Advanced pre-screening of export grain and oilseed commodities using machine learning on long read sequencing

Funding period: 2020-2024
Lead: Guillaume Bilodeau
Total GRDI funding: $338,500

Canadian exports of grains, oilseeds, and other crops exceeded 40M tonnes in 2018, with approximately 16M for wheat, 10M for canola, and 3.7M for soybean (Canadian grain exports, 2018). The CFIA is responsible to certify shipments are free of specific pathogens, following international grain and seed export trade regulations. Failing to detect targeted pathogens when present in a shipment can have major negative repercussions on Canada's economy and reputation, and jeopardizes access to major markets if detected by the importing country. The MinION sequencing technology (Oxford Nanopore) allows multiple metagenomics samples to be combined in a single sequencing run while maintaining the sequencing depth per sample that is required for detection sensitivity and identification accuracy. Thus, the MinION is a fit-for-purpose tool to pre-screen grain and seed samples for the detection of plant pathogens. This project aims to determine if the MinION sequencing technology is an effective and efficient tool to detect regulated plant pathogens in export grain, seed, and oilseed commodities, such as wheat, canola, and soybean. The information generated from this project will provide a framework for future screening methods for the early detection of new and emerging pathogens.


  • Lebas, B, Adams, I, Al Rwahnih, M, Baeyen, S, Bilodeau, G, Blouin, AG, Boonham, N, Candresse, T, Chandelier, A, De Jonghe, K, Fox, A, Gaafar, YZA, Gentit, P, Haegeman, A, Ho, W, Hurtado-Gonzales, O, Jonkers, W, Kreuze, J, Kutjnak, D, Landa, B, Liu, M, Maclot, F, Malapi-Wight, M, Maree, HJ, Martoni, F, Mehle, N, Minafra, A, Mollov, D, Moreira, A, Nakhla, M, Petter, F, Piper, AM, Ponchart, J, Rae, R, Remenant, B, Rivera, Y, Rodoni, B, Roenhorst, J, Rollin, J, Saldarelli, P, Santala, J, Souza-Richards, R, Spadaro, D, Studholme, DJ, Sultmanis, S, van der Vlugt, R, Tamisier, L, Trontin, C, Vazquez-Iglesias, I, Vicente, CSL, Vossenberg, BTLH, Wetzel, T, Ziebell, H, Massart, S. 2022. Facilitating the adoption of high-throughput sequencing technologies as a plant pest diagnostic test in laboratories: A step-by-step description. EPPO Bulletin [online] 52(2), 394-418.
  • Tremblay ED, Carey J, Bilodeau GJ, Hambleton S. 2021. Four in silico designed and validated qPCR assays to detect and discriminate Tilletia indica and T. Walkeri, individually or as a complex. Biology 10(12): 1295.

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For additional information, please contact:
Genomics R&D Initiative