Faculty Opinions recommendation of Replication stress checkpoint signaling controls tRNA gene transcription.
Bibliographic record
Abstract
In budding yeast, the transcriptional machinery at tRNA genes naturally interferes with replication in a way that can promote chromosome breakage. Here we show that a signaling module composed of core components of the replication stress checkpoint pathway represses this fork-pausing machinery in normally cycling and genotoxin-treated cells. Specifically, the sensor kinase Mec1, the signaling adaptor Mrc1 and the transducer kinase Rad53 relay signals that globally repress tRNA gene transcription during unchallenged proliferation and under conditions of replication stress. Repressive signaling in genotoxin-treated cells requires Rad53-dependent activation of a conserved repressor of tRNA gene transcription, Maf1. Cells lacking Maf1 are sensitive to replication stress under conditions of elevated tRNA gene transcription. We propose that checkpoint control of the fork-pausing activity of tRNA genes complements the repertoire of replisome-targeted mechanisms by which checkpoint proteins promote faithful DNA replication. PMID: 20639887 Funding information This work was supported by: Canadian Institutes of Health Research, Canada
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.082 | 0.047 |
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".