannac@stanford.edu.ORCID http://orcid.org/0000-0002-7157-607X
Kelley PaskovDepartment of Biomedical Data Science, Stanford University, Stanford, USA.
Nate StockhamDepartment of Neuroscience, Stanford University, Stanford, USA.
Kevin TabatabaeiFaculty of Health Sciences, McMaster University, Hamilton, Canada.
Jae-Yoon JungDepartment of Biomedical Data Science, Stanford University, Stanford, USA.
Peter WashingtonDepartment of Bioengineering, Stanford University, Stanford, USA.
Maya VarmaDepartment of Computer Science, Stanford University, Stanford, USA.
Min Woo SunDepartment of Biomedical Data Science, Stanford University, Stanford, USA.
Sepideh MalekiDepartment of Computer Science, University of Texas Austin, Austin, USA.
Dennis P WallDepartment of Biomedical Data Science, Stanford University, Stanford, USA. dpwall@stanford.edu.
Stanford University · USMcMaster University · CAStanford Medicine · USThe University of Texas at Austin · US

Funding

National Science Foundation GRFP
6 · The paper itself

Abstract

The evolutionary dynamics of SARS-CoV-2 have been carefully monitored since the COVID-19 pandemic began in December 2019. However, analysis has focused primarily on single nucleotide polymorphisms and largely ignored the role of insertions and deletions (indels) as well as recombination in SARS-CoV-2 evolution. Using sequences from the GISAID database, we catalogue over 100 insertions and deletions in the SARS-CoV-2 consensus sequences. We hypothesize that these indels are artifacts of recombination events between SARS-CoV-2 replicates whereby RNA-dependent RNA polymerase (RdRp) re-associates with a homologous template at a different loci ("imperfect homologous recombination"). We provide several independent pieces of evidence that suggest this. (1) The indels from the GISAID consensus sequences are clustered at specific regions of the genome. (2) These regions are also enriched for 5' and 3' breakpoints in the transcription regulatory site (TRS) independent transcriptome, presumably sites of RNA-dependent RNA polymerase (RdRp) template-switching. (3) Within raw reads, these indel hotspots have cases of both high intra-host heterogeneity and intra-host homogeneity, suggesting that these indels are both consequences of de novo recombination events within a host and artifacts of previous recombination. We briefly analyze the indels in the context of RNA secondary structure, noting that indels preferentially occur in "arms" and loop structures of the predicted folded RNA, suggesting that secondary structure may be a mechanism for TRS-independent template-switching in SARS-CoV-2 or other coronaviruses. These insights into the relationship between structural variation and recombination in SARS-CoV-2 can improve our reconstructions of the SARS-CoV-2 evolutionary history as well as our understanding of the process of RdRp template-switching in RNA viruses.

Indexed as

GenomicsRecombinationRNA virusSARS-CoV-2

Identifiers

PMID33743803
PMCPMC7980745
OpenAlexW3136786679

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.