Sequence-Specific DNA Binding by the αNAC Coactivator Is Required for Potentiation of c-Jun-Dependent Transcription of the Osteocalcin Gene
Bibliographic record
Abstract
Since the c-Jun coactivator alphaNAC was initially identified in a differential screen for genes expressed in differentiated osteoblasts, we examined whether the osteocalcin gene, a specific marker of terminal osteoblastic differentiation, could be a natural target for the coactivating function of alphaNAC. We had also previously shown that alphaNAC can specifically bind DNA in vitro, but it remained unclear whether the DNA-binding function of alphaNAC is expressed in vivo or if it is required for coactivation. We have identified an alphaNAC binding site within the murine osteocalcin gene proximal promoter region and demonstrated that recombinant alphaNAC or alphaNAC from ROS17/2.8 nuclear extracts can specifically bind this element. Using transient transfection assays, we have shown that alphaNAC specifically potentiated the c-Jun-dependent transcription of the osteocalcin promoter and that this activity specifically required the DNA-binding domain of alphaNAC. Chromatin immunoprecipitation confirmed that alphaNAC occupies its binding site on the osteocalcin promoter in living osteoblastic cells expressing osteocalcin. Inhibition of the expression of endogenous alphaNAC in osteoblastic cells by use of RNA interference provoked a decrease in osteocalcin gene transcription. Our results show that the osteocalcin gene is a target for the alphaNAC coactivating function, and we propose that alphaNAC is specifically targeted to the osteocalcin promoter through its DNA-binding activity as a means to achieve increased specificity in gene transcription.
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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 | 0.001 |
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".