The yeast Shu complex couples error‐free post‐replication repair to homologous recombination
Bibliographic record
Abstract
DNA post-replication repair (PRR) functions to bypass replication-blocking lesions and prevent damage-induced cell death. PRR employs two different mechanisms to bypass damaged DNA. While translesion synthesis has been well characterized, little is known about the molecular events involved in error-free bypass, although it has been assumed that homologous recombination (HR) is required for such a mode of lesion bypass. We undertook a genome-wide synthetic genetic array screen for novel genes involved in error-free PRR and observed evidence of genetic interactions between error-free PRR and HR. Furthermore, this screen identified and assigned four genes, CSM2, PSY3, SHU1 and SHU2, whose products form a stable Shu complex, to the error-free PRR pathway. Previous studies have indicated that the Shu complex is required for efficient HR and that inactivation of any of these genes is able to suppress the severe phenotypes of top3 and sgs1. We confirmed and further extended some of the reported observations and demonstrated that error-free PRR mutations are also epistatic to sgs1. Based on the above analyses, we propose a model in which error-free PRR utilizes the Shu complex to recruit HR to facilitate template switching, followed by double-Holliday junction resolution by Sgs1-Top3. This mechanism appears to be conserved throughout eukaryotes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".