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miRNA Expression Profiling: From Reference Genes to Global Mean Normalization

  • Barbara D’haene
  • Pieter Mestdagh
  • Jan Hellemans
  • Jo Vandesompele
Part of the Methods in Molecular Biology book series (MIMB, volume 822)

Abstract

MicroRNAs (miRNAs) are an important class of gene regulators, acting on several aspects of cellular function such as differentiation, cell cycle control, and stemness. These master regulators constitute an invaluable source of biomarkers, and several miRNA signatures correlating with patient diagnosis, prognosis, and response to treatment have been identified. Within this exciting field of research, whole-genome RT-qPCR-based miRNA profiling in combination with a global mean normalization strategy has proven to be the most sensitive and accurate approach for high-throughput miRNA profiling (Mestdagh et al., Genome Biol 10:R64, 2009). In this chapter, we summarize the power of the previously described global mean normalization method in comparison to the multiple reference gene normalization method using the most stably expressed small RNA controls. In addition, we compare the original global mean method to a modified global mean normalization strategy based on the attribution of equal weight to each individual miRNA during normalization. This modified algorithm is implemented in Biogazelle’s qbasePLUS software and is presented here for the first time.

Key words

miRNA profiling miRNA expression RT-qPCR Global mean normalization 

Notes

Acknowledgment

This work was supported by the European Union Framework 7 project SysKid; Grant Number: 241544 (B. D’haene).

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Barbara D’haene
    • 1
  • Pieter Mestdagh
    • 2
  • Jan Hellemans
    • 1
  • Jo Vandesompele
    • 2
  1. 1.BiogazelleZwijnaardeBelgium
  2. 2.Center for Medical Genetics, Ghent UniversityGhentBelgium

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