Quantitative Analysis of miRNA Expression in Epithelial Cells and Tissues

  • Markus Bitzer
  • Wenjun Ju
  • Xiaohong Jing
  • Jiri ZavadilEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 820)


Reliable detection of the microRNA (miRNA) precursor and mature form expression levels is a fundamental starting block for more focused studies of the biogenesis and functional roles of these important post-transcriptional modulators of gene expression. Building on our expertise with miRNA expression programs downstream of TGF-β/Smad signaling in homeostasis as well as in pathological conditions associated with epithelial tissues, we present a series of detailed and broadly applicable protocols for expression profiling of the mature miRNA forms using quantitative real-time PCR TaqMan, both single assays or low-density arrays. We next highlight key steps necessary for the detection of primary precursors of miRNAs (­pri-miRNAs) to address the initial steps of miRNA biogenesis, and we finally review some most widely used computational algorithms for miRNA target prediction used to complement experimental identification of the target mRNAs and proteins.

Key words

microRNA miRNA miRNA expression Pri-miRNA expression Quantitative real-time PCR TaqMan Array MicroRNA Card TaqMan MicroRNA Assay Primer3 SYBR Green PCR miRNA target prediction TGF-β Epithelial cell Epithelial tissue 



Formalin-fixed, paraffin-embedded


Laser capture microdissection




Primary precursor of miRNA


Quantitative real-time polymerase chain reaction


RNA interference


Reverse transcription/transcriptase


TaqMan low-density array(s)


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Markus Bitzer
    • 1
  • Wenjun Ju
    • 2
  • Xiaohong Jing
    • 3
  • Jiri Zavadil
    • 4
    Email author
  1. 1.Internal Medicine, Nephrology, Michigan Diabetes Research and Training CenterUniversity of MichiganAnn ArborUSA
  2. 2.Internal Medicine, Nephrology, Center for Computational Medicine and BioinformaticsUniversity of MichiganAnn ArborUSA
  3. 3.Computational Biology Center, Memorial Sloan-Kettering Cancer CenterNew YorkUSA
  4. 4.Department of Pathology, Center for Health Informatics and BioinformaticsNew York University Langone Medical CenterNew YorkUSA

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