Genetic variation at RYR1, IGF2, FUT1, MUC13, and KPL2 mutations affecting production traits in Chinese commercial pig breeds
Bibliographic record
Abstract
The identification of causative mutations affecting economically important traits has benefited the worldwide pig industry. We investigated the genetic variation at five loci including RYR1, IGF2, FUT1, MUC13, and KPL2 affecting traits related to production, reproduction, and disease resistance in a sample of 8009 pigs representing 3 commercial breeds (Duroc, Landrace, and Large White) from 28 farms in China. We found that all breeds, especially Duroc pigs, have high frequencies of favourable alleles for lean production and stress resistance at the IGF2 and RYR1 loci. However, all breeds have low frequencies of the diarrhea-resistant allele of FUT1, indicating that multigenerational selection is required for E. coli F18+ resistant pigs. No linkage disequilibrium was found between the RYR1 and FUT1 loci on pig chromosome 6, supporting the possibility of combined selection for both F18 and stress-resistant pigs. Relatively high frequencies (> 0.5) of the MUC13 allele conferring resistance to E. coli F4ac were found in all three breeds with the highest frequency in Duroc pigs, suggesting that the breeders can establish F4ac diarrhea-resistant lines in a few generations. No defective allele at the KPL2 locus causing immotile short-tail sperms was found in Large White pigs of American, Canadian, Danish, English, and French origin, supporting the conclusion that the KPL2 defective allele is present exclusively in Finnish Large White pigs. These results provide useful information for pig breeding schemes in China.
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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 | 0.000 | 0.000 |
| 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".