Disruption of exon-bridging interactions between the minor and major spliceosomes results in alternative splicing around minor introns
Bibliographic record
Abstract
Vertebrate genomes contain major (>99.5%) and minor (<0.5%) introns that are spliced by the major and minor spliceosomes, respectively. Major intron splicing follows the exon-definition model, whereby major spliceosome components first assemble across exons. However, since most genes with minor introns predominately consist of major introns, formation of exon-definition complexes in these genes would require interaction between the major and minor spliceosomes. Here, we report that minor spliceosome protein U11-59K binds to the major spliceosome U2AF complex, thereby supporting a model in which the minor spliceosome interacts with the major spliceosome across an exon to regulate the splicing of minor introns. Inhibition of minor spliceosome snRNAs and U11-59K disrupted exon-bridging interactions, leading to exon skipping by the major spliceosome. The resulting aberrant isoforms contained a premature stop codon, yet were not subjected to nonsense-mediated decay, but rather bound to polysomes. Importantly, we detected elevated levels of these alternatively spliced transcripts in individuals with minor spliceosome-related diseases such as Roifman syndrome, Lowry-Wood syndrome and early-onset cerebellar ataxia. In all, we report that the minor spliceosome informs splicing by the major spliceosome through exon-definition interactions and show that minor spliceosome inhibition results in aberrant alternative splicing in disease.
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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) | 0.001 | 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 | 0.001 |
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".