PRDM proteins control Wnt/β-catenin activity to regulate craniofacial chondrocyte differentiation
Bibliographic record
Abstract
Summary Cranial neural crest (NCC)-derived chondrocyte precursors undergo a dynamic differentiation and maturation process to establish a scaffold for subsequent bone formation, alterations in which contribute to congenital birth defects. Here, we demonstrate that transcription factor and histone methyltransferase proteins Prdm3 and Prdm16 control the differentiation switch of cranial NCCs to craniofacial cartilage. Loss of either results in hypoplastic and unorganized chondrocytes due to impaired cellular orientation and polarity. We show that PRDMs regulate cartilage differentiation by controlling the timing of Wnt/β-catenin activity in strikingly different ways: prdm3 represses while prdm16 activates global gene expression, though both by regulating Wnt enhanceosome activity and chromatin accessibility. Finally, we show that manipulating Wnt/β-catenin signaling pharmacologically or generating prdm3-/-;prdm16-/- double mutants rescues craniofacial cartilage defects. Our findings reveal upstream regulatory roles for Prdm3 and Prdm16 in cranial NCCs to control Wnt/β-catenin transcriptional activity during chondrocyte differentiation to ensure proper development of the craniofacial skeleton. Highlights Prdm3 and Prdm16 are required for chondrocyte organization in vertebrate craniofacial cartilage Loss of Prdm3 and Prdm16 alters expression of Wnt/β-catenin signaling components Prdm3 and Prdm16 oppositely control global chromatin accessibility Prdm3 and Prdm16 cartilage defects can be rescued pharmacologically or genetically
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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) | 0.002 | 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".