Conserved recombination patterns across coronavirus subgenera
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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.
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SciScore for 10.1101/2021.11.21.469423: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Each of the six subgenus-level datasets was aligned with MAFFT using default settings (Katoh and Standley 2013). MAFFTsuggested: (MAFFT, RRID:SCR_011811)Identification of potential transcriptional regulatory sequences: SuPER was used to detect transcriptional regulatory sequence leader (TRS-L) sites and a custom Python (Rossum and Drake 2010) script was used to infer transcriptional regulatory sequence body (TRS-B) sites (Yang et al. 2021). Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are …
SciScore for 10.1101/2021.11.21.469423: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Each of the six subgenus-level datasets was aligned with MAFFT using default settings (Katoh and Standley 2013). MAFFTsuggested: (MAFFT, RRID:SCR_011811)Identification of potential transcriptional regulatory sequences: SuPER was used to detect transcriptional regulatory sequence leader (TRS-L) sites and a custom Python (Rossum and Drake 2010) script was used to infer transcriptional regulatory sequence body (TRS-B) sites (Yang et al. 2021). Pythonsuggested: (IPython, RRID:SCR_001658)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 15. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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