4.8 Article

Copy Number Variation Analysis by Ligation-Dependent PCR Based on Magnetic Nanoparticles and Chemiluminescence

Journal

THERANOSTICS
Volume 5, Issue 1, Pages 71-85

Publisher

IVYSPRING INT PUBL
DOI: 10.7150/thno.10117

Keywords

Copy number variation; Ligation-dependent PCR; Magnetic nanoparticles; Chemiluminescence

Funding

  1. National Basic Research Program (973 Program) of China [2010CB933903, 2014CB744501]
  2. National Nature Science Foundation of China (NSFC) [61271056, 31201003, 81301305, 21205013, 61471168]
  3. state key laboratory of bioelectronics of southeast university [2012F12, 2012F13]
  4. Natural Science Foundation of Jiangsu Province [BK20130892]

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A novel system for copy number variation (CNV) analysis was developed in the present study using a combination of magnetic separation and chemiluminescence (CL) detection technique. The amino-modified probes were firstly immobilized onto carboxylated magnetic nanoparticles (MNPs) and then hybridized with biotin-dUTP products, followed by amplification with ligation-dependent polymerase chain reaction (PCR). After streptavidin-modified alkaline phosphatase (STV-AP) bonding and magnetic separation, the CL signals were then detected. Results showed that the quantification of PCR products could be reflected by CL signal values. Under optimum conditions, the CL system was characterized for quantitative analysis and the CL intensity exhibited a linear correlation with logarithm of the target concentration. To validate the methodology, copy numbers of six genes from the human genome were detected. To compare the detection accuracy, multiplex ligation-dependent probe amplification (MLPA) and MNPs-CL detection were performed. Overall, there were two discrepancies by MLPA analysis, while only one by MNPs-CL detection. This research demonstrated that the novel MNPs-CL system is a useful analytical tool which shows simple, sensitive, and specific characters which are suitable for CNV analysis. Moreover, this system should be improved further and its application in the genome variation detection of various diseases is currently under further investigation.

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