Suppressor of Fused Chaperones Gli Proteins To Generate Transcriptional Responses to Sonic Hedgehog Signaling
Bibliographic record
Abstract
Cellular responses to the graded Sonic Hedgehog (Shh) morphogenic signal are orchestrated by three Gli genes that give rise to both transcription activators and repressors. An essential downstream regulator of the pathway, encoded by the tumor suppressor gene Suppressor of fused (Sufu), plays critical roles in the production, trafficking, and function of Gli proteins, but the mechanism remains controversial. Here, we show that Sufu is upregulated in active Shh responding tissues and accompanies Gli activators translocating into and Gli repressors out of the nucleus. Trafficking of Sufu to the primary cilium, potentiated by Gli activators but not repressors, was found to be coupled to its nuclear import. We have identified a nuclear export signal (NES) motif of Sufu in juxtaposition to the protein kinase A (PKA) and glycogen synthase kinase 3 (GSK3) dual phosphorylation sites and show that Sufu binds the chromatin with both Gli1 and Gli3. Close comparison of neural tube development among individual Ptch1−/−, Sufu−/−, and Ptch1−/−; Sufu−/− double mutant embryos indicates that Sufu is critical for the maximal activation of Shh signaling essential to the specification of the most-ventral neurons. These data define Sufu as a novel class of molecular chaperone required for every aspect of Gli regulation and function.
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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".