Competition between Heterochromatic Loci Allows the Abundance of the Silencing Protein, Sir4, to Regulate de novo Assembly of Heterochromatin
Bibliographic record
Abstract
Changes in the locations and boundaries of heterochromatin are critical during development, and de novo assembly of silent chromatin in budding yeast is a well-studied model for how new sites of heterochromatin assemble. De novo assembly cannot occur in the G1 phase of the cell cycle and one to two divisions are needed for complete silent chromatin assembly and transcriptional repression. Mutation of DOT1, the histone H3 lysine 79 (K79) methyltransferase, and SET1, the histone H3 lysine 4 (K4) methyltransferase, speed de novo assembly. These observations have led to the model that regulated demethylation of histones may be a mechanism for how cells control the establishment of heterochromatin. We find that the abundance of Sir4, a protein required for the assembly of silent chromatin, decreases dramatically during a G1 arrest and therefore tested if changing the levels of Sir4 would also alter the speed of de novo establishment. Halving the level of Sir4 slows heterochromatin establishment, while increasing Sir4 speeds establishment. yku70Δ and ubp10Δ cells also speed de novo assembly, and like dot1Δ cells have defects in subtelomeric silencing, suggesting that these mutants may indirectly speed de novo establishment by liberating Sir4 from telomeres. Deleting RIF1 and RIF2, which suppresses the subtelomeric silencing defects in these mutants, rescues the advanced de novo establishment in yku70Δ and ubp10Δ cells, but not in dot1Δ cells, suggesting that YKU70 and UBP10 regulate Sir4 availability by modulating subtelomeric silencing, while DOT1 functions directly to regulate establishment. Our data support a model whereby the demethylation of histone H3 K79 and changes in Sir4 abundance and availability define two rate-limiting steps that regulate de novo assembly of heterochromatin.
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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 | 0.001 | 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".