首页> 美国卫生研究院文献>Asian-Australasian Journal of Animal Sciences >Genome-wide Association Study (GWAS) and Its Application for Improving the Genomic Estimated Breeding Values (GEBV) of the Berkshire Pork Quality Traits
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Genome-wide Association Study (GWAS) and Its Application for Improving the Genomic Estimated Breeding Values (GEBV) of the Berkshire Pork Quality Traits

机译:全基因组关联研究(GWAS)及其在提高伯克郡猪肉品质性状的基因组估计育种值(GEBV)中的应用

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摘要

The missing heritability has been a major problem in the analysis of best linear unbiased prediction (BLUP). We introduced the traditional genome-wide association study (GWAS) into the BLUP to improve the heritability estimation. We analyzed eight pork quality traits of the Berkshire breeds using GWAS and BLUP. GWAS detects the putative quantitative trait loci regions given traits. The single nucleotide polymorphisms (SNPs) were obtained using GWAS results with p value <0.01. BLUP analyzed with significant SNPs was much more accurate than that with total genotyped SNPs in terms of narrow-sense heritability. It implies that genomic estimated breeding values (GEBVs) of pork quality traits can be calculated by BLUP via GWAS. The GWAS model was the linear regression using PLINK and BLUP model was the G-BLUP and SNP-GBLUP. The SNP-GBLUP uses SNP-SNP relationship matrix. The BLUP analysis using preprocessing of GWAS can be one of the possible alternatives of solving the missing heritability problem and it can provide alternative BLUP method which can find more accurate GEBVs.
机译:在最佳线性无偏预测(BLUP)的分析中,缺失的遗传力一直是一个主要问题。我们将传统的全基因组关联研究(GWAS)引入到BLUP中,以改进遗传力估计。我们使用GWAS和BLUP分析了伯克希尔品种的八个猪肉品质性状。 GWAS根据给定的特征检测假定的数量性状基因座区域。使用GWAS结果获得单核苷酸多态性(SNP),p值<0.01。就窄义遗传力而言,用显着SNP分析的BLUP比用总基因型SNP分析的准确得多。这意味着BLUP可以通过GWAS计算猪肉品质性状的基因组估计育种值(GEBV)。 GWAS模型是使用PLINK的线性回归,而BLUP模型是G-BLUP和SNP-GBLUP。 SNP-GBLUP使用SNP-SNP关系矩阵。使用GWAS预处理进行BLUP分析可能是解决遗留性遗传问题的一种可能替代方法,它可以提供可找到更准确的GEBV的替代BLUP方法。

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