DLA-DRB1, DQA1, and DQB1 Alleles and Haplotypes in North American Gray Wolves
Bibliographic record
Abstract
The canine major histocompatibility complex contains highly polymorphic genes, many of which are critical in regulating immune response. Since domestic dogs evolved from Gray Wolves (Canis lupus), common DLA class II alleles should exist. Sequencing was used to characterize 175 Gray Wolves for DLA class II alleles, and data from 1856 dogs, covering 85 different breeds of mostly European origin, were available for comparison. Within wolves, 28 new alleles were identified, all occurring in at least 2 individuals. Three DLA-DRB1, 8 DLA-DQA1, and 6 DLA-DQB1 alleles also identified in dogs were present. Twenty-eight haplotypes were identified, of which 2 three-locus haplotypes, and many DLA-DQA1/DQB1 haplotypes, are also found in dogs. The wolves studied had relatively few dog DLA alleles and may therefore represent a remnant population descended from Asian wolves. The single European wolf included carried a haplotype found in both these North American wolves and in many dog breeds. Furthermore, one wolf DQB1 allele has been found in Shih Tzu, a breed of Asian origin. These data suggest that the wolf ancestors of Asian and European dogs may have had different gene pools, currently reflected in the DLA alleles present in dog breeds.
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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".