T396I Mutation of Mouse Sufu Reduces the Stability and Activity of Gli3 Repressor
Bibliographic record
Abstract
Hedgehog signaling is primarily transduced by two transcription factors: Gli2, which mainly acts as a full-length activator, and Gli3, which tends to be proteolytically processed from a full-length form (Gli3FL) to an N-terminal repressor (Gli3REP). Recent studies using a Sufu knockout mouse have indicated that Sufu is involved in regulating Gli2 and Gli3 activator and repressor activity at multiple steps of the signaling cascade; however, the mechanism of specific Gli2 and Gli3 regulation remains to be elucidated. In this study, we established an allelic series of ENU-induced mouse strains. Analysis of one of the missense alleles, SufuT396I, showed that Thr396 residue of Sufu played a key role in regulation of Gli3 activity. SufuT396I/T396I embryos exhibited severe polydactyly, which is indicative of compromised Gli3 activity. Concomitantly, significant quantitative reductions of unprocessed Gli3 (Gli3FL) and processed Gli3 (Gli3REP) were observed in vivo as well as in vitro. Genetic experiments showed that patterning defects in the limb buds of SufuT396I/T396I were rescued by a constitutive Gli3REP allele (Gli3∆699), strongly suggesting that SufuT396I reduced the truncated Gli3 repressor. In contrast, SufuT396I qualitatively exhibited no mutational effects on Gli2 regulation. Taken together, the results of this study show that the Thr396 residue of Sufu is specifically required for regulation of Gli3 but not Gli2. This implies a novel Sufu-mediated mechanism in which Gli2 activator and Gli3 repressor are differentially regulated.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".