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Assessing haplotype-based models for genomic evaluation in Holstein cattle

机译:评估荷斯坦牛基于单倍型的基因组评价模型

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A single-nucleotide polymorphisms-based genomic relationship matrix (G(SNP)) discriminate less identity by state from identity by descent (IBD) alleles compared with a multi-locus haplotype-based relationship matrix (G(HAP)), which can better capture IBD alleles and recent relationships. We aimed to compare the prediction reliability and prediction bias of genomic best linear unbiased prediction (GBLUP) using either G(SNP) or G(HAP) in Holstein cattle. Therefore, a total of 57 traits with a wide range of heritability values were analyzed. Classical validation tests were done using a validation dataset comprised of 50k genotype records of 561-669 proven bulls born in 2010-2011 with an official estimated breeding value (EBV) in 2016 and a training set of 5314-19 678 bulls born before 2010, depending on the trait. The method for building the genomic relationship matrix (G) had significant, but small effect on observed reliability (r(GEBV)(2)) (p & 0.0001) and bias (p & 0.0001). A significant interaction between G and the level of trait heritability on r(GEBV )(2)and bias was also observed (p & 0.0001). The small gains in r(GEBV)(2) and small reductions in the bias by using G(HAP)BLUP were increased when predicting moderate to high-heritability traits compared with low-heritability traits.
机译:基于单核苷酸多态性的基因组关系基质(G(SNP))通过中脑(IBD)等位基因与基于多基因座单倍型的关系矩阵(G(HAP))相比,通过下降(IBD)等位基因的状态判别较少的身份(G(HAP)),这可以更好捕获IBD等位基因和最近的关系。我们旨在使用Holstein牛的G(SNP)或G(HAP)进行基因组最佳线性无偏见预测(GBLUP)的预测可靠性和预测偏差。因此,分析了总共57个具有广泛遗传性值的特征。经典验证测试是使用由50K基因型记录的验证数据集完成,验证的公牛队在2010 - 2011年出生于2010年的官方估计的繁殖价值(EBV),并在2010年之前出生的5314-19辆公牛队进行培训套装,取决于特质。构建基因组关系基质(G)的方法对观察到的可靠性(R(GeBV)(2))(P& 0.0001)和偏置(P& 0.0001)效果显着,但对观察到的可靠性(R(GeBV)(2))效果很小。还观察到G和特质遗传性水平之间的显着相互作用(P& LT; 0.0001)。当与低遗传性特征相比,当预测中度至高遗传性性状时,r(GeBV)(2)和使用G(HAP)增孔的偏差小的降低的小增益增加。

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