Altered microRNA expression in bovine skeletal muscle with age
Bibliographic record
Abstract
Age-dependent decline in skeletal muscle function leads to several inherited and acquired muscular disorders in elderly individuals. The levels of microRNAs (miRNAs) could be altered during muscle maintenance and repair. We therefore performed a comprehensive investigation for miRNAs from five different periods of bovine skeletal muscle development using next-generation small RNA sequencing. In total, 511 miRNAs, including one putatively novel miRNA, were identified. Thirty-six miRNAs were differentially expressed between prenatal and postnatal stages of muscle development including several myomiRs (miR-1, miR-206 and let-7 families). Compared with miRNA expression between different muscle tissues, 14 miRNAs were up-regulated and 22 miRNAs were down-regulated in the muscle of postnatal stage. In addition, a novel miRNA was predicted and submitted to the miRBase database as bta-mir-10020. A dual luciferase reporter assay was used to demonstrate that bta-mir-10020 directly targeted the 3'-UTR of the bovine ANGPT1 gene. The overexpression of bta-mir-10020 significantly decreased the DsRed fluorescence in the wild-type expression cassette compared to the mutant type. Using three computational approaches - miranda, pita and rnahybrid - these differentially expressed miRNAs were also predicted to target 3609 bovine genes. Disease and biological function analyses and the KEGG pathway analysis revealed that these targets were statistically enriched in functionality for muscle growth and disease. Our miRNA expression analysis findings from different states of muscle development and aging significantly expand the repertoire of bovine miRNAs now shown to be expressed in muscle and could contribute to further studies on growth and developmental disorders in this tissue type.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".