Data Normalization Strategies for MicroRNA Quantification

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 con...

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Published in:	Clinical chemistry (Baltimore, Md.) Vol. 61; no. 11; pp. 1333 - 1342
Main Authors:	Schwarzenbach, Heidi, da Silva, Andreia Machado, Calin, George, Pantel, Klaus
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 01.11.2015
Subjects:	Animals Biomarkers Body fluids Cancer Chromatography Gene expression Gene Expression Profiling - methods Gene Expression Profiling - standards Grants Humans Laboratories Melanoma Methods MicroRNAs - genetics Oligonucleotide Array Sequence Analysis - methods Oligonucleotide Array Sequence Analysis - standards Physiology Pilot projects Proteins Real-Time Polymerase Chain Reaction - methods Real-Time Polymerase Chain Reaction - standards Reference Standards Reproducibility of Results Studies Workflow
ISSN:	0009-9147, 1530-8561
Online Access:	Get full text
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Abstract	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. 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. 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.
AbstractList	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. 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. 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. BACKGROUNDDifferent 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.CONTENTIn 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.SUMMARYA 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. 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. 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. 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.
Author	Schwarzenbach, Heidi Pantel, Klaus da Silva, Andreia Machado Calin, George
Author_xml	– sequence: 1 givenname: Heidi surname: Schwarzenbach fullname: Schwarzenbach, Heidi organization: Department of Tumour Biology, Center of Experimental Medicine, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany – sequence: 2 givenname: Andreia Machado surname: da Silva fullname: da Silva, Andreia Machado organization: Department of Experimental Therapeutics and The Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, TX, Instituto de Investigação em Saúde, Universidade do Porto, Porto, Portugal, INEB, Institute of Biomedical Engineering, Universidade do Porto, Porto, Portugal – sequence: 3 givenname: George surname: Calin fullname: Calin, George organization: Department of Experimental Therapeutics and The Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, TX – sequence: 4 givenname: Klaus surname: Pantel fullname: Pantel, Klaus organization: Department of Tumour Biology, Center of Experimental Medicine, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/26408530$$D View this record in MEDLINE/PubMed
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Snippet	Different technologies, such as quantitative real-time PCR or microarrays, have been developed to measure microRNA (miRNA) expression levels. Quantification of... BACKGROUNDDifferent technologies, such as quantitative real-time PCR or microarrays, have been developed to measure microRNA (miRNA) expression levels....
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SubjectTerms	Animals Biomarkers Body fluids Cancer Chromatography Gene expression Gene Expression Profiling - methods Gene Expression Profiling - standards Grants Humans Laboratories Melanoma Methods MicroRNAs - genetics Oligonucleotide Array Sequence Analysis - methods Oligonucleotide Array Sequence Analysis - standards Physiology Pilot projects Proteins Real-Time Polymerase Chain Reaction - methods Real-Time Polymerase Chain Reaction - standards Reference Standards Reproducibility of Results Studies Workflow
Title	Data Normalization Strategies for MicroRNA Quantification
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