Identification of a set of endogenous reference genes for miRNA expression studies in Parkinson's disease blood samples

BMC Res Notes. 2014 Oct 10:7:715. doi: 10.1186/1756-0500-7-715.

Abstract

Background: Research on microRNAs (miRNAs) is becoming an increasingly attractive field, as these small RNA molecules are involved in several physiological functions and diseases. To date, only few studies have assessed the expression of blood miRNAs related to Parkinson's disease (PD) using microarray and quantitative real-time PCR (qRT-PCR). Measuring miRNA expression involves normalization of qRT-PCR data using endogenous reference genes for calibration, but their choice remains a delicate problem with serious impact on the resulting expression levels. The aim of the present study was to evaluate the suitability of a set of commonly used small RNAs as normalizers and to identify which of these miRNAs might be considered reliable reference genes in qRT-PCR expression analyses on PD blood samples.

Results: Commonly used reference genes snoRNA RNU24, snRNA RNU6B, snoRNA Z30 and miR-103a-3p were selected from the literature. We then analyzed the effect of using these genes as reference, alone or in any possible combination, on the measured expression levels of the target genes miR-30b-5p and miR-29a-3p, which have been previously reported to be deregulated in PD blood samples.

Conclusions: We identified RNU24 and Z30 as a reliable and stable pair of reference genes in PD blood samples.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Calibration
  • Case-Control Studies
  • Databases, Genetic
  • Gene Expression Profiling / methods
  • Gene Expression Profiling / standards*
  • Genetic Markers
  • Humans
  • MicroRNAs / blood*
  • Oligonucleotide Array Sequence Analysis / standards
  • Parkinson Disease / blood*
  • Parkinson Disease / genetics*
  • Predictive Value of Tests
  • Real-Time Polymerase Chain Reaction / standards
  • Reference Standards
  • Reproducibility of Results

Substances

  • Genetic Markers
  • MicroRNAs