Applying a Modified Metabarcoding Approach for the Sequencing of Macrofungal Specimens from Fungarium Collections

Premise: Fungaria are an underutilized resource for understanding fungal biodiversity. The effort and cost of producing DNA barcode sequence data for large numbers of fungal specimens can be prohibitive. This study applies a modified metabarcoding approach that provides a labor-efficient and cost-effective solution for sequencing the fungal DNA barcodes of hundreds of specimens at once.

Methods: We applied a two-step PCR approach using nested, barcoded primers to sequence the fungal nrITS2 region of 766 macrofungal specimens using the Illumina platform. The specimens represent a broad taxonomic sampling of the Dikarya. Of these, 382 specimens were analyzed to identify molecular operational taxonomic units (MOTUs) using a phylogenetic approach. The raw sequences were trimmed, filtered, assessed, and analyzed using the DADA2 amplicon de-noising toolkit and Biopython. The sequences were compared to the NCBI and UNITE databases and Sanger nrITS sequences from the same specimens.

Results: The taxonomic identities derived from the nrITS2 sequence data were >90% accurate across all specimens sampled. A phylogenetic analysis of the sequences identified 20 MOTUs.

Discussion: The results demonstrate the capacity of these methods to produce nrITS2 sequences from large numbers of fungarium specimens. This provides an opportunity to more effectively use fungarium collections to advance fungal diversity identification and documentation.