An RB1CC1 Missense Variant in Nova Scotia Duck Tolling Retrievers with Degenerative Encephalopathy
Bibliographic record
Abstract
Background/Objectives: A slowly progressive hereditary neurological disorder classified as degenerative encephalopathy (DE) occurs in Nova Scotia Duck Tolling Retrievers. The disease is characterized by frequent episodes of pronounced involuntary movements during sleep, cognitive impairment, anxiety, heightened sensitivity to sensory stimuli, and compulsive behaviors. The clinical signs are accompanied by the degeneration of several brain regions. A study was undertaken to identify the molecular genetic basis of this disorder. Methods: Whole genome sequences (WGSs) from the DNA of affected and unaffected Nova Scotia Duck Tolling Retrievers were aligned to the Dog10K_Boxer_Tasha reference genome assembly and to the WGSs of 334 additional control dogs generated by this laboratory. Results: A missense C>T variant was identified in RB1CC1 exon 22 chromosome 29:4891014 that was uniquely homozygous in the affected dog. This variant predicts a p.G1503R change in the amino acid sequence of RB1CC1. Genotyping of 2950 Nova Scotia Duck Tolling Retrievers at the variant locus found complete concordance between the disease phenotype and RB1CC1 genotype. Conclusions: RBCC1 is an essential component of a protein complex that mediates the initiation of autophagosome formation. Therefore, it appears likely that the disease results, at least in part, from impaired autophagy. Consistent with this possibility, brain neurons of an affected dog were found to contain abnormal lysosomal storage body-like inclusions. This disorder could serve as a valuable model to elucidate the mechanisms underlying human diseases associated with impaired autophagy. Identification of the disease-causing DNA sequence variant will enable owners of Nova Scotia Duck Tolling Retrievers to screen their dogs for the RB1CC1 risk variant.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".