Data Normalization Strategies for MicroRNA Quantification

Clin Chem. 2015 Nov;61(11):1333-42. doi: 10.1373/clinchem.2015.239459. Epub 2015 Sep 25.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Gene Expression Profiling / methods*
  • Gene Expression Profiling / standards
  • Humans
  • MicroRNAs / genetics*
  • Oligonucleotide Array Sequence Analysis / methods
  • Oligonucleotide Array Sequence Analysis / standards
  • Real-Time Polymerase Chain Reaction / methods*
  • Real-Time Polymerase Chain Reaction / standards
  • Reference Standards
  • Reproducibility of Results
  • Workflow

Substances

  • MicroRNAs