Genetic Structure of Susceptibility Traits for Hip Dysplasia and Microsatellite Informativeness of an Outcrossed Canine Pedigree
Bibliographic record
Abstract
An outcrossed canine pedigree was developed for quantitative trait locus (QTL) mapping of hip dysplasia by breeding dysplastic Labrador retrievers to trait-free greyhounds. Measured susceptibility traits included age at onset of femoral capital chondroepiphyseal ossification (OSS), maximum hip distraction (laxity) index (DI), and the dorsolateral subluxation (DLS) score. The pedigrees consisted of 147 dogs representing four generations. For 59 dogs genotyped with 65 microsatellites, the median heterozygosity and polymorphic information content (PIC) values of the F(1) generation were 0.82 and 0.68, respectively. Seventy-seven percent of microsatellites had a PIC greater than 0.59 in the F(1)s. Ninety-six percent of alleles showed Mendelian inheritance. Based on marker informativeness, approximately 350 randomly selected markers would be required for genome-wide screening to obtain an average interval between informative markers of 10 cM. Heritability was estimated as 0.43, 0.5, and 0.61 for OSS, DI, and the DLS score, respectively. Biometric estimates of the mean (+/- variance) effective number of segregating QTLs was 1.2 (+/- 0.05), 0.8 (+/- 0.02), and 1.0 (+/- 0.03) for OSS, DI, and the DLS score, respectively. The distributions of simulated backcross trait data suggested that the loci controlling these traits acted additively and that the DI may be controlled by a major locus. When combined with previous power and quantitative genetic analyses, these estimates indicate that this pedigree is informative for QTL mapping of hip dysplasia traits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".