猪的出生体重是畜牧业的重要经济因素。鉴定出生体重的基因和变体非常重要。在这项研究中,我们整合了两种基因分型方法,单核苷酸多态性(SNP)芯片分析和限制性位点相关DNA测序(RAD-seq)以基因型全基因组SNP。总的来说,用SNP芯片和RAD-seq检测到45,175和139,634个SNP,分别。组合SNP面板的全基因组关联研究(GWAS)确定了两个重要的基因座,分别位于chr1:97,745,041和chr4:112,031,589,分别解释了表型变异的6.36%和4.25%。为了减少包含因果变异的间隔,我们在GWAS识别的区域中估算了序列水平的SNP,并将致病变异精细映射到两个较窄的基因组间隔中:一个~100kb的间隔包含71个SNP,一个更宽的~870kb的间隔包含432个SNP.这个精细的定位突出了四个有希望的候选基因,SKOR2、SMAD2、VAV3和NTNG1。此外,功能基因,SLC25A24、PRMT6和STXBP3也位于精细作图区域附近。这些结果表明,这些候选基因可能对猪的出生体重有很大贡献。
Birth weight of pigs is an important economic factor in the livestock industry. The identification of the genes and variants that underlie birth weight is of great importance. In this
study, we integrated two genotyping methods, single nucleotide polymorphism (SNP) chip analysis and restriction site associated DNA sequencing (RAD-seq) to genotype genome-wide SNPs. In total, 45,175 and 139,634 SNPs were detected with the SNP chip and RAD-seq, respectively. The genome-wide association
study (GWAS) of the combined SNP panels identified two significant loci located at chr1: 97,745,041 and chr4: 112,031,589, that explained 6.36% and 4.25% of the phenotypic variance respectively. To reduce interval containing causal variants, we imputed sequence-level SNPs in the GWAS identified regions and fine-mapped the causative variants into two narrower genomic intervals: a ∼100 kb interval containing 71 SNPs and a broader ∼870 kb interval with 432 SNPs. This fine-mapping highlighted four promising candidate genes, SKOR2, SMAD2, VAV3, and NTNG1. Additionally, the functional genes, SLC25A24, PRMT6 and STXBP3, are also located near the fine-mapping region. These results suggest that these candidate genes may have contribute substantially to the birth weight of pigs.