Fungal Community Profiling and Pathogen Detection in Conifer Seed Lots: Benchmarking Oxford Nanopore DNA Metabarcoding Against Conventional Methods

Seedborne fungal pathogens, either native or exotic, spread through seed trade and pose serious risks to reforestation efforts. Traditional pathogen detection methods, such as seed plating assays, are limited in scope and sensitivity. We assessed the potential of DNA-metabarcoding with Oxford Nanopore Technologies (ONT) to detect and identify fungal pathogens in conifer seed lots. Using ONT-based sequencing of the internal transcribed spacer (ITS) and translation elongation factor 1-alpha (TEF1) loci, we analyzed 20 seed lots from Douglas fir ( Pseudotsuga menziesii) and interior spruce ( Picea engelmannii × glauca). Our results were benchmarked against culture-based and real-time PCR assays. The ITS ONT assay detected a broad range of fungal taxa, including conifer pathogens such as Fusarium spp., Sirococcus conigenus, and Caloscypha fulgens. Although the TEF1 ONT assay showed lower detection sensitivity, it increased the robustness of species complex resolution within the Fusarium genus. We observed a strong correlation between ITS ONT read counts and real-time PCR quantification cycle (Cq) values, indicating the potential for quantitative pathogen load assessment. Differences between detection methods highlighted the importance of optimizing seed sampling strategies to improve pathogen detection consistency. The portability, affordability, and ongoing improvements in ONT technology suggest a promising future for its application in forest seed diagnostics and biosecurity monitoring. [Formula: see text] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .