Normalization of circulating microRNA expression data obtained by quantitative real-time RT-PCR

Francesco Marabita*, Paola De Candia, Anna Torri, Jesper Tegner, Sergio Abrignani, Riccardo L. Rossi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

140 Scopus citations

Abstract

The high-throughput analysis of microRNAs (miRNAs) circulating within the blood of healthy and diseased individuals is an active area of biomarker research. Whereas quantitative real-time reverse transcription polymerase chain reaction (qPCR)-based methods are widely used, it is yet unresolved how the data should be normalized. Here, we show that a combination of different algorithms results in the identification of candidate reference miRNAs that can be exploited as normalizers, in both discovery and validation phases. Using the methodology considered here, we identify normalizers that are able to reduce nonbiological variation in the data and we present several case studies, to illustrate the relevance in the context of physiological or pathological scenarios. In conclusion, the discovery of stable reference miRNAs from high-throughput studies allows appropriate normalization of focused qPCR assays.

Original languageEnglish (US)
Pages (from-to)204-212
Number of pages9
JournalBriefings in bioinformatics
Volume17
Issue number2
DOIs
StatePublished - Mar 1 2016

Keywords

  • Circulating miRNA
  • GeNorm
  • Normalization
  • Normfinder
  • QPCR
  • Reference genes

ASJC Scopus subject areas

  • Information Systems
  • Molecular Biology

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