Next-Generation Sequencing of Ancient and Recent Fungarium Specimens

Singleton-based species names and fungal rarity: Does the number really matter?

Fungi are among the least known organisms on earth, with an estimated number of species between 1.5 and 10 million. This number is expected to be refined, especially with increasing knowledge about microfungi in undersampled habitats and increasing amounts of data derived from environmental DNA sequencing. A significant proportion of newly generated sequences fail to match with already named species, and thus represent what has been referred to as fungal "dark taxa". Due to the challenges associated with observing, identifying, and preserving sporophores, many macro- and microfungal species are only known from a single collection, specimen, isolate, and/or sequence-a singleton. Mycologists are consequently used to working with "rare" sequences and specimens. However, rarity and singleton phenomena lack consideration and valorization in fungal studies. In particular, the practice of publishing new fungal species names based on a single specimen remains a cause of debate. Here, we provide some elements of reflection on this issue in the light of the specificities of the fungal kingdom and global change context. If multiple independent sources of data support the existence of a new taxon, we encourage mycologists to proceed with formal description, irrespective of the number of specimens at hand. Although the description of singleton-based species may not be considered best practice, it does represent responsible science in the light of closing the Linnean biodiversity shortfall.

Does One Size Fit All? Variations in the DNA Barcode Gaps of Macrofungal Genera

The nuclear ribosomal internal transcribed spacer (nrITS) region has been widely used in fungal diversity studies. Environmental metabarcoding has increased the importance of the fungal DNA barcode in documenting fungal diversity and distribution. The DNA barcode gap is seen as the difference between intra- and inter-specific pairwise distances in a DNA barcode. The current understanding of the barcode gap in macrofungi is limited, inhibiting the development of best practices in applying the nrITS region toward research on fungal diversity. This study examined the barcode gap using 5146 sequences representing 717 species of macrofungi from eleven genera, eight orders and two phyla in datasets assembled by taxonomic experts. Intra- and inter-specific pairwise distances were measured from sequence and phylogenetic data. The results demonstrate that barcode gaps are influenced by differences in intra- and inter-specific variance in pairwise distances. In terms of DNA barcode behavior, variance is greater in the ITS1 than ITS2, and variance is greater in both relative to the combined nrITS region. Due to the difference in variance, the barcode gaps in the ITS2 region are greater than in the ITS1. Additionally, the taxonomic approach of "splitting" taxa into numerous taxonomic units produces greater barcode gaps when compared to "lumping". The results show variability in the barcode gaps between fungal taxa, demonstrating a need to understand the accuracy of DNA barcoding in quantifying species richness. For taxonomic studies, variability in nrITS sequence data supports the application of multiple molecular markers to corroborate the taxonomic and systematic delineation of species.

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 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.