Transcription of ncRNAs promotes repair of UV induced DNA lesions in Saccharomyces cerevisiae subtelomeres
Bibliographic record
Abstract
Ultraviolet light causes DNA lesions that are removed by nucleotide excision repair (NER). The efficiency of NER is conditional to transcription and chromatin structure. UV induced photoproducts are repaired faster in the gene transcribed strands than in the non-transcribed strands or in transcriptionally inactive regions of the genome. This specificity of NER is known as transcription-coupled repair (TCR). The discovery of pervasive non-coding RNA transcription (ncRNA) advocates for ubiquitous contribution of TCR to the repair of UV photoproducts, beyond the repair of active gene-transcribed strands. Chromatin rules transcription, and telomeres form a complex structure of proteins that silences nearby engineered ectopic genes. The essential protective function of telomeres also includes preventing unwanted repair of double-strand breaks. Thus, telomeres were thought to be transcriptionally inert, but more recently, ncRNA transcription was found to initiate in subtelomeric regions. On the other hand, induced DNA lesions like the UV photoproducts must be recognized and repaired also at the ends of chromosomes. In this study, repair of UV induced DNA lesions was analyzed in the subtelomeric regions of budding yeast. The T4-endonuclease V nicking-activity at cyclobutene pyrimidine dimer (CPD) sites was exploited to monitor CPD formation and repair. The presence of two photoproducts, CPDs and pyrimidine (6,4)-pyrimidones (6-4PPs), was verified by the effective and precise blockage of Taq DNA polymerase at these sites. The results indicate that UV photoproducts in silenced heterochromatin are slowly repaired, but that ncRNA transcription enhances NER throughout one subtelomeric element, called Y', and in distinct short segments of the second, more conserved element, called X. Therefore, ncRNA-transcription dependent TCR assists global genome repair to remove CPDs and 6-4PPs from subtelomeric DNA.
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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".