Department of Animal and Poultry Science, Virginia Tech, Blacksburg 24061; Animal Genomics and Improvement Laboratory, Agriculture Research Service, USDA, Beltsville, MD 20705-2350.
Department of Animal and Dairy Science, University of Georgia, Athens 30605.
J Dairy Sci. 2019 Mar;102(3):2336-2346. doi: 10.3168/jds.2018-15434. Epub 2019 Jan 11.
The objective was to compare methods of modeling missing pedigree in single-step genomic BLUP (ssGBLUP). Options for modeling missing pedigree included ignoring the missing pedigree, unknown parent groups (UPG) based on A (the numerator relationship matrix) or H (the unified pedigree and genomic relationship matrix), and metafounders. The assumptions for the distribution of estimated breeding values changed with the different models. We simulated data with heritabilities of 0.3 and 0.1 for dairy cattle populations that had more missing pedigrees for animals of lesser genetic merit. Predictions for the youngest generation and UPG solutions were compared with the true values for validation. For both traits, ssGBLUP with metafounders provided accurate and unbiased predictions for young animals while also appropriately accounting for genetic trend. Accuracy was least and bias was greatest for ssGBLUP with UPG for H for the trait with heritability of 0.3 and with UPG for A for the trait with heritability of 0.1. For the trait with heritability of 0.1 and UPG for H, the UPG accuracy (SD) was -0.49 (0.12), suggesting poor estimates of genetic trend despite having little bias for validations on young, genotyped animals. Problems with UPG estimates were likely caused by the lesser amount of information available for the lower heritability trait. Hence, UPG need to be defined differently based on the trait and amount of information. More research is needed to investigate accounting for UPG in A to better account for missing pedigrees for genotyped animals.
本研究旨在比较单步基因组最佳线性无偏预测（ssGBLUP）中缺失系谱的建模方法。缺失系谱建模的选择包括忽略缺失系谱、基于 A（分子关系矩阵）或 H（统一系谱和基因组关系矩阵）的未知亲本群（UPG）和元祖先。估计育种值分布的假设随不同模型而变化。我们模拟了具有 0.3 和 0.1 遗传力的奶牛群体的数据，这些群体的遗传价值较低的动物的系谱缺失较多。对最年轻一代的预测和 UPG 解决方案与验证的真实值进行了比较。对于两种性状，具有元祖先的 ssGBLUP 为年轻动物提供了准确且无偏的预测，同时适当考虑了遗传趋势。对于遗传力为 0.3 的性状和 H 的 UPG 对于遗传力为 0.1 的性状的 UPG 对于 H 的 ssGBLUP，准确性最低，偏差最大。对于遗传力为 0.1 的性状和 H 的 UPG，UPG 准确性（SD）为-0.49（0.12），尽管对年轻的、基因分型的动物进行验证时偏差较小，但遗传趋势的估计较差。UPG 估计存在问题可能是由于较低遗传力性状的信息量较少所致。因此，需要根据性状和信息量的不同来定义 UPG。需要进一步研究在 A 中考虑 UPG 以更好地为基因分型动物的缺失系谱提供信息。
