Abstract：
This study aimed at evaluating the quality of imputation accuracy (IA) by marker (IAm) and by individual (IAi) in US crossbred dairy cattle. Holstein × Jersey crossbreds were used to evaluate IA from a low- (7K) to a medium-density (50K) SNP chip. Crossbred animals, as well as their sires (53), dams (77), and maternal grandsires (63), were all genotyped with a 78K SNP chip. Seven different scenarios of reference populations were tested, in which some scenarios used different family relationships and others added random unrelated purebred and crossbred individuals to those different family relationship scenarios. The same scenarios were tested on Holstein and Jersey purebred animals to compare these outcomes against those attained in crossbred animals. The genotype imputation was performed with findhap (version 4) software (VanRaden, 2015). There were no significant differences in IA results depending on whether the sire of imputed individuals was Holstein and the dam was Jersey, or vice versa. The IA increased significantly with the addition of related individuals in the reference population, from 86.70 ± 0.06% when only sires or dams were included in the reference population to 90.09 ± 0.06% when sire (S), dam (D), and maternal grandsire genomic data were combined in the reference population. In all scenarios including related individuals in the reference population, IAm and IAi were significantly superior in purebred Jersey and Holstein animals than in crossbreds, ranging from 90.75 ± 0.06 to 94.02 ± 0.06%, and from 90.88 ± 0.11 to 94.04 ± 0.10%, respectively. Additionally, a scenario called SPB+DLD(where PB indicates purebread and LD indicates low density), similar to the genomic evaluations performed on US crossbred dairy, was tested. In this scenario, the information from the 5 evaluated breeds (Ayrshire, Brown Swiss, Guernsey, Holstein, and Jersey) genotyped with a 50K SNP chip and genomic information from the dams genotyped with a 7K SNP chip were combined in the reference population, and the IAm and IAi were 80.87 ± 0.06% and 80.85 ± 0.08%, respectively. Adding randomly nonrelated genotyped individuals in the reference population reduced IA for both purebred and crossbred cows, except for scenario SPB+DLD, where adding crossbreds to the reference population increased IA values. Our findings demonstrate that IA for US Holstein × Jersey crossbred ranged from 85 to 90%, and emphasize the significance of designing and defining the reference population for improved IA.
摘要：
本研究旨在通过标记（IAm）和个体（IAi）评估美国杂交奶牛的归因准确性（IA）的质量。Holstein×Jersey杂种用于评估从低（7K）到中等密度（50K）SNP芯片的归因准确性。杂交动物,以及他们的父亲（53），水坝(77),和外公(63)，全部用78KSNP芯片进行基因分型。测试了参考种群的七个不同方案，其中某些方案使用不同的家庭关系，而其他一些方案则将随机无关的纯种和杂交个体添加到这些不同的家庭关系方案中。在荷斯坦和泽西岛纯种动物上测试了相同的情况，以将这些结果与杂交动物中获得的结果进行比较。用findhap(版本4)软件进行基因型插补。IA结果没有显着差异，具体取决于估算个体的父亲是荷斯坦州，大坝是泽西岛，反之亦然。随着参考人群中相关个体的增加，IA显著增加，从只有父系或水坝被包括在参考人群中的86.70±0.06%到父系中的90.09±0.06%，水坝,在参考人群中合并了母亲的基因组信息。在所有情况下，包括参考人群中的相关个体，纯种泽西岛和荷斯坦动物的IAm和IAi明显优于杂种，范围从90.75±0.06到94.02±0.06%，从90.88±0.11到94.04±0.10%，分别。此外,我们测试了一种名为SPB+DLD的方案,该方案与对美国杂交乳品进行的基因组评估相似.在这种情况下，来自5个评估品种的信息(艾尔郡，棕色瑞士，根西岛,Holstein,和Jersey）用50KSNP芯片进行基因分型，并用7KSNP芯片进行基因分型的大坝的基因组信息在参考人群中组合，IAm和IAi为80.87±0.06%，80.85±0.08%，分别。在参考群体中随机添加非相关基因分型个体降低了纯种和杂交母牛的IA，除了方案SPB+DLD，在参考种群中添加杂种会增加IA值。我们的发现表明，美国荷斯坦×泽西岛杂交的IA从85%到90%不等，并强调设计和定义参考群体对改进IA的重要性。
