A New Mutation in MC1R Explains a Coat Color Phenotype in 2 “Old” Breeds: Saluki and Afghan Hound
Bibliographic record
Abstract
Melanocortin 1 Receptor (MC1R) has been studied in a wide variety of domestic animals (Klungland et al. 1995; Marklund et al. 1996; Våge et al. 1997; Kijas et al. 1998; Newton et al. 2000; Våge et al. 2003), and also several wild animals (Robbins et al. 1993; Ritland et al. 2001; Eizirik et al. 2003; Nachman et al. 2003; McRobie et al. 2009) in relation to coat color variation. A variety of phenotypic changes have been reported including coat colors from pure black to pure red, as well as some phenotypes with hairs with red and black bands. One phenotype, called grizzle in Salukis and domino in Afghan Hounds, appears to be unique to these 2 old dog breeds. This pattern is characterized by a pale face with a widow's peak above the eyes. The body hairs on the dorsal surface of Salukis and Afghan Hounds have both phaeomelanin and eumelanin portions, even though they had an a(t)/a(t) genotype at ASIP. In addition, all had at least one copy of a newly identified mutation in MC1R, g.233G>T, resulting in p.Gly78Val. This new allele, that we suggest be designated as E(G), is dominant to the E and e (p.Arg306ter) alleles at MC1R but recessive to the E(M) (p.Met264Val) allele. The K(B) allele (p.Gly23del) at DEFB103 and the a(y) allele (p.Ala82Ser and p.Arg83His) of ASIP are epistatic to grizzle and domino.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".