A Rapid Detection Method for the Ryanodine Receptor 1 (C7360G) Mutation in Quarter Horses
Bibliographic record
Abstract
BACKGROUND: Anesthetic-induced malignant hyperthermia has been documented in Quarter Horses and is caused by a single-point mutation in the ryanodine receptor 1 gene at nucleotide C7360G generating a R2454G amino acid substitution. An accurate, faster molecular test that is less prone to contamination would facilitate screening for the mutation in horses intended for breeding, in those undergoing surgical procedures, and in those with clinical signs compatible with malignant hyperthermia. OBJECTIVE: To report a rapid and accurate method for the detection of the ryanodine receptor 1 C7360G mutation. ANIMALS: Eleven diseased, 10 healthy, and 225 randomly selected Quarter Horses. METHODS: This study included horses with the ryanodine receptor 1 C7360G mutation as detected by gene sequencing. Available genomic and complementary DNA extracted from whole blood, hair or skeletal muscle was used for genetic analysis. Real-time polymerase chain reaction (RT-PCR) melting curve analysis was performed by equine specific primers and 2 hybridization probes (sensor and anchor probes) that contain the site of the mutation. Results from this method were blinded and compared with nucleic acid sequencing for validation. RESULTS: A rapid genotyping assay with fluorescence resonance energy transfer probes and melting curve analysis was accurate (100% agreement, K= 1) for identification of affected horses. The prevalence of the mutation in a random population of Quarter Horses was 1.3%. CONCLUSIONS AND CLINICAL IMPORTANCE: Malignant hyperthermia in Quarter Horses can be rapidly and accurately detected by RT-PCR melting curve genotyping with hybridization probes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".