Data Normalization Strategies for MicroRNA Quantification

Author:

Schwarzenbach Heidi1,da Silva Andreia Machado234,Calin George2,Pantel Klaus1

Affiliation:

1. Department of Tumour Biology, Center of Experimental Medicine, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

2. Department of Experimental Therapeutics and The Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, TX

3. Instituto de Investigação em Saúde, Universidade do Porto, Porto, Portugal

4. INEB, Institute of Biomedical Engineering, Universidade do Porto, Porto, Portugal

Abstract

Abstract BACKGROUND Different technologies, such as quantitative real-time PCR or microarrays, have been developed to measure microRNA (miRNA) expression levels. Quantification of miRNA transcripts implicates data normalization using endogenous and exogenous reference genes for data correction. However, there is no consensus about an optimal normalization strategy. The choice of a reference gene remains problematic and can have a serious impact on the actual available transcript levels and, consequently, on the biological interpretation of data. CONTENT In this review article we discuss the reliability of the use of small RNAs, commonly reported in the literature as miRNA expression normalizers, and compare different strategies used for data normalization. SUMMARY A workflow strategy is proposed for normalization of miRNA expression data in an attempt to provide a basis for the establishment of a global standard procedure that will allow comparison across studies.

Funder

FCT–Fundação para a Ciência e a Tecnologia

NIH/NCI

University of Texas MD Anderson Cancer Center

Melanoma Foundation

Publisher

Oxford University Press (OUP)

Subject

Biochemistry (medical),Clinical Biochemistry

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