Independent Nonframeshift Deletions in the MC1R Gene Are Not Associated with Melanistic Coat Coloration in Three Mustelid Lineages
Bibliographic record
Abstract
Sequence variation within the 5' flanking (about 240 bp) and exon regions (426 bp) of the melanocortin-1 receptor (MC1R) gene was examined to determine the potential role of this protein in the melanistic coat coloration of 17 mustelid species in four genera: Gulo (wolverines), Martes (martens), Mustela (weasels), and Meles (badgers). Members of the genera Mustela and Meles, together with Martes flavigula and Martes pennanti, were shown to have intact gene sequences. However, several "in frame" deletions of the MC1R gene region implicated in melanism of other species were detected within members of the genera Martes and Gulo. For instance, Gulo gulo possessed a 15 bp deletion in the second transmembrane domain coding region, while Martes americana, Martes melampus, Martes zibellina, and Martes martes shared a 45 bp deletion overlapping this area. In addition, Martes foina was found to possess a 10 bp insertion followed closely by a 28 bp deletion immediately downstream of the deletion found in other martens. Notably, none of these indels was associated with a melanistic phenotype. Phylogenetic analysis revealed that each of these nonrandomly distributed deletions arose independently during the evolution of this family. Specific indel-neighboring motifs appear to largely account for the biased and repeated occurrence of deletion events in the Martes/Gulo clade.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".