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一种基于多重连接探针扩增技术的疾病相关多等位基因拷贝数变异高分辨率基因分型方法。

An MLPA-based approach for high-resolution genotyping of disease-related multi-allelic CNVs.

作者信息

Marcinkowska-Swojak Malgorzata, Klonowska Katarzyna, Figlerowicz Marek, Kozlowski Piotr

机构信息

European Centre of Bioinformatics and Genomics, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland.

European Centre of Bioinformatics and Genomics, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704 Poznan, Poland; Poznan University of Technology, Pl. Marii Sklodowskiej-Curie 5, 60-965 Poznan, Poland.

出版信息

Gene. 2014 Aug 10;546(2):257-62. doi: 10.1016/j.gene.2014.05.072. Epub 2014 Jun 2.

Abstract

Copy number variation has recently been recognized as an important type of genetic variation that modifies human phenotypes. Copy number variants (CNVs) are being increasingly associated with various human phenotypes and diseases. However, the lack of an appropriate method that allows fast, inexpensive and, most importantly, accurate CNVs genotyping significantly hampers CNV analysis. This limitation especially affects the analysis of multi-allelic CNVs that frequently modify various phenotypes. Recently, we developed a multiplex ligation-dependent probe amplification (MLPA)-based strategy for multiplex copy number genotyping and the validation of candidate CNV-miRNAs. Here we present the adaptation and optimization of this recently developed method for high-resolution genotyping of individual disease-related multi-allelic CNVs. We developed appropriate assays for three well-known and extensively studied CNVs: CNV-CCL3L1, CNV-DEFB, and CNV-UGT2B17, which have been associated with various human phenotypes including inflammation-related and infectious diseases. With the use of these assays we identified several general factors that allow to increase the resolution of the copy number genotyping. Performed experiments confirmed the high reproducibility and accuracy of the obtained genotyping results. The reliability of the results and relatively low per-genotype cost makes this strategy an attractive method for large-scale experiments such as genotype-phenotype association studies.

摘要

拷贝数变异最近被认为是一种修饰人类表型的重要遗传变异类型。拷贝数变异(CNV)与各种人类表型和疾病的关联日益增加。然而,缺乏一种能够实现快速、廉价且最重要的是准确的CNV基因分型的合适方法,这严重阻碍了CNV分析。这一限制尤其影响对频繁修饰各种表型的多等位基因CNV的分析。最近,我们开发了一种基于多重连接依赖探针扩增(MLPA)的策略,用于多重拷贝数基因分型和候选CNV-miRNA的验证。在此,我们展示了对这种最近开发的方法进行调整和优化,以用于对个体疾病相关多等位基因CNV进行高分辨率基因分型。我们针对三个广为人知且经过广泛研究的CNV开发了合适的检测方法:CNV-CCL3L1、CNV-DEFB和CNV-UGT2B17,它们与包括炎症相关和传染病在内的各种人类表型有关。通过使用这些检测方法,我们确定了几个能够提高拷贝数基因分型分辨率的一般因素。所进行的实验证实了获得的基因分型结果具有高重现性和准确性。结果的可靠性以及相对较低的每个基因型成本,使得该策略成为诸如基因型-表型关联研究等大规模实验的一种有吸引力的方法。

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