AbstractThe ongoing SARS-CoV-2 pandemic is the third zoonotic coronavirus identified in the last twenty years. Previously, four other known coronaviruses moved from animal reservoirs into humans and now cause primarily mild-to-moderate respiratory disease. The emergence of these viruses likely involved a period of intense transmission before becoming endemic, highlighting the recurrent threat to human health posed by animal coronaviruses. Enzootic and epizootic coronaviruses of diverse lineages 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 dynamics of recombination between related sequences, we developed an open-source computational workflow (IDPlot) to measure nucleotide identity, locate recombination breakpoints, and infer phylogenetic relationships. We analyzed recombination dynamics among three groups of coronaviruses with impacts on livestock or human health: SARSr-CoV, Betacoronavirus-1, and SADSr-CoV. We found that all three groups undergo recombination with highly diverged viruses, disrupting phylogenetic relationships and revealing contributions of unknown coronavirus lineages to the genetic diversity of established groups. Dynamic patterns of recombination impact inferences of relatedness between diverse coronaviruses and expand the genetic pool that may contribute to future zoonotic events. These results illustrate the limitations of current sampling approaches for anticipating zoonotic threats to human and animal health.
The cost of replication fidelity in an RNA virus
