hnRNP A1/A2 and Sam68 collaborate with SRSF10 to control the alternative splicing response to oxaliplatin-mediated DNA damage
Bibliographic record
Abstract
Little is known about how RNA binding proteins cooperate to control splicing, and how stress pathways reconfigure these assemblies to alter splice site selection. We have shown previously that SRSF10 plays an important role in the Bcl-x splicing response to DNA damage elicited by oxaliplatin in 293 cells. Here, RNA affinity assays using a portion of the Bcl-x transcript required for this response led to the recovery of the SRSF10-interacting protein 14-3-3ε and the Sam68-interacting protein hnRNP A1. Although SRSF10, 14-3-3ε, hnRNP A1/A2 and Sam68 do not make major contributions to the regulation of Bcl-x splicing under normal growth conditions, upon DNA damage they become important to activate the 5' splice site of pro-apoptotic Bcl-xS. Our results indicate that DNA damage reconfigures the binding and activity of several regulatory RNA binding proteins on the Bcl-x pre-mRNA. Moreover, SRSF10, hnRNP A1/A2 and Sam68 collaborate to drive the DNA damage-induced splicing response of several transcripts that produce components implicated in apoptosis, cell-cycle control and DNA repair. Our study reveals how the circuitry of splicing factors is rewired to produce partnerships that coordinate alternative splicing across processes crucial for cell fate.
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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".