<i>HDAC9</i>structural variants disrupting<i>TWIST1</i>transcriptional regulation lead to craniofacial and limb malformations
Bibliographic record
Abstract
Structural variants (SVs) can affect protein-coding sequences as well as gene regulatory elements. However, SVs disrupting protein-coding sequences that also function ascis-regulatory elements remain largely uncharacterized. Here, we show that craniosynostosis patients with SVs containing the histone deacetylase 9(HDAC9) protein-coding sequence are associated with disruption ofTWIST1regulatory elements that reside within theHDAC9sequence. Based on SVs within theHDAC9‐TWIST1locus, we defined the 3′-HDAC9sequence as a criticalTWIST1regulatory region, encompassing craniofacialTWIST1enhancers and CTCF sites. Deletions of eitherTwist1enhancers (eTw5-7Δ/Δ) or CTCF site (CTCF-5Δ/Δ) within theHdac9protein-coding sequence led to decreasedTwist1expression and altered anterior/posterior limb expression patterns of SHH pathway genes. This decreasedTwist1expression results in a smaller sized and asymmetric skull and polydactyly that resemblesTwist1+/−mouse phenotype. Chromatin conformation analysis revealed that theTwist1promoter interacts withHdac9sequences that encompassTwist1enhancers and a CTCF site, and that interactions depended on the presence of both regulatory regions. Finally, a large inversion of the entireHdac9sequence (Hdac9INV/+) in mice that does not disruptHdac9expression but repositionsTwist1regulatory elements showed decreasedTwist1expression and led to a craniosynostosis-like phenotype and polydactyly. Thus, our study elucidates essential components ofTWIST1transcriptional machinery that reside within theHDAC9sequence. It suggests that SVs encompassing protein-coding sequences could lead to a phenotype that is not attributed to its protein function but rather to a disruption of the transcriptional regulation of a nearby gene.
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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 | 0.000 | 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) | 0.003 | 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".