Extensive Recombination-driven Coronavirus Diversification Expands the Pool of Potential Pandemic Pathogens. (4th November 2022)

• Record Type: Journal Article
• Authors: Goldstein, Stephen A; Brown, Joe; Pedersen, Brent S; Quinlan, Aaron R; Elde, Nels C
• Editors: Pfeifer, Susanne
• Is Part Of: Genome biology and evolution. Volume 14:Number 12(2022)
• Publication Date: 2022-11-04
• Subjects: virology -- evolution -- coronaviruses; Genomics -- Periodicals; Genes -- Periodicals; 572.8605
• DOI: 10.1093/gbe/evac161
• Languages: English
• ISSNs: 1759-6653

Abstract

Abstract: The ongoing SARS-CoV-2 pandemic is the third zoonotic coronavirus identified in the last 20 years. Enzootic and epizootic coronaviruses of diverse lineages also pose a significant threat to livestock, as most recently observed for virulent strains of porcine epidemic diarrhea virus (PEDV) and swine acute diarrhea-associated coronavirus (SADS-CoV). Unique to RNA viruses, coronaviruses encode a proofreading exonuclease (ExoN) that lowers point mutation rates to increase the viability of large RNA virus genomes, which comes with the cost of limiting virus adaptation via point mutation. This limitation can be overcome by high rates of recombination that facilitate rapid increases in genetic diversification. To compare the dynamics of recombination between related sequences, we developed an open-source computational workflow (IDPlot) that bundles nucleotide identity, recombination, and phylogenetic analysis into a single pipeline. We analyzed recombination dynamics among three groups of coronaviruses with noteworthy impacts on human health and agriculture: SARSr-CoV, Betacoronavirus-1, and SADSr-CoV. We found that all three groups undergo recombination with highly diverged viruses from undersampled or unsampled lineages, including in typically highly conserved regions of the genome. In several cases, no parental origin of recombinant regions could be found in genetic databases, demonstrating our shallow characterization of coronavirus diversity and expanding the genetic pool that may contribute to future zoonotic events. Our results also illustrate the limitations of current sampling approaches for anticipating zoonotic threats to human and animal health.