Subtelomeric<i>ACS</i>-containing Proto-silencers Act as Antisilencers in Replication Factors Mutants in<i>Saccharomyces cerevisiae</i>
Bibliographic record
Abstract
Subtelomeric genes are either fully active or completely repressed and can switch their state about once per 20 generations. This meta-stable telomeric position effect is mediated by strong repression signals emitted by the telomere and relayed/enhanced by weaker repressor elements called proto-silencers. In addition, subtelomeric regions contain sequences with chromatin partitioning and antisilencing activities referred to as subtelomeric antisilencing regions. Using extensive mutational analysis of subtelomeric elements, we show that ARS consensus sequence (ACS)-containing proto-silencers convert to antisilencers in several replication factor mutants. We point out the significance of the B1 auxiliary sequence next to ACS in mediating these effects. In contrast, an origin-derived ACS does not convert to antisilencer in mutants and its B1 element has little bearing on silencing. These results are specific for the analyzed ACS and in addition to the effects of each mutation (relative to wild type) on global silencing. Another line of experiments shows that Mcm5p possesses antisilencing activity and is recruited to telomeres in an ACS-dependent manner. Mcm5p persists at this location at the late stages of S phase. We propose that telomeric ACS are not static proto-silencers but conduct finely tuned silencing and antisilencing activities mediated by ACS-bound factors.
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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".