Transiently depleting RNPS1 leads to perdurable changes in alternative splicing
Bibliographic record
Abstract
ABSTRACT While robust regulatory mechanisms are expected to control the production of splice variants that confer distinct functions, a low level of stochasticity may be tolerated. To investigate stringency of regulation, we followed changes in the splicing of 192 alternative cassette exons after growth of cancer-derived HCT116 cells and embryonic colonocytes. In both cell lines approximately 15% of alternative splicing events changed by more than 10 percentage points over a 42-day period. We then carried out a cycle of transient depletions targeting RNPS1, a splicing regulator implicated in genomic stability. For alternative splicing units not regulated by RNPS1, the level of splicing changes was similar to the stochastic value obtained after normal growth. However, the frequency of perdurable changes was at least twice that value for splicing events regulated by RNPS1. A swap allele assay performed on four RNPS1-responsive units that underwent splicing changes indicated the presence of mutations mediating this effect. Specifically, a T to C mutation in a RNPS1-responsive exon of ADARB1 confered exon skipping. Our results suggest that fluctuations in the level of a splicing regulator preferentially impact the integrity of genes encoding transcripts that are regulated by this splicing factor to produce perdurable changes in alternative splicing. We discuss the potential implication of this process in human evolution.
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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".