Nucleolar Pol II interactome reveals TBPL1, PAF1, and Pol I at intergenic rDNA drive rRNA biogenesis
Bibliographic record
Abstract
Ribosomal DNA (rDNA) repeats harbor ribosomal RNA (rRNA) genes and intergenic spacers (IGS). RNA polymerase (Pol) I transcribes rRNA genes yielding rRNA components of ribosomes. IGS-associated Pol II prevents Pol I from excessively synthesizing IGS non-coding RNAs (ncRNAs) that can disrupt nucleoli and rRNA production. Here, compartment-enriched proximity-dependent biotin identification (compBioID) revealed the TATA-less-promoter-binding TBPL1 and transcription-regulatory PAF1 with nucleolar Pol II. TBPL1 localizes to TCT motifs, driving Pol II and Pol I and maintaining its baseline ncRNA levels. PAF1 promotes Pol II elongation, preventing unscheduled R-loops that hyper-restrain IGS Pol I-associated ncRNAs. PAF1 or TBPL1 deficiency disrupts nucleolar organization and rRNA biogenesis. In PAF1-deficient cells, repressing unscheduled IGS R-loops rescues nucleolar organization and rRNA production. Depleting IGS Pol I-dependent ncRNAs is sufficient to compromise nucleoli. We present the nucleolar interactome of Pol II and show that its regulation by TBPL1 and PAF1 ensures IGS Pol I ncRNAs maintaining nucleolar structure and function. By revealing the nucleolar interactome of RNA Pol II, the authors show the regulation of transcription by TBPL1 and PAF1 within ribosomal DNA’s intergenic spacers ensures baseline ncRNA levels critical to nucleolar structure and function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".