A novel role for CARM1 in promoting nonsense-mediated mRNA decay: potential implications for spinal muscular atrophy
Bibliographic record
Abstract
Loss of 'Survival of Motor Neurons' (SMN) leads to spinal muscular atrophy (SMA), a disease characterized by degeneration of spinal cord alpha motor neurons, resulting in muscle weakness, paralysis and death during early childhood. SMN is required for assembly of the core splicing machinery, and splicing defects were documented in SMA. We previously uncovered that Coactivator-Associated Methyltransferase-1 (CARM1) is abnormally up-regulated in SMA, leading to mis-regulation of a number of transcriptional and alternative splicing events. We report here that CARM1 can promote decay of a premature terminating codon (PTC)-containing mRNA reporter, suggesting it can act as a mediator of nonsense-mediated mRNA decay (NMD). Interestingly, this pathway, while originally perceived as solely a surveillance mechanism preventing expression of potentially detrimental proteins, is now emerging as a highly regulated RNA decay pathway also acting on a subset of normal mRNAs. We further show that CARM1 associates with major NMD factor UPF1 and promotes its occupancy on PTC-containing transcripts. Finally, we identify a specific subset of NMD targets that are dependent on CARM1 for degradation and that are also misregulated in SMA, potentially adding exacerbated targeting of PTC-containing mRNAs to the already complex array of molecular defects associated with this disease.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".