Genetic variation in Pro-melanin-concentrating hormone affects carcass traits in Bos taurus cattle
Bibliographic record
Abstract
The purpose of this research was to determine whether genetic variation existed within Bos taurus Pro-melanin-concentrating hormone (PMCH), and whether this variation would affect carcass traits. PMCH had previously been shown to affect appetite and metabolism in rodent species, thus it was desirable to determine whether the gene had a similar effect in cattle, which could be interpreted based on carcass measurements of weight gain and fat production. Cattle PMCH was sequenced and an adenosine-to-thymine (A>T) single nucleotide polymorphism (SNP) was detected 134 bp upstream of the translational start site. The SNP alleles were determined to significantly affect carcass traits including average fat and grade fat in two populations of cattle, and shear force measurements in one population. The adenosine homozygotes were found to have the highest fat levels and the thymine homozygotes the least, while the heterozygous animals had intermediate fat levels. Shear force values in the one available population indicated that cuts of meat from the adenosine homozygotes were most tender, while cuts from the thymine homozygotes were least tender. The SNP was also found to significantly affect tenderness and palatability of meat, as evaluated by a consumer taste panel. The meat from adenosine homozygotes was found to be most tender and palatable. These results could not be validated as this data was unavailable in additional populations. The location of the SNP suggested that it may affect PMCH transcription rates. In silico examination of the different alleles indicated that the thymine allele introduces a novel transcriptional repressor binding site for Adenovirus E4 Promoter Binding protein (E4BP4). Thus, it is believed that the SNP may affect transcriptional levels of the gene by reducing transcription rates in the presence of the thymine allele. Cattle producers are expected to produce cattle with consistent amounts of lean meat and fat. Genetic testing of alleles found to affect fat production and meat tenderness traits are currently available to producers. A DNA test to select breeding stock based on PMCH alleles could be used in conjunction with other tests currently available to further improve carcass quality by selecting for animals with beneficial alleles at numerous genetic loci. Additionally, producers could make use of these findings to genetically sort cattle upon feedlot entry, maximizing the consistency of the finished beef product.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".