Identification, sequence characteristics, and expression patterns of Wnt genes in Eriocheir sinensis
Bibliographic record
Abstract
Wnt genes play crucial roles in various biological mechanisms, such as cell signaling, development, and tissue homeostasis. Recent studies have highlighted the critical role of Wnt genes in limb regeneration. However, the identification and characterization of Wnt genes in the Chinese mitten crab ( Eriocheir sinensis ) remains unexplored. In this study, we conducted a whole-genome identification of Wnts in E . sinensis , and analyzing the sequence characteristics and expression patterns. In summary, 29 Wnt genes were identified in E. sinensis and classed into eight groups based on the sequence similarity. Notably, Wnt7 gene in E. sinensis exists expansion of species-specific. Chromosome location analysis revealed that 14 Wnts were located on chromosomes while the remaining genes were mapped to scaffold segments. Gene structure analysis revealed that Wnt genes contain 10 conserved motifs and the Wnt domain, indicating the conservation of Wnt genes. RNA-seq results further revealed that Wnt5 and Wnt11 may function in limb regeneration. Overall, these findings provide new insights for further functional characterization of Wnts , highlighting the complex mechanism of the Wnts in the regulation of limb regeneration.
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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 | 0.001 |
| 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".