Quantitative and sensitive detection of GNAS mutations causing mccune-albright syndrome with next generation sequencing.
Quantitative and sensitive detection of GNAS mutations causing mccune-albright syndrome with next generation sequencing.
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DOI：
10.1371/journal.pone.0060525
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Hasegawa T
中科院分区：
文献类型：
--
作者：
Narumi S;Matsuo K;Ishii T;Tanahashi Y;Hasegawa T
体细胞激活GNAS突变导致McCune-Albright综合征（MAS）。由于突变丰度低，需要突变特异性富集程序，如肽核酸（PNA）方法，以检测外周血中的突变。新一代测序技术（NGS）可以独立分析数百万个PCR扩增子，因此有望定量检测低丰度的GNAS突变。在本研究中，我们的目的是开发一种基于NGS的方法来检测低丰度的体细胞GNAS突变。在MiSeq仪器上对包含GNAS的外显子8和9的PCR扩增子进行测序，其中大多数激活突变发生在所述外显子8和9中。正如预期的那样，我们的基于NGS的方法可以以非常高的读取深度（约100，000）和低错误率对GNAS基因座进行测序。使用克隆的突变体和野生型DNA样品进行的系列稀释研究显示，稀释度和测量的突变丰度之间存在线性相关性，表明突变定量的可靠性。使用连续稀释的样品，确定了三种突变检测方法（PNA法、NGS法以及PNA和NGS的组合使用[PNA-NGS]）的检出限。PNA法的最低可检测突变丰度为1%，NGS法为0.03%，PNA-NGS法为0.01%。最后，我们用三种方法分析了16例MAS患者的白细胞DNA样本，并比较了它们的突变检出率。PNA法、NGS法和PNA-NGS法对16例患者外周血标本的突变检出率分别为56%、63%和75%。总之，NGS可以从外周血样品中定量和灵敏地检测体细胞激活GNAS突变。目前，PNA-NGS方法可能是检测低丰度GNAS突变的最灵敏的方法。
Somatic activating GNAS mutations cause McCune-Albright syndrome (MAS). Owing to low mutation abundance, mutant-specific enrichment procedures, such as the peptide nucleic acid (PNA) method, are required to detect mutations in peripheral blood. Next generation sequencing (NGS) can analyze millions of PCR amplicons independently, thus it is expected to detect low-abundance GNAS mutations quantitatively. In the present study, we aimed to develop an NGS-based method to detect low-abundance somatic GNAS mutations. PCR amplicons encompassing exons 8 and 9 of GNAS, in which most activating mutations occur, were sequenced on the MiSeq instrument. As expected, our NGS-based method could sequence the GNAS locus with very high read depth (approximately 100,000) and low error rate. A serial dilution study with use of cloned mutant and wildtype DNA samples showed a linear correlation between dilution and measured mutation abundance, indicating the reliability of quantification of the mutation. Using the serially diluted samples, the detection limits of three mutation detection methods (the PNA method, NGS, and combinatory use of PNA and NGS [PNA-NGS]) were determined. The lowest detectable mutation abundance was 1% for the PNA method, 0.03% for NGS and 0.01% for PNA-NGS. Finally, we analyzed 16 MAS patient-derived leukocytic DNA samples with the three methods, and compared the mutation detection rate of them. Mutation detection rate of the PNA method, NGS and PNA-NGS in 16 patient-derived peripheral blood samples were 56%, 63% and 75%, respectively. In conclusion, NGS can detect somatic activating GNAS mutations quantitatively and sensitively from peripheral blood samples. At present, the PNA-NGS method is likely the most sensitive method to detect low-abundance GNAS mutation.
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