Genome-Wide Association Study for Individual Primal Cut Quality Traits in Canadian Commercial Crossbred Pigs
Bibliographic record
Abstract
This study identified genomic variants and potential candidate genes associated with 11 primal cut traits (back fat, belly fat, total fat, loin fat, ham fat, picnic fat, butt fat, loin intramuscular fat content, ham side fat, shoulder dorsal fat, and belly side fat thicknesses) in Canadian commercial crossbred pigs. Genome-wide association studies using whole genome sequencing data were conducted using genotyping data from 1118 commercial crossbred pigs. This analysis revealed multiple QTLs across chromosomes SSC1, 2, 3, 6, 7, 9, 14, 15, and 17, associated with fat traits. Notably, an SNP at position 160,230,075 bp on SSC1 was significantly associated with multiple fat traits, including belly fat, butt fat, ham fat, loin fat, picnic fat, and side fat. Common genes in windows associated with multiple traits, such as MC4R, RNF152, and CDH20 were shared across these traits, suggesting pleiotropic effects. Some of the QTLs were near previously identified QTLs or candidate genes that have been reported to be linked to meat quality traits associated with backfat and intramuscular fat. Other candidate genes identified in the study include TNFRSF11A, LEPR, and genes from the SERPINB family, highlighting their roles in fat deposition and composition. Additional candidate genes were also implicated in regulation of fat metabolism, adipogenesis, and adiposity. These findings offer valuable insights into the genetic architecture of fat traits in pigs, which could inform breeding strategies aimed at improving the pork quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".