Agouti Sequence Polymorphisms in Coyotes, Wolves and Dogs Suggest Hybridization
Bibliographic record
Abstract
Domestic dogs have been shown to have multiple alleles of the Agouti Signal Peptide (ASIP) in exon 4 and we wished to determine the level of polymorphism in the common wild canids of Canada, wolves and coyotes, in comparison. All Canadian coyotes and most wolves have banded hairs. The ASIP coding sequence of the wolf did not vary from the domestic dog but one variant was detected in exon 4 of coyotes that did not alter the arginine at this position. Two other differences were found in the sequence flanking exon 4 of coyotes compared with the 45 dogs and 1 wolf. The coyotes also demonstrated a relatively common polymorphism in the 3' UTR sequence that could be used for population studies. One of the ASIP alleles (R96C) in domestic dogs causes a solid black coat color in homozygotes. Although some wolves are melanistic, this phenotype does not appear to be caused by this same mutation. However, one wolf, potentially a dog-wolf hybrid or descendant thereof, was heterozygous for this allele. Likewise 2 coyotes, potentially dog-coyote or wolf-coyote hybrid descendants, were heterozygous for the several polymorphisms in and flanking exon 4. We could conclude that these were coyote-dog hybrids because both were heterozygous for 2 mutations causing fawn coat color in dogs.
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 | 0.000 |
| 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) | 0.001 | 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".