<i>Corticotropin releasing hormone</i>is a promising candidate gene for marbling and subcutaneous fat depth in beef cattle
Bibliographic record
Abstract
The gene corticotropin releasing hormone (CRH) is mapped on bovine chromosome 14 (BTA14), where more than 30 fat-related quantitative trait loci (QTLs) have been reported in dairy and beef cattle. The gene product regulates secretion of adrenocorticotrophin hormone, the hypothalamic-pituitary-adrenal axis, and multiple hypothalamic functions; therefore, we hypothesized that CRH is a promising candidate gene for beef marbling score (BMS) and subcutaneous fat depth (SFD) in a Wagyu x Limousin F2 population. Two pairs of primers were designed and a total of 5 single nucleotide polymorphisms (SNPs) were identified: g.9657C>T, c.10718G>C, c.10841G>A, c.10893A>C, and c.10936G>C (AAFC03076794.1). Among the 4 cSNPs, c.10718G>C, c.10841G>A, and c.10936G>C are missense mutations leading to amino acid changes from arginine to proline, from serine to asparagine, and from aspartic acid to histidine, respectively. These 5 SNPs were genotyped on ~250 F2 progeny, but only 4 were selected as tagging SNPs for association analysis because no historical recombination was observed between c.10718G>C and c.10893A>C. Statistical analysis showed that g.9657C>T, c.10718G>C, and c.10936G>C and their haplotypes had significant effects on SFD, but only c.10936G>C was significantly associated with BMS. The SNP in the promoter (g.9657C>T) led to gain/loss of a CpG site and 4 potential regulatory binding sites. Different haplotypes among the 4 cSNPs significantly affected mRNA secondary structures but were not associated with phenotypes. Overall, our results provide further evidence that CRH is a promising candidate gene for a concordant QTL related to lipid metabolism in mammals.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".