Trafficking of mRNAs containing ALREX-promoting elements through nuclear speckles
Bibliographic record
Abstract
In vertebrates, the majority of mRNAs that encode secreted, membrane-bound or mitochondrial proteins contain RNA elements that activate an alternative mRNA nuclear export (ALREX) pathway. Here we demonstrate that mRNAs containing ALREX-promoting elements are trafficked through nuclear speckles. Although ALREX-promoting elements enhance nuclear speckle localization, additional features within the mRNA largely drive this process. Depletion of two TREX-associated RNA helicases, UAP56 and its paralog URH49, or inhibition of the TREX-associated nuclear transport factor, TAP, not only inhibits ALREX, but also appears to trap these mRNAs in nuclear speckles. mRNAs that contain ALREX-promoting elements associate with UAP56 in vivo. Finally, we demonstrate that mRNAs lacking a poly(A)-tail are not efficiently exported by the ALREX pathway and show enhanced association with nuclear speckles. Our data suggest that within the speckle, ALREX-promoting elements, in conjunction with the poly(A)-tail, likely stimulate UAP56/URH49 and TAP dependent steps that lead to the eventual egress of the export-competent mRNP from these structures.
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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".