The project
VirAnimalOne: Application of animal genomics and data mining to predict and monitor novel coronavirus potential infections
VirAnimalOne is focused on large scale mining of publicly deposited genomic and transcriptomic datasets available from ENA/SRA and derived from pets, livestock and wild animal species:
1) to identify unexpected coronavirus sequences. Virus sequences will be detected by adapting the bioinformatic pipeline of Bovo et al. (2017) and using a viral metagenomic approach against the NCBI Viral Genome Resource and a customized reference database.
2) to mine the host animal genomes for potential variants that might confer resistance or susceptibility to SARS-CoV-2 and other coronaviruses known to infect both humans and animals. Animal genome NGS reads (from ENA/SRA) will be aligned to the corresponding reference genomes and variants in host genes involved in coronavirus infection will be identified, in silico characterized for tolerated or deleterious effects using VEP, SIFT and other tools.
3) to phylogenetically and structurally evaluate host receptor conformations and infer potential animal susceptibility to coronavirus infections, with particular attention for SARS-Cov-2. Comparative annotation of sequence variants in host genes and multispecies alignments will be performed to infer the functional effects based on spike protein recognition sites or other functional interacting and catalysing sites.