<i>In vitro</i> transcription system delineates the distinct roles of the coactivators pCAF and p300 during MyoD/E47-dependent transactivation
Bibliographic record
Abstract
The transcriptional coactivators p300 and pCAF are necessary for the myogenic factor MyoD to initiate the expression of skeletal muscle genes. In addition to mediating histone acetylation, both of these factors can acetylate MyoD; however, the complexity of cellular systems used to study MyoD has impeded delineation of the specific roles of these two acetyltransferases. Therefore, we established a MyoD-dependent in vitro transcription system that permits us to determine the roles of p300 and pCAF during MyoD-dependent transcriptional activation. Consistent with results from cellular systems, we demonstrate that maximal levels of transactivation in vitro require both p300 and pCAF, as well as the cofactor acetyl CoA. Dissection of the steps leading to transcription initiation revealed that the activities of p300 and pCAF are not redundant. During the initial stages of transactivation, p300 acetylates histone H3 and H4 within the promoter region and then recruits pCAF to MyoD. Once tethered to the promoter, pCAF acetylates MyoD to facilitate the transactivation process. Thus, we have established that pCAF and p300 carry out sequential and functionally distinct events on a promoter leading to transcriptional activation. Further dissection of this in vitro transcription system should be highly useful toward elucidating the mechanism by which coactivators facilitate differential gene expression by MyoD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".