Evidence map›Paper›PMID 41294086›Full record

ArticleMolecular ecology resources2026

Advancing Yeast Identification Using High-Throughput DNA Barcode Data From a Curated Culture Collection.

Duong Vu, Michel de Vries, Bert Gerrits van den Ende, Jos Houbraken, R Henrik Nilsson, Balázs Brankovics, Margarita Hernández‐Restrepo, Johannes Z Groenewald, Pedro W Crous, Ferry Hagen and 3 more

Erratum issuedAbstract read
In one paragraph

Article in Molecular ecology resources, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Duong VuWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.ORCID 0000-0001-7960-2765
Michel de VriesWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Bert Gerrits van den EndeWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Jos HoubrakenWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
R Henrik NilssonDepartment of Biological & Environmental Sciences, Gothenburg Global Biodiversity Centre, University of Gothenburg, Göteborg, Sweden.ORCID 0000-0002-8052-0107
Balázs BrankovicsWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Margarita Hernández‐RestrepoWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Johannes Z GroenewaldWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Pedro W CrousWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Ferry HagenWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Wieland MeyerWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Gerard J M VerkleyWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.
Marizeth GroenewaldWesterdijk Fungal Biodiversity Institute, Utrecht, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Yeast identification is essential in fields ranging from microbiology and biotechnology to food science and medicine. While DNA barcoding has become the standard for identifying cultured strains, environmental DNA (eDNA) metabarcoding has revolutionised microbial community profiling, providing deeper insights into yeast communities across diverse ecosystems. A major challenge in DNA (meta)barcoding remains the limited availability of high-quality reference sequences, which are critical for accurate species identification and comprehensive taxonomic profiling of both environmental and clinical samples. To address this gap, the Westerdijk Fungal Biodiversity Institute (WI) launched a DNA barcoding initiative in 2006 to generate high-quality, often type-derived ITS and LSU barcodes for all ~100,000 fungal strains preserved in the CBS culture collection, including approximately 15,000 yeasts. Building on the yeast barcode dataset released in 2016, we now present an expanded set of 2856 ITS and 3815 LSU sequences, representing 911 and 1137 yeast species, respectively. Notably, 27%-29% of these sequences are derived from ex-type cultures. Using both newly generated and previously published barcodes, we assess the taxonomic resolution of commonly used yeast metabarcoding markers (ITS, ITS1, ITS2 and LSU) and propose marker-specific similarity cutoffs for different yeast taxonomic groups. These results provide actionable guidance for marker selection and improve the interpretation of metabarcoding data. We further demonstrate the impact of well-curated reference databases with up-to-date taxonomy by reanalyzing Human Microbiome Project data, revealing how diet and environment shape the gut mycobiota.

Indexed as

DNA Barcoding, TaxonomicYeastsDNA, FungalDNA, Ribosomal SpacerHigh-Throughput Nucleotide SequencingSequence Analysis, DNADNA, FungalDNA, Ribosomal SpacerDNA barcodingeDNA metabarcodingsimilarity cutoffyeast identification

Identifiers

PMID41294086
PMCPMC12649295

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.