TAF6δ orchestrates an apoptotic transcriptome profile and interacts functionally with p53
Bibliographic record
Abstract
BACKGROUND: TFIID is a multiprotein complex that plays a pivotal role in the regulation of RNA polymerase II (Pol II) transcription owing to its core promoter recognition and co-activator functions. TAF6 is a core TFIID subunit whose splice variants include the major TAF6alpha isoform that is ubiquitously expressed, and the inducible TAF6delta. In contrast to TAF6alpha, TAF6delta is a pro-apoptotic isoform with a 10 amino acid deletion in its histone fold domain that abolishes its interaction with TAF9. TAF6delta expression can dictate life versus death decisions of human cells. RESULTS: Here we define the impact of endogenous TAF6delta expression on the global transcriptome landscape. TAF6delta was found to orchestrate a transcription profile that included statistically significant enrichment of genes of apoptotic function. Interestingly, gene expression patterns controlled by TAF6delta share similarities with, but are not equivalent to, those reported to change following TAF9 and/or TAF9b depletion. Finally, because TAF6delta regulates certain p53 target genes, we tested and demonstrated a physical and functional interaction between TAF6delta and p53. CONCLUSION: Together our data define a TAF6delta-driven apoptotic gene expression program and show crosstalk between the p53 and TAF6delta pathways.
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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".