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Evaluation of mitochondrial genes as DNA barcode for Basidiomycota

2009· article· en· W1995226895 on OpenAlexafffund
Agathe Vialle, Nicolas Feau, Mathieu Allaire, Maryna Ya. Didukh, Francis Martin, Jean‐Marc Moncalvo, Richard C. Hamelin

Bibliographic record

VenueMolecular Ecology Resources · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsUniversité LavalCenter for Northern StudiesUniversity of TorontoNatural Resources CanadaCanadian Forest Service
FundersNatural Sciences and Engineering Research Council of CanadaGenome Canada
KeywordsBiologyNADH dehydrogenaseDNA barcodingMitochondrial DNACytochrome c oxidaseGeneBarcodeCytochrome c oxidase subunit IGeneticsIn silicoRespiratory chainProtein subunitMitochondrial respiratory chainCytochrome bMitochondrionMolecular biologyEvolutionary biology

Abstract

fetched live from OpenAlex

Our study evaluated in silico the potential of 14 mitochondrial genes encoding the subunits of the respiratory chain complexes, including cytochrome c oxidase I (CO1), as Basidiomycota DNA barcode. Fifteen complete and partial mitochondrial genomes were recovered and characterized in this study. Mitochondrial genes showed high values of molecular divergence, indicating a potential for the resolution of lower-level relationships. However, numerous introns occurred in CO1 as well as in six other genes, potentially interfering with polymerase chain reaction amplification. Considering these results and given the minimal length of 600-bp that is optimal for a fungal barcode, the genes encoding for the ATPase subunit 6, the cytochrome oxidase subunit 3 and the NADH dehydrogenase subunit 6 have the most promising characteristics for DNA barcoding among the mitochondrial genes studied. However, biological validation on two fungal data sets indicated that no single mitochondrial gene gave a better taxonomic resolution than the ITS, the region already widely used in fungal taxonomy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.266
Teacher spread0.254 · 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 teacher head, not a consensus.

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

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

Citations117
Published2009
Admission routes2
Has abstractyes

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