Conserved recombination patterns across coronavirus subgenera

Author:

de Klerk Arné1ORCID,Swanepoel Phillip1,Lourens Rentia2,Zondo Mpumelelo1ORCID,Abodunran Isaac1,Lytras Spyros3ORCID,MacLean Oscar A3ORCID,Robertson David3ORCID,Kosakovsky Pond Sergei L4ORCID,Zehr Jordan D4,Kumar Venkatesh5,Stanhope Michael J6ORCID,Harkins Gordon7,Murrell Ben5,Martin Darren P1ORCID

Affiliation:

1. Institute of Infectious Diseases and Molecular Medicine, Division Of Computational Biology, Department of Integrative Biomedical Sciences, University of Cape Town , Cape Town 7701, South Africa

2. Division of Neurosurgery, Neuroscience Institute, Department of Surgery, University of Cape Town , Cape Town, 7701, South Africa

3. MRC-University of Glasgow Centre for Virus Research, University of Glasgow , Glasgow G61 1QH, UK

4. Department of Biology, Temple University, Institute for Genomics and Evolutionary Medicine , Philadelphia, PA 19122, USA

5. Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet , Stockholm, 14186, Sweden

6. Department of Population and Ecosystem Health, College of Veterinary Medicine, Cornell University , Ithaca, NY, 14853, USA

7. South African National Bioinformatics Institute, University of the Western Cape , Cape Town, 7535, South Africa

Abstract

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.

Funder

ADK

South African National Research Foundation

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Virology,Microbiology

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