热门话题:利用表型、全谱系和基因组信息统一方法对荷斯坦综合评分进行遗传评估。

Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score.

机构信息

Animal and Dairy Science Department, University of Georgia, Athens 30602; Instituto Nacional de Investigación Agropecuaria, Las Brujas 90200, Uruguay.

出版信息

J Dairy Sci. 2010 Feb;93(2):743-52. doi: 10.3168/jds.2009-2730.

Abstract

The first national single-step, full-information (phenotype, pedigree, and marker genotype) genetic evaluation was developed for final score of US Holsteins. Data included final scores recorded from 1955 to 2009 for 6,232,548 Holsteins cows. BovineSNP50 (Illumina, San Diego, CA) genotypes from the Cooperative Dairy DNA Repository (Beltsville, MD) were available for 6,508 bulls. Three analyses used a repeatability animal model as currently used for the national US evaluation. The first 2 analyses used final scores recorded up to 2004. The first analysis used only a pedigree-based relationship matrix. The second analysis used a relationship matrix based on both pedigree and genomic information (single-step approach). The third analysis used the complete data set and only the pedigree-based relationship matrix. The fourth analysis used predictions from the first analysis (final scores up to 2004 and only a pedigree-based relationship matrix) and prediction using a genomic based matrix to obtain genetic evaluation (multiple-step approach). Different allele frequencies were tested in construction of the genomic relationship matrix. Coefficients of determination between predictions of young bulls from parent average, single-step, and multiple-step approaches and their 2009 daughter deviations were 0.24, 0.37 to 0.41, and 0.40, respectively. The highest coefficient of determination for a single-step approach was observed when using a genomic relationship matrix with assumed allele frequencies of 0.5. Coefficients for regression of 2009 daughter deviations on parent-average, single-step, and multiple-step predictions were 0.76, 0.68 to 0.79, and 0.86, respectively, which indicated some inflation of predictions. The single-step regression coefficient could be increased up to 0.92 by scaling differences between the genomic and pedigree-based relationship matrices with little loss in accuracy of prediction. One complete evaluation took about 2h of computing time and 2.7 gigabytes of memory. Computing times for single-step analyses were slightly longer (2%) than for pedigree-based analysis. A national single-step genetic evaluation with the pedigree relationship matrix augmented with genomic information provided genomic predictions with accuracy and bias comparable to multiple-step procedures and could account for any population or data structure. Advantages of single-step evaluations should increase in the future when animals are pre-selected on genotypes.

摘要

美国荷斯坦牛最终评分的首次全国单步、全信息(表型、系谱和标记基因型)遗传评估。数据包括 1955 年至 2009 年 6232548 头荷斯坦奶牛的最终评分记录。来自合作奶牛 DNA 资源库(马里兰州贝尔茨维尔)的 BovineSNP50(Illumina,圣地亚哥,加利福尼亚)基因型可用于 6508 头公牛。三种分析均使用当前用于全国美国评估的重复性动物模型。前两种分析仅使用了截至 2004 年的最终评分记录。第一项分析仅使用基于系谱的关系矩阵。第二项分析使用基于系谱和基因组信息的关系矩阵(单步方法)。第三项分析使用完整数据集和仅基于系谱的关系矩阵。第四项分析使用第一项分析的预测(截至 2004 年的最终评分记录和仅基于系谱的关系矩阵)和使用基于基因组的矩阵进行预测以获得遗传评估(多步方法)。在构建基因组关系矩阵时测试了不同的等位基因频率。使用基于父母平均、单步和多步方法的年轻公牛预测值与 2009 年女儿偏差之间的决定系数分别为 0.24、0.37 至 0.41 和 0.40。当使用假定等位基因频率为 0.5 的基因组关系矩阵时,单步方法的最高决定系数。2009 年女儿偏差对父母平均、单步和多步预测值的回归系数分别为 0.76、0.68 至 0.79 和 0.86,表明预测值略有膨胀。通过将基因组和基于系谱的关系矩阵之间的差异缩放,单步回归系数可提高到 0.92,而预测精度几乎没有损失。一次完整的评估大约需要 2 小时的计算时间和 2.7 吉字节的内存。单步分析的计算时间比基于系谱的分析略长(2%)。使用系谱关系矩阵增强基因组信息的全国单步遗传评估提供了与多步程序相当的准确性和偏差的基因组预测,并且可以解释任何群体或数据结构。当动物根据基因型预先选择时,单步评估的优势将在未来增加。

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