Identification of candidate markers on bovine chromosome 14 (BTA14) under milk production trait quantitative trait loci in Holstein
Bibliographic record
Abstract
The objective of this study was to identify single-nucleotide polymorphisms using a bovine chromosome 14 high-density SNP panel after accounting for the effect of DGAT1. Linkage disequilibrium information and sire heterozygosity were used to select markers for linkage analysis on bovine chromosome 14 for milk production traits in 321 Holstein animals. Results show putative milk peaks at 42 and 61 cM, both at p<0.10, a fat yield peak at 42 and 63 cM, both at p<0.05; a protein yield peak at 42 (p<0.01) and 84 cM (p<0.05); fat per cent peaks at 3 (p<0.01) and 29 cM (p<0.05), and a protein per cent peak at 4 cM (p<0.05). Once quantitative trait loci positions were established, allele substitution effects for all markers were evaluated using the same statistical model. Overlaying information between quantitative trait loci (QTL) and allele effect analysis enabled the identification (p<0.01) of 20 SNPs under the milk yield QTL, 2 under both of the fat yield peaks, 8 and 9 under the protein yield peaks, 2 and 6 for the fat per cent peaks and 5 for the protein per cent peak. One SNP in particular, ss61514555:A>C, showed association with 3 of the 5 traits: milk (p=1.59E-04), fat (p=6.88E-05) and protein yields (p=5.76E-05). Overall, combining information from linkage disequilibrium, sire heterozygosity and genetic knowledge of traits enabled the characterization of additional markers with significant associations with milk production traits.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".