The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, Scotland, UK.
Genet Sel Evol. 2019 Jun 26;51(1):33. doi: 10.1186/s12711-019-0478-2.
In this paper, we evaluate the performance of using family-specific low-density genotype arrays to increase the accuracy of pedigree-based imputation. Genotype imputation is a widely used tool that decreases the costs of genotyping a population by genotyping the majority of individuals on a low-density array and using statistical regularities between the low-density and high-density individuals to fill in the missing genotypes. Previous work on population-based imputation has found that it is possible to increase the accuracy of imputation by maximizing the number of informative markers on an array. In the context of pedigree-based imputation, where the informativeness of a marker depends only on the genotypes of an individual's parents, it may be beneficial to select the markers on each low-density array on a family-by-family basis.
In this paper, we examined four family-specific low-density marker selection strategies and evaluated their performance in the context of a real pig breeding dataset. We found that family-specific or sire-specific arrays could increase imputation accuracy by 0.11 at one marker per chromosome, by 0.027 at 25 markers per chromosome and by 0.007 at 100 markers per chromosome.
These results suggest that there may be room to use family-specific genotyping for very-low-density arrays particularly if a given sire or sire-dam pairing have a large number of offspring.
在本文中，我们评估了使用特定于家族的低密度基因型数组来提高基于系谱的推断准确性的性能。基因型推断是一种广泛使用的工具，通过对低密度数组中的大多数个体进行基因分型，并利用低密度个体和高密度个体之间的统计规律来填补缺失的基因型，从而降低了对人群进行基因分型的成本。基于人群的推断的先前工作发现，通过最大化数组上的信息量标记数量，可以提高推断的准确性。在基于系谱的推断中，标记的信息量仅取决于个体父母的基因型，因此可能有助于根据家族的情况逐个选择低密度数组上的标记。
在本文中，我们研究了四种特定于家族的低密度标记选择策略，并在真实的猪育种数据集的背景下评估了它们的性能。我们发现，每个染色体上每个标记增加 0.11 的信息量，每个染色体上 25 个标记增加 0.027 的信息量，每个染色体上 100 个标记增加 0.007 的信息量。
这些结果表明，对于非常低密度的数组，可能有空间使用特定于家族的基因分型，特别是如果给定的父本或父本-母本配对有大量后代。
