The QKI-5 and QKI-6 RNA Binding Proteins Regulate the Expression of MicroRNA 7 in Glial Cells
Bibliographic record
Abstract
The quaking (qkI) gene encodes 3 major alternatively spliced isoforms that contain unique sequences at their C termini dictating their cellular localization. QKI-5 is predominantly nuclear, whereas QKI-6 is distributed throughout the cell and QKI-7 is cytoplasmic. The QKI isoforms are sequence-specific RNA binding proteins expressed mainly in glial cells modulating RNA splicing, export, and stability. Herein, we identify a new role for the QKI proteins in the regulation of microRNA (miRNA) processing. We observed that small interfering RNA (siRNA)-mediated QKI depletion of U343 glioblastoma cells leads to a robust increase in miR-7 expression. The processing from primary to mature miR-7 was inhibited in the presence QKI-5 and QKI-6 but not QKI-7, suggesting that the nuclear localization plays an important role in the regulation of miR-7 expression. The primary miR-7-1 was bound by the QKI isoforms in a QKI response element (QRE)-specific manner. We observed that the pri-miR-7-1 RNA was tightly bound to Drosha in the presence of the QKI isoforms, and this association was not observed in siRNA-mediated QKI or Drosha-depleted U343 glioblastoma cells. Moreover, the presence of the QKI isoforms led to an increase presence of pri-miR-7 in nuclear foci, suggesting that pri-miR-7-1 is retained in the nucleus by the QKI isoforms. miR-7 is known to target the epidermal growth factor (EGF) receptor (EGFR) 3' untranslated region (3'-UTR), and indeed, QKI-deficient U343 cells had reduced EGFR expression and decreased ERK activation in response to EGF. Elevated levels of miR-7 are associated with cell cycle arrest, and it was observed that QKI-deficient U343 that harbor elevated levels of miR-7 exhibited defects in cell proliferation that were partially rescued by the addition of a miR-7 inhibitor. These findings suggest that the QKI isoforms regulate glial cell function and proliferation by regulating the processing of certain miRNAs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".