Dynamic epigenetic states of ribosomal RNA promoters during the cell cycle
Bibliographic record
Abstract
It has previously been shown that the ribosomal RNA (rRNA) promoter is regulated through epigenetic mechanisms. It is unclear however whether epigenetic marks are stable in somatic cells or whether and how they vary with cell cycle dynamics. Here we present an analysis of epigenetic marks in cells positioned at different phases of the cell cycle following synchronization using a double thymidine block. We show that the levels of acetylated histone 4 are highest in early S phase, coinciding with the peak of binding of the transcriptional activators UBF and MBD3 to the rRNA promoter. Additionally, binding of the DNA methyltransferase DNMT1 is highest during mid-S phase, while DNMT3B binding peaks later in G2. Bisulfite mapping of the rRNA promoter reveals that the DNA methylation state varies during the cell cycle being lowest during early and late S phase. Interestingly, although the interaction of RNA polymerase I with the promoter and its progress along the gene coincides with epigenetic activation, the burst in levels of rRNA transcript did not occur until after DNA synthesis was complete. This suggests that although the rRNA promoter is poised for transcription early in the cell cycle, the accumulation of rRNA transcripts requires additional signals later in the cell cycle. This data is consistent with the idea that epigenetic states are dynamic in somatic cells and might participate in physiological cellular responses.
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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 | 0.000 | 0.000 |
| 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".