Disrupted minor intron splicing is prevalent in Mendelian disorders
Bibliographic record
Abstract
BACKGROUND: Splicing is crucial for proper gene expression, and is predominately executed by the major spliceosome. Conversely, 722 introns in 699 human minor intron-containing genes (MIGs) are spliced by the minor spliceosome. Splicing of these minor introns is disrupted in diseases caused by pathogenic variants in the minor spliceosome, ultimately leading to the aberrant expression of a subset of these MIGs. However, the effect of variants in minor introns and MIGs on diseases remains unexplored. METHODS: Variants in MIGs and associated clinical manifestations were identified using ClinVar. The HPO database was then used to curate the related symptoms and affected organ systems. RESULTS: We found pathogenic variants in 211 MIGs, which commonly resulted in intellectual disability, seizures and microcephaly. This revealed a subset of MIGs whose aberrant splicing may contribute to the pathogenesis of minor spliceosome-related diseases. Moreover, we identified 51 pathogenic variants in minor intron splice sites that reduce the splice site strength and can induce alternative splicing. CONCLUSION: These findings highlight that disrupted minor intron splicing has a broader impact on human diseases than previously appreciated. The hope is that this knowledge will aid in the development of therapeutic strategies that incorporate the minor intron splicing pathway.
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 | 0.000 | 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) | 0.000 | 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".