Dual Processing of R-Loops and Topoisomerase I Induces Transcription-Dependent DNA Double-Strand Breaks
Bibliographic record
Abstract
Although accumulation of DNA damage and genomic instability in resting cells can cause neurodegenerative disorders, our understanding of how transcription produces DNA double-strand breaks (DSBs) is limited. Transcription-blocking topoisomerase I cleavage complexes (TOP1ccs) are frequent events that prime DSB production in non-replicating cells. Here, we report a mechanism of their formation by showing that they arise from two nearby single-strand breaks (SSBs) on opposing DNA strands: one SSB from the removal of transcription-blocking TOP1ccs by the TDP1 pathway and the other from the cleavage of R-loops by endonucleases, including XPF, XPG, and FEN1. Genetic defects in TOP1cc removal (TDP1, PNKP, and XRCC1) or in the resolution of R-loops (SETX) enhance DSB formation and prevent their repair. Such deficiencies cause neurological disorders. Owing to the high frequency of TOP1cc trapping and the widespread distribution of R-loops, these persistent transcriptional DSBs could accumulate over time in neuronal cells, contributing to the neurodegenerative diseases.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".