Analysis of genomic copy number variation in equine recurrent airway obstruction (heaves)
Bibliographic record
Abstract
We explored the involvement of genomic copy number variants (CNVs) in susceptibility to recurrent airway obstruction (RAO), or heaves-an asthmalike inflammatory disease in horses. Analysis of 16 RAO-susceptible (cases) and six RAO-resistant (control) horses on a custom-made whole-genome 400K equine tiling array identified 245 CNV regions (CNVRs), 197 previously known and 48 new, distributed on all horse autosomes and the X chromosome. Among the new CNVRs, 30 were exclusively found in RAO cases and were further analyzed by quantitative PCR, including additional cases and controls. Suggestive association (P = 0.03; corrected P = 0.06) was found between RAO and a loss on chromosome 5 involving NME7, a gene necessary for ciliary functions in lungs and involved in primary ciliary dyskinesia in humans. The CNVR could be a potential marker for RAO susceptibility but needs further study in additional RAO cohorts. Other CNVRs were not associated with RAO, although several involved genes of interest, such as SPI2/SERPINA1 from the serpin gene family, which are associated with chronic obstructive pulmonary disease and asthma in humans. The SPI2/SERPINA1 CNVR showed striking variation among horses, but it was not significantly different between RAO cases and controls. The findings provide baseline information on the relationship between CNVs and RAO susceptibility. Discovery of new CNVs and the use of a larger population of RAO-affected and control horses are needed to shed more light on their significance in modulating this complex and heterogeneous disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".