The host innate immune response mediated by type I interferon (IFN) and the resulting up-regulation of hundreds of interferon-stimulated genes (ISGs) provide an immediate barrier to virus infection. Studies of the type I ‘interferome’ have mainly been carried out at a single species level, often lacking the power necessary to understand key evolutionary features of this pathway. Here, using a single experimental platform, we determined the properties of the interferomes of multiple vertebrate species and developed a webserver to mine the dataset. This approach revealed a conserved ‘core’ of 62 ISGs, including genes not previously associated with IFN, underscoring the ancestral functions associated with this antiviral host response. We show that gene expansion contributes to the evolution of the IFN system and that interferomes are shaped by lineage-specific pressures. Consequently, each mammal possesses a unique repertoire of ISGs, including genes common to all mammals and others unique to their specific species or phylogenetic lineages. An analysis of genes commonly down-regulated by IFN suggests that epigenetic regulation of transcription is a fundamental aspect of the IFN response. Our study provides a resource for the scientific community highlighting key paradigms of the type I IFN response.

Summary CoV-GLUE is an online web application for the interpretation and analysis of SARS-CoV-2 virus genome sequences, with a focus on amino acid sequence variation. It is based on the GLUE data-centric bioinformatics environment and provides a browsable database of amino acid replacements and coding region indels that have been observed in sequences from the pandemic. Users may also analyse their own SARS-CoV-2 sequences by submitting them to the web application to receive an interactive report containing visualisations of phylogenetic classification and highlighting genomic variation of potentially high impact, for example linked to primer mismatches.Availability and implementation Available at http://cov-glue.cvr.gla.ac.uk. Implemented using GLUE, an open source framework for the development of virus sequence data resources. Contact josh.singer@glasgow.ac.uk

Virus host shifts are generally associated with novel adaptations to exploit the cells of the new host species optimally. Surprisingly, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has apparently required little to no significant adaptation to humans since the start of the Coronavirus Disease 2019 (COVID-19) pandemic and to October 2020. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus the early SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses. In contrast, our analysis detects evidence for significant positive episodic diversifying selection acting at the base of the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in these ancestral bat hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor about 1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. While an undiscovered “facilitating” intermediate species cannot be discounted, collectively, our results support the progenitor of SARS-CoV-2 being capable of efficient human–human transmission as a consequence of its adaptive evolutionary history in bats, not humans, which created a relatively generalist virus.

BackgroundVirus genome sequences, generated in ever-higher volumes, can provide new scientific insights and inform our responses to epidemics and outbreaks. To facilitate interpretation, such data must be organised and processed within scalable computing resources that encapsulate virology expertise. GLUE (Genes Linked by Underlying Evolution) is a data-centric bioinformatics environment for building such resources. The GLUE core data schema organises sequence data along evolutionary lines, capturing not only nucleotide data but associated items such as alignments, genotype definitions, genome annotations and motifs. Its flexible design emphasises applicability to different viruses and to diverse needs within research, clinical or public health contexts.ResultsHCV-GLUE is a case study GLUE resource for hepatitis C virus (HCV). It includes an interactive public web application providing sequence analysis in the form of a maximum-likelihood-based genotyping method, antiviral resistance detection and graphical sequence visualisation. HCV sequence data from GenBank is categorised and stored in a large-scale sequence alignment which is accessible via web-based queries. Whereas this web resource provides a range of basic functionality, the underlying GLUE project can also be downloaded and extended by bioinformaticians addressing more advanced questions.ConclusionGLUE can be used to rapidly develop virus sequence data resources with public health, research and clinical applications. This streamlined approach, with its focus on reuse, will help realise the full value of virus sequence data.

Background: Virus genome sequences, generated in ever-higher volumes, can