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利用国家育种值或多性状跨国评估育种值进行跨国基因组预测。

Across-countries genomic prediction using national breeding values or multitrait across-countries evaluation breeding values.

机构信息

Interbull Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Science, Box 7023, 75007 Uppsala, Sweden.

Interbull Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Science, Box 7023, 75007 Uppsala, Sweden.

出版信息

J Dairy Sci. 2022 Apr;105(4):3282-3295. doi: 10.3168/jds.2021-20877. Epub 2022 Feb 3.

Abstract

In across-country genomic predictions for dairy cattle, 2 kinds of bull information can be used as dependent variables. The first is estimated breeding value (EBV) from the national genetic evaluations, assuming genetic correlations between countries are less than 1. The second is EBV from multitrait across-countries evaluation (MACE), assuming genetic correlations between countries equal 1. In the present study, the level of bias and reliability of a cross-countries genomic prediction using national EBV or MACE EBV as the dependent variable were investigated. Data from Brown Swiss Organizations joining the InterGenomics Service by Interbull Centre (Uppsala, Sweden) were used. National and MACE EBV of 3 traits (protein yield, cow conception rate, and calving interval) from 7, 5, and 4 countries, respectively, were used, resulting in 16 trait-country combinations. Genotypes for 45,473 SNP markers and deregressed (national or MACE) EBV of 7,490; 5,833; and 5,177 bulls were used in analysis of protein yield, cow conception rate, and calving interval, respectively. For most of trait-country combinations, the use of MACE EBV via single-trait approach resulted in less biased and more reliable across-countries genomic predictions. In case some of the MACE EBV might have been inflated, the resulting single-trait genomic predictions were inflated as well. For these specific cases, the use of national EBV via multitrait approach provided less bias and more reliable across-countries genomic predictions.

摘要

在奶牛的跨国基因组预测中,可以将两种公牛信息用作因变量。第一种是来自国家遗传评估的估计育种值(EBV),假设国家间的遗传相关系数小于 1。第二种是来自跨国多性状评估(MACE)的 EBV,假设国家间的遗传相关系数等于 1。本研究探讨了使用国家 EBV 或 MACE EBV 作为因变量进行跨国基因组预测的偏倚和可靠性水平。使用了来自参与 InterGenomics 服务的 Brown Swiss 组织的数据,该服务由 Interbull 中心(瑞典乌普萨拉)提供。使用了 7、5 和 4 个国家的 3 个性状(蛋白质产量、奶牛受胎率和产犊间隔)的国家和 MACE EBV,共 16 个性状-国家组合。在分析蛋白质产量、奶牛受胎率和产犊间隔时,使用了 45473 个 SNP 标记和 7490、5833 和 5177 头公牛的去回归(国家或 MACE) EBV。对于大多数性状-国家组合,使用 MACE EBV 通过单性状方法可获得更低的偏倚和更可靠的跨国基因组预测。在某些 MACE EBV 可能被夸大的情况下,由此产生的单性状基因组预测也被夸大了。对于这些特定情况,使用多性状方法的国家 EBV 可提供更低的偏倚和更可靠的跨国基因组预测。

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