Shi Liangyu, Wang Ligang, Fang Lingzhao, Li Mianyan, Tian Jingjing, Wang Lixian, Zhao Fuping
Key Laboratory of Animal Genetics, Breeding and Reproduction (Poultry) of Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan, China.
Front Genet. 2022 Nov 25;13:1078696. doi: 10.3389/fgene.2022.1078696. eCollection 2022.
Growth and fat deposition are complex traits, which can affect economical income in the pig industry. Due to the intensive artificial selection, a significant genetic improvement has been observed for growth and fat deposition in pigs. Here, we first investigated genomic-wide association studies (GWAS) and population genomics (e.g., selection signature) to explore the genetic basis of such complex traits in two Large White pig lines ( = 3,727) with the GeneSeek GGP Porcine HD array ( = 50,915 SNPs). Ten genetic variants were identified to be associated with growth and fatness traits in two Large White pig lines from different genetic backgrounds by performing both within-population GWAS and cross-population GWAS analyses. These ten significant loci represented eight candidate genes, , , , , , , , . One of them, gene was simultaneously identified for both two lines in trait. Compared to single-population GWAS, cross-population GWAS was less effective for identifying SNPs with population-specific effect but more powerful for detecting SNPs with population-shared effects. We further detected genomic regions specifically selected in each of two populations, but did not observe a significant enrichment for the heritability of growth and backfat traits in such regions. In summary, the candidate genes will provide an insight into the understanding of the genetic architecture of growth-related traits and backfat thickness, and may have a potential use in the genomic breeding programs in pigs.
生长和脂肪沉积是复杂性状,会影响养猪业的经济收益。由于强烈的人工选择,猪的生长和脂肪沉积已出现显著的遗传改良。在此,我们首先利用GeneSeek GGP猪HD芯片(含50,915个单核苷酸多态性位点(SNPs))对两个大白猪品系(n = 3,727)进行全基因组关联研究(GWAS)和群体基因组学研究(如选择印记),以探究此类复杂性状的遗传基础。通过进行群体内GWAS和跨群体GWAS分析,在两个来自不同遗传背景的大白猪品系中鉴定出10个与生长和脂肪性状相关的遗传变异。这10个显著位点代表8个候选基因,分别为[具体基因名称]。其中,[具体基因名称]基因在两个品系的[具体性状]中均被同时鉴定出来。与单群体GWAS相比,跨群体GWAS在识别具有群体特异性效应的SNPs方面效果较差,但在检测具有群体共享效应的SNPs方面更具效力。我们进一步检测了两个群体各自特有的基因组区域,但未观察到这些区域在生长和背膘性状遗传力方面有显著富集。总之,这些候选基因将有助于深入了解生长相关性状和背膘厚度的遗传结构,并可能在猪的基因组育种计划中具有潜在用途。