Arginine methylation of DDX5 RGG/RG motif by PRMT5 regulates RNA:DNA resolution
Bibliographic record
Abstract
Abstract Aberrant transcription-associated RNA:DNA hybrid (R-loop) formation often lead to catastrophic conflicts during replication resulting in DNA double strand breaks and genome instability. To prevent such conflicts, these hybrids require dissolution by helicases and/or RNaseH. Little information is known about how these helicases are regulated. Herein, we identify DDX5, an RGG/RG motif containing DEAD-box family of RNA helicase, as a crucial player in R-loop resolution. We define at the mechanistic level the function of DDX5 in R-loop resolution. In vitro , recombinant DDX5 resolves R-loops in an ATP-dependent manner leading to R-loop degradation by the XRN2 exoribonuclease. DDX5 deficient cells accumulated R-loops at loci known to form R-loops using RNA:DNA immunoprecipitation (DRIP)-qPCR and increased RNaseH sensitive RAD51 foci. PRMT5, an arginine methyltransferase, associated with DDX5 and methylated its RGG/RG motif. This motif was required to associate with XRN2 and resolve cellular R-loops. Furthermore, PRMT5 deficient cells accumulated R-loops, as detected by DRIP-qPCR resulting in increased gH2AX foci. Our findings define a new mechanism by which an RNA helicase, DDX5, is modulated by arginine methylation to resolve R-loops.
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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".