A nucleosome turnover map reveals that the stability of histone H4 Lys20 methylation depends on histone recycling in transcribed chromatin
Bibliographic record
Abstract
Nucleosome composition actively contributes to chromatin structure and accessibility. Cells have developed mechanisms to remove or recycle histones, generating a landscape of differentially aged nucleosomes. This study aimed to create a high-resolution, genome-wide map of nucleosome turnover in Schizosaccharomyces pombe. The recombination-induced tag exchange (RITE) method was used to study replication-independent nucleosome turnover through the appearance of new histone H3 and the disappearance or preservation of old histone H3. The genome-wide location of histones was determined by chromatin immunoprecipitation-exonuclease methodology (ChIP-exo). The findings were compared with diverse chromatin marks, including histone variant H2A.Z, post-translational histone modifications, and Pol II binding. Finally, genome-wide mapping of the methylation states of H4K20 was performed to determine the relationship between methylation (mono, di, and tri) of this residue and nucleosome turnover. Our analysis showed that histone recycling resulted in low nucleosome turnover in the coding regions of active genes, stably expressed at intermediate levels. High levels of transcription resulted in the incorporation of new histones primarily at the end of transcribed units. H4K20 was methylated in low-turnover nucleosomes in euchromatic regions, notably in the coding regions of long genes that were expressed at low levels. This transcription-dependent accumulation of histone methylation was dependent on the histone chaperone complex FACT. Our data showed that nucleosome turnover is highly dynamic in the genome and that several mechanisms are at play to either maintain or suppress stability. In particular, we found that FACT-associated transcription conserves histones by recycling them and is required for progressive H4K20 methylation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 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) | 0.000 | 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".