Preferential binding of a stable G3<scp>BP</scp> ribonucleoprotein complex to intron‐retaining transcripts in mouse brain and modulation of their expression in the cerebellum
Bibliographic record
Abstract
Neuronal granules play an important role in the localization and transport of translationally silenced messenger ribonucleoproteins in neurons. Among the factors associated with these granules, the RNA-binding protein G3BP1 (stress-granules assembly factor) is involved in neuronal plasticity and is induced in Alzheimer's disease. We immunopurified a stable complex containing G3BP1 from mouse brain and performed high-throughput sequencing and cross-linking immunoprecipitation to identify the associated RNAs. The G3BP-complex contained the deubiquitinating protease USP10, CtBP1 and the RNA-binding proteins Caprin-1, G3BP2a and splicing factor proline and glutamine rich, or PSF. The G3BP-complex binds preferentially to transcripts that retain introns, and to non-coding sequences like 3'-untranslated region and long non-coding RNAs. Specific transcripts with retained introns appear to be enriched in the cerebellum compared to the rest of the brain and G3BP1 depletion decreased this intron retention in the cerebellum of G3BP1 knockout mice. Among the enriched transcripts, we found an overrepresentation of genes involved in synaptic transmission, especially glutamate-related neuronal transmission. Notably, G3BP1 seems to repress the expression of the mature Grm5 (metabotropic glutamate receptor 5) transcript, by promoting the retention of an intron in the immature transcript in the cerebellum. Our results suggest that G3BP is involved in a new functional mechanism to regulate non-coding RNAs including intron-retaining transcripts, and thus have broad implications for neuronal gene regulation, where intron retention is widespread.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".