Integrated genome-wide association studies, meta-analysis, and Bayesian fine mapping reveal novel quantitative trait loci’s and functional candidate genes for vulva traits in large white pigs
Bibliographic record
Abstract
The size and angle of the vulva are economically important traits in pig production. Gilts with small or upward-tilted vulva are typically culled directly. Selective breeding aimed at improving vulva traits can enhance the retention rate of replacement gilts. This study aimed to systematically explore the key quantitative trait loci (QTL) and genes influencing vulva traits in Large White pigs using genome-wide association studies (GWAS) and meta-analysis techniques. Data on vulva length (VL), vulva width (VW), and vulva angle scores (VAS) were collected from 2,197 Large White gilts across three distinct populations (313 from PIC, 1,169 from Topigs, and 715 from Canada), with genotyping performed using a 50K single-nucleotide polymorphism (SNP) array. The SNP-chip data were imputed to the whole-genome sequencing (iWGS) level. This study used iWGS data to conduct GWAS, identifying a genomic region (SSC5: 103.04-103.34 Mb) significantly associated with VAS in both the Topigs and Canadian Large White pig populations. The significance of this region was further strengthened through multi-population meta-analysis. The most significant SNP (rs3470833446), identified on chromosome 14 and associated with VW in PIC Large White pigs, explained 16.98% of the phenotypic variation (PVE). Multi-population meta-analysis identified novel significant SNPs associated with VL on SSC4, VW on SSC1, SSC4, and SSC6, and VAS on SSC2 and SSC5. Furthermore, a significant potential pleiotropic QTL (SSC4: 36.42-41.24 Mb) regulating both VL and VW was identified. Bayes fine mapping was employed to determine the confidence intervals for these novel QTLs, with the most refined confidence interval narrowed down to 30 kb (SSC4: 38.73-38.76 Mb for VW, and SSC5: 103.20-103.23 Mb for VAS). Based on the biological functions of the genes, the following were identified as novel regulatory candidate genes for vulva traits: VIP, NAV3, and ESR1. These findings reveal potential key genes and genetic mechanisms influencing vulva traits in pigs, providing a crucial molecular genetic basis for improving pig breeding and reproductive performance.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".