Harnessing RNA-based DNA repair pathways for targeted gene editing
Bibliographic record
Abstract
ABSTRACT Recent studies have revealed a role for RNA in the repair of DNA double-strand breaks. Here, we show that the asymmetric DNA overhangs generated by the small TevSaCas9 dual nuclease informs a simple and robust editing strategy in human cells whereby Polθ and Rad52 are recruited to repair the double-strand break. The 2-nt, 3’ DNA overhang generated by the I-TevI nuclease domain of TevSaCas9 hybridizes with the 3’ end of a co-localized repair template guide RNA to specifically license repair. Substitutions that destabilize the repair duplex reduce editing efficiency. Targeted RNA-templated repair (rep-editing) harnesses cellular RNA-based DNA repair pathways to introduce precise nucleotide edits, deletions and insertions in human cells with high efficiency and fidelity independent of co-delivered repair functions. The small size of TevSaCas9 and RNA repair template offers delivery advantages over size-constrained or multi-component editing systems.
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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 | 0.001 | 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".