Huang Y, Wu F, Tang X, Li J, Ge M, Wang M, Wei J, Xiao S, Zhang Z
National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Jiangxi Agricultural University, Nanchang 330045, China.
National Key Laboratory for Swine Genetic Improvement and Germplasm Innovation, Jiangxi Agricultural University, Nanchang 330045, China.
Animal. 2025 Nov;19(11):101654. doi: 10.1016/j.animal.2025.101654. Epub 2025 Sep 9.
Growth, fatness, and reproductive traits are key economic traits that significantly influence the efficiency and long-term sustainability of commercial pig production. While genome-wide association study (GWAS) has proven to be an effective approach for identifying genetic variants associated with key traits, the significant loci identified by GWAS do not necessarily correspond to the true causal genes. To address this, we performed GWAS on 4 560 pigs from three populations to investigate six traits: right teat number (RTN), left teat number (LTN), body length (BL), body height (BH), BW and backfat thickness (BFT). We incorporated three post-GWAS analyses: expression quantitative trait loci mapping, Bayesian colocalisation analysis, and Mendelian randomisation to prioritise candidate causal genes. Genes supported by at least two independent lines of evidence were prioritised as high-confidence causal candidates. GWAS identified one novel lead single nucleotide polymorphism (SNP) on Sus scrofa chromosome 7 (SSC7) for teat number and two new lead SNPs for BFT on SSC1 and SSC18. A total of 16 and 23 potential causal genes were identified for LTN and RTN, respectively. Among these, four genes (ABCD4, ALDH6A1, ENTPD5, and ISCA2) were supported by all four lines of evidence for both traits. For BL, four out of ten candidate genes (ABCD4, PTGR2, ENTPD5 and FAM161B) received full support. For BFT, two of 23 genes (EXOSC2 and USP20) were fully supported. Regarding BW, among six genes, ASS1 ranked the highest and was supported by three lines of evidence. For BH, 12 genes, including PTK6 and STMN3, were supported by two lines of evidence. In summary, the integration of GWAS with multiple post-GWAS analyses provides a powerful and systematic strategy to refine association signals and prioritise putative causal genes. The novel loci and candidate genes identified expand genetic resources for marker-assisted selection and provide insights into the genetic basis of growth performance and reproductive traits in the pig industry.
生长、肥瘦度和繁殖性状是关键经济性状，对商品猪生产的效率和长期可持续性有重大影响。虽然全基因组关联研究（GWAS）已被证明是识别与关键性状相关的遗传变异的有效方法，但GWAS鉴定出的显著位点不一定对应于真正的因果基因。为解决这一问题，我们对来自三个群体的4560头猪进行了GWAS，以研究六个性状：右乳头数（RTN）、左乳头数（LTN）、体长（BL）、体高（BH）、体重（BW）和背膘厚度（BFT）。我们纳入了三种GWAS后分析：表达数量性状位点定位、贝叶斯共定位分析和孟德尔随机化，以确定候选因果基因的优先级。至少有两条独立证据支持的基因被优先列为高可信度因果候选基因。GWAS在猪7号染色体（SSC7）上鉴定出一个与乳头数相关的新的领先单核苷酸多态性（SNP），在SSC1和SSC18上鉴定出两个与BFT相关的新的领先SNP。分别为LTN和RTN鉴定出16个和23个潜在因果基因。其中，四个基因（ABCD4、ALDH6A1、ENTPD5和ISCA2）在这两个性状的所有四条证据中均得到支持。对于BL，十个候选基因中有四个（ABCD4、PTGR2、ENTPD5和FAM161B）得到了充分支持。对于BFT，23个基因中有两个（EXOSC2和USP20）得到了充分支持。关于BW，在六个基因中，ASS1排名最高，有三条证据支持。对于BH，包括PTK6和STMN3在内的12个基因有两条证据支持。总之，GWAS与多种GWAS后分析的整合提供了一种强大而系统的策略，以优化关联信号并确定推定因果基因的优先级。鉴定出的新位点和候选基因扩展了标记辅助选择的遗传资源，并为养猪业生长性能和繁殖性状的遗传基础提供了见解。
