Long-range histone acetylation: biological significance, structural implications, and mechanismsThis paper is one of a selection of papers published in this Special Issue, entitled 27th International West Coast Chromatin and Chromosome Conference, and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
Genomic characterization of various euchromatic regions in higher eukaryotes has revealed that domain-wide hyperacetylation (over several kb) occurs at a range of loci, including individual genes, gene family clusters, compound clusters, and more general clusters of unrelated genes. Patterns of long-range histone hyperacetylation are strictly conserved within each unique cellular system studied and they reflect biological variability in gene regulation. Domain-wide histone acetylation consists generally of nonuniform peaks of enriched hyperacetylation of specific core histones, histone isoforms, and (or) histone variants against a backdrop of nonspecific acetylation across the domain in question. Here we review the characteristics of long-range histone acetylation in some higher eukaryotes and draw special attention to recent literature on the multiple effects that histone hyperacetylation has on chromatin's structural integrity and how they affect transcription. These include the thermal, ionic, cumulative, and isoform-specific (H4 K16) consequences of acetylation that result in a more dynamic core complex and chromatin fiber.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".