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Record W2945193283 · doi:10.3390/jof5020039

A Universally Primed-Polymerase Chain Reaction (UP-PCR) Marker to Discriminate Clonostachys rosea ACM941 from Related Strains

2019· article· en· W2945193283 on OpenAlexaffabout
Zerihun A. Demissie, William G. Brown, Michèle C. Loewen

Bibliographic record

VenueJournal of Fungi · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsWilfrid Laurier UniversityQueen's UniversityUniversity of OttawaNational Research Council Canada
FundersOffice of ScienceJoint Genome InstituteU.S. Department of Energy
KeywordsBiologyPolymerase chain reactionMolecular markerStrain (injury)Primer (cosmetics)GenomeFusariumGeneticsGene

Abstract

fetched live from OpenAlex

Clonostachys rosea strain ACM941 is an effective biocontrol agent against several crop diseases including Fusarium head blight. In anticipation of its increased relevance going forward, the development of a reliable DNA-based molecular marker to track it is essential. Universally primed-PCR (UP-PCR) has been used successfully to differentiate other C. rosea strains. Herein, the development of a UP-PCR marker for ACM941 is described. A combination of two primers (AS15 and L45) produced a ~450 bp fragment that was unique to ACM941 compared to other commercial biocontrol agents. Primers subsequently designed based on the obtained fragment also produced a similarly unique band from ACM941 alone. BLAST analysis of the amplified sequence did not yield any homologous sequence in available online databases or within the closely related C. rosea IK726 and CBS125111 strains’ genomes. The specificity of this marker for ACM941 was validated against ten additional C. rosea strains isolated from Canada, with ACM941 producing the brightest band. Taken together, these results imply that the UP-PCR primers AS15 and L45 and the amplified fragment can be used to detect and monitor the ACM941 strain after its release into the environment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.589

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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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

Citations9
Published2019
Admission routes2
Has abstractyes

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