Detangling the evolutionary developmental integration of dentate jaws: evidence that a <i>p63</i> gene network regulates odontogenesis exclusive of mandible morphogenesis
Bibliographic record
Abstract
SUMMARY Vertebrate jaws and dentitions fit and function together, yet the genetic processes that coordinate cranial and dental morphogenesis and evolution remain poorly understood. Teeth but not jaws fail to form in the edentate p63 −/− mouse mutant, which we used here to identify genes important to odontogenesis, but not jaw morphogenesis, and that may allow dentitions to change during development and evolution without necessarily affecting the jaw skeleton. With the working hypothesis that tooth and jaw development are autonomously controlled by discreet gene regulatory networks, using gene expression microarray assays validated by quantitative reverse‐transcription PCR we contrasted expression in mandibular prominences at embryonic days (E) 10–13 of mice with normal lower jaw development but either normal ( p63 +/− , p63 +/+ ) or arrested ( p63 −/− ) tooth development. The p63 −/− mice showed significantly different expression (fold change ≥2, ≤−2; P ≤ 0.05) of several genes. Some of these are known to help regulate odontogenesis (e.g., p63 , Osr2 , Cldn3/4 ) and/or to be targets of p63 (e.g., Jag1/2 , Fgfr2 ); other genes have no previously reported roles in odontogenesis or the p63 pathway (e.g., Fermt1 , Cbln1 , Pltp , Krt8 ). As expected, from E10 to E13, few genes known to regulate mandible morphogenesis differed in expression between mouse strains. This study newly links several genes to odontogenesis and/or to the p63 signaling network. We propose that these genes act in a novel odontogenic network that is exclusive of lower jaw morphogenesis, and posit that this network evolved in oral, not pharyngeal, teeth.
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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".