INRA, UMR1313 Génétique Animale et Biologie Intégrative, 78350 Jouy-en-Josas, France.
J Dairy Sci. 2012 Jul;95(7):4136-40. doi: 10.3168/jds.2011-5133.
Low-density chips are appealing alternative tools contributing to the reduction of genotyping costs. Imputation enables researchers to predict missing genotypes to recreate the denser coverage of the standard 50K (∼50,000) genotype. Two alternative in silico chips were defined in this study that included markers selected to optimize minor allele frequency and spacing. The objective of this study was to compare the imputation accuracy of these custom low-density chips with a commercially available 3K chip. Data consisted of genotypes of 4,037 Holstein bulls, 1,219 Montbéliarde bulls, and 991 Blonde d'Aquitaine bulls. Criteria to select markers to include in low-density marker panels are described. To mimic a low-density genotype, all markers except the markers present on the low-density panel were masked in the validation population. Imputation was performed using the Beagle software. Combining the directed acyclic graph obtained with Beagle with the PHASEBOOK algorithm provides fast and accurate imputation that is suitable for routine genomic evaluations based on imputed genotypes. Overall, 95 to 99% of alleles were correctly imputed depending on the breed and the low-density chip used. The alternative low-density chips gave better results than the commercially available 3K chip. A low-density chip with 6,000 markers is a valuable genotyping tool suitable for both dairy and beef breeds. Such a tool could be used for preselection of young animals or large-scale screening of the female population.
低密度芯片是一种有吸引力的替代工具,可以降低基因分型成本。 基因分型数据的缺失信息可以通过 imputation 来预测,从而重新创建更密集的标准 50K(约 50,000 个)基因型数据。 在本研究中定义了两种替代的 in silico 芯片,这些芯片包含了为优化次要等位基因频率和间隔而选择的标记。 本研究的目的是比较这些定制的低密度芯片与商业上可用的 3K 芯片的 imputation 准确性。 数据包括 4037 头荷斯坦公牛、1219 头蒙贝利亚尔公牛和 991 头 Blonde d'Aquitaine 公牛的基因型。 描述了选择用于低密度标记面板的标记的标准。 为了模拟低密度基因型,在验证群体中,除了低密度面板上的标记之外,所有标记都被屏蔽。 采用 Beagle 软件进行 imputation。 用 Beagle 获得的有向无环图与 PHASEBOOK 算法相结合,提供了快速准确的 imputation,适用于基于 imputed 基因型的常规基因组评估。 总体而言,根据品种和使用的低密度芯片,95%至 99%的等位基因被正确 imputed。 替代的低密度芯片比商业上可用的 3K 芯片效果更好。 一个有 6000 个标记的低密度芯片是一种适用于奶牛和肉牛品种的有价值的基因分型工具。 这种工具可用于年轻动物的预选或女性群体的大规模筛选。