Complementary Roles of Yeast Rad4p and Rad34p in Nucleotide Excision Repair of Active and Inactive rRNA Gene Chromatin
Bibliographic record
Abstract
Nucleotide excision repair (NER) removes a plethora of DNA lesions. It is performed by a large multisubunit protein complex that finds and repairs damaged DNA in different chromatin contexts and nuclear domains. The nucleolus is the most transcriptionally active domain, and in yeast, transcription-coupled NER occurs in RNA polymerase I-transcribed genes (rDNA). Here we have analyzed the roles of two members of the xeroderma pigmentosum group C family of proteins, Rad4p and Rad34p, during NER in the active and inactive rDNA. We report that Rad4p is essential for repair in the intergenic spacer, the inactive rDNA coding region, and for strand-specific repair at the transcription initiation site, whereas Rad34p is not. Rad34p is necessary for transcription-coupled NER that starts about 40 nucleotides downstream of the transcription initiation site of the active rDNA, whereas Rad4p is not. Thus, although Rad4p and Rad34p share sequence homology, their roles in NER in the rDNA locus are almost entirely distinct and complementary. These results provide evidences that transcription-coupled NER and global genome NER participate in the removal of UV-induced DNA lesions from the transcribed strand of active rDNA. Furthermore, nonnucleosome rDNA is repaired faster than nucleosome rDNA, indicating that an open chromatin structure facilitates NER in vivo.
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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 | 0.001 |
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".