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High-Throughput Profiling of Mature MicroRNA by Real-Time PCR

  • Jinmai Jiang
  • Eun Joo Lee
  • Melissa G. Piper
  • Clay B. Marsh
  • Thomas D. SchmittgenEmail author
Protocol
Part of the Neuromethods book series (NM, volume 58)

Abstract

Real-time quantitative PCR has become a staple technique of most molecular biology laboratories. Configuration of quantitative PCR instruments into 384-well plates has allowed the technology to function as a low-density gene expression array. In this chapter, we present protocols and data that apply quantitative PCR to profile hundreds of genes simultaneously. TaqMan probe and primer sets were pipetted individually into 384-well reaction plates using liquid-handling robots. This substantially increased throughput and reduced error. This protocol was used to expression profile mature miRNAs in total RNA isolated from circulating microvesicles and in peripheral blood mononuclear cells (PBMCs) of healthy donors. Using a robotics system to load the 384-well plates into the quantitative PCR instrument, 420 miRNAs were profiled in RNA isolated from microvesicles and PBMCs of 50 patients in about 2 weeks. Using equipment located in many gene expression laboratories or core facilities, low-density gene expression profiling may be easily achieved with minimal error.

Key words

MicroRNA Noncoding RNA Gene expression 

Notes

Acknowledgment

This work is supported by Grant CA114304 (T.D.S.).

References

  1. 1.
    Bartel DP. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004;116:281–97.PubMedCrossRefGoogle Scholar
  2. 2.
    Barbarotto E, Schmittgen TD, Calin GA. MicroRNAs and cancer: profile, profile, profile. Int J Cancer 2008;122:969–77.PubMedCrossRefGoogle Scholar
  3. 3.
    Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer 2006;6:857–66.PubMedCrossRefGoogle Scholar
  4. 4.
    Liu CG, Calin GA, Meloon B, et al. An oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues. Proc Natl Acad Sci U S A 2004;101:9740–4.PubMedCrossRefGoogle Scholar
  5. 5.
    Wang H, Ach RA, Curry B. Direct and sensitive miRNA profiling from low-input total RNA. RNA 2007;13:151–9.PubMedCrossRefGoogle Scholar
  6. 6.
    Schmittgen TD, Livak KJ. Analyzing real-time PCR data by the comparative C(T) method. Nat Protoc 2008;3:1101–8.PubMedCrossRefGoogle Scholar
  7. 7.
    Griffiths-Jones S. The microRNA Registry. Nucleic Acids Res 2004;32:D109–11.PubMedCrossRefGoogle Scholar
  8. 8.
    Mestdagh P, Feys T, Bernard N, et al. High-throughput stem-loop RT-qPCR miRNA expression profiling using minute amounts of input RNA. Nucleic Acids Res 2008;36:e143.PubMedCrossRefGoogle Scholar
  9. 9.
    Ratajczak J, Wysoczynski M, Hayek F, Janowska-Wieczorek A, Ratajczak MZ. Membrane-derived microvesicles: important and underappreciated mediators of cell-to-cell communication. Leukemia 2006;20:1487–95.PubMedCrossRefGoogle Scholar
  10. 10.
    Valadi H, Ekstrom K, Bossios A, Sjostrand M, Lee JJ, Lotvall JO. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol 2007;9:654–9.PubMedCrossRefGoogle Scholar
  11. 11.
    Hunter MP, Ismail N, Zhang X, et al. Detection of microRNA expression in human peripheral blood microvesicles. PLoS ONE 2008;3:e3694.PubMedCrossRefGoogle Scholar
  12. 12.
    Vandesompele J, De Preter K, Pattyn F, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002;3:RESEARCH0034.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Jinmai Jiang
  • Eun Joo Lee
  • Melissa G. Piper
  • Clay B. Marsh
  • Thomas D. Schmittgen
    • 1
    Email author
  1. 1.Department of Pharmacy and the Comprehensive Cancer CenterCollege of Medicine, Ohio State UniversityColumbusUSA

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