Data from: Improving the resolution of canine genome-wide association studies using genotype imputation: a study of two breeds

Genotype imputation using a reference panel that combines high-density array data and publicly available whole genome sequence consortium variant data is potentially a cost-effective method to increase the density of extant lower-density array datasets. In this study three datasets (two Border Collie; one Italian Spinone) generated using a legacy array (Illumina CanineHD, 173,662 SNPs) were utilised to assess the feasibility and accuracy of this approach and to gather additional evidence for the efficacy of canine genotype imputation. The cosmopolitan reference panels used to impute genotypes comprised dogs of 158 breeds, mixed breed dogs, wolves, and Chinese indigenous dogs as well as breed-specific individuals genotyped using the Axiom Canine HD array. The two Border Collie reference panels comprised 808 individuals including 79 Border Collies and 426,326 or 426,332 SNPs; and the Italian Spinone reference panel comprised 807 individuals including 38 Italian Spinoni and 476,313 SNPs. A high accuracy for imputation was observed, with the lowest accuracy observed for one of the Border Collie datasets (mean R2 = 0.94) and the highest for the Italian Spinone dataset (mean R2 = 0.97). This study’s findings demonstrate that imputation of a legacy array study set using a reference panel comprising both breed-specific array data and multi-breed variant data derived from whole genomes is effective and accurate. The process of canine genotype imputation, using the valuable growing resource of publicly available canine genome variant datasets alongside breed-specific data, is described in detail to facilitate and encourage use of this technique in canine genetics.结合高密度芯片数据与公开获取的全基因组测序联盟变异数据的参考面板（reference panel）进行基因型填充（Genotype imputation），是提升现有低密度芯片数据集密度的一种潜在高性价比方案。本研究利用3组由传统芯片（legacy array）生成的数据集，其中2组为边境牧羊犬数据集、1组为意大利史毕诺犬数据集，这些数据集均基于Illumina犬用高密度芯片（Illumina CanineHD，包含173662个单核苷酸多态性位点（Single Nucleotide Polymorphism，简称SNPs））构建，以评估该方法的可行性与准确性，并为犬类基因型填充的有效性补充更多实证依据。本研究使用的多品种参考面板涵盖158个犬品种的个体、混种犬、狼以及中国本土犬，同时包含利用Axiom犬用高密度芯片（Axiom Canine HD array）完成基因分型的品种特异性个体。两组边境牧羊犬参考面板共包含808个个体，其中包含79只边境牧羊犬，变异位点数量分别为426326或426332个SNPs；意大利史毕诺犬参考面板则包含807个个体，其中38只为意大利史毕诺犬，位点数量为476313个SNPs。本研究观测到较高的基因型填充准确率：其中一组边境牧羊犬数据集的准确率最低（平均决定系数（R-squared，R²）=0.94），意大利史毕诺犬数据集的准确率最高（平均R²=0.97）。本研究结果证实，结合品种特异性芯片数据与全基因组来源的多品种变异数据构建参考面板，对传统芯片研究数据集进行基因型填充的方案兼具有效性与准确性。本研究详细阐述了结合公开获取的犬类基因组变异数据集（这一日益增长的宝贵资源）与品种特异性数据的犬类基因型填充流程，以期推动该技术在犬类遗传学研究中的应用与推广。