Evidence map›Paper›PMID 35814334›Full record

ArticleVirus evolution2022

Conserved recombination patterns across coronavirus subgenera.

Arné de Klerk, Phillip Swanepoel, Rentia Lourens, Mpumelelo Zondo, Isaac Abodunran, Spyros Lytras, Oscar A MacLean, David Robertson, Sergei L Kosakovsky Pond, Jordan D Zehr and 5 more

Open access · goldAbstract read
In one paragraph

Article in Virus evolution, 2022. 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
4.0field-weighted citation impact, top 5% 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, 35 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Patterns of Recombination in Coronaviruses.International journal of molecular sciences · 2025
    Article
  7. Article
  8. Virus evolution · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. The coronavirus recombination pathway.Cell host & microbe · 2023
    Review
  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

15 authors at 6 institutions in 4 countries.

Arné de KlerkInstitute of Infectious Diseases and Molecular Medicine, Division Of Computational Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town 7701, South Africa.ORCID https://orcid.org/0000-0002-9525-6820
Phillip SwanepoelInstitute of Infectious Diseases and Molecular Medicine, Division Of Computational Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town 7701, South Africa.
Rentia LourensDivision of Neurosurgery, Neuroscience Institute, Department of Surgery, University of Cape Town, Cape Town, 7701, South Africa.
Mpumelelo ZondoInstitute of Infectious Diseases and Molecular Medicine, Division Of Computational Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town 7701, South Africa.ORCID https://orcid.org/0000-0002-7670-5520
Isaac AbodunranInstitute of Infectious Diseases and Molecular Medicine, Division Of Computational Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town 7701, South Africa.
Spyros LytrasMRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow G61 1QH, UK.ORCID https://orcid.org/0000-0003-4202-6682
Oscar A MacLeanMRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow G61 1QH, UK.ORCID https://orcid.org/0000-0003-4919-4697
David RobertsonMRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow G61 1QH, UK.ORCID https://orcid.org/0000-0001-6338-0221
Sergei L Kosakovsky PondDepartment of Biology, Temple University, Institute for Genomics and Evolutionary Medicine, Philadelphia, PA 19122, USA.ORCID https://orcid.org/0000-0003-4817-4029
Jordan D ZehrDepartment of Biology, Temple University, Institute for Genomics and Evolutionary Medicine, Philadelphia, PA 19122, USA.
Venkatesh KumarDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 14186, Sweden.
Michael J StanhopeDepartment of Population and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, 14853, USA.ORCID https://orcid.org/0000-0002-4590-1529
Gordon HarkinsSouth African National Bioinformatics Institute, University of the Western Cape, Cape Town, 7535, South Africa.
Ben MurrellDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 14186, Sweden.
Darren P MartinInstitute of Infectious Diseases and Molecular Medicine, Division Of Computational Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town 7701, South Africa.ORCID https://orcid.org/0000-0002-8785-0870
University of Cape Town · ZAMRC University of Glasgow Centre for Virus Research · GBKarolinska Institutet · SETemple University · USCornell University · USUniversity of the Western Cape · ZA

Funding

Turning big data analysis infrastructure for HIV researchR01AI134384 · NIAID · PENNSYLVANIA STATE UNIVERSITY, THE · PI NEKRUTENKO, ANTON, POND, SERGEI L KOSAKOVSKY · 2017 to 2021
$4.2M
HIV Evolution Defines Virus-Host/Drug Interactions In Viremic and Aviremic PeopleR01AI140970 · NIAID · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Ronald I Swanstrom, Shuntai Zhou · 2018 to 2026
$4.1M
Medical Research Council MC_PC_19026Medical Research Council MC_UU_12014/12NIAID NIH HHS R01 AI134384NIAID NIH HHS R01 AI140970
6 · The paper itself

Abstract

Recombination contributes to the genetic diversity found in coronaviruses and is known to be a prominent mechanism whereby they evolve. It is apparent, both from controlled experiments and in genome sequences sampled from nature, that patterns of recombination in coronaviruses are non-random and that this is likely attributable to a combination of sequence features that favour the occurrence of recombination break points at specific genomic sites, and selection disfavouring the survival of recombinants within which favourable intra-genome interactions have been disrupted. Here we leverage available whole-genome sequence data for six coronavirus subgenera to identify specific patterns of recombination that are conserved between multiple subgenera and then identify the likely factors that underlie these conserved patterns. Specifically, we confirm the non-randomness of recombination break points across all six tested coronavirus subgenera, locate conserved recombination hot- and cold-spots, and determine that the locations of transcriptional regulatory sequences are likely major determinants of conserved recombination break-point hotspot locations. We find that while the locations of recombination break points are not uniformly associated with degrees of nucleotide sequence conservation, they display significant tendencies in multiple coronavirus subgenera to occur in low guanine-cytosine content genome regions, in non-coding regions, at the edges of genes, and at sites within the Spike gene that are predicted to be minimally disruptive of Spike protein folding. While it is apparent that sequence features such as transcriptional regulatory sequences are likely major determinants of where the template-switching events that yield recombination break points most commonly occur, it is evident that selection against misfolded recombinant proteins also strongly impacts observable recombination break-point distributions in coronavirus genomes sampled from nature.

Indexed as

CoronavirusEvolutionPhylogeneticsRecombinationSelection

Identifiers

PMID35814334
PMCPMC9261289
OpenAlexW4282839494

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.