Unligated Okazaki Fragments Induce PCNA Ubiquitination and a Requirement for Rad59-Dependent Replication Fork Progression
Bibliographic record
Abstract
Deficiency in DNA ligase I, encoded by CDC9 in budding yeast, leads to the accumulation of unligated Okazaki fragments and triggers PCNA ubiquitination at a non-canonical lysine residue. This signal is crucial to activate the S phase checkpoint, which promotes cell cycle delay. We report here that a pol30-K107 mutation alleviated cell cycle delay in cdc9 mutants, consistent with the idea that the modification of PCNA at K107 affects the rate of DNA synthesis at replication forks. To determine whether PCNA ubiquitination occurred in response to nicks or was triggered by the lack of PCNA-DNA ligase interaction, we complemented cdc9 cells with either wild-type DNA ligase I or a mutant form, which fails to interact with PCNA. Both enzymes reversed PCNA ubiquitination, arguing that the modification is likely an integral part of a novel nick-sensory mechanism and not due to non-specific secondary mutations that could have occurred spontaneously in cdc9 mutants. To further understand how cells cope with the accumulation of nicks during DNA replication, we utilized cdc9-1 in a genome-wide synthetic lethality screen, which identified RAD59 as a strong negative interactor. In comparison to cdc9 single mutants, cdc9 rad59Δ double mutants did not alter PCNA ubiquitination but enhanced phosphorylation of the mediator of the replication checkpoint, Mrc1. Since Mrc1 resides at the replication fork and is phosphorylated in response to fork stalling, these results indicate that Rad59 alleviates nick-induced replication fork slowdown. Thus, we propose that Rad59 promotes fork progression when Okazaki fragment processing is compromised and counteracts PCNA-K107 mediated cell cycle arrest.
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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".