Perinuclear localization of slow troponin C m RNA in muscle cells is controlled by a <i>cis</i>-element located at its 3′ untranslated region
Bibliographic record
Abstract
The process of mRNA localization within a specific cytoplasmic region is an integral aspect of the regulation of gene expression. Furthermore, colocalization of mRNAs and their respective translation products may facilitate the proper assembly of multi-subunit complexes like the thick and thin filaments of muscle. This postulate was tested by investigating the cytoplasmic localization of three mRNAs-the alpha-actin, slow troponin C (sTnC), and slow troponin I (sTnI), which encode different poly-peptide partners of the thin filament. Using in situ hybridization we showed that all three thin filament mRNAs are localized in the perinuclear cytoplasm of cultured C2C12 muscle cells. Their localization differs from that of the nonmuscle beta-actin mRNA, which is localized in the peripheral region of both proliferating nondifferentiated myoblasts and the differentiated myocytes. Analysis of the localization signal of the sTnC mRNA showed that a 40-nucleotide-long region of the sTnC mRNA 3' UTR is sufficient to confer the perinuclear localization on a heterologous reporter beta-Gal mRNA. This localization signal showed tissue specificity and worked only in the differentiated myocytes, but not in the proliferating myoblasts or in HeLa cells. The predicted secondary structure of the localization signal suggests the presence of multiple stem and loop structures in this region of the 3' UTR. Mutations within the stem region of the localization signal, which abolish the base pairing in this region, significantly reduced its perinuclear mRNA localization activity. Using UV-induced photo-cross-linking of RNA and proteins we found that a myotube-specific 42-kDa polypeptide binds to the localization signal.
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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".