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Record W2240081306 · doi:10.3767/003158515x689135

One fungus, which genes? Development and assessment of universal primers for potential secondary fungal DNA barcodes

2015· article· en· W2240081306 on OpenAlexafffund
J. Benjamin Stielow, C. André Lévesque, Keith A. Seifert, Wieland Meyer, László Irinyi, Daphne J. Smits, R. Renfurm, G.J.M. Verkley, Marizeth Groenewald, Delphine Chaduli, Anne Lomascolo, Stéphane Welti, Laurence Lesage‐Meessen, Anne Favel, Abdullah M. S. Al‐Hatmi, Ulrike Damm, Neriman Yılmaz, Jos Houbraken, L. Lombard, William Quaedvlieg, M. Binder, Lea Vaas, Duong Vu, Andrey Yurkov, Dominik Begerow, O. Roehl, Marco Alexandre Guerreiro, Álvaro Fonseca, Kittipan Samerpitak, Anne D. van Diepeningen, Somayeh Dolatabadi, Leandro F. Moreno, Serge Casarégola, Sandrine Mallet, Noémie Jacques, Luca Roscini, Eleonora Egidi, Chantal Bizet, Dea Garcia‐Hermoso, María P. Martín, Siwen Deng, J.Z. Groenewald, Teun Boekhout, Z. Wilhelm de Beer, Irene Barnes, Tuan A. Duong, Michael J. Wingfield, Sybren de Hoog, P.W. Crous, Christopher T. Lewis, Sarah Hambleton, Tarek A. A. Moussa, Hassan Alzahrani, Omar A. Almaghrabi, Gerry Louis-Seize, R. Assabgui, Wayne McCormick, Karolina Dukik, Gianluigi Cardinali, Ursula Eberhardt, Michèl de Vries, Vincent Robert

Bibliographic record

VenuePersoonia - Molecular Phylogeny and Evolution of Fungi · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsAlberta Biodiversity Monitoring InstituteAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaKing Abdulaziz UniversityMedical Research CouncilAlfred P. Sloan Foundation
KeywordsBiologyPrimer (cosmetics)GeneticsRibosomal RNAGeneElongation factorInternal transcribed spacerRNAPolymerase chain reactionMolecular biologyComputational biologyRibosome

Abstract

fetched live from OpenAlex

The aim of this study was to assess potential candidate gene regions and corresponding universal primer pairs as secondary DNA barcodes for the fungal kingdom, additional to ITS rDNA as primary barcode. Amplification efficiencies of 14 (partially) universal primer pairs targeting eight genetic markers were tested across > 1 500 species (1 931 strains or specimens) and the outcomes of almost twenty thousand (19 577) polymerase chain reactions were evaluated. We tested several well-known primer pairs that amplify: i) sections of the nuclear ribosomal RNA gene large subunit (D1-D2 domains of 26/28S); ii) the complete internal transcribed spacer region (ITS1/2); iii) partial β -tubulin II (TUB2); iv) γ-actin (ACT); v) translation elongation factor 1-α (TEF1α); and vi) the second largest subunit of RNA-polymerase II (partial RPB2, section 5-6). Their PCR efficiencies were compared with novel candidate primers corresponding to: i) the fungal-specific translation elongation factor 3 (TEF3); ii) a small ribosomal protein necessary for t-RNA docking; iii) the 60S L10 (L1) RP; iv) DNA topoisomerase I (TOPI); v) phosphoglycerate kinase (PGK); vi) hypothetical protein LNS2; and vii) alternative sections of TEF1α. Results showed that several gene sections are accessible to universal primers (or primers universal for phyla) yielding a single PCR-product. Barcode gap and multi-dimensional scaling analyses revealed that some of the tested candidate markers have universal properties providing adequate infra- and inter-specific variation that make them attractive barcodes for species identification. Among these gene sections, a novel high fidelity primer pair for TEF1α, already widely used as a phylogenetic marker in mycology, has potential as a supplementary DNA barcode with superior resolution to ITS. Both TOPI and PGK show promise for the Ascomycota, while TOPI and LNS2 are attractive for the Pucciniomycotina, for which universal primers for ribosomal subunits often fail.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.224
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations571
Published2015
Admission routes2
Has abstractyes

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