Transcription Factor IIS Cooperates with the E3 Ligase UBR5 to Ubiquitinate the CDK9 Subunit of the Positive Transcription Elongation Factor B
Bibliographic record
Abstract
Elongation of transcription by mammalian RNA polymerase II (RNAPII) is regulated by specific factors, including transcription factor IIS (TFIIS) and positive transcription elongation factor b (P-TEFb). We show that the E3 ubiquitin ligase UBR5 associates with the CDK9 subunit of positive transcription elongation factor b to mediate its polyubiquitination in human cells. TFIIS also binds UBR5 to stimulate CDK9 polyubiquitination. Co-localization of UBR5, CDK9, and TFIIS along specific regions of the γ fibrinogen (γFBG) gene indicates that a ternary complex involving these factors participates in the transcriptional regulation of this gene. In support of this notion, overexpression of TFIIS not only modifies the ubiquitination pattern of CDK9 in vivo but also increases the association of CDK9 with various regions of the γFBG gene. Notably, the TFIIS-mediated increase in CDK9 loading is obtained during both basal and activated transcription of the γFBG gene. This increased CDK9 binding is paralleled by an increase in the recruitment of RNAPII along the γFBG gene and the phosphorylation of the C-terminal domain of the RNAPII largest subunit RPB1 on Ser-2, a known target of CDK9. Together, these results identify UBR5 as a novel E3 ligase that regulates transcription and define an additional function of TFIIS in the regulation of CDK9.
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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 | 0.000 |
| 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".