Large-scale evaluation of the ability of RNA-binding proteins to activate exon inclusion
Bibliographic record
Abstract
RNA-binding proteins (RBPs) modulate alternative splicing outcomes to determine isoform expression and cellular survival. To identify RBPs that directly drive alternative exon inclusion, we developed tethered function luciferase-based splicing reporters that provide rapid, scalable and robust readouts of exon inclusion changes and used these to evaluate 718 human RBPs. We performed enhanced cross-linking immunoprecipitation, RNA sequencing and affinity purification-mass spectrometry to investigate a subset of candidates with no prior association with splicing. Integrative analysis of these assays indicates surprising roles for TRNAU1AP, SCAF8 and RTCA in the modulation of hundreds of endogenous splicing events. We also leveraged our tethering assays and top candidates to identify potent and compact exon inclusion activation domains for splicing modulation applications. Using these identified domains, we engineered programmable fusion proteins that outperform current artificial splicing factors at manipulating inclusion of reporter and endogenous exons. This tethering approach characterizes the ability of RBPs to induce exon inclusion and yields new molecular parts for programmable splicing control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 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".