Effect of runx2b deficiency in intermuscular bones on the regulatory network of lncRNA-miRNA-mRNA
Bibliographic record
Abstract
Intermuscular bones (IBs) are mineralized spicules that negatively impact the quality and value of fish products. Runx2b is a crucial modulator in promoting bone formation through regulating osteoblast differentiation. Previous studies suggested that loss of runx2b gene completely inhibited IBs formation in zebrafish. However, how the whole transcriptome , including mRNA and non-coding RNA (ncRNA), affects the IBs development in runx2b −/− zebrafish are not known. The aim of this study was to identify the regulatory networks of differentially expressed (DE) lncRNAs, miRNAs, and mRNAs in zebrafish with and without IBs ( runx2b +/+ fish and runx2b −/− fish) utilizing high-throughput sequencing techniques. All together there are 1051 mRNAs, 456 lncRNAs, and 18 miRNAs differentially expressed were found between these two strains. The analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) has highlighted significant pathways linked to the development of IBs, specifically the TGF-beta and Wnt signaling pathways , and a number of genes concentrated on these two signaling pathways related to the formation of IBs. Further, 1989 competing endogenous RNA (ceRNA) networks were created according to the correlation among mRNAs, miRNAs and lncRNAs. The ceRNA networks results revealed 52 ceRNA pairs related to the IBs formation, consisting of 52 mRNAs, 37 lncRNAs, and 6 miRNAs. Of these, we found that dre-miR-2189 was the key element of ceRNA pairs, interacting with 19 mRNAs and 11 lncRNAs, and MSTRG.13175.1 could regulate sp7 expression by interacting with dre-miR-2189 to function in osteogenic differentiation. Subsequent experiments at the cellular level also revealed the interaction mechanism. The outcomes indicated a crucial role of miRNAs and lncRNAs in the development of fish IBs, which offer new views into the functions of ncRNAs involved in IBs formation.
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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 | 0.001 | 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".