Nuclear RNA cap-chaperones eIF4E and NCBP2 govern distinct fates for 1000s of mRNAs uncovering an unexpected regulatory point in gene expression
Bibliographic record
Abstract
G) "cap" on the 5'end of mRNAs which is bound by the nuclear cap-binding protein NCBP2 with its cofactor NCBP1. The NCBP1/2 complex chaperones capped mRNA through these processing steps. NCBP2 is considered the sole nuclear cap-binding factor and thus its cap-chaperone role is thought to be a constitutive, housekeeping activity. However, another cap-binding protein, the eukaryotic translation initiation factor eIF4E, is also found in the nucleus. Two cap-binding factors co-existing in the nucleus intimate an undiscovered regulatory point in gene expression or, alternatively, redundancy to ensure gene expression fidelity. Consistent with the former possibility, eIF4E and NCBP2 drove distinct gene expression, transcriptomic, and splicing signatures impacting ~2500 transcripts involved in distinct biological programmes with only ~360 transcripts in common and of these only 79 common splicing events. Thus, each cap-chaperone designates distinct mRNA populations for specific processing revealing a new step in gene expression. We denote this mRNA specification of cap-chaperones (SOCCS). We uncovered multiple molecular mechanisms that contribute to SOCCS: distinct spatial localization of eIF4E and NCBP2 within the nucleus, identification of sequence motifs within targeted mRNAs segregated by eIF4E or NCBP2 sensitivity, distinct protein partners for these cap-chaperones and differential impacts on the production of key spliceosome components e.g. U2AF1, PRP31, SF3B1 and SNRNP200 indicative of distinct transcriptomic landscapes produced by eIF4E or NCBP2 overexpression. In all, the realization that multiple cap-binding proteins coexist in the nucleus led us to identify an unexpected gene-expression regulatory point which engaged distinct biological programmes.
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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 | 0.000 |
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 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".