Two <i><scp>MC</scp>1R</i> loss‐of‐function alleles in cream‐coloured Australian Cattle Dogs and white Huskies
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.
Bibliographic record
Abstract
Summary Loss‐of‐function variants in the MC 1R gene cause recessive red or yellow coat‐colour phenotypes in many species. The canine MC 1R :c.916C>T (p.Arg306Ter) variant is widespread and found in a homozygous state in many uniformly yellow‐ or red‐coloured dogs. We investigated cream‐coloured Australian Cattle Dogs whose coat colour could not be explained by this variant. A genome‐wide association study with 10 cream and 123 red Australian Cattle Dogs confirmed that the cream locus indeed maps to MC 1R . Whole‐genome sequencing of cream dogs revealed a single nucleotide variant within the MITF binding site of the canine MC 1R promoter. We propose to designate the mutant alleles at MC 1R :c.916C>T as e 1 and at the new promoter variant as e 2 . Both alleles segregate in the Australian Cattle Dog breed. When we considered both alleles in combination, we observed perfect association between the MC 1R genotypes and the cream coat colour phenotype in a cohort of 10 cases and 324 control dogs. Analysis of the MC 1R transcript levels in an e 1 /e 2 compound heterozygous dog confirmed that the transcript levels of the e 2 allele were markedly reduced with respect to the e 1 allele. We further report another MC 1R loss‐of‐function allele in Alaskan and Siberian Huskies caused by a 2‐bp deletion in the coding sequence, MC 1R :c.816_817del CT . We propose to term this allele e 3 . Huskies that carry two copies of MC 1R loss‐of‐function alleles have a white coat colour.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it