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Record W2912296822 · doi:10.1371/journal.pone.0210165

Development and validation of probe-based multiplex real-time PCR assays for the rapid and accurate detection of freshwater fish species

2019· article· en· W2912296822 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsNOSM UniversityLaurentian University
FundersUniversity of British ColumbiaMitacsMcMaster UniversityWashington and Lee UniversityBruce PowerUniversity of Florida
KeywordsBiologyCoregonus clupeaformisPrimer (cosmetics)MicropterusMultiplexBass (fish)ZoologyFisheryGeneticsChemistryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Reliable species identification methods are important for industrial environmental monitoring programs. Probe based real-time quantitative polymerase chain reaction (qPCR) provides an accurate, cost-effective and high-throughput method for species identification. Here we present the development and validation of species-specific primers and probes for the cytochrome c oxidase (COI) gene for the identification of eight ecologically and economically important freshwater fish species: lake whitefish (Coregonus clupeaformis), yellow perch (Perca flavescens), rainbow smelt (Osmerus mordax), brook trout (Salvelinus fontinalis), smallmouth bass (Micropterus dolomieu), round whitefish (Prosopium cylindraceum), spottail shiner (Notropis hudsonius) and deepwater sculpin (Myoxocephalus thompsonii). In order to identify novel primer-probe sets with maximum species-specificity, two separate primer-probe design criteria were employed. Highest ranked primer-probe sets from both methods were assayed to identify sequences that demonstrated highest specificity. Specificity was determined using control species from same genus and non-target species from different genus. Selected primer-probe sets were optimized for annealing temperature and primer-probe concentrations to identify minimum reagent parameters. The selected primer-probe sets were highly sensitive, with DNA concentrations as low as 1 ng adequate for positive species identification. A decoder algorithm was developed based on the cumulative qPCR results that allowed for full automation of species identification. Blinded experiments revealed that the combination of the species-specific primer/probes sets with the automated species decoder resulted in target species identification with 100% accuracy. We also conducted a cost/time comparison analysis between the qPCR assays established in this study with other species identification methods. The qPCR technique was the most cost-effective and least time consuming method of species identification. In summary, probe-based multiplex qPCR assays provide a rapid and accurate method for freshwater fish species identification, and the methodology established in this study can be utilized for various other species identification initiatives.

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.

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 score0.011
Threshold uncertainty score0.172

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 head0.052
GPT teacher head0.237
Teacher spread0.185 · 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