A role for Chk1 in blocking transcriptional elongation of p21 RNA during the S-phase checkpoint
Bibliographic record
Abstract
We reported previously that when cells are arrested in S phase, a subset of p53 target genes fails to be strongly induced despite the presence of high levels of p53. When DNA replication is inhibited, reduced p21 mRNA accumulation is correlated with a marked reduction in transcription elongation. Here we show that ablation of the protein kinase Chk1 rescues the p21 transcription elongation defect when cells are blocked in S phase, as measured by increases in both p21 mRNA levels and the presence of the elongating form of RNA polymerase II (RNAPII) toward the 3' end of the p21 gene. Recruitment of specific elongation and 3' processing factors (DSIF, CstF-64, and CPSF-100) is also restored. While additional components of the RNAPII transcriptional machinery, such as TFIIB and CDK7, are recruited more extensively to the p21 locus after DNA damage than after replication stress, their recruitment is not enhanced by ablation of Chk1. Significantly, ablating Chk2, a kinase closely related in substrate specificity to Chk1, does not rescue p21 mRNA levels during S-phase arrest. Thus, Chk1 has a direct and selective role in the elongation block to p21 observed during S-phase arrest. These findings demonstrate for the first time a link between the replication checkpoint mediated by ATR/Chk1 and the transcription elongation/3' processing machinery.
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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 | 0.001 |
| 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".