The minor and major spliceosome interact to regulate alternative splicing around minor introns
Bibliographic record
Abstract
Abstract Mutations in minor spliceosome components are linked to diseases such as Roifman syndrome, Lowry-Wood syndrome, and early-onset cerebellar ataxia (EOCA). Here we report that besides increased minor intron retention, Roifman syndrome and EOCA can also be characterized by elevated alternative splicing (AS) around minor introns. Consistent with the idea that the assembly/activity of the minor spliceosome informs AS in minor intron-containing genes (MIGs), inhibition of all minor spliceosome snRNAs led to upregulated AS. Notably, alternatively spliced MIG isoforms were bound to polysomes in the U11-null dorsal telencephalon, which suggested that aberrant MIG protein expression could contribute to disease pathogenesis. In agreement, expression of an aberrant isoform of the MIG Dctn3 by in utero electroporation, affected radial glial cell divisions. Finally, we show that AS around minor introns is executed by the major spliceosome and is regulated by U11-59K of the minor spliceosome, which forms exon-bridging interactions with proteins of the major spliceosome. Overall, we extend the exon-definition model to MIGs and postulate that disruptions of exon-bridging interactions might contribute to disease severity and pathogenesis.
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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) | 0.002 | 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".