Intron retention: a human <i>DKC1</i> gene common splicing event
Bibliographic record
Abstract
Identification of alternatively spliced transcripts produced by a gene is a crucial step in deciphering the bulk of its biological roles and the overall processes that regulate its activity. By using a combination of bioinformatic and molecular approaches we identified, cloned, and characterized 3 novel alternative splice isoforms derived from human dyskeratosis congenita 1 (hDKC1), an essential human gene causative of the X-linked dyskeratosis congenita disease and involved in multiple functions related to cell growth, proliferation, and telomere maintenance. Expression of the new isoforms, all characterized by intron retention, was confirmed by RT-PCR in a panel of diverse cell lines and normal human tissues, and despite the presence of premature termination codons, was not down-regulated by the mechanism of nonsense-mediated decay. Accumulation of these transcripts fluctuated distinctly in the diverse tissues and during in vitro differentiation of Caco2 cells, suggesting that their ratio may contribute to the gene functional diversity across different cell types. Intriguingly, the structure of one isoform leads to exonize an intronically encoded small nucleolar RNA (snoRNA), highlighting an additional layer of complexity that can contribute to overall gene regulation.
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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 | 0.000 |
| 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".