Pangenome mining for quarantine organisms

Plant pathogen quarantine organisms (“q-organisms”) pose a serious threat to agriculture and natural ecosystems such as forests. Q-organisms can cause significant ecological and economical damage. Efficient and timely monitoring of the presence of q-organisms is essential to prevent their spread, contain infected locations and reduce the damage. The highly dynamic and rapidly evolving genomes of pathogens make it challenging to incorporate the naturally occurring diversity in traditional reference genome-based monitoring. In this project, we will make use of novel genome data of q-organisms and design and implement bioinformatics strategies to mine this data at the pangenomics scale. This research project will involve developing software and code for q-organism monitoring around three key pillars; (i) pangenome construction, (ii) data visualization and (iii) artificial intelligence. This project will help to understand the evolution, migration, and selection of q-organisms, characterize their pathogenic traits, and design novel assays as well as update existing assays. Overall, this project will provide important tools for the National Plant Protection Organization and inspection services to effectively monitor q-organisms.