The unfolded protein response regulates ER exit sites via SNRPB-dependent RNA splicing and contributes to bone development
Bibliographic record
Abstract
Splicing and endoplasmic reticulum (ER)-proteostasis are two key processes that ultimately regulate the functional proteins that are produced by a cell. However, the extent to which these processes interact remains poorly understood. Here, we identify SNRPB and other components of the Sm-ring, as targets of the unfolded protein response and novel regulators of export from the ER. Mechanistically, The Sm-ring regulates the splicing of components of the ER export machinery, including Sec16A, a component of ER exit sites. Loss of function of SNRPB is causally linked to cerebro-costo-mandibular syndrome (CCMS), a genetic disease characterized by bone defects. We show that heterozygous deletion of SNRPB in mice resulted in bone defects reminiscent of CCMS and that knockdown of SNRPB delays the trafficking of type-I collagen. Silencing SNRPB inhibited osteogenesis in vitro, which could be rescued by overexpression of Sec16A. This rescue indicates that the role of SNRPB in osteogenesis is linked to its effects on ER-export. Finally, we show that SNRPB is a target for the unfolded protein response, which supports a mechanistic link between the spliceosome and ER-proteostasis. Our work highlights components of the Sm-ring as a novel node in the proteostasis network, shedding light on CCMS pathophysiology.
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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 | 0.000 |
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".