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Design and Optimization of Reverse-Transcription Quantitative PCR Experiments.

Journal article
Authors A Tichopad
R Kitchen
I Riedmaier
C Becker
Anders Ståhlberg
Mikael Kubista
Published in Clinical chemistry
Volume 55
Issue 10
Pages 1816-1823
ISSN 1530-8561
Publication year 2009
Published at Institute of Neuroscience and Physiology, Department of Clinical Neuroscience and Rehabilitation
Pages 1816-1823
Language en
Links dx.doi.org/10.1373/clinchem.2009.12...
Subject categories Medical and Health Sciences

Abstract

BACKGROUND: Quantitative PCR (qPCR) is a valuable technique for accurately and reliably profiling and quantifying gene expression. Typically, samples obtained from the organism of study have to be processed via several preparative steps before qPCR. METHOD: We estimated the errors of sample withdrawal and extraction, reverse transcription (RT), and qPCR that are introduced into measurements of mRNA concentrations. We performed hierarchically arranged experiments with 3 animals, 3 samples, 3 RT reactions, and 3 qPCRs and quantified the expression of several genes in solid tissue, blood, cell culture, and single cells. RESULTS: A nested ANOVA design was used to model the experiments, and relative and absolute errors were calculated with this model for each processing level in the hierarchical design. We found that intersubject differences became easily confounded by sample heterogeneity for single cells and solid tissue. In cell cultures and blood, the noise from the RT and qPCR steps contributed substantially to the overall error because the sampling noise was less pronounced. CONCLUSIONS: We recommend the use of sample replicates preferentially to any other replicates when working with solid tissue, cell cultures, and single cells, and we recommend the use of RT replicates when working with blood. We show how an optimal sampling plan can be calculated for a limited budget.

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