Prolonged FOS activity disrupts a global myogenic transcriptional program by altering 3D chromatin architecture in primary muscle progenitor cells
Bibliographic record
Abstract
BACKGROUND: The AP-1 transcription factor, FBJ osteosarcoma oncogene (FOS), is induced in adult muscle satellite cells (SCs) within hours following muscle damage and is required for effective stem cell activation and muscle repair. However, why FOS is rapidly downregulated before SCs enter cell cycle as progenitor cells (i.e., transiently expressed) remains unclear. Further, whether boosting FOS levels in the proliferating progeny of SCs can enhance their myogenic properties needs further evaluation. METHODS: We established an inducible, FOS expression system to evaluate the impact of persistent FOS activity in muscle progenitor cells ex vivo. We performed various assays to measure cellular proliferation and differentiation, as well as uncover changes in RNA levels and three-dimensional (3D) chromatin interactions. RESULTS: Persistent FOS activity in primary muscle progenitor cells severely antagonizes their ability to differentiate and form myotubes within the first 2 weeks in culture. RNA-seq analysis revealed that ectopic FOS activity in muscle progenitor cells suppressed a global pro-myogenic transcriptional program, while activating a stress-induced, mitogen-activated protein kinase (MAPK) transcriptional signature. Additionally, we observed various FOS-dependent, chromosomal re-organization events in A/B compartments, topologically associated domains (TADs), and genomic loops near FOS-regulated genes. CONCLUSIONS: Our results suggest that elevated FOS activity in recently activated muscle progenitor cells perturbs cellular differentiation by altering the 3D chromosome organization near critical pro-myogenic genes. This work highlights the crucial importance of tightly controlling FOS expression in the muscle lineage and suggests that in states of chronic stress or disease, persistent FOS activity in muscle precursor cells may disrupt the muscle-forming process.
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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) | 0.001 | 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".