Multiple and Specific mRNA Processing Targets for the Major Human hnRNP Proteins
Bibliographic record
Abstract
Alternative splicing is a key mechanism regulating gene expression, and it is often used to produce antagonistic activities particularly in apoptotic genes. Heterogeneous nuclear ribonucleoparticle (hnRNP) proteins form a family of RNA-binding proteins that coat nascent pre-mRNAs. Many but not all major hnRNP proteins have been shown to participate in splicing control. The range and specificity of hnRNP protein action remain poorly documented, even for those affecting splice site selection. We used RNA interference and a reverse transcription-PCR screening platform to examine the implications of 14 of the major hnRNP proteins in the splicing of 56 alternative splicing events in apoptotic genes. Out of this total of 784 alternative splicing reactions tested in three human cell lines, 31 responded similarly to a knockdown in at least two different cell lines. On the other hand, the impact of other hnRNP knockdowns was cell line specific. The broadest effects were obtained with hnRNP K and C, two proteins whose role in alternative splicing had not previously been firmly established. Different hnRNP proteins affected distinct sets of targets with little overlap even between closely related hnRNP proteins. Overall, our study highlights the potential contribution of all of these major hnRNP proteins in alternative splicing control and shows that the targets for individual hnRNP proteins can vary in different cellular contexts.
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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 | 0.001 | 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".