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A comprehensive, automatically updated fungal ITS sequence dataset for reference-based chimera control in environmental sequencing efforts

Journal article
Authors R. Henrik Nilsson
Leho Tedersoo
Martin Ryberg
Erik Kristiansson
Martin Hartmann
Martin Unterseher
Teresita M. Porter
Johan Bengtsson-Palme
Donald M. Walker
Filipe de Sousa
Hannes Andres Gamper
Ellen Larsson
Karl-Henrik Larsson
Urmas Kõljalg
Robert C. Edgar
Kessy Abarenkov
Published in Microbes and Environments
Volume 30
Issue 2
Pages 145-150
ISSN 1342-6311
Publication year 2015
Published at Department of Mathematical Sciences, Mathematical Statistics
Department of Biological and Environmental Sciences
Institute of Biomedicine, Department of Infectious Medicine
Pages 145-150
Language en
Keywords fungi, chimera detection, reference dataset, molecular ecology, PCR artifacts
Subject categories Bioinformatics (Computational Biology), Microbiology, Bioinformatics and Systems Biology, Terrestrial ecology, Biological Systematics, Medical microbiology, Soil biology, Microbiology and immunology


The nuclear ribosomal internal transcribed spacer (ITS) region is the most commonly chosen genetic marker for the molecular identification of fungi in environmental sequencing and molecular ecology studies. Several analytical issues complicate such efforts, one of which is the formation of chimeric—artificially joined—DNA sequences during PCR amplification or sequence assembly. Several software tools are currently available for chimera detection, but rely to various degrees on the presence of a chimera-free reference dataset for optimal performance. However, no such dataset is available for use with the fungal ITS region. This study introduces a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database for the molecular identification of fungi. This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. The performance of the dataset on a large set of artificial chimeras was above 99.5%, and we subsequently used the dataset to remove nearly 1,000 compromised fungal ITS sequences from public circulation. The dataset is available at and is subject to web-based third-party curation.

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