The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications

Rolf Henrik Nilsson (Corresponding Author), Karl-Henrik Larsson, Andy F S Taylor, Johan Bengtsson-Palme, Thomas S Jeppesen, Dmitry Schigel, Peter Kennedy, Kathryn Picard, Frank Oliver Glöckner, Leho Tedersoo, Irja Saar, Urmas Kõljalg, Kessy Abarenkov

Research output: Contribution to journalArticle

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Abstract

UNITE (https://unite.ut.ee/) is a web-based database and sequence management environment for the molecular identification of fungi. It targets the formal fungal barcode-the nuclear ribosomal internal transcribed spacer (ITS) region-and offers all ∼1 000 000 public fungal ITS sequences for reference. These are clustered into ∼459 000 species hypotheses and assigned digital object identifiers (DOIs) to promote unambiguous reference across studies. In-house and web-based third-party sequence curation and annotation have resulted in more than 275 000 improvements to the data over the past 15 years. UNITE serves as a data provider for a range of metabarcoding software pipelines and regularly exchanges data with all major fungal sequence databases and other community resources. Recent improvements include redesigned handling of unclassifiable species hypotheses, integration with the taxonomic backbone of the Global Biodiversity Information Facility, and support for an unlimited number of parallel taxonomic classification systems.

Original languageEnglish
Pages (from-to)D259-264
Number of pages6
JournalNucleic Acids Research
Volume47
Issue numberD1
Early online date29 Oct 2018
DOIs
Publication statusPublished - 8 Jan 2019

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Keywords

  • DNA
  • MARKER
  • SEARCH
  • SEQUENCE
  • SOFTWARE
  • TOOL

ASJC Scopus subject areas

  • Genetics

Cite this

Nilsson, R. H., Larsson, K-H., Taylor, A. F. S., Bengtsson-Palme, J., Jeppesen, T. S., Schigel, D., ... Abarenkov, K. (2019). The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research, 47(D1), D259-264. https://doi.org/10.1093/nar/gky1022