Paf1C regulates RNA polymerase II progression by modulating elongation rate
Bibliographic record
Abstract
Elongation factor Paf1C regulates several stages of the RNA polymerase II (Pol II) transcription cycle, although it is unclear how it modulates Pol II distribution and progression in mammalian cells. We found that conditional ablation of Paf1 resulted in the accumulation of unphosphorylated and Ser5 phosphorylated Pol II around promoter-proximal regions and within the first 20 to 30 kb of gene bodies, respectively. Paf1 ablation did not impact the recruitment of other key elongation factors, namely, Spt5, Spt6, and the FACT complex, suggesting that Paf1 function may be mechanistically distinguishable from each of these factors. Moreover, loss of Paf1 triggered an increase in TSS-proximal nucleosome occupancy, which could impose a considerable barrier to Pol II elongation past TSS-proximal regions. Remarkably, accumulation of Ser5P in the first 20 to 30 kb coincided with reductions in histone H2B ubiquitylation within this region. Furthermore, we show that nascent RNA species accumulate within this window, suggesting a mechanism whereby Paf1 loss leads to aberrant, prematurely terminated transcripts and diminution of full-length transcripts. Importantly, we found that loss of Paf1 results in Pol II elongation rate defects with significant rate compression. Our findings suggest that Paf1C is critical for modulating Pol II elongation rates by functioning beyond the pause-release step as an "accelerator" over specific early gene body regions.
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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 | 0.001 | 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".