Hidden evolutionary constraints dictate the retention of coronavirus accessory genes (preprint)

Genetic innovation is fundamental to the ability of viruses to adapt in the face of host immunity. Coronaviruses exhibit many mechanisms of innovation given flexibility in genomic composition relative to most RNA virus families (1-5). Examples include the acquisition of unique accessory genes that can originate by capture of cellular genes or through duplication and divergence of existing viral genes (6-8). Accessory genes may be influential in dictating viral host range and cellular tropism, but little is known about how selection acts on these variable regions of virus genomes. We used experimental evolution of mouse hepatitis virus (MHV) with an inactive native phosphodiesterase, NS2, that encodes a complementing cellular AKAP7 gene (9), to simulate the capture of a host gene and found hidden patterns of constraint that determine the fate of coronavirus accessory genes. After courses of serial infection, AKAP7 was retained under strong selection but rapidly lost under relaxed selection. In contrast, the gene encoding inactive NS2, ORF2, remained intact, suggesting it is under cryptic evolutionary constraint. Guided by the retention of ORF2 and hints of similar patterns in related betacoronaviruses, we analyzed the evolution of SARS-CoV-2 ORF8, which arose via gene duplication (6) and contains premature stop codons in several globally successful lineages. As with MHV ORF2, the coding-defective SARS-CoV-2 ORF8 gene remains largely intact, mirroring patterns observed during MHV experimental evolution and extending these findings to viruses currently adapting to humans. Retention of inactive genes challenges assumptions on the dynamics of gene loss in virus genomes and can help guide evolutionary analysis of emerging and pandemic coronaviruses.

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic (preprint)

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Wholesale Seafood Market, the site with the most reported wildlife vendors in the city of Wuhan, China. Here, we analyze publicly available qPCR and sequencing data from environmental samples collected in the Huanan market in early 2020. We demonstrate that the SARS-CoV-2 genetic diversity linked to this market is consistent with market emergence, and find increased SARS-CoV-2 positivity near and within a particular wildlife stall. We identify wildlife DNA in all SARS-CoV-2 positive samples from this stall. This includes species such as civets, bamboo rats, porcupines, hedgehogs, and one species, raccoon dogs, known to be capable of SARS-CoV-2 transmission. We also detect other animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them to those from other markets. This analysis provides the genetic basis for a short list of potential intermediate hosts of SARS-CoV-2 to prioritize for retrospective serological testing and viral sampling.

Extensive recombination-driven coronavirus diversification expands the pool of potential pandemic pathogens (preprint)

The 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.