Conserved recombination patterns across coronavirus subgenera

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 breakpoints 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 breakpoints 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 breakpoint hot-spot locations. We find that while the locations of recombination breakpoints 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 breakpoints most commonly occur, it is evident that selection against misfolded recombinant proteins also strongly impacts observable recombination breakpoint distributions in coronavirus genomes sampled from nature.

Emergence and widespread circulation of a recombinant SARS-CoV-2 lineage in North America

“…The mapping of these deletions provides an entirely independent data source to evaluate the occurrence of recombination from the commonly used nucleotide-level sequence changes that were also used to test for genomic mosaicism-the consistency between the results from these two data types provides strong evidence for the occurrence of a recombination event in our data. Furthermore, an inferred recombination breakpoint located near the start of the S protein reading frame generally coincides with previously described recombination hotspots for other coronaviruses (de Klerk et al, 2021;Sabir et al, 2016;Yang et al, 2021) and for SARS-CoV-2 (Boni et al, 2020;Jackson et al, 2021;Li et al, 2020;Lytras et al, 2021).…”

In-depth study of tomato and weed viromes reveals undiscovered plant virus diversity in an agroecosystem

“…Genomes of different isolates gathered from GenBank and viral RefSeq database [34] were aligned using MUSCLE [51] implemented in MEGA X [52] and checked for possible recombinants in RDP v. 4 [53]. All recombination events with p-val<10 −4 reported by at least four methods were considered significant, based on the methods from related studies [54,55]. Phylogenetic analyses were performed on alignments free of recombinants.…”

Natural selection differences detected in key protein domains between non-pathogenic and pathogenic feline coronavirus phenotypes

“…CoVs are known to extensively recombine ( Banner and Lai 1991 ; Liao and Lai 1992 ; Graham and Baric 2010 ; de Klerk et al. 2022 ; Lytras et al.…”