Center for Quantitative Genetics and Genomics, Aarhus University, 8830 Tjele, Denmark.
Departmento de Anatomía, Embriología y Genética Animal, Universidad de Zaragoza, 50013 Saragoza, Spain.
Genetics. 2021 Oct 2;219(2). doi: 10.1093/genetics/iyab130.
In animal and plant breeding and genetics, there has been an increasing interest in intermediate omics traits, such as metabolomics and transcriptomics, which mediate the effect of genetics on the phenotype of interest. For inclusion of such intermediate traits into a genetic evaluation system, there is a need for a statistical model that integrates phenotypes, genotypes, pedigree, and omics traits, and a need for associated computational methods that provide estimated breeding values. In this paper, a joint model for phenotypes and omics data is presented, and a formula for the breeding values on individuals is derived. For complete omics data, three equivalent methods for best linear unbiased prediction of breeding values are presented. In all three cases, this requires solving two mixed model equation systems. Estimation of parameters using restricted maximum likelihood is also presented. For incomplete omics data, extensions of two of these methods are presented, where in both cases, the extension consists of extending an omics-related similarity matrix to incorporate individuals without omics data. The methods are illustrated using a simulated data set.
在动植物育种和遗传学中,人们对中间组学性状(如代谢组学和转录组学)越来越感兴趣,这些性状介导了遗传对感兴趣的表型的影响。为了将这些中间性状纳入遗传评估系统,需要一种能够整合表型、基因型、系谱和组学性状的统计模型,以及提供估计育种值的相关计算方法。本文提出了一种用于表型和组学数据的联合模型,并推导出了个体的育种值公式。对于完整的组学数据,提出了三种用于最佳线性无偏预测育种值的等效方法。在所有三种情况下,这都需要求解两个混合模型方程组。还提出了使用受限最大似然估计参数的方法。对于不完全的组学数据,提出了其中两种方法的扩展,在这两种情况下,扩展都包括扩展一个与组学相关的相似性矩阵,以纳入没有组学数据的个体。该方法使用模拟数据集进行了说明。