Guanine Nucleotide-Binding Protein-Like 1 (GNL1) binds RNA G-quadruplex structures in genes associated with Parkinson’s disease
Bibliographic record
Abstract
RNAs are highly regulated at the post-transcriptional level in neurodegenerative diseases and just a few mutations can significantly affect the fate of neuronal cells. To date, the impact of G-quadruplex (G4) regulation in neurodegenerative diseases like Parkinson’s disease (PD) has not been analysed. In this study, in silico potential G4s located in deregulated genes related to the nervous system were initially identified and were found to be significantly enriched. Several G4 sequences found in the 5ʹ untranslated regions (5ʹUTR) of mRNAs associated with Parkinson’s disease were demonstrated to in fact fold in vitro by biochemical assays. Subcloning of the full-length 5ʹUTRs of these candidates upstream of a luciferase reporter system led to the demonstration that the G4s of both Parkin RBR E3 Ubiquitin Protein Ligase (PRKN) and Vacuolar Protein Sorting-Associated Protein 35 (VPS35) significantly repressed the translation of both genes in SH-SY5Y cells. Subsequently, a strategy of using label-free RNA affinity purification assays with either of these two G4 sequences as bait isolated the Guanine Nucleotide-Binding Protein-Like 1 (GNL1). The latter was shown to have a higher affinity for the G4 sequences than for their mutated version. This study sheds light on new RNA G-quadruplexes located in genes dysregulated in Parkinson disease and a new G4-binding protein, GNL1.
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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".