4.7 Article

Copy-Number Variation Genotyping of GSTT1 and GSTM1 Gene Deletions by Real-Time PCR

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CLINICAL CHEMISTRY
卷 55, 期 9, 页码 1680-1685

出版社

AMER ASSOC CLINICAL CHEMISTRY
DOI: 10.1373/clinchem.2008.120105

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资金

  1. British Lung Foundation
  2. Asthma, Allergy & Inflammation Research Charity
  3. Infection, Inflammation and Immunity Division, School of Medicine, University of Southampton
  4. Medical Research Council UK
  5. MRC [G0401540] Funding Source: UKRI
  6. Medical Research Council [U1475000004, G0401540, G9815508] Funding Source: researchfish

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BACKGROUND: Structural variation in the human genome is increasingly recognized as being highly prevalent and having relevance to common human diseases. Array-based comparative genome-hybridization technology can be used to determine copy-number variation (CNV) across entire genomes, and quantitative PCR (qPCR) can be used to validate de novo variation or assays of common CNV in disease-association studies. Analysis of large qPCR data sets can be complicated and time-consuming, however. METHODS: We describe qPCR assays for GSTM1 (glutathione S-transferase mu 1) and GSTT1 (glutathione S-transferase theta 1) gene deletions that can genotype up to 192 samples in duplicate 5-mu L reaction volumes in < 2 h on the ABI Prism 7900HT Sequence Detection System. To streamline data handling and analysis of these CNVs by qPCR, we developed a novel interactive, macro-driven Microsoft Excel (R) spreadsheet. As proof of principle, we used our software to analyze CNV data for 1478 DNA samples from a family-based cohort. RESULTS: With only 8 ng of DNA template, we assigned CNV genotypes (i.e., 2, 1, or 0 copies) to either 96% (GSTM1) or 91% (GSTT1) of all DNA samples in a single round of PCR amplification. Genotyping accuracy, as ascertained by familial inheritance, was > 99.5%, and independent genotype assignments with replicate real-time PCR runs were 100% concordant. CONCLUSIONS: The genotyping assay for GSTM1 and GSTT1 gene deletion is suitable for large genetic epidemiologic studies and is a highly effective analysis system that is readily adaptable to analysis of other CNVs. (C) 2009 American Association for Clinical Chemistry

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