Regulation of Multiple Core Spliceosomal Proteins by Alternative Splicing-Coupled Nonsense-Mediated mRNA Decay
Bibliographic record
Abstract
Alternative splicing (AS) can regulate gene expression by introducing premature termination codons (PTCs) into spliced mRNA that subsequently elicit transcript degradation by the nonsense-mediated mRNA decay (NMD) pathway. However, the range of cellular functions controlled by this process and the factors required are poorly understood. By quantitative AS microarray profiling, we find that there are significant overlaps among the sets of PTC-introducing AS events affected by individual knockdown of the three core human NMD factors, Up-Frameshift 1 (UPF1), UPF2, and UPF3X/B. However, the levels of some PTC-containing splice variants are less or not detectably affected by the knockdown of UPF2 and/or UPF3X, compared with the knockdown of UPF1. The intron sequences flanking the affected alternative exons are often highly conserved, suggesting important regulatory roles for these AS events. The corresponding genes represent diverse cellular functions, and surprisingly, many encode core spliceosomal proteins and assembly factors. We further show that conserved, PTC-introducing AS events are enriched in genes that encode core spliceosomal proteins. Where tested, altering the expression levels of these core spliceosomal components affects the regulation of PTC-containing splice variants from the corresponding genes. Together, our results show that AS-coupled NMD can have different UPF factor requirements and is likely to regulate many general components of the spliceosome. The results further implicate general spliceosomal components in AS regulation.
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 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".