Normalization methods for miRNA quantification

MicroRNAs or miRNAs, are small ~22 nucleotide noncoding RNAs that regulate gene expression.

miRNAs are considered to post-transcriptionally regulate the cleavage of target mRNAs or just repress their translation. The regulatory roles of miRNAs have been identified not only in developmental timing, cell differentiation, proliferation and apoptosis, but also in tumorigenesis and host-pathogen interactions. 1,2,3,4,5,6

microRNAs can be quantified by real-time PCR using TaqMan assays.

Applied Biosystems™ TaqMan™ MicroRNA Assays are innovative tools for miRNA research—from isolation through discovery, profiling, quantitation, validation and functional analysis. The new Applied Biosystems™ TaqMan Advanced miRNA Assays use ligation-based universal reverse transcription for a streamlined and highly sensitive workflow. The standard TaqMan MicroRNA Assays, which employ target-specific stem-loop reverse transcription primers for 3’ extended templates, continue to cover a range of species using standard TaqMan Assay–based real-time PCR.

In a microRNA expression experiment, variation in the amount of starting material, sample collection, RNA preparation and quality, and reverse transcription efficiency can contribute to quantification errors. For these reasons, it is important to use proper normalization controls when quantifying miRNAs.

There are 3 different normalization methods which allow you to control certain aspects of your experimental process when analyzing miRNAs by qPCR:

1. Endogenous controls

Normalization using endogenous control genes is currently the most accurate method to correct for potential differences in RNA input or RT efficiency biases

2. Exogenous controls

Exogenous controls or “spike-ins” are typically used to monitor extraction efficiency or sample input amount for difficult samples such as plasma/serum or other biofluids

3. Mean expression value normalization, or “global mean normalization”

Large scale miRNA expression profiling studies may utilize global mean normalization, which uses the calculated mean of all miRNAs in a given sample as the normalizer.
Historically, non-coding RNAs such as snRNAs and snoRNAs were used as endogenous normalizers for miRNA quantification. But, more recently, key opinion leaders in the miRNA community have moved away from the use of snoRNAs/snRNAs as endogenous controls for the following reasons:

  • They are bigger than miRNAs
  • They do not ‘mirror’ the physiochemical properties of miRNA
  • They have different cellular processing and different functions than miRNAs
  • The expression levels of snoRNA and snRNA have been recently found to be associated with cancer and prognosis.

The miRNA community has also suggested that the ideal endogenous control has gene expression that is relatively constant and moderately abundant across a variety of tissues and cell types and treatment. miRNAs that are uniformly expressed can be used as an endogenous control. 

There are several miRNAs that have been shown in the literature and in experimental studies to be expressed at relatively constant levels across many different tissues types:


There are several miRNAs that have been shown in the literature and in experimental studies to be expressed at relatively constant levels across many different tissues types (show table).

It is recommended to validate 2 or more of these miRNAs as endogenous controls for the target cell, tissue, or treatment that you are using because no single control can act as a universal endogenous control for all experimental conditions. In addition, synthetic miRNA molecules can be used as spike-in controls and are extremely useful as exogenous controls in difficult samples such as serum/ plasma.

Spike- ins, or exogenous controls are synthetic RNA oligonucleotides that are added to the sample. A spike-in control should be a target sequence that is not present in your sample. For example, ath-miR-159a (need pronunciation guidance) is not present in humans so it is a good exogenous control for human.

For more information please email: qPCR@rhenium.co.il


  1. J. Liu, Control of protein synthesis and mRNA degradation by microRNAs Curr. Opin. Cell Biol., 20 (2008), pp. 214-221
  2. V. Scaria, et al., Host-virus interaction: a new role for microRNAs Retrovirology, 3 (2006), p. 68
  3. S. Tsuchiya, et al., MicroRNA: biogenetic and functional mechanisms and involvements in cell differentiation and cancer, J. Pharmacol. Sci., 101 (2006), pp. 267-270
  4. W.C. Cho, OncomiRs: the discovery and progress of microRNAs in cancers, Mol. Cancer, 6 (2007), p. 6
  5. A. Drakaki, D. Iliopoulos, MicroRNA gene networks in oncogenesis, Curr. Genomics, 10 (2009), pp. 35-41
  6. G. Tzur, et al., Comprehensive gene and microRNA expression profiling reveals a role for microRNAs in human liver development, PLoS One, 4 (2009), p. e7511

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