Dataset Information

Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme.

ABSTRACT: BACKGROUND: The development of microarrays permits us to monitor transcriptomes on a genome-wide scale. To validate microarray measurements, quantitative-real time-reverse transcription PCR (Q-RT-PCR) is one of the most robust and commonly used approaches. The new challenge in gene quantification analysis is how to explicitly incorporate statistical estimation in such studies. In the realm of statistical analysis, the various available methods of the probe level normalization for microarray analysis may result in distinctly different target selections and variation in the scores for the correlation between microarray and Q-RT-PCR. Moreover, it remains a major challenge to identify a proper internal control for Q-RT-PCR when confirming microarray measurements. RESULTS: Sixty-six Affymetrix microarray slides using lung adenocarcinoma tissue RNAs were analyzed by a statistical re-sampling method in order to detect genes with minimal variation in gene expression. By this approach, we identified DDX5 as a novel internal control for Q-RT-PCR. Twenty-three genes, which were differentially expressed between adjacent normal and tumor samples, were selected and analyzed using 24 paired lung adenocarcinoma samples by Q-RT-PCR using two internal controls, DDX5 and GAPDH. The percentage correlation between Q-RT-PCR and microarray were 70% and 48% by using DDX5 and GAPDH as internal controls, respectively. CONCLUSION: Together, these quantification strategies for Q-RT-PCR data processing procedure, which focused on minimal variation, ought to significantly facilitate internal control evaluation and selection for Q-RT-PCR when corroborating microarray data.

SUBMITTER: Su LJ

PROVIDER: S-EPMC1894975 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

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Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme.

Su Li-Jen LJ Chang Ching-Wei CW Wu Yu-Chung YC Chen Kuang-Chi KC Lin Chien-Ju CJ Liang Shu-Ching SC Lin Chi-Hung CH Whang-Peng Jacqueline J Hsu Shih-Lan SL Chen Chen-Hsin CH Huang Chi-Ying F CY

BMC genomics 20070601

<h4>Background</h4>The development of microarrays permits us to monitor transcriptomes on a genome-wide scale. To validate microarray measurements, quantitative-real time-reverse transcription PCR (Q-RT-PCR) is one of the most robust and commonly used approaches. The new challenge in gene quantification analysis is how to explicitly incorporate statistical estimation in such studies. In the realm of statistical analysis, the various available methods of the probe level normalization for microarr ...[more]

PMID: 17540040

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Project description:MicroRNAs (miRNAs) have critical functions in various biological processes. MiRNA profiling is an important tool for the identification of differentially expressed miRNAs in normal cellular and disease processes. A technical challenge remains for high-throughput miRNA expression analysis as the number of miRNAs continues to increase with in silico prediction and experimental verification. Our study critically evaluated the performance of a novel miRNA expression profiling approach, quantitative RT-PCR array (qPCR-array), compared to miRNA detection with oligonucleotide microchip (microarray).High reproducibility with qPCR-array was demonstrated by comparing replicate results from the same RNA sample. Pre-amplification of the miRNA cDNA improved sensitivity of the qPCR-array and increased the number of detectable miRNAs. Furthermore, the relative expression levels of miRNAs were maintained after pre-amplification. When the performance of qPCR-array and microarrays were compared using different aliquots of the same RNA, a low correlation between the two methods (r=-0.443) indicated considerable variability between the two assay platforms. Higher variation between replicates was observed in miRNAs with low expression in both assays. Finally, a higher false positive rate of differential miRNA expression was observed using the microarray compared to the qPCR-array.Our studies demonstrated high reproducibility of TaqMan qPCR-array. Comparison between different reverse transcription reactions and qPCR-arrays performed on different days indicated that reverse transcription reactions did not introduce significant variation in the results. The use of cDNA pre-amplification increased the sensitivity of miRNA detection. Although there was variability associated with pre-amplification in low abundance miRNAs, the latter did not involve any systemic bias in the estimation of miRNA expression. Comparison between microarray and qPCR-array indicated superior sensitivity and specificity of qPCR-array.

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Dataset Information

Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme.

Publications

Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme.

Similar Datasets

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