<i>CDKN1C</i> mutation in Wiedemann–Beckwith syndrome patients reduces RNA splicing efficiency and identifies a splicing enhancer
Bibliographic record
Abstract
Wiedemann-Beckwith syndrome (WBS) is a human overgrowth disorder that is accompanied by an increased risk of embryonal tumors and is associated with dsyregulation of the imprinting of genes in chromosome 11p15.5. Maternally inherited mutations in the imprinted CDKN1C gene are known to be associated with WBS. We have identified a novel mutation in several members of a large family affected by WBS. The mutation is a G --> T change in a run of seven G's near the 5' splice site of intron 3. All obligate carriers and affected individuals carry the mutation, and in each affected case, the allele was inherited maternally, strongly suggesting a role in causing WBS. The mutation is located in a poly-G tract in the intron; intronic G-rich sequences in other genes have been shown to have a role in promoting splicing. In transfected 293HEK cells, we found that the G --> T mutation reduced splicing efficiency. Mutation of all seven G's in the poly-G tract further reduced splicing efficiency, supporting a role for the G-tract as a splicing enhancer. The fibroblasts of one affected patient showed a similar reduction in splicing efficiency. Maternal monoallelic expression of CDKN1C was verified in this patient cell line. However, the total amount of spliced message was not reduced by the mutation in spite of the reduced efficiency of splicing. We discuss the possible role of the splicing defect in the pathogenesis of WBS in this pedigree.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".