Massey University, Ruakura Research Centre, Hamilton, 3240, New Zealand.
Iowa State University, 225C Kildee Hall, Ames, IA, 50011, USA.
Genet Sel Evol. 2022 Oct 31;54(1):72. doi: 10.1186/s12711-022-00759-x.
Single-step genomic best linear unbiased prediction (GBLUP) involves a joint analysis of individuals with genotype information, and their ancestors, descendants, or contemporaries, without recorded genotypes. Livestock applications typically represent populations with fewer individuals with genotypes relative to the number not genotyped. Most breeding programmes are structured, consisting of a nucleus tier in which selection drives genetic gains that are propagated through descendants that represent parents in multiplier and commercial tiers. In some cases, the genotypes in the nucleus tier are proprietary to a breeding company, and not publicly available for a whole industry analysis. Bayesian inference involves combining a defined description of prior information with new information to generate a posterior distribution that contains all available information on parameters of interest. A natural extension of Bayesian analysis would be to use information from the posterior distribution to define the prior distribution in a subsequent analysis.
We derive the mixed model equations for inference on breeding values for non genotyped individuals in that subset of the population that is of current interest, using only data on the performance of current individuals and their immediate pedigree, along with prior information defined from the posterior distribution of an external BLUP or single-step GBLUP analysis of the ancestors of the current population.
Identical estimates of breeding values and their prediction error covariances for current animals of interest in the multiplier or commercial tier can be obtained without requiring neither the genomic relationship matrix nor genotypes of any of their ancestors in the nucleus tier, as can be obtained from a single analysis using pedigree, performance, and genomic information from all tiers. The Bayesian analysis of the current population does not require explicit information on unselected genotyped animals in the external population.
单步基因组最佳线性无偏预测（GBLUP）涉及对具有基因型信息的个体及其祖先、后代或同时代人的联合分析，而无需记录基因型。家畜应用通常代表具有基因型的个体数量相对较少的群体，而不是未进行基因分型的个体数量。大多数育种计划是结构化的，包括一个核心层，在该层中选择驱动遗传增益，这些增益通过代表乘数和商业层父母的后代传播。在某些情况下，核心层的基因型是育种公司专有的，而不是整个行业分析的公开可用。贝叶斯推理涉及将先验信息的定义描述与新信息相结合，以生成包含有关感兴趣参数的所有可用信息的后验分布。贝叶斯分析的自然扩展将是使用后验分布中的信息在随后的分析中定义先验分布。
我们使用当前感兴趣的人群中未进行基因分型的个体的性能及其直接谱系的数据，以及从当前人群祖先的外部 BLUP 或单步 GBLUP 分析的后验分布定义的先验信息，推导出用于推断未进行基因分型个体的育种值的混合模型方程。
可以在不要求核层中当前感兴趣的乘数或商业层中动物的基因组关系矩阵或其任何祖先的基因型的情况下，为感兴趣的当前动物获得相同的育种值估计值及其预测误差协方差，就像使用来自所有层的系谱、性能和基因组信息的单个分析一样。当前群体的贝叶斯分析不需要外部群体中未选择的基因分型动物的显式信息。
