Selective forces shaping diversity in the class I region of the major histocompatibility complex in dairy cattle
Why this work is in the frame
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Bibliographic record
Abstract
The major histocompatibility complex (MHC) is one of the most diverse regions of the mammalian genome. Diversity in MHC genes is integral to their function in the immune system, and while pathogens play a key role in shaping this diversity, the contribution of other selective forces remains unclear. The controlled breeding of cattle offers an excellent model for the identification and exploration of these forces. We characterized the MHC class I genes present in a sample of Canadian Holstein A.I. bulls and compared the results with those obtained in an earlier study. No evidence for a reduction in MHC diversity over 20 years was observed, but the relative frequency of some haplotypes had changed: the formerly rare A12 (w12B) haplotype had become the most common, together with A15, while A19, which dominated the earlier sample, had significantly reduced in frequency. Only 7% of bulls in the current study were MHC homozygous compared with the 14% expected under Hardy-Weinberg. To identify the selective forces at work, a gene substitution model was used to calculate the effects of MHC on selection traits using estimated breeding values for each bull. Significant associations between MHC and production, disease and fertility traits were identified, suggesting that MHC diversity is not merely shaped by disease in this controlled breeding system. The decrease in a common haplotype, the reduced number of homozygous bulls and the associations with disease and production traits together indicate that MHC diversity in dairy cattle is maintained by heterozygote advantage.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it