A chromosome-level genome assembly for the Silkie chicken resolves complete sequences for key chicken metabolic, reproductive, and immunity genes
Bibliographic record
Abstract
A set of high-quality pan-genomes would help identify important genes that are still hidden/incomplete in bird reference genomes. In an attempt to address these issues, we have assembled a de novo chromosome-level reference genome of the Silkie (Gallus gallus domesticus), which is an important avian model for unique traits, like fibromelanosis, with unclear genetic foundation. This Silkie genome includes the complete genomic sequences of well-known, but unresolved, evolutionarily, endocrinologically, and immunologically important genes, including leptin, ovocleidin-17, and tumor-necrosis factor-α. The gap-less and manually annotated MHC (major histocompatibility complex) region possesses 38 recently identified genes, with differentially regulated genes recovered in response to pathogen challenges. We also provide whole-genome methylation and genetic variation maps, and resolve a complex genetic region that may contribute to fibromelanosis in these animals. Finally, we experimentally show leptin binding to the identified leptin receptor in chicken, confirming an active leptin ligand-receptor system. The Silkie genome assembly not only provides a rich data resource for avian genome studies, but also lays a foundation for further functional validation of resolved genes.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".