Fine mapping of quantitative trait loci and assessment of positional candidate genes for backfat on bovine chromosome 14 in a commercial line of Bos taurus1
Bibliographic record
Abstract
Backfat thickness is one of the major quantitative traits that affect carcass quality in beef cattle. In this study, we have fine mapped a QTL for backfat EBV on bovine chromosome 14, using an identical-by-descent haplotype-sharing analysis, in a commercial line of Bos taurus. We also examined the association between gene-specific single nucleotide polymorphism (SNP) markers of the genes diacylgcerol acyltransferase 1 (DGAT1) and thyroglobulin (TG) and the backfat EBV. The results indicate that the QTL region for backfat identified on chromosome 14 is in agreement with previous studies. However, neither of the two polymorphisms of candidate genes tested, DGAT1 nor TG, showed a significant (P > 0.10) association with the backfat EBV in the cattle populations examined. However, a strong association (P = 0.0058) was detected between a microsatellite marker (CSSM66) lying approximately mid-way between the two candidate genes and the backfat EBV. These results suggest that other SNP of DGAT1, TG, or other gene(s) in the chromosomal region should be examined to test whether they have a significant effect on lipid metabolism.
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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) | 0.002 | 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".