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热带杂交奶牛群体中的基因型推断。

Genotype imputation in a tropical crossbred dairy cattle population.

机构信息

Departamento de Medicina Veterinária, Universidade de São Paulo (USP), Faculdade de Zootecnia e Engenharia de Alimentos, Pirassununga, SP, 13635-900, Brazil.

Departamento de Ciências Exatas, Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, SP, 14884-900, Brazil.

出版信息

J Dairy Sci. 2017 Dec;100(12):9623-9634. doi: 10.3168/jds.2017-12732. Epub 2017 Oct 4.

Abstract

The objective of this study was to investigate different strategies for genotype imputation in a population of crossbred Girolando (Gyr × Holstein) dairy cattle. The data set consisted of 478 Girolando, 583 Gyr, and 1,198 Holstein sires genotyped at high density with the Illumina BovineHD (Illumina, San Diego, CA) panel, which includes ∼777K markers. The accuracy of imputation from low (20K) and medium densities (50K and 70K) to the HD panel density and from low to 50K density were investigated. Seven scenarios using different reference populations (RPop) considering Girolando, Gyr, and Holstein breeds separately or combinations of animals of these breeds were tested for imputing genotypes of 166 randomly chosen Girolando animals. The population genotype imputation were performed using FImpute. Imputation accuracy was measured as the correlation between observed and imputed genotypes (CORR) and also as the proportion of genotypes that were imputed correctly (CR). This is the first paper on imputation accuracy in a Girolando population. The sample-specific imputation accuracies ranged from 0.38 to 0.97 (CORR) and from 0.49 to 0.96 (CR) imputing from low and medium densities to HD, and 0.41 to 0.95 (CORR) and from 0.50 to 0.94 (CR) for imputation from 20K to 50K. The CORR exceeded 0.96 (for 50K and 70K panels) when only Girolando animals were included in RPop (S1). We found smaller CORR when Gyr (S2) was used instead of Holstein (S3) as RPop. The same behavior was observed between S4 (Gyr + Girolando) and S5 (Holstein + Girolando) because the target animals were more related to the Holstein population than to the Gyr population. The highest imputation accuracies were observed for scenarios including Girolando animals in the reference population, whereas using only Gyr animals resulted in low imputation accuracies, suggesting that the haplotypes segregating in the Girolando population had a greater effect on accuracy than the purebred haplotypes. All chromosomes had similar imputation accuracies (CORR) within each scenario. Crossbred animals (Girolando) must be included in the reference population to provide the best imputation accuracies.

摘要

本研究旨在探讨在杂交 Girolando(Gyr×Holstein)奶牛群体中进行基因型推断的不同策略。该数据集包括 478 头 Girolando、583 头 Gyr 和 1198 头荷斯坦公牛,它们均采用 Illumina BovineHD(Illumina,圣地亚哥,CA)面板进行高密度基因分型,该面板包含约 777K 个标记。我们研究了从低(20K)和中密度(50K 和 70K)到高密度面板以及从低到 50K 密度的基因型推断的准确性。针对从低到中密度和从低到 50K 密度的基因型推断,我们测试了七种使用不同参考群体(RPop)的方案,这些方案分别考虑了 Girolando、Gyr 和 Holstein 品种,或这些品种的动物组合。我们对 166 头随机选择的 Girolando 动物的基因型进行了群体基因型推断。使用 FImpute 进行了种群基因型推断。推断准确性通过观测基因型与推断基因型之间的相关性(CORR)和正确推断的基因型比例(CR)来衡量。这是第一篇关于 Girolando 群体中基因型推断准确性的论文。样本特异性推断准确性范围为 0.38 到 0.97(CORR)和 0.49 到 0.96(CR),从低和中密度推断到高密度,以及 0.41 到 0.95(CORR)和 0.50 到 0.94(CR)从 20K 推断到 50K。当仅将 Girolando 动物纳入 RPop 时(S1),CORR 超过了 0.96(对于 50K 和 70K 面板)。当使用 Gyr(S2)而不是 Holstein(S3)作为 RPop 时,我们发现 CORR 较小。在 S4(Gyr+Girolando)和 S5(Holstein+Girolando)之间也观察到了相同的行为,因为目标动物与荷斯坦种群的关系比与 Gyr 种群的关系更密切。在参考群体中包含 Girolando 动物的情况下,观察到了最高的推断准确性,而仅使用 Gyr 动物则导致推断准确性较低,这表明在 Girolando 群体中分离的单倍型对准确性的影响大于纯合单倍型。在每个方案中,所有染色体的推断准确性(CORR)都相似。必须将杂交动物(Girolando)纳入参考群体,以提供最佳的推断准确性。

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