Genes affecting coat colour and pattern in domestic dogs: a review
Bibliographic record
Abstract
Tremendous progress has been made in identifying genes involved in pigmentation in dogs in the past few years. Comparative genomics has both aided and benefited from these findings. Seven genes that cause specific coat colours and/or patterns in dogs have been identified: melanocortin 1 receptor, tyrosinase related protein 1, agouti signal peptide, melanophilin, SILV (formerly PMEL17), microphthalmia-associated transcription factor and beta-defensin 103. Although not all alleles have been yet identified at each locus, DNA tests are available for many. The identification of these alleles has provided information on interactions in this complex set of genes involved in both pigmentation and neurological development. The review also discusses pleiotropic effects of some coat colour genes as they relate to disease. The alleles found in various breeds have shed light on some potential breed development histories and phylogenetic relationships. The information is of value to dog breeders who have selected for and against specific colours since breed standards and dog showing began in the late 1800s. Because coat colour is such a visible trait, this information will also be a valuable teaching resource.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".