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Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR qPCR Arrays
Published on: December 3, 2010
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MicroRNA profiling in plasma samples using qPCR arrays: Recommendations for correct analysis and interpretation
Andreas B Gevaert1,2, Isabel Witvrouwen1,2, Christiaan J Vrints1,2
1Laboratory of Cellular and Molecular Cardiology, Research Group Cardiovascular Diseases, Department of Translational Pathophysiological Research, University of Antwerp, Antwerp, Belgium.
Plos One
|February 24, 2018
Summary
Optimizing TaqMan Low Density Arrays (TLDA) for plasma microRNA (miRNA) profiling requires specific preamplification and normalization. The geNorm algorithm is recommended for accurate miRNA data analysis, avoiding U6 normalization.
Area of Science:
- Molecular Biology
- Genomics
Background:
- MicroRNAs (miRNAs) are crucial gene regulators.
- Pre-analytical and analytical challenges exist for plasma miRNA screening using TaqMan Low Density Arrays (TLDA).
Purpose of the Study:
- To optimize the TLDA protocol for plasma miRNA analysis.
- To identify optimal RNA isolation, preamplification, and data normalization strategies.
Main Methods:
- Evaluated three RNA isolation protocols and preamplification dilutions.
- Defined informative miRNAs based on quantification cycle values and technical variability.
- Compared normalization strategies including exogenous, endogenous, and mathematical algorithms (geNorm, NormFinder).
Main Results:
- A preamplification step without dilution increased amplification by 49%.
- 218 miRNAs (59%) were identified as informative.
- The geNorm algorithm significantly reduced data dispersion compared to other methods; U6 normalization performed poorly.
Conclusions:
- Recommend implementing preamplification without dilution for TLDA plasma miRNA profiling.
- Advise a stepwise approach to exclude non-informative miRNAs.
- Recommend geNorm for normalization and advise against using U6.
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