Analyses of POL30 (PCNA) reveal positional effects in transient repression or bi-modal active/silent state at the sub-telomeres of S. cerevisiae
Bibliographic record
Abstract
BACKGROUND: Classical studies on position effect variegation in Drosophila have demonstrated the existence of bi-modal Active/Silent state of the genes juxtaposed to heterochromatin. Later studies with irreversible methods for the detection of gene repression have revealed a similar phenomenon at the telomeres of Saccharomyces cerevisiae and other species. In this study, we used dual reporter constructs and a combination of reversible and non-reversible methods to present evidence for the different roles of PCNA and histone chaperones in the stability and the propagation of repressed states at the sub-telomeres of S. cerevisiae. RESULTS: We show position dependent transient repression or bi-modal expression of reporter genes at the VIIL sub-telomere. We also show that mutations in the replicative clamp POL30 (PCNA) or the deletion of the histone chaperone CAF1 or the RRM3 helicase lead to transient de-repression, while the deletion of the histone chaperone ASF1 causes a shift from transient de-repression to a bi-modal state of repression. We analyze the physical interaction of CAF1 and RRM3 with PCNA and discuss the implications of these findings for our understanding of the stability and transmission of the epigenetic state of the genes. CONCLUSIONS: There are distinct modes of gene silencing, bi-modal and transient, at the sub-telomeres of S. cerevisiae. We characterise the roles of CAF1, RRM3 and ASF1 in these modes of gene repression. We suggest that the interpretations of past and future studies should consider the existence of the dissimilar states of gene silencing.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".