Technical considerations for genotyping multi-allelic copy number variation (CNV), in regions of segmental duplication.

Technical considerations for genotyping multi-allelic copy number variation (CNV), in regions of segmental duplication.
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DOI:
10.1186/1471-2164-15-329
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发表时间:
2014-05-01
期刊:
影响因子:
4.4
通讯作者:
White SJ
White SJ
中科院分区:
生物学2区
文献类型:
--
作者:
Cantsilieris S;Western PS;Baird PN;White SJ

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染色体内片段复制为非等位基因同源重组提供了底物,促进了人类基因组拷贝数的广泛变异。许多多拷贝基因家族嵌入具有高水平序列同一性(>95%)的基因组区域,因此构成了相当大的分析挑战。在某些情况下,分析这些区域所涉及的复杂性在很大程度上被低估了。快速、经济有效的多拷贝基因区域分析通常采用定量方法,然而定量数据并不是绝对确定的手段。因此,任何容易产生测量误差程度的技术都可能产生模棱两可的结果,从而可能导致与复杂疾病的虚假关联。在本研究中,我们着重于测试定量分析技术的准确性和可重复性。参考C-C趋化因子配体-3-like-1 (CCL3L1)基因,我们采用实时定量PCR (QPCR)、多重连接依赖探针扩增(MLPA)和平行比率测试(PRT)进行分析。在控制了检测性能的潜在外部变量(包括DNA浓度、质量、制备和储存条件)后,我们发现实时QPCR产生的数据并不紧密地聚集在拷贝数整数值周围,其变化大大大于MLPA或PRT系统。我们发现,四舍五入实时QPCR测量的方法可能会导致拷贝数基因型的错误评分,并建议在解释QPCR数据时应谨慎。我们得出结论,实时QPCR本质上容易产生测量误差,即使在似乎有利于关联研究的条件下。我们的研究结果表明,DNA样品的物理化学性质的潜在变异性不能完全解释实时QPCR系统表现不佳的原因。我们建议使用PRT或MLPA等更可靠的方法对疾病关联研究中的多等位基因拷贝数变异进行基因分型,并提出了几种可以实施的方法,以确保使用定量方法进行拷贝数分型的质量。
Intrachromosomal segmental duplications provide the substrate for non-allelic homologous recombination, facilitating extensive copy number variation in the human genome. Many multi-copy gene families are embedded within genomic regions with high levels of sequence identity (>95%) and therefore pose considerable analytical challenges. In some cases, the complexity involved in analyzing such regions is largely underestimated. Rapid, cost effective analysis of multi-copy gene regions have typically implemented quantitative approaches, however quantitative data are not an absolute means of certainty. Therefore any technique prone to degrees of measurement error can produce ambiguous results that may lead to spurious associations with complex disease. In this study we have focused on testing the accuracy and reproducibility of quantitative analysis techniques. With reference to the C-C Chemokine Ligand-3-like-1 (CCL3L1) gene, we performed analysis using real-time Quantitative PCR (QPCR), Multiplex Ligation-dependent Probe Amplification (MLPA) and Paralogue Ratio Test (PRT). After controlling for potential outside variables on assay performance, including DNA concentration, quality, preparation and storage conditions, we find that real-time QPCR produces data that does not cluster tightly around copy number integer values, with variation substantially greater than that of the MLPA or PRT systems. We find that the method of rounding real-time QPCR measurements can potentially lead to mis-scoring of copy number genotypes and suggest caution should be exercised in interpreting QPCR data. We conclude that real-time QPCR is inherently prone to measurement error, even under conditions that would seem favorable for association studies. Our results indicate that potential variability in the physicochemical properties of the DNA samples cannot solely explain the poor performance exhibited by the real-time QPCR systems. We recommend that more robust approaches such as PRT or MLPA should be used to genotype multi-allelic copy number variation in disease association studies and suggest several approaches which can be implemented to ensure the quality of the copy number typing using quantitative methods.
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