Sumoylation is Required for the Cytoplasmic Accumulation of a Subset of mRNAs
Bibliographic record
Abstract
In order to discover novel proteins that promote the nuclear export of newly synthesized mRNAs in mammalian cells, we carried out a limited RNAi screen for proteins required for the proper cytoplasmic distribution of a model intronless mRNA. From this screen we obtained two hits, Ubc9 (SUMO-conjugating E2 enzyme) and GANP (germinal center-associated nuclear protein). Depletion of Ubc9 inhibited the proper cytoplasmic distribution of certain overexpressed intronless mRNAs, while depletion of GANP affected all tested mRNAs. Depletion of Sae1, which is also required for sumoylation, partially inhibited the cytoplasmic distribution of our model mRNA. Interestingly, the block in cytoplasmic accumulation in Ubc9-depleted cells could be overcome if an intron was incorporated into the mRNA. Surprisingly, Ubc9-depleted cells had normal nuclear export of newly synthesized intronless mRNAs, indicating that the observed accumulation of the model mRNA in the nuclei of transfected cells was likely due to some more general perturbation. Indeed, depletion of Ubc9, coupled with the overexpression of the intronless mRNAs, caused the redistribution of the nuclear speckle protein SC35 to cytoplasmic foci. Our results suggest that sumoylation may play a role in the proper assembly of mRNPs and/or the distribution of key RNA binding proteins, and may thus contribute to general protein expression patterns.
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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 | 0.001 |
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".