Literature DB >> 11846613

Use of real-time quantitative PCR to validate the results of cDNA array and differential display PCR technologies.

M S Rajeevan1, D G Ranamukhaarachchi, S D Vernon, E R Unger.   

Abstract

Real-time reverse transcription polymerase chain reaction (RT-PCR) methods that monitor product accumulation were adapted for the validation of differentially expressed genes. We describe a real-time quantitative PCR assay that uses SYBR Green I dye-based detection and product melting curve analysis to validate differentially expressed genes identified by gene expression profiling technologies. Since SYBR Green I dye is a nonspecific intercalating dye, the reaction is made specific by using "hot-start" PCR and empirically determined annealing and signal acquisition temperatures for each gene-specific primer. Relative expression levels were quantified by constructing a standard curve using cDNA dilutions of a highly expressed gene. Using this approach, real-time PCR validated 17 of 21 (71%) genes identified by DNA arrays, and all but 1 of 13 (91%) genes identified by differential display PCR (DD-PCR). Validation of differentially expressed genes detected by array analysis was related to hybridization intensity. Real-time RT-PCR results suggest that genes identified by DNA arrays with a two to fourfold difference in expression cannot be accepted as true or false without validation. Validation of differentially expressed genes detected by DD-PCR was not affected by band intensities. Regardless of the gene expression profiling technology (microarrays, DD-PCR, serial analysis of gene expression and subtraction hybridization), once the sequence of gene of interest is known, the real-time RT-PCR approach is well suited for validation of differential expression since it is quantitative and rapid and requires 1000-fold less RNA than conventional assays. Copyright 2001 Elsevier Science (USA).

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Year:  2001        PMID: 11846613     DOI: 10.1006/meth.2001.1266

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


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