本研究旨在分析血管生成素样蛋白3(angiopoietin-like protein 3,ANGPTL3)基因的单核苷酸多态性(SNPs)及其与中国西门塔尔牛肉质性状的关联性,寻找可用于辅助选择的分子标记。随机选取饲养条件相同的98头中国西门塔尔牛为研究对象,采用P...本研究旨在分析血管生成素样蛋白3(angiopoietin-like protein 3,ANGPTL3)基因的单核苷酸多态性(SNPs)及其与中国西门塔尔牛肉质性状的关联性,寻找可用于辅助选择的分子标记。随机选取饲养条件相同的98头中国西门塔尔牛为研究对象,采用PCR-SSCP技术结合DNA测序技术检测ANGPTL3基因的SNP。运用SPSS 19.0软件对ANGPTL3基因的不同基因型与肉质性状进行关联性分析。经测序发现,ANGPTL3基因外显子4中存在1个突变位点G7358C,存在2种基因型:CD、DD。关联性分析结果表明,G7358C突变位点的不同基因型与胴体脂肪覆盖率、眼肌面积、肌内脂肪和大理石花纹差异显著相关(P<0.05),CC基因型个体胴体脂肪覆盖率、眼肌面积、肌内脂肪和大理石花纹显著高于CD基因型个体(P<0.05)。试验结果表明,G7358C位点的CC基因型为优势基因型,与胴体脂肪覆盖率、眼肌面积、肌内脂肪和大理石花纹等肉用性状有相关性,ANGPTL3基因有望作为分子标记辅助选择的候选基因。展开更多
Genomic selection has been demonstrated as a powerful technology to revolutionize animal breeding. However, marker density and minor allele frequency can affect the predictive ability of genomic estimated breeding val...Genomic selection has been demonstrated as a powerful technology to revolutionize animal breeding. However, marker density and minor allele frequency can affect the predictive ability of genomic estimated breeding values （GEBVs）. To investigate the impact of marker density and minor allele frequency on predictive ability, we estimated GEBVs by constructing the different subsets of single nucleotide polymorphisms （SNPs） based on varying markers densities and minor allele frequency （MAF） for average daily gain （ADG）, live weight （LW） and carcass weight （CW） in 1 059 Chinese Simmental beef cattle. Two strategies were proposed for SNP selection to construct different marker densities： 1） select evenly-spaced SNPs （Strategy 1 ）, and 2） select SNPs with large effects estimated from BayesB （Strategy 2）. Furthermore, predictive ability was assessed in terms of the correlation between predicted genomic values and corrected phenotypes from 10-fold cross-validation. Predictive ability for ADG, LW and CW using autosomal SNPs were 0.13＋0.002, 0.21＋0.003 and 0.25＋0.003, respectively. In our study, the predictive ability increased dramatically as more SNPs were included in analysis until 200K for Strategy 1. Under Strategy 2, we found the predictive ability slightly increased when marker densities increased from 5K to 20K, which indicated the predictive ability of 20K （3% of 770K） SNPs with large effects was equal to the predictive ability of using all SNPs. For different MAF bins, we obtained the highest predictive ability for three traits with MAF bin 0.01-0.1. Our result suggested that designing a low-density chip by selecting low frequency markers with large SNP effects sizes should be helpful for commercial application in Chinese Simmental cattle.展开更多
文摘本研究旨在分析血管生成素样蛋白3(angiopoietin-like protein 3,ANGPTL3)基因的单核苷酸多态性(SNPs)及其与中国西门塔尔牛肉质性状的关联性,寻找可用于辅助选择的分子标记。随机选取饲养条件相同的98头中国西门塔尔牛为研究对象,采用PCR-SSCP技术结合DNA测序技术检测ANGPTL3基因的SNP。运用SPSS 19.0软件对ANGPTL3基因的不同基因型与肉质性状进行关联性分析。经测序发现,ANGPTL3基因外显子4中存在1个突变位点G7358C,存在2种基因型:CD、DD。关联性分析结果表明,G7358C突变位点的不同基因型与胴体脂肪覆盖率、眼肌面积、肌内脂肪和大理石花纹差异显著相关(P<0.05),CC基因型个体胴体脂肪覆盖率、眼肌面积、肌内脂肪和大理石花纹显著高于CD基因型个体(P<0.05)。试验结果表明,G7358C位点的CC基因型为优势基因型,与胴体脂肪覆盖率、眼肌面积、肌内脂肪和大理石花纹等肉用性状有相关性,ANGPTL3基因有望作为分子标记辅助选择的候选基因。
基金supported by the National Natural Science Foundation of China(31201782,31672384 and 31372294)the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences(ASTIPIAS03)+3 种基金the Cattle Breeding Innovative Research Team of Chinese Academy of Agricultural Sciences(cxgc-ias-03)the Key Technology R&D Program of China during the 12th Five-Year Plan period(2011BAD28B04)the National High Technology Research and Development Program of China(863 Program 2013AA102505-4)the Beijing Natural Science Foundation,China(6154032)
文摘Genomic selection has been demonstrated as a powerful technology to revolutionize animal breeding. However, marker density and minor allele frequency can affect the predictive ability of genomic estimated breeding values （GEBVs）. To investigate the impact of marker density and minor allele frequency on predictive ability, we estimated GEBVs by constructing the different subsets of single nucleotide polymorphisms （SNPs） based on varying markers densities and minor allele frequency （MAF） for average daily gain （ADG）, live weight （LW） and carcass weight （CW） in 1 059 Chinese Simmental beef cattle. Two strategies were proposed for SNP selection to construct different marker densities： 1） select evenly-spaced SNPs （Strategy 1 ）, and 2） select SNPs with large effects estimated from BayesB （Strategy 2）. Furthermore, predictive ability was assessed in terms of the correlation between predicted genomic values and corrected phenotypes from 10-fold cross-validation. Predictive ability for ADG, LW and CW using autosomal SNPs were 0.13＋0.002, 0.21＋0.003 and 0.25＋0.003, respectively. In our study, the predictive ability increased dramatically as more SNPs were included in analysis until 200K for Strategy 1. Under Strategy 2, we found the predictive ability slightly increased when marker densities increased from 5K to 20K, which indicated the predictive ability of 20K （3% of 770K） SNPs with large effects was equal to the predictive ability of using all SNPs. For different MAF bins, we obtained the highest predictive ability for three traits with MAF bin 0.01-0.1. Our result suggested that designing a low-density chip by selecting low frequency markers with large SNP effects sizes should be helpful for commercial application in Chinese Simmental cattle.
