<i>ABCA4</i>midigenes reveal the full splice spectrum of all reported noncanonical splice site variants in Stargardt disease
Bibliographic record
Abstract
Stargardt disease is caused by variants in theABCA4gene, a significant part of which are noncanonical splice site (NCSS) variants. In case a gene of interest is not expressed in available somatic cells, small genomic fragments carrying potential disease-associated variants are tested for splice abnormalities using in vitro splice assays. We recently discovered that when using small minigenes lacking the proper genomic context, in vitro results do not correlate with splice defects observed in patient cells. We therefore devised a novel strategy in which a bacterial artificial chromosome was employed to generate midigenes, splice vectors of varying lengths (up to 11.7 kb) covering almost the entireABCA4gene. These midigenes were used to analyze the effect of all 44 reported and three novel NCSS variants onABCA4pre-mRNA splicing. Intriguingly, multi-exon skipping events were observed, as well as exon elongation and intron retention. The analysis of all reported NCSS variants inABCA4allowed us to reveal the nature of aberrant splicing events and to classify the severity of these mutations based on the residual fraction of wild-type mRNA. Our strategy to generate large overlapping splice vectors carrying multiple exons, creating a toolbox for robust and high-throughput analysis of splice variants, can be applied to all human genes.
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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 | 0.001 |
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".