Disease-Causing 7.4 kb Cis-Regulatory Deletion Disrupting Conserved Non-Coding Sequences and Their Interaction with the FOXL2 Promotor: Implications for Mutation Screening
Bibliographic record
Abstract
To date, the contribution of disrupted potentially cis-regulatory conserved non-coding sequences (CNCs) to human disease is most likely underestimated, as no systematic screens for putative deleterious variations in CNCs have been conducted. As a model for monogenic disease we studied the involvement of genetic changes of CNCs in the cis-regulatory domain of FOXL2 in blepharophimosis syndrome (BPES). Fifty-seven molecularly unsolved BPES patients underwent high-resolution copy number screening and targeted sequencing of CNCs. Apart from three larger distant deletions, a de novo deletion as small as 7.4 kb was found at 283 kb 5' to FOXL2. The deletion appeared to be triggered by an H-DNA-induced double-stranded break (DSB). In addition, it disrupts a novel long non-coding RNA (ncRNA) PISRT1 and 8 CNCs. The regulatory potential of the deleted CNCs was substantiated by in vitro luciferase assays. Interestingly, Chromosome Conformation Capture (3C) of a 625 kb region surrounding FOXL2 in expressing cellular systems revealed physical interactions of three upstream fragments and the FOXL2 core promoter. Importantly, one of these contains the 7.4 kb deleted fragment. Overall, this study revealed the smallest distant deletion causing monogenic disease and impacts upon the concept of mutation screening in human disease and developmental disorders in particular.
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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 | 0.000 |
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".