Nkd1 functions downstream of Axin2 to attenuate Wnt signaling
Bibliographic record
Abstract
Wnt signaling is a crucial developmental pathway involved in early development as well as stem-cell maintenance in adults and its misregulation leads to numerous diseases. Thus, understanding the regulation of this pathway becomes vitally important. Axin2 and Nkd1 are widely utilized negative feedback regulators in Wnt signaling where Axin2 functions to destabilize cytoplasmic β-catenin, and Nkd1 functions to inhibit the nuclear localization of β-catenin. Here, we set out to further understand how Axin2 and Nkd1 regulate Wnt signaling by creating axin2gh1/gh1, nkd1gh2/gh2 single mutants and axin2gh1/gh1;nkd1gh2/gh2 double mutant zebrafish using sgRNA/Cas9. All three Wnt regulator mutants were viable and had impaired heart looping, neuromast migration defects, and behavior abnormalities in common, but there were no signs of synergy in the axin2gh1/gh1;nkd1gh2/gh2 double mutants. Further, Wnt target gene expression by qRT-PCR and RNA-seq, and protein expression by mass spectrometry demonstrated that the double axin2gh1/gh1;nkd1gh2/gh2 mutant resembled the nkd1gh2/gh2 phenotype demonstrating that Nkd1 functions downstream of Axin2. In support of this, the data further demonstrates that Axin2 uniquely alters the properties of β-catenin-dependent transcription having novel readouts of Wnt activity compared with nkd1gh2/gh2 or the axin2gh1/gh1;nkd1gh2/gh2 double mutant. We also investigated the sensitivity of the Wnt regulator mutants to exacerbated Wnt signaling, where the single mutants displayed characteristic heightened Wnt sensitivity, resulting in an eyeless phenotype. Surprisingly, this phenotype was rescued in the double mutant, where we speculate that cross-talk between Wnt/β-catenin and Wnt/Planar Cell Polarity pathways could lead to altered Wnt signaling in some scenarios. Collectively, the data emphasizes both the commonality and the complexity in the feedback regulation of Wnt signaling.
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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 | 0.001 |
| 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".