Institute of Animal Breeding, Bavarian State Research Center for Agriculture, 85586 Grub, Germany.
Institute of Animal Breeding, Bavarian State Research Center for Agriculture, 85586 Grub, Germany.
J Dairy Sci. 2019 Apr;102(4):3266-3273. doi: 10.3168/jds.2018-15592. Epub 2019 Feb 22.
Single-step genomic evaluations have the advantage of simultaneously combining all pedigree, phenotypic, and genotypic information available. However, systems with a large number of genotyped animals have some computational challenges. In many genomic breeding programs, genomic predictions of young animals should become available for selection decisions in the shortest time possible, which requires either a very effective estimation or an approximation with negligible loss in accuracy. We investigated different procedures for predicting breeding values of young genotyped animals without setting up the full single-step system augmented for the additional genotypes. Methods were based on transmitting the information from single-step breeding values of genotyped animals that took part in the previous full run to young animals, either through genomic relationships or through a marker-based model. The different procedures were tested on real data from the April 2017 run of the German-Austrian official genomic evaluation for Fleckvieh. The data set included 62,559 genotyped animals and was used to run single-step evaluations for 23 conformation traits. A further data set comprising 1,768 young animals was used for interim prediction and we called it the validation set. The reference values for validation were the predicted breeding values of the young animals from a full single-step run containing the genotypes of all 64,327 animals. Correlations between the approximated predictions and those from the full single-step run also containing genotypes from young animals averaged 0.9932 for the best method (from 0.990 to 0.995 across traits). In conclusion, prediction of single-step breeding values for young animals can be well approximated using systems of size equal to the number of markers.
一步法基因组评估具有同时结合所有系谱、表型和基因型信息的优势。然而,具有大量基因分型动物的系统存在一些计算挑战。在许多基因组育种计划中,年轻动物的基因组预测应该在尽可能短的时间内为选择决策提供,这需要非常有效的估计或近似,而不会在准确性上造成显著损失。我们研究了不同的方法,在不建立为额外基因型增强的完整一步法系统的情况下,预测年轻基因分型动物的育种值。方法基于将参与前一次完整运行的基因分型动物的一步法育种值的信息传递给年轻动物,要么通过基因组关系,要么通过基于标记的模型。在德国-奥地利 2017 年 4 月的弗莱克维赫官方基因组评估的实际数据上测试了不同的方法。数据集包括 62559 只基因分型动物,用于 23 个体型性状的一步法评估。另一个数据集包括 1768 只年轻动物,用于中间预测,我们称之为验证集。验证的参考值是从包含所有 64327 只动物基因型的完整一步法运行中得出的年轻动物的预测育种值。最佳方法的近似预测与包含年轻动物基因型的完整一步法运行的预测值之间的相关性平均为 0.9932(跨性状从 0.990 到 0.995)。总之,使用与标记数相等的系统可以很好地近似预测年轻动物的一步法育种值。