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低密度基因分型在纯血马中的应用。

The utility of low-density genotyping for imputation in the Thoroughbred horse.

机构信息

Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK.

出版信息

Genet Sel Evol. 2014 Feb 4;46(1):9. doi: 10.1186/1297-9686-46-9.

Abstract

BACKGROUND

Despite the dramatic reduction in the cost of high-density genotyping that has occurred over the last decade, it remains one of the limiting factors for obtaining the large datasets required for genomic studies of disease in the horse. In this study, we investigated the potential for low-density genotyping and subsequent imputation to address this problem.

RESULTS

Using the haplotype phasing and imputation program, BEAGLE, it is possible to impute genotypes from low- to high-density (50K) in the Thoroughbred horse with reasonable to high accuracy. Analysis of the sources of variation in imputation accuracy revealed dependence both on the minor allele frequency of the single nucleotide polymorphisms (SNPs) being imputed and on the underlying linkage disequilibrium structure. Whereas equidistant spacing of the SNPs on the low-density panel worked well, optimising SNP selection to increase their minor allele frequency was advantageous, even when the panel was subsequently used in a population of different geographical origin. Replacing base pair position with linkage disequilibrium map distance reduced the variation in imputation accuracy across SNPs. Whereas a 1K SNP panel was generally sufficient to ensure that more than 80% of genotypes were correctly imputed, other studies suggest that a 2K to 3K panel is more efficient to minimize the subsequent loss of accuracy in genomic prediction analyses. The relationship between accuracy and genotyping costs for the different low-density panels, suggests that a 2K SNP panel would represent good value for money.

CONCLUSIONS

Low-density genotyping with a 2K SNP panel followed by imputation provides a compromise between cost and accuracy that could promote more widespread genotyping, and hence the use of genomic information in horses. In addition to offering a low cost alternative to high-density genotyping, imputation provides a means to combine datasets from different genotyping platforms, which is becoming necessary since researchers are starting to use the recently developed equine 70K SNP chip. However, more work is needed to evaluate the impact of between-breed differences on imputation accuracy.

摘要

背景

尽管过去十年高密度基因分型的成本大幅降低,但它仍然是获得用于马基因组疾病研究的大型数据集所需的限制因素之一。在这项研究中,我们研究了利用低密度基因分型和随后的推断来解决这个问题的可能性。

结果

使用单倍型相位和推断程序 BEAGLE,可以合理到高度准确地从低密度(50K)推断出纯血马的基因型。推断准确性变化的来源分析表明,不仅依赖于要推断的单核苷酸多态性(SNP)的次要等位基因频率,而且还依赖于潜在的连锁不平衡结构。虽然低密度面板上 SNP 的等距间隔效果很好,但优化 SNP 选择以增加其次要等位基因频率是有利的,即使面板随后用于具有不同地理起源的群体。用连锁不平衡图谱距离替换碱基对位置减少了 SNP 之间推断准确性的变化。虽然 1K SNP 面板通常足以确保超过 80%的基因型被正确推断,但其他研究表明,2K 到 3K 的面板更有效,可以最大限度地减少基因组预测分析中随后的准确性损失。不同低密度面板的准确性和基因分型成本之间的关系表明,2K SNP 面板将具有良好的性价比。

结论

使用 2K SNP 面板进行低密度基因分型,然后进行推断,可以在成本和准确性之间取得平衡,这可能会促进更广泛的基因分型,并因此在马中使用基因组信息。除了为高密度基因分型提供低成本替代方案外,推断还提供了一种结合来自不同基因分型平台的数据集的方法,这在研究人员开始使用最近开发的马 70K SNP 芯片时变得越来越必要。然而,还需要做更多的工作来评估品种间差异对推断准确性的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83bb/3930001/c6a1a07acddd/1297-9686-46-9-1.jpg

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