DNA double-strand break-derived RNA drives TIRR/53BP1 complex dissociation
Bibliographic record
Abstract
Tudor-interacting repair regulator (TIRR) is an RNA-binding protein and a negative regulator of the DNA-repair factor p53-binding protein 1 (53BP1). In non-damage conditions, TIRR is bound to 53BP1. After DNA damage, TIRR and 53BP1 dissociate, and 53BP1 binds the chromatin at the double-strand break (DSB) to promote non-homologous end joining (NHEJ)-mediated repair. However, the exact mechanistic details of this dissociation after damage are unknown. Increasing evidence has implicated RNA as a crucial factor in the DNA damage response (DDR). Here, we show that RNA can separate TIRR/53BP1. Specifically, RNA with a hairpin secondary structure, transcribed at the DSB by RNA polymerase II (RNAPII), promotes TIRR/53BP1 complex separation. This hairpin RNA binds to the same residues on TIRR as 53BP1. Our results uncover a role of DNA-damage-derived RNA in modulating a protein-protein interaction and contribute to our understanding of DSB repair.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".