What Quality Suffices for Nanopore Metabarcoding? Reconsidering Methodology and Ectomycorrhizae in Decaying Fagus sylvatica Bark as Case Study.

Abstract

Nanopore raw read accuracy has improved to over 99%, making it a potential tool for metabarcoding. For broad adoption, guidelines on quality filtering are needed to ensure reliable taxonomic unit recovery. This study aims to provide those guidelines for a fungal metabarcoding context and to apply them to a case study of ectomycorrhizae in the decaying bark of Fagus sylvatica. We introduce the eNano pipeline to test two standard metabarcoding approaches: (1) Reference-based mapping leveraging UNITE's species hypothesis system (SH approach); (2) Constructing 98% OTUs (OTU approach). Our results demonstrate that both approaches are effective with Nanopore data. When using a reference database, we recommend strict mapping criteria rather than Phred-based filtering. Leveraging the SH-system further enhances reproducibility and facilitates cross-study communication. For the 98% OTUs, filtering reads at ≥Q25 is recommended. Our case study reveals that the decay gradient is a primary determinant of community composition and that specific mycorrhizal fungi colonize decaying bark. Complementing our metabarcoding results with root tip morphotypification, we identify Laccaria amethystina and Tomentella sublilacina as key ectomycorrhizae of saplings on decaying logs. These findings demonstrate that Nanopore sequencing can provide valuable ecological insights and support its broader use in fungal metabarcoding as read quality continues to improve.