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Real-time quantification of microRNAs by stem–loop RT–PCR

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      Abstract

      A novel microRNA (miRNA) quantification method has been developed using stem–loop RT followed by TaqMan PCR analysis. Stem–loop RT primers are better than conventional ones in terms of RT efficiency and specificity. TaqMan miRNA assays are specific for mature miRNAs and discriminate among related miRNAs that differ by as little as one nucleotide. Furthermore, they are not affected by genomic DNA contamination. Precise quantification is achieved routinely with as little as 25 pg of total RNA for most miRNAs. In fact, the high sensitivity, specificity and precision of this method allows for direct analysis of a single cell without nucleic acid purification. Like standard TaqMan gene expression assays, TaqMan miRNA assays exhibit a dynamic range of seven orders of magnitude. Quantification of five miRNAs in seven mouse tissues showed variation from less than 10 to more than 30 000 copies per cell. This method enables fast, accurate and sensitive miRNA expression profiling and can identify and monitor potential biomarkers specific to tissues or diseases. Stem–loop RT–PCR can be used for the quantification of other small RNA molecules such as short interfering RNAs (siRNAs). Furthermore, the concept of stem–loop RT primer design could be applied in small RNA cloning and multiplex assays for better specificity and efficiency.

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      Most cited references 39

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      Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

       K Livak,  T Schmittgen (2001)
      The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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        MicroRNAs: genomics, biogenesis, mechanism, and function.

         David Bartel (2004)
        MicroRNAs (miRNAs) are endogenous approximately 22 nt RNAs that can play important regulatory roles in animals and plants by targeting mRNAs for cleavage or translational repression. Although they escaped notice until relatively recently, miRNAs comprise one of the more abundant classes of gene regulatory molecules in multicellular organisms and likely influence the output of many protein-coding genes.
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          The functions of animal microRNAs.

           Victor Ambros (2004)
          MicroRNAs (miRNAs) are small RNAs that regulate the expression of complementary messenger RNAs. Hundreds of miRNA genes have been found in diverse animals, and many of these are phylogenetically conserved. With miRNA roles identified in developmental timing, cell death, cell proliferation, haematopoiesis and patterning of the nervous system, evidence is mounting that animal miRNAs are more numerous, and their regulatory impact more pervasive, than was previously suspected.
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            Author and article information

            Affiliations
            simpleApplied Biosystems 850 Lincoln Centre Drive, Foster City, CA 94404, USA
            Author notes
            *To whom correspondence should be addressed. Tel: +1 650 638 5245; Fax: +1 650 638 6343; Email: chencx@ 123456appliedbiosystems.com
            Journal
            Nucleic Acids Res
            Nucleic Acids Research
            Nucleic Acids Research
            Oxford University Press
            0305-1048
            1362-4962
            2005
            2005
            27 November 2005
            : 33
            : 20
            : e179
            1292995
            10.1093/nar/gni178
            16314309
            © The Author 2005. Published by Oxford University Press. All rights reserved

            The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@ 123456oxfordjournals.org

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            Methods Online

            Genetics

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