Data Normalization Strategies for MicroRNA Quantification. (6th January 2020)

• Record Type: Journal Article
• Authors: Schwarzenbach, Heidi; da Silva, Andreia Machado; Calin, George; Pantel, Klaus
• Is Part Of: Clinical chemistry. Volume 61:Number 11(2015)
• Page Start: 1333
• Page End: 1342
• Publication Date: 2020-01-06
• Subjects: Clinical chemistry -- Periodicals; Pharmaceutical chemistry -- Periodicals; Biochemistry -- Periodicals; Biochimie -- Périodiques; Diagnostics biologiques -- Périodiques; Biochemistry; Clinical chemistry; Pharmaceutical chemistry; Biochemistry; Laboratory Techniques and Procedures; Klinische chemie; Periodicals; 616.075605
• DOI: 10.1373/clinchem.2015.239459
• Languages: English
• ISSNs: 0009-9147

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.