Forks on the Run: Can the Stalling of DNA Replication Promote Epigenetic Changes?
Bibliographic record
Abstract
Built of DNA polymerases and multiple associated factors, the replication fork steadily progresses along the DNA template and faithfully replicates DNA. This model can be found in practically every textbook of genetics, with the more complex situation of chromatinized DNA in eukaryotes often viewed as a variation. However, the replication-coupled disassembly/reassembly of chromatin adds significant complexity to the whole replication process. During the course of eukaryotic DNA replication the forks encounter various conditions and numerous impediments. These include nucleosomes with a variety of post-translational modifications, euchromatin and heterochromatin, differentially methylated DNA, tightly bound proteins, active gene promoters and DNA loops. At such positions the forks slow down or even stall. Dedicated factors stabilize the fork and prevent its rotation or collapse, while other factors resolve the replication block and facilitate the resumption of elongation. The fate of histones during replication stalling and resumption is not well understood. In this review we briefly describe recent advances in our understanding of histone turnover during DNA replication and focus on the possible mechanisms of nucleosome disassembly/reassembly at paused replication forks. We propose that replication pausing provides opportunities for an epigenetic change of the associated locus.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".