RNA-binding Protein Quaking Stabilizes Sirt2 mRNA during Oligodendroglial Differentiation
Bibliographic record
Abstract
Myelination is controlled by timely expression of genes involved in the differentiation of oligodendrocyte precursor cells (OPCs) into myelinating oligodendrocytes (OLs). Sirtuin 2 (SIRT2), a NAD + -dependent deacetylase, plays a critical role in OL differentiation by promoting both arborization and downstream expression of myelin-specific genes. However, the mechanisms involved in regulating SIRT2 expression during OL development are largely unknown. The RNA-binding protein quaking (QKI) plays an important role in myelination by post-transcriptionally regulating the expression of several myelin specific genes. In quaking viable (qk v /qk v ) mutant mice, SIRT2 protein is severely reduced; however, it is not known whether these genes interact to regulate OL differentiation. Here, we report for the first time that QKI directly binds to Sirt2 mRNA via a common quaking response element (QRE) located in the 3′ untranslated region (UTR) to control SIRT2 expression in OL lineage cells. This interaction is associated with increased stability and longer half-lives of Sirt2.1 and Sirt2.2 transcripts leading to increased accumulation of Sirt2 transcripts. Consistent with this, overexpression of qkI promoted the expression of Sirt2 mRNA and protein. However, overexpression of the nuclear isoform qkI-5 promoted the expression of Sirt2 mRNA, but not SIRT2 protein, and delayed OL differentiation. These results suggest that the balance in the subcellular distribution and temporal expression of QKI isoforms control the availability of Sirt2 mRNA for translation. Collectively, our study demonstrates that QKI directly plays a crucial role in the post-transcriptional regulation and expression of Sirt2 to facilitate OL differentiation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".