Characterization of swine adiponectin and adiponectin receptor polymorphisms and their association with reproductive traits
Bibliographic record
Abstract
In this study, polymorphisms in genes encoding porcine adiponectin (ADIPOQ) and its receptors (ADIPOR1 and ADIPOR2) were evaluated for associations with reproductive traits in a Landrace sow population. Sixteen SNPs were identified, and among these, associations were found between reproductive traits and five SNPs. Heterozygous multiparous females for SNP ADIPOQEF601160:c.178G>A had fewer stillborn piglets (P < 0.05) and shorter weaning-to-oestrus intervals (P < 0.05). Multiparous females bearing the mutant allele for SNP ADIPOQEF601160:c.*1094_1095insC gave birth to fewer stillborn piglets (P < 0.05). In addition, selection for the ADIPOQ [A;C] haplotype is expected to result in multiparous sows having the lowest number of stillborn piglets and shorter weaning-to-oestrus intervals. In second-parity sows, the polymorphism in ADIPOR1 (AY856513:c.*129A>C) showed significant associations with live-born (P < 0.01) and stillborn (P < 0.05) piglets. In multiparous sows, a significant association was observed for an ADIPOR2 polymorphism (AY856514:c.*112G>A), with the c.*112GA genotype associated with shorter weaning-to-oestrus intervals (P < 0.01). Haplotype analyses of ADIPOR2 SNPs revealed that selection in favour of the [A;C] haplotype and against the [G;G] haplotype may result in sows having an increased number of live-born piglets and shorter weaning-to-oestrus intervals. We have therefore described specific SNPs and haplotypes that are associated with large litter size, fewer stillborn and mummified piglets and shorter weaning-to-oestrus intervals. Selection for these SNPs and haplotypes is a strategy to improve reproductive success in pigs.
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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 | 0.001 | 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) | 0.001 | 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".