Introducing ribosomal tandem repeat barcoding for fungi
Journal article, 2019
Sequence comparison and analysis of the various ribosomal genetic markers are the dominant molecular methods for identification and description of fungi. However, new environmental fungal lineages known only from DNA data reveal significant gaps in our sampling of the fungal kingdom in terms of both taxonomy and marker coverage in the reference sequence databases. To facilitate the integration of reference data from all of the ribosomal markers, we present three sets of general primers that allow for amplification of the complete ribosomal operon from the ribosomal tandem repeats. The primers cover all ribosomal markers: ETS, SSU, ITS1, 5.8S, ITS2, LSU and IGS. We coupled these primers successfully with third-generation sequencing (PacBio and Nanopore sequencing) to showcase our approach on authentic fungal herbarium specimens (Basidiomycota), aquatic chytrids (Chytridiomycota) and a poorly understood lineage of early diverging fungi (Nephridiophagidae). In particular, we were able to generate high-quality reference data with Nanopore sequencing in a high-throughput manner, showing that the generation of reference data can be achieved on a regular desktop computer without the involvement of any large-scale sequencing facility. The quality of the Nanopore generated sequences was 99.85%, which is comparable with the 99.78% accuracy described for Sanger sequencing. With this work, we hope to stimulate the generation of a new comprehensive standard of ribosomal reference data with the ultimate aim to close the huge gaps in our reference datasets.
Sanger
PacBio
ribosomal operon
IGS
third-generation sequencing
Nanopore
Author
Christian Wurzbacher
University of Gothenburg
Gothenburg Global Biodiversity Centre
Technical University of Munich
Ellen Larsson
University of Gothenburg
Gothenburg Global Biodiversity Centre
Johan Bengtsson Palme
University of Gothenburg
University of Wisconsin Madison
Silke Van den Wyngaert
Leibniz-Institute of Freshwater Ecology and Inland Fisheries
Sten Svantesson
University of Gothenburg
Gothenburg Global Biodiversity Centre
Erik Kristiansson
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
University of Gothenburg
Maiko Kagami
Leibniz-Institute of Freshwater Ecology and Inland Fisheries
Yokohama National University
Toho University
R. Henrik Nilsson
Gothenburg Global Biodiversity Centre
University of Gothenburg
Molecular Ecology Resources
1755-098X (ISSN) 1755-0998 (eISSN)
Vol. 19 1 118-127Subject Categories
Biological Systematics
Bioinformatics (Computational Biology)
Bioinformatics and Systems Biology
DOI
10.1111/1755-0998.12944
PubMed
30240145