Lipid kinase PIP5K1A regulates <i>let-7</i> microRNA biogenesis through interacting with nuclear export protein XPO5
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs first discovered in Caenorhabditis elegans. The let-7 miRNA is highly conserved in sequence, biogenesis and function from C. elegans to humans. During miRNA biogenesis, XPO5-mediated nuclear export of pre-miRNAs is a rate-limiting step and, therefore, might be critical for the quantitative control of miRNA levels, yet little is known about how this is regulated. Here we show a novel role for lipid kinase PPK-1/PIP5K1A (phosphatidylinositol-4-phosphate 5-kinase) in regulating miRNA levels. We found that C. elegans PPK-1 functions in the lin-28/let-7 heterochronic pathway, which regulates the strict developmental timing of seam cells. In C. elegans and human cells, PPK-1/PIP5K1A regulates let-7 miRNA levels. We investigated the mechanism further in human cells and show that PIP5K1A interacts with nuclear export protein XPO5 in the nucleus to regulate mature miRNA levels by blocking the binding of XPO5 to pre-let-7 miRNA. Furthermore, we demonstrate that this role for PIP5K1A is kinase-independent. Our study uncovers the novel finding of a direct connection between PIP5K1A and miRNA biogenesis. Given that miRNAs are implicated in multiple diseases, including cancer, this new finding might lead to a novel therapeutic opportunity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".