Diversity of crop-associated oomycetes using metabarcoding data from aerial spore and suction traps

Citation

Tremblay, É. D., Goulet, B. B., Brunet, B. M. T., Lord, É., & Parent, J.-P. (2023, 2023/05/31 - 2023/06/02). Diversity of crop-associated oomycetes using metabarcoding data from aerial spore and suction traps. Talk presented at the 4th Annual CanFunNet Fungal Biology Conference, Virtual Event.

Résumé en langage clair

Plant pathogens are a major threat to food security. They can negatively affect crops, seeds, and animal feed. Among plant pathogen types of microorganisms, there are oomycetes. The represent a threat to plant health and are becoming increasingly prevalent in new regions. One of the reason is the increasing of more permissive weather conditions in new areas due climate change. In fact, new introduction and spread of unwanted plant pathogens can lead stricter trade regulations. As a result, new pests can become regulated, which consequently impacts imports and exports. In this project, we use molecular biology to assess the biodiversity and incidence of oomycetes using spore and suction insect traps. High-Throughput Sequencing—specifically metabarcoding allows us to characterize oomycetes in agricultural fields from the provinces of Ontario and Quebec. Preliminary results will be presented as a of baseline information on crop health and an attempt to predict further incidences through AI modelling. This approach has the potential to improve risk readiness and response measures.

Résumé

Phytopathogens are a major threat to food security impacting crops, seeds, and animal feed. Threats to plant health caused by phytopathogens, such as oomycetes, are becoming increasingly prevalent in new regions with more permissive conditions resulting from climate change. For example, the introduction and spread of phytopathogenic adventive species can lead to increasingly strict international trade regulations such as the inclusion of new pests to a regulated pest list, impacting imports and exports. In this project, we use High-Throughput Sequencing—specifically metabarcoding—to assess the biodiversity of oomycete phytopathogens and characterize their incidence from aerial spore and suction traps in agricultural fields located in Ontario and Quebec. Preliminary results from our workflow will be presented. This study will provide baseline information on crop health in relation to phytopathogenic oomycete incidence. It will also improve risk readiness and response measures through the future development of predictive models to forecast oomycete distribution.