Identification of key genes and pathways associated with duck (<i>Anas platyrhynchos</i>) embryonic skin development using weighted gene co-expression network analysis
Bibliographic record
Abstract
Skin and feather follicle morphogenesis are important processes for duck development; however, the mechanisms underlying morphogenesis at the embryonic stage remain unclear. To improve the understanding of these processes, we used transcriptome and weighted gene co-expression network analyses to identify the critical genes and pathways involved in duck skin development. Five modules were found to be the most related to five key stages in skin development that span from embryonic day 8 (E8) to postnatal day 7 (D7). Using STEM software, 6519 genes from five modules were clustered into 10 profiles to reveal key genes. Above all, we obtained several key module genes including WNT3A, NOTCH1, SHH, BMP2, NOG, SMAD3, and TGFβ2. Furthermore, we revealed that several pathways play critical roles throughout the skin development process, including the Wnt pathway and cytoskeletal rearrangement-related pathways, whereas others are involved in specific stages of skin development, such as the Notch, Hedgehog, and TGF-beta signaling pathways. Overall, this study identified the pathways and genes that play critical roles in skin development, which may provide a basis for high-quality down-type meat duck breeding.
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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".