Activation of Fgf4 Gene Expression in the Myotomes Is Regulated by Myogenic bHLH Factors and by Sonic Hedgehog
Bibliographic record
Abstract
The Fgf4 gene encodes an important signaling molecule which is expressed in specific developmental stages, including the inner cell mass of the blastocyst, the myotomes, and the limb bud apical ectodermal ridge (AER). Using a transgenic approach, we previously identified overlapping but distinct enhancer elements in the Fgf4 3' untranslated region necessary and sufficient for myotome and AER expression. Here we have investigated the hypothesis that Fgf4 is a target of myogenic bHLH factors. We show by mutational analysis that a conserved E box located in the Fgf4 myotome enhancer is required for Fgf4-lacZ expression in the myotomes. A DNA probe containing the E box binds MYF5, MYOD, and bHLH-like activities from nuclear extracts of differentiating C2-7 myoblast cells, and both MYF5 and MYOD can activate gene expression of reporter plasmids containing the E-box element. Analyses of Myf5 and MyoD knockout mice harboring Fgf4-lacZ transgenes show that Myf5 is required for Fgf4 expression in the myotomes, while MyoD is not, but MyoD can sustain Fgf4 expression in the ventral myotomes in the absence of Myf5. Sonic hedgehog (Shh) signaling has been shown to have an essential inductive function in the expression of Myf5 and MyoD in the epaxial myotomes, but not in the hypaxial myotomes. We show here that expression of an Fgf4-lacZ transgene in Shh-/- embryos is suppressed not only in the epaxial but also in the hypaxial myotomes, while it is maintained in the AER. This suggests that Shh mediates Fgf4 activation in the myotomes through mechanisms independent of its role in the activation of myogenic factors. Thus, a cascade of events, involving Shh and bHLH factors, is responsible for activating Fgf4 expression in the myotomes in a spatial- and temporal-specific manner.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".