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10:58
Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays
Published on: December 4, 2010
Selection of control genes for quantitative RT-PCR based on microarray data.
Natalia Shulzhenko1, Anatoly Yambartsev, Amador Goncalves-Primo
1Immunogenetics Division, Pediatrics Department, Universidade Federal de Sao Paulo--UNIFESP, Sao Paulo, SP, Brazil.
Biochemical and Biophysical Research Communications
|September 27, 2005
Summary
Selecting appropriate internal reference genes is crucial for accurate gene expression analysis using reverse transcription quantitative polymerase chain reaction (RT-PCR). This study presents a reliable method using microarray data to identify stable control genes for RT-PCR normalization.
Area of Science:
- Molecular Biology
- Genomics
- Biotechnology
Background:
- Accurate quantification of target gene expression via RT-PCR requires reliable internal reference genes.
- Microarray data offers a rich source for identifying such control genes.
Purpose of the Study:
- To develop and validate a strategy for selecting control genes from microarray data for RT-PCR.
- To assess the reliability of this selection strategy in endomyocardial biopsies.
Main Methods:
- Utilized order statistics and binomial distribution to assess the probability of identifying low-varying genes.
- Divided microarray data into subsets to identify consistently low-standard deviation genes.
- Normalized RT-PCR data using selected control genes.
Main Results:
- Identified 14 common low-varying genes from two microarray data subsets.
- Achieved high correlation (r = 0.9, p < 0.001) between microarray and RT-PCR expression data after normalization.
- Validated findings in an independent RT-PCR dataset.
Conclusions:
- A simple and effective strategy for selecting and validating control genes from microarray data was demonstrated.
- This method is applicable across various experimental designs and tissue types for RT-PCR analysis.
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