Validation of Short Interfering RNA Knockdowns by Quantitative Real-Time PCR

  • Sukru Tuzmen
  • Jeff Kiefer
  • Spyro Mousses
Part of the Methods in Molecular Biology book series (MIMB, volume 353)

Abstract

RNA interference (RNAi) is a natural mechanism, that is triggered by the introduction of double-stranded RNA into a cell. The long double-stranded RNA is then processed into short interfering RNA (siRNA) that mediates sequence-specific degradation of homologous transcripts. This phenomenon can be exploited to experimentally trigger RNAi and downregulate gene expression by transfecting mammalian cells with synthetic siRNA. Thus, siRNAs can be designed to specifically silence the expression of genes bearing a particular target sequence. In this chapter, we present methods and procedures for alidating the effects of siRNA-based gene silencing on target gene expression. To illustrate our approach, we use examples from our analysis of a Cancer Gene Library of 278 siRNAs targeting 139 classic oncogenes and tumor suppressor genes (Qiagen Inc., Germantown, MD). Specifically, this library was used for high-throughput RNAi phenotype analysis followed by gene expression analysis to validate gene silencing for siRNA that produced a phenotype. Methods and protocols are presented that illustrate how sequence-specific gene silencing of effective siRNAs are analyzed and validated by quantitative real-time PCR assays to measure the extent of target gene silencing, as well as effects on various gene expression end points.

Key Words

Dicer gene expression gene knockdown gene quantification gene silencing housekeeping genes nonradioactive analysis quantitative real-time PCR reference genes relative quantification RISC RNA RNAi siRNA transcription 

References

  1. 1.
    Hannon, G. J. (2002) RNA interference. Nature 418, 244–251.PubMedCrossRefGoogle Scholar
  2. 2.
    Elbashir, S. M., Harborth, J., Lendeckel, W., Yalcin, A., Weber, K., and Tuschl, T. (2001) Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature 411, 494–498.PubMedCrossRefGoogle Scholar
  3. 3.
    Fire, A., Xu, S., Montgomery, M. K., Kostas, S. A., Driver, S. E., and Mello, C. C. (1998) Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 391, 806–811.PubMedCrossRefGoogle Scholar
  4. 4.
    Hemann, M. T., Fridman, J. S., Zilfou, J. T., et al. (2003) An epi-allelic series of p53 hypomorphs created by stable RNAi produces distinct tumor phenotypes in vivo. Nat. Genet. 33, 396–400.PubMedCrossRefGoogle Scholar
  5. 5.
    Carmell, M. A., Zhang, L., Conklin, D. S., Hannon, G. J., and Rosenquist, T. A. (2003) Germline transmission of RNAi in mice. Nat. Struct. Biol. 10, 91–92.PubMedCrossRefGoogle Scholar
  6. 6.
    Tiscornia, G., Singer, O., Ikawa, M., and Verma, I. M. (2003) A general method for gene knockdown in mice by using lentiviral vectors expressing small interfering RNA. Proc. Natl. Acad. Sci. USA 100, 1844–1848.PubMedCrossRefGoogle Scholar
  7. 7.
    Tuschl, T. (2001) RNA interference and small interfering RNAs. Chembiochem. 2, 239–245.PubMedCrossRefGoogle Scholar
  8. 8.
    Caplen, N. J. (2003) RNAi as a gene therapy approach. Expert. Opin. Biol. Ther. 3, 575–586.PubMedCrossRefGoogle Scholar
  9. 9.
    Wilda, M., Fuchs, U., Wossmann, W., and Borkhardt, A. (2002) Killing of leukemic cells with a BCR/ABL fusion gene by RNA interference (RNAi). Oncogene 21, 5716–5724.PubMedCrossRefGoogle Scholar
  10. 10.
    Brummelkamp, T. R., Bernards, R., and Agami, R. (2002) Stable suppression of tumorigenicity by virus-mediated RNA interference. Cancer Cell 2, 243–247.PubMedCrossRefGoogle Scholar
  11. 11.
    Scherr, M., Battmer, K., Winkler, T., Heidenreich, O., Ganser, A., and Eder, M. (2003) Specific inhibition of bcr-abl gene expression by small interfering RNA. Blood 101, 1566–1569.PubMedCrossRefGoogle Scholar
  12. 12.
    Kamath, R. S. and Ahringer, J. (2003) Genome-wide RNAi screening in Caenorhabditis elegans. Methods 30, 313–321.PubMedCrossRefGoogle Scholar
  13. 13.
    Pothof, J., van Haaften, G., Thijssen, K., et al. (2003) Identification of genes that protect the C. elegans genome against mutations by genome-wide RNAi. Genes Dev. 17, 443–448.PubMedCrossRefGoogle Scholar
  14. 14.
    Lum, L., Yao, S., Mozer, B., et al. (2003) Identification of Hedgehog pathway components by RNAi in Drosophila cultured cells. Science 299, 2039–2045.PubMedCrossRefGoogle Scholar
  15. 15.
    Hammond, S. M., Bernstein, E., Beach, D., and Hannon, G. J. (2000) An RNA-directed nuclease mediates post-transcriptional gene silencing in Drosophila cells. Nature 404, 293–296.PubMedCrossRefGoogle Scholar
  16. 16.
    Hammond, L. A., Davidson, K., Lawrence, R., et al. (2001) Exploring the mechanisms of action of FB642 at the cellular level. J. Cancer Res. Clin. Oncol. 127, 301–313.PubMedCrossRefGoogle Scholar
  17. 17.
    Bernstein, E., Caudy, A. A., Hammond, S. M., and Hannon, G. J. (2001) Role for a bidentate ribonuclease in the initiation step of RNA interference. Nature 409, 363–366.PubMedCrossRefGoogle Scholar
  18. 18.
    Azorsa, O.D., Mousses, S., Caplen, J. N. (2004) Gene silencing through RNA interfererence: Potential for therapeutics and functional genomics. Letters in Peptide Science 10, 361–372.CrossRefGoogle Scholar
  19. 19.
    Bustin, S. A. (2002) Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. J. Mol. Endocrinol. 29, 23–39.PubMedCrossRefGoogle Scholar
  20. 20.
    Schmittgen, T. D. (2001) Real-time quantitative PCR. Methods 25, 383–385.PubMedCrossRefGoogle Scholar
  21. 21.
    Livak, K. J. and Schmittgen, T. D. (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT Method. Methods 25, 402–408.PubMedCrossRefGoogle Scholar
  22. 22.
    Ginzinger, D. G. (2002) Gene quantification using real-time quantitative PCR: an emerging technology hits the mainstream. Exp. Hematol. 30, 503–512.PubMedCrossRefGoogle Scholar
  23. 23.
    Schmittgen, T. D., Zakrajsek, B. A., Mills, A. G., Gorn, V., Singer, M. J., and Reed, M. W. (2000) Quantitative reverse transcription-polymerase chain reaction to study mRNA decay: comparison of endpoint and real-time methods. Anal. Biochem. 285, 194–204.PubMedCrossRefGoogle Scholar
  24. 24.
    Schmittgen, T. D. and Zakrajsek, B. A. (2000) Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. J. Biochem. Biophys. Methods 46, 69–81.PubMedCrossRefGoogle Scholar
  25. 25.
    Chen, C. Y. and Shyu, A. B. (1994) Selective degradation of early-response-gene mRNAs: functional analyses of sequence features of the AU-rich elements. Mol. Cell. Biol. 14, 8471–8482.PubMedGoogle Scholar
  26. 26.
    Iyer, V. R., Eisen, M. B., Ross, D. T., et al. (1999) The transcriptional program in the response of human fibroblasts to serum. Science 283, 83–87.PubMedCrossRefGoogle Scholar
  27. 27.
    Giulietti, A., Overbergh, L., Valckx, D., Decallonne, B., Bouillon, R., and Mathieu, C. (2001) An overview of real-time quantitative PCR: applications to quantify cytokine gene expression. Methods 25, 386–401.PubMedCrossRefGoogle Scholar
  28. 28.
    Niesters, H. G. (2001) Quantitation of viral load using real-time amplification techniques. Methods 25, 419–429.PubMedCrossRefGoogle Scholar
  29. 29.
    Longo, M. C., Berninger, M. S., and Hartley, J. L. (1990) Use of uracil DNA glycosylase to control carry-over contamination in polymerase chain reactions. Gene 93, 125–128.PubMedCrossRefGoogle Scholar
  30. 30.
    Varshney, U., Hutcheon, T., and van de Sande, J. H. (1988) Sequence analysis, expression, and conservation of Escherichia coli uracil DNA glycosylase and its gene (ung). J. Biol. Chem. 263, 7776–7784.PubMedGoogle Scholar
  31. 31.
    Lindahl, T., Ljungquist, S., Siegert, W., Nyberg, B., and Sperens, B. (1977) DNA N-glycosidases: properties of uracil-DNA glycosidase from Escherichia coli. J. Biol. Chem. 252, 3286–3294.PubMedGoogle Scholar
  32. 32.
    Erlich, H. A., Gelfand, D., and Sninsky, J. J. (1991) Recent advances in the polymerase chain reaction. Science 252, 1643–1651.PubMedCrossRefGoogle Scholar
  33. 33.
    Wilfinger, W. W., Mackey, K., and Chomczynski, P. (1997) Effect of pH and ionic strength on the spectrophotometric assessment of nucleic acid purity. Biotechniques 22, 474–476, 478–481.PubMedGoogle Scholar
  34. 34.
    Heid, C. A., Stevens, J., Livak, K. J., and Williams, P. M. (1996) Real time quantitative PCR. Genome Res. 6, 986–994.PubMedCrossRefGoogle Scholar
  35. 35.
    Lakowicz, J. R. and Keating, S. (1983) Binding of an indole derivative to micelles as quantified by phase-sensitive detection of fluorescence. J. Biol. Chem. 258, 5519–5524.PubMedGoogle Scholar
  36. 36.
    Thellin, O., Zorzi, W., Lakaye, B., et al. (1999) Housekeeping genes as internal standards: use and limits. J. Biotechnol. 75, 291–295.PubMedCrossRefGoogle Scholar
  37. 37.
    Vandesompele, J., De Preter, K., Pattyn, F., et al. (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3, RESEARCH0034.1–0034.11.CrossRefGoogle Scholar
  38. 38.
    Mullis, K. B. (1990) Target amplification for DNA analysis by the polymerase chain reaction. Ann. Biol. Clin. (Paris) 48, 579–582.Google Scholar
  39. 39.
    Walker, N. J. (2002) Tech.Sight. A technique whose time has come. Science 296, 557–559.PubMedCrossRefGoogle Scholar
  40. 40.
    Pfaffl, M. W. (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 29, e45.PubMedCrossRefGoogle Scholar

Copyright information

© Humana Press Inc. 2007

Authors and Affiliations

  • Sukru Tuzmen
    • 1
  • Jeff Kiefer
    • 2
  • Spyro Mousses
    • 3
  1. 1.Molecular Genetics Laboratory, Pharmaceutical Genomics DivisionTranslational Genomics InstituteScottsdale
  2. 2.Knowledge Mining Laboratory, Pharmaceutical Genomics DivisionTranslational Genomics Research InstituteScottsdale
  3. 3.Cancer Drug Development Laboratory, Pharmaceutical Genomics DivisionTranslational Genomics Research InstituteScottsdale

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