P061
RAVEN and iMAGE: An integrated approach to analyse and visualise whole genome data for Mycobacterium bovis genomic surveillance and epidemiology
P D Ranasinghe(1) A R Allen(1)
1:Agri-Food and Biosciences Institute
The recent SARS-Cov-2 pandemic highlighted the importance of modern genomics in tracking a new global pathogen. Genome sequencing facilitates phylogenetic analysis, epidemiological insights, and the identification of sources for emerging pathogens and lineages worldwide. This was a consciousness-raising event for many policymakers and public health officials, who acknowledged the value of pathogen genome epidemiology and the tools available to improve responses to disease outbreaks. These tools are, however, not just useful for novel, pandemic pathogens. They can readily be applied to endemic, zoonotic pathogens such as Mycobacterium bovis, which causes animal tuberculosis.
In the ‘One Health’ era, the need to apply such methods to pathogens like M. bovis has renewed efforts to modernise public, veterinary, and laboratory services. Such laboratories need flexible, modular bioinformatic tools adaptable to different pathogen types and data visualisation platforms which can present phylogeographic and phylogenetic information in an interactive and user-friendly manner. This is essential for facilitating wider adoption of pathogen genomic surveillance data by computer science and genomics non-specialists who perform key public-facing roles in veterinary and public health.
We present two in-house program solutions to address these issues: Rapid Assembly and Variant Evaluation Network (RAVEN), a pipeline for read and assembly-based pathogen genome characterisation and SNP calling, and interactive Mycobacterium bovis Genome Epidemiology (iMAGE) tool, a Shiny application built in R for visualising phylogenetic and phylogeographic information. As the next step, we aim to bundle our tools in virtual containers to distribute and deploy the application reproducibly on multiple operating systems.
