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 Lactarius 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 Lactarius 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.
Premise: Fungaria are a largely untapped source for understanding fungal biodiversity. The effort and cost in 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 and cost-effective solution for sequencing the fungal DNA barcode from hundreds of specimens at once. Methods: A two-step PCR approach uses nested barcoded primers to nrITS2 sequence data. We applied this to 766 macrofungal specimens that represent a broad taxonomic sampling of the Dikarya, of which 382 Lactarius specimens are used to identify molecular operational taxonomic units (MOTUs) through a phylogenetic approach. Scripts in Python and R were used to organize sequence data and execute packages CutAdapt and DADA2 were used for primer removal and assessing sequence quality. Sequences were compared to NCBI and UNITE databases and Sanger-produced sequences. Results: Specimen taxonomic identities from nrITS2 sequence data are >90% accurate across all specimens sampled. Phylogenetic analysis of Lactarius 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 in advancing fungal diversity identification and documentation.
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