Since the first reports of a novel SARS-like coronavirus in December 2019 in Wuhan, China, there has been intense interest in understanding how SARS-CoV-2 emerged in the human population. Recent debate has coalesced around two competing ideas: a “laboratory escape” scenario and zoonotic emergence. Here, we critically review the current scientific evidence that may help clarify the origin of SARS-CoV-2.

The cross-species transmission of viruses from one host species to another is responsible for the majority of emerging infections. However, it is unclear whether some virus families have a greater propensity to jump host species than others. If related viruses have an evolutionary history of co-divergence with their hosts there should be evidence of topological similarities between the virus and host phylogenetic trees, whereas host jumping generates incongruent tree topologies. By analyzing co-phylogenetic processes in 19 virus families and their eukaryotic hosts we provide a quantitative and comparative estimate of the relative frequency of virus-host co-divergence versus cross-species transmission among virus families. Notably, our analysis reveals that cross-species transmission is a near universal feature of the viruses analyzed here, with virus-host co-divergence occurring less frequently and always on a subset of viruses. Despite the overall high topological incongruence among virus and host phylogenies, the Hepadnaviridae, Polyomaviridae, Poxviridae, Papillomaviridae and Adenoviridae, all of which possess double-stranded DNA genomes, exhibited more frequent co-divergence than the other virus families studied here. At the other extreme, the virus and host trees for all the RNA viruses studied here, particularly the Rhabdoviridae and the Picornaviridae, displayed high levels of topological incongruence, indicative of frequent host switching. Overall, we show that cross-species transmission plays a major role in virus evolution, with all the virus families studied here having the potential to jump host species, and that increased sampling will likely reveal more instances of host jumping. Emerging infectious diseases are often characterized by host switching events, in which a pathogen jumps from its original host to infect a novel species. However, given the ecological and genetic barriers a virus must overcome to jump species and adapt to new hosts, it might be reasonable to assume that successful cross-species transmission is a relatively rare occurrence and that viruses are instead more likely to co-diverge with their hosts. Using a comparative co-phylogenetic analysis performed at the scale of virus family we have revealed that co-divergence is relatively infrequent among 19 diverse families of RNA and DNA viruses, such that cross-species transmission plays a central role in virus evolution. Host jumping was especially common in viruses with RNA genomes, and by drawing broad-scale comparisons our analysis reveals which virus families have a greater propensity to jump species barriers and hence successfully emerge in new hosts. Finally, our data suggest that sampling more viruses increases the likelihood of detecting host jumping events.

The study of virus disease emergence, whether it can be predicted and how it might be prevented, has become a major research topic in biomedicine. Here we show that efforts to predict disease emergence commonly conflate fundamentally different evolutionary and epidemiological time scales, and are likely to fail because of the enormous number of unsampled viruses that could conceivably emerge in humans. Although we know much about the patterns and processes of virus evolution on evolutionary time scales as depicted in family-scale phylogenetic trees, these data have little predictive power to reveal the short-term microevolutionary processes that underpin cross-species transmission and emergence. Truly understanding disease emergence therefore requires a new mechanistic and integrated view of the factors that allow or prevent viruses spreading in novel hosts. We present such a view, suggesting that both ecological and genetic aspects of virus emergence can be placed within a simple population genetic framework, which in turn highlights the importance of host population size and density in determining whether emergence will be successful. Despite this framework, we conclude that a more practical solution to preventing and containing the successful emergence of new diseases entails ongoing virological surveillance at the human–animal interface and regions of ecological disturbance.

A synthesis of phenotypic and quantitative genomic traits is provided for bacteria and archaea, in the form of a scripted, reproducible workflow that standardizes and merges 26 sources. The resulting unified dataset covers 14 phenotypic traits, 5 quantitative genomic traits, and 4 environmental characteristics for approximately 170,000 strain-level and 15,000 species-aggregated records. It spans all habitats including soils, marine and fresh waters and sediments, host-associated and thermal. Trait data can find use in clarifying major dimensions of ecological strategy variation across species. They can also be used in conjunction with species and abundance sampling to characterize trait mixtures in communities and responses of traits along environmental gradients.

Significance: With changes in land use and increased urbanization, the frequency with which pathogens jump species barriers to emerge in new hosts is expected to rise. Knowing which viruses may be more likely to become transmissible among humans, as opposed to only generating dead-end spillover infections, would be of considerable benefit to pandemic planning. Using multivariate modeling and multimodel inference, we sought to both identify and quantify those biological features of viruses that best determine interhuman transmissibility. This analysis revealed that chronic, nonsegmented, non–vector-borne, nonenveloped viruses with low host mortality had the highest likelihood of being transmissible among humans whereas genomic features had little predictive power. Our analysis therefore reveals that multiple virological features determine the likelihood of successful emergence.