Animal Genetics and Breeding Unit, University of New England, Armidale, NSW, 2351, Australia.
Genet Sel Evol. 2018 Aug 3;50(1):39. doi: 10.1186/s12711-018-0410-1.
A common measure employed to evaluate the efficacy of livestock improvement schemes is the genetic trend, which is calculated as the means of predicted breeding values for animals born in successive time periods. This implies that different cohorts refer to the same base population. For genetic evaluation schemes integrating genomic information with records for all animals, genotyped or not, this is often not the case: expected means for pedigree founders are zero whereas values for genotyped animals are expected to sum to zero at the (mean) time corresponding to the frequencies that are used to center marker allele counts when calculating genomic relationships.
The paper examines estimates of genetic trends from single-step genomic evaluations. After a review of methods which propose to align pedigree-based and genomic relationship matrices, simulation is used to illustrate the effects of alignments and choice of assumed gene frequencies on trajectories of genetic trends.
The results show that methods available to alleviate differences between the founder populations implied by the two types of relationship matrices perform well; in particular, the meta-founder approach is advantageous. An application to data from routine genetic evaluation of Australian sheep is shown, confirming their effectiveness for practical data.
Aligning pedigree and genomic relationship matrices for single step genetic evaluation for populations under selection is essential. Fitting meta-founders is an effective and simple method to avoid distortion of estimates of genetic trends.
评估家畜改良计划效果的常用方法是遗传趋势,它是通过对不同时期出生的动物的预测育种值的平均值来计算的。这意味着不同的群体指的是同一基础群体。对于整合了基因组信息和所有动物记录(无论是否进行基因分型)的遗传评估计划,情况通常并非如此:系谱创始人的预期均值为零,而基因分型动物的预期值在(均值)时间上为零,该时间对应于用于计算基因组关系时标记等位基因计数的频率中心。
本文检查了单步基因组评估中遗传趋势的估计。在回顾了提出对齐基于系谱和基因组关系矩阵的方法之后,模拟用于说明对齐和假设基因频率的选择对遗传趋势轨迹的影响。
结果表明,可用于缓解两种关系矩阵所暗示的基础群体之间差异的方法效果良好;特别是,元基础方法具有优势。对来自澳大利亚绵羊常规遗传评估的数据进行了应用,证实了它们对实际数据的有效性。
对于处于选择下的单步遗传评估,对齐系谱和基因组关系矩阵是必要的。拟合元基础是避免遗传趋势估计失真的有效且简单的方法。