Fission yeast histone chaperone Rtt106 regulates histone levels, prevents early division, and promotes genome stability
Bibliographic record
Abstract
ABSTRACT Chromatin packaging influences gene expression and is linked to genome stability through the establishment and maintenance of histone modifications. Histone chaperone proteins regulate chromatin assembly and thus packaging. We tested how loss of the histone chaperone Rtt106 affects genome stability through cell cycle checkpoint stability in response to cellular stress. We tested how double mutants lacking DNA replication or DNA damage checkpoint kinases are impacted by the absence of histone chaperone rtt106 . Rtt106 brings histone H3 and histone H4 together into complexes. We found that rtt106 Δ cells with loss of the DNA replication checkpoint ( cds1 Δ , rad3 Δ) were more sensitive to hydroxyurea. However, DNA damage kinase chk1 Δ rtt106 Δ cells became less sensitive to DNA damaging drugs. The effects of Rtt106 on growth are observed in division timing, where rtt106 Δ cells show early division in the presence of drug. Coupled to a decrease in histone H3 levels and increased mutation rate, our work shows how non-essential Rtt106 activities contribute to genome stability. By regulating histone levels and use, Rtt106 regulates the cell division and may function in chromatin arm coherence and segregation.
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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".