In vivo recruitment of exon junction complex proteins to transcription sites in mammalian cell nuclei
Bibliographic record
Abstract
Studies over the past years indicate that there is extensive coupling between nuclear export of mRNA and pre-mRNA processing. Here, we visualized the distribution of exon junction complex (EJC) proteins and RNA export factors relative to sites of abundant pre-mRNA synthesis in the nucleus. We analyzed both HeLa cells infected with adenovirus and murine erythroleukemia (MEL) cells stably transfected with the human beta-globin gene. Using in situ hybridization and confocal microscopy, we observe accumulation of EJC proteins (REF/Aly, Y14, SRm160, UAP56, RNPS1, and Magoh) and core spliceosome components (U snRNPs) at sites of transcription. This suggests that EJC proteins bind stably to pre-mRNA cotranscriptionally. No concentration of the export factors NXF1/TAP, p15, and Dbp5 was detected on nascent transcripts, arguing that in mammalian cells these proteins bind the mRNA shortly before or after release from the sites of transcription. These results also suggest that binding of EJC proteins to the mRNA is not sufficient to recruit TAP-p15, consistent with recent findings showing that the EJC does not play a crucial role in mRNA export. Contrasting to the results obtained in MEL cells expressing normal human beta-globin transcripts, mutant pre-mRNAs defective in splicing and 3'end processing do not colocalize with SRm160, REF, UAP56, or Sm proteins. This shows that the accumulation of EJC proteins at transcription sites requires efficient processing of the nascent pre-mRNAs, arguing that transcription per se is not sufficient for the stable assembly of the EJC.
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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 | 0.000 |
| 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".