Genome-wide association study provides insights into the genetic architecture of bone size and mass in chickens
Bibliographic record
Abstract
Bone size is an important trait for chickens because of its association with osteoporosis in layers and meat production in broilers. Here, we employed high density genotyping platforms to detect candidate genes for bone traits. Estimates of the narrow heritabilities ranged from 0.37 ± 0.04 for shank length to 0.59 ± 0.04 for tibia length. The dominance heritability was 0.12 ± 0.04 for shank length. Using a linear mixed model approach, we identified a promising locus within NCAPG on chromosome 4, which was associated with tibia length and mass, femur length and area, and shank length. In addition, three other loci were associated with bone size or mass at a Bonferroni-corrected genome-wide significance threshold of 1%. One region on chicken chromosome 1 between 168.38 and 171.82 Mb harbored HTR2A, LPAR6, CAB39L, and TRPC4. A second region that accounted for 2.2% of the phenotypic variance was located around WNT9A on chromosome 2, where allele substitution was predicted to be associated with tibia length. Four candidate genes identified on chromosome 27 comprising SPOP, NGFR, GIP, and HOXB3 were associated with tibia length and mass, femur length and area, and shank length. Genome partitioning analysis indicated that the variance explained by each chromosome was proportional to its length.
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 | 0.001 | 0.001 |
| 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".