Cataloging the potential functional diversity of Cacna1e splice variants using long-read sequencing
Bibliographic record
Abstract
BACKGROUND: The degree to which alternative RNA splicing influences the function and structure of voltage gated calcium channel (VGCC) splice variants is poorly understood. Here we used long-read RNA-sequencing to catalog rat Cacna1e (Cav2.3) splice variants, and computationally prioritize which are likely to impact channel function. RESULT: We sequenced Cacna1e transcripts from rat thalamus using Oxford Nanopore sequencing yielding the structure of 2,110 Cacna1e splice variants. Of these, up to 154 had the potential encode for a functional channel based on predicted amino acid sequences. Our analysis revealed a total of 31 cassette splicing events (in various combinations) potentially affecting channel function, with three cassette exons appreciably expressed and conserved. CONCLUSION: Our work both provides the first long-read sequencing of Cacna1e and the first computational evaluation of Cacna1e splice variants for future follow-up. This overall strategy to provide the field with prioritized transcripts will improve our understanding of Cacna1e function, its role in disease pathophysiology, and serve as a general approach to evaluate splice variant function across multiple ion channel types.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".