Genetic dissection of nonconventional introns reveals codominant noncanonical splicing code in <i>Euglena</i>
Bibliographic record
Abstract
Pre-mRNA splicing is essential for eukaryotic gene expression and is achieved through the accurate recognition of exon–intron boundaries. Although nonconventional introns, which do not follow the conventional GT-AG splicing rule, have been identified in several species, these introns are typically rare in any given genome. Here, we demonstrate the widespread occurrence of nonconventional introns (71.8% of all introns) in the Euglena agilis genome and identify consensus motifs at these nonconventional exon–intron boundaries. We assessed the splicing efficiency of nonconventional introns and variants with point mutations via genomic knock-in within the second exon of Glucan synthase-like 2 in Euglena gracilis and genetically defined the sequence signature (5′-N 3 CDG-/-CH′GN 5–6 |R exon -3′) required for their proper splicing. This signature is present in 61.2% of all nonconventional introns detected in the E. agilis genome. Accordingly, we present a noncanonical splicing code for Euglena introns, highlighting the global coexistence of dual splicing rules for conventional and nonconventional introns.
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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 | 0.001 |
| 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".