Transcriptional profiling of muscle tissue in growing Japanese Black cattle to identify genes involved with the development of intramuscular fat
Bibliographic record
Abstract
Japanese Black cattle are characterised by a unique ability to deposit intramuscular fat with lower melting temperature. In this study, 3 consecutive biopsies from Longissimus muscle tissue were taken and RNA isolated from 3 Japanese Black (Tajima strain) and 3 Holstein animals at age 11–20 months. The gene expression changes in these samples were analysed using a bovine fat/muscle cDNA microarray. A mixed-ANOVA model was fitted to the intensity signals. A total of 335 (4.8%) array elements were identified as differentially expressed genes in this breed × time comparison study. Genes preferentially expressed in Japanese Black are associated with mono-unsaturated fatty acid synthesis, fat deposition, adipogenesis development and muscle regulation, while examples of genes preferentially expressed in Holstein come from functional classes involved in connective tissue and skeletal muscle development. The gene expression differences detected between the Longissimus muscle of the 2 breeds give important clues to the molecular basis for the unique features of the Japanese Black breed, such as the onset and rate of adipose tissue development, metabolic differences, and signalling pathways involved in converting carbohydrate to lipid during lipogenesis. These findings will impact on industry management strategies designed to manipulate intramuscular adipose development at different development stages to gain maximum return for beef products.
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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 | 0.000 | 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) | 0.000 | 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".