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Record W4387168471 · doi:10.1101/2023.09.28.559974

Identification of a link between splicing and endoplasmic reticulum proteostasis

2023· preprint· en· W4387168471 on OpenAlexaff
Muhammad Zahoor, Yanchen Dong, Marco Preußner, Sabrina Alam, Renata Hajdu, Veronika Reiterer, Stephan Geley, Valérie Cormier‐Daire, Florian Heyd, Loydie A. Jerome‐Majewska, Hesso Farhan

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsProteostasisEndoplasmic reticulumRNA splicingCell biologyUnfolded protein responseSpliceosomeRegulatorBiologyGeneticsGeneRNA

Abstract

fetched live from OpenAlex

Abstract The role of general splicing in endoplasmic reticulum (ER)-proteostasis remains poorly understood. Here, we identify SNRPB, a component of the spliceosome, as a novel regulator of export from the ER. Mechanistically, SNRPB regulates the splicing of components of the ER export machinery, including Sec16A, a regulator 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 intracellular accumulation of type-1 collagen as well as bone defects reminiscent of CCMS. Silencing SNRPB inhibited osteogenesis in vitro, which could be rescued by overexpression of Sec16A. This 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 (UPR), which supports a mechanistic link between the spliceosome and ER-proteostasis. Our work highlights SNRPB as a novel node in the proteostasis network, shedding light on CCMS pathophysiology.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.236
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicEndoplasmic Reticulum Stress and Disease→French-language works237,207→