Association of a missense mutation in the bovine leptin gene with carcass fat content and leptin mRNA levels
Bibliographic record
Abstract
Previously, we have shown that alleles of the BM1500 microsatellite, located 3.6 kb downstream of the leptin gene in cattle, were associated with carcass fat measures in a population of 154 unrelated beef bulls. Subsequently, a cytosine (C) to thymine (T) transition that encoded an amino acid change of an arginine to a cysteine was identified in exon 2 of the leptin gene. A PCR-RFLP was designed and allele frequencies in four beef breeds were correlated with levels of carcass fat. The T allele was associated with fatter carcasses and the C allele with leaner carcasses. The frequencies of the SNP alleles among breeds indicated that British breeds have a higher frequency of the T allele whereas the continental breeds have a higher occurrence of the C allele. A ribonuclease protection assay was developed to quantify leptin mRNA in a separate group of animals selected by genotype. Animals homozygous for thymine expressed higher levels of leptin mRNA. This may suggest that the T allele, which adds an extra cysteine to the protein, imparts a partial loss of biological function and hence could be the causative mutation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 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".