Department of Animal Science, North Carolina State University, Raleigh, NC 27607.
Department of Agriculture, Food, Environment and Forestry, University of Florence, Florence, 50144, Italy.
J Dairy Sci. 2024 Jan;107(1):398-411. doi: 10.3168/jds.2023-23250. Epub 2023 Aug 23.
This study aimed at evaluating the quality of imputation accuracy (IA) by marker (IA) and by individual (IA) 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, IA and IA 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 S+D(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 IA and IA 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 S+D, 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.
本研究旨在评估美国杂交奶牛中基于标记(IA)和个体(IA)的插补准确性(IA)的质量。使用荷斯坦×泽西杂交牛来评估从低密度(7K)到中密度(50K)SNP 芯片的 IA。杂交动物及其父本(53)、母本(77)和母系祖父(63)均使用 78K SNP 芯片进行基因分型。测试了七种不同的参考群体情景,其中一些情景使用不同的亲缘关系,而其他情景则在这些不同的亲缘关系情景中添加了随机无关的纯血和杂交个体。在荷斯坦和泽西纯血动物中测试了相同的情景,以比较在杂交动物中获得的结果。基因型的插补是使用 findhap(版本 4)软件(VanRaden,2015)进行的。在参考群体中,无论父本是荷斯坦、母本是泽西,还是反之,IA 结果没有显著差异。随着参考群体中相关个体的增加,IA 显著增加,从仅包括父本或母本的参考群体中 86.70±0.06%增加到包括父本(S)、母本(D)和母系祖父基因组数据的参考群体中 90.09±0.06%。在所有包括参考群体中相关个体的情景中,纯血泽西和荷斯坦动物的 IA 和 IA 都显著优于杂交动物,范围分别为 90.75±0.06%至 94.02±0.06%和 90.88±0.11%至 94.04±0.10%。此外,还测试了一种称为 S+D(其中 PB 表示纯血,LD 表示低密度)的情景,类似于在美国杂交奶牛中进行的基因组评估。在这种情况下,将用 50K SNP 芯片基因分型的 5 个评估品种(Ayrshire、Brown Swiss、Guernsey、Holstein 和 Jersey)的信息与用 7K SNP 芯片基因分型的母本的基因组信息结合在参考群体中,IA 和 IA 分别为 80.87±0.06%和 80.85±0.08%。在参考群体中添加随机非相关的基因分型个体降低了纯血和杂交牛的 IA,除了 S+D 情景外,在该情景中,向参考群体中添加杂交牛增加了 IA 值。我们的研究结果表明,美国荷斯坦×泽西杂交牛的 IA 范围在 85%到 90%之间,强调了设计和定义参考群体以提高 IA 的重要性。