Interplays of Gli2 and Gli3 and their requirement in mediating Shh-dependent sclerotome induction
Bibliographic record
Abstract
Sonic hedgehog (Shh) signaling is essential for sclerotome development in the mouse. Gli2 and Gli3 are thought to be the primary transcriptional mediators of Shh signaling; however, their roles in Shh induction of sclerotomal genes have not been investigated. Using a combination of mutant analysis and in vitro explant assays, we demonstrate that Gli2 and Gli3 are required for Shh-dependent sclerotome induction. Gli2(-/-)Gli3(-/-) embryos exhibit a severe loss of sclerotomal gene expression, and somitic mesoderm from these embryos cannot activate sclerotomal genes in response to exogenous Shh. We find that one copy of either Gli2 or Gli3 is required to mediate Shh induction of sclerotomal markers Pax1 and Pax9 in vivo and in vitro. Although Gli2 is generally considered an activator and Gli3 a repressor, our results also reveal a repressor function for Gli2 and an activator function for Gli3 in the developing somite. To further dissect the function of each Gli, we used adenovirus to overexpress Gli1, Gli2 and Gli3 in presomitic mesoderm explants. We find that each Gli preferentially activates a distinct set of Shh target genes, suggesting that the functions of Shh in patterning, growth and negative feedback are divided preferentially between different Gli proteins in the somite.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".