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; Venkatesh Kumar; Michael J Stanhope; Gordon Harkins; Ben Murrell; Darren P Martin

doi:10.1093/ve/veac054

Conserved recombination patterns across coronavirus subgenera

Virus Evol. 2022 Jun 14;8(2):veac054. doi: 10.1093/ve/veac054. eCollection 2022.

Authors

Affiliations

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

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.

Keywords: Coronavirus; Evolution; Phylogenetics; Recombination; Selection.

Abstract

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