Cytoplasmic and Nuclear Retained DMPK mRNAs Are Targets for RNA Interference in Myotonic Dystrophy Cells
Bibliographic record
Abstract
Small interfering RNA (siRNA) duplexes induce the specific cleavage of target RNAs in mammalian cells. Their involvement in down-regulation of gene expression is termed RNA interference (RNAi). It is widely believed that RNAi predominates in the cytoplasm. We report here the co-existence of cytoplasmic and nuclear RNAi phenomena in primary human myotonic dystrophy type 1 (DM1) cells by targeting myotonic dystrophy protein kinase (DMPK) mRNAs. Heterozygote DM1 myoblasts from a human DM1 fetus produce a nuclear retained mutant DMPK transcript with large CUG repeats ( approximately 3,200) from one allele of the DMPK gene and a wild type transcript with 18 CUG repeats, thus providing for both a nuclear and cytoplasmic expression profile to be evaluated. We demonstrate here for the first time down-regulation of the endogenous nuclear retained mutant DMPK mRNAs targeted with lentivirus-delivered short hairpin RNAs (shRNAs). This nuclear RNAi(-like) phenomenon was not observed when synthetic siRNAs were delivered by cationic lipids, suggesting either a link between processing of the shRNA and nuclear import or a separate pathway for processing shRNAs in the nuclei. Our observation of simultaneous RNAi on both cytoplasmic and nuclear retained DMPK has important implications for post-transcriptional gene regulation in both compartments of mammalian cells.
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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) | 0.001 | 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".