Single nucleotide polymorphisms in the <i>corticotrophin</i>‐<i>releasing hormone</i> and <i>pro</i>‐<i>opiomelancortin</i> genes are associated with growth and carcass yield in beef cattle
Bibliographic record
Abstract
A single nucleotide polymorphism (SNP) in the corticotrophin-releasing hormone gene (CRH C22G) alters the fourth amino acid in the signal sequence from proline to arginine. Two other SNPs (CRH A145G and C240G) occur in the propeptide region at residue positions 45 and 77, respectively, that result in serine/asparagine and histidine/aspartic acid substitutions respectively. These SNPs, as well as SNPs in pro-opiomelancortin (POMC), leptin (LEP) and melanocortin-4 receptor (MC4R), were evaluated for associations with average daily gain, end-of-test rib-eye area, shipping weight and hot carcass weight in a group of 256 steers using a general linear model. The CRH C22G SNP was associated with end-of-test rib-eye area (P < 0.034) and hot carcass weight (P < 0.0015). The SNP in POMC was associated with shipping weight (P < 0.0078) and hot carcass weight (P = 0.006) while it approached significance for average daily gain (P < 0.07). The SNP in MC4R approached significance for hot carcass weight (P < 0.085) while no significance was observed between the leptin SNP and the above listed traits. Because both CRH and POMC regulate appetite, potential interaction effects between these two genes were assessed. The absence of an interaction effect between CRH and POMC with hot carcass weight suggests that these genes act independently to increase carcass yield. These gene effects used singularly or together could result in an economic benefit to the beef industry.
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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 | 0.001 |
| 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) | 0.001 | 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".