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Global analysis of gene expression by differential display

A mathematical model

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Abstract

Differential display (DD) is one of the most commonly used approaches for identifying differentially expressed genes. However, there has been lack of an accurate guidance on how many DD polymerase chain reaction (PCR) primer combinations are needed to display most of the genes expressed in a eukaryotic cell. This study critically evaluated the gene coverage by DD as a function of the number of arbitrary primers, the number of 3′ bases of an arbitrary primer required to completely match an mRNA target sequence, the additional 5′ base match(s) of arbitrary primers in first-strand cDNA recognition, and the length of mRNA tails being analyzed. The resulting new DD mathematical model predicts that 80 to 160 arbitrary 13mers, when used in combinations with 3 one-base anchored oligo-dT primers, would allow any given mRNA within a eukaryotic cell to be detected with a 74% to 93% probability, respectively. The prediction was supported by both computer simulation of the DD process and experimental data from a comprehensive fluorescent DD screening for target genes of tumor-suppressor p53. Thus, this work provides a theoretical foundation upon which global analysis of gene expression by DD can be pursued.

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References

  1. Hogenesch, J.B., Ching, K.A., Batalov, S., et al. (2001) A Comparison of the Celera and Ensembl Predicted Gene Sets Reveals Little Overlap in Novel Genes. Cell, 106, 413–415.

    Article  PubMed  CAS  Google Scholar 

  2. Liang, P. and Pardee, A. B. (1992) Differential display of eukaryotic mRNA by means of the polymerase chain reaction. Science, 257, 967–971.

    Article  PubMed  CAS  Google Scholar 

  3. Velculescu VE, Zhang L, Vogelstein B, and Kinzler KW. (1995) Serial analysis of gene expression. Science, 270, 484–487.

    Article  PubMed  CAS  Google Scholar 

  4. Schena, M., Shalon, D., Davis, R. W. and Brown, P.O. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 270, 467–470.

    Article  PubMed  CAS  Google Scholar 

  5. Brenner, S. (1999) “Sillycon valley fever”. Current Biol., 9, R671.

  6. Wooster, R. (2000) Cancer classification with DNA microarrays: is less more? Trends Genet., 16, 327–329.

    Article  PubMed  CAS  Google Scholar 

  7. Liang, P. (2000) Gene discovery using differential display. Genet. Eng. News, 20, 37.

    Google Scholar 

  8. Mir, K. U. (2000) The hypothesis isther is no hypothesis. Trends Genet., 16, 63–64.

    Article  PubMed  CAS  Google Scholar 

  9. Gibbs, W. W. (2001) Shrinking to enormity: DNA microarrays are reshaping basic biology — but scientists fear they may soon drown in the data. Scientific American, 284, 33–34.

    Article  CAS  Google Scholar 

  10. Mills, J.C, Roth, K.A, Cagan, R.L, Gordon, J.I. (2001) DNA microarrays and beyond: completing the journey from tissue to cell. Nat. Cell Biol., 8, E175–178.

    Article  CAS  Google Scholar 

  11. Goryachev, A.B, Macgregor, P.F, Edwards, A.M. (2001) Unfolding of microarray data. J Comput Biol., 8, 443–461.

    Article  PubMed  CAS  Google Scholar 

  12. Shedden, K and Cooper, S. (2002) Analysis of cell-cycle-specific gene expression in human cells as determined by microarrays and double-thymidine block synchronization. Proc Natl Acad Sci USA, 99, 4379–4384.

    Article  PubMed  CAS  Google Scholar 

  13. Cooper, S. (2002) Cell cycle analysis and microarrays. Trends Genet., 18, 289–290.

    Article  PubMed  CAS  Google Scholar 

  14. Liang, P. and Pardee, AB. (2003) Analyzing differential gene expression in cancer. NatRev. Vancer, 3, 869–883.

    Article  CAS  Google Scholar 

  15. Stollberg, J., Urschitz, J., Urban, Z. and Boyd, C. D. (2000) A quantitative evaluation of SAGE. Genome Res., 10, 1241–1248.

    Article  PubMed  CAS  Google Scholar 

  16. Liang, P., Averboukh, L. and Pardee, A. B. (eds.) (1994) Method of differential display in Methods in Molecular Genetics, Adolph, K. W., ed., Academic Press, New York, pp. 3–16.

    Google Scholar 

  17. Liang, P., Bauer, D., Averboukh, L., Warthoe, P. Rohrwild, M., Muller, H., Strauss, M. and Pardee, A. B. (1995) Analysis of altered gene expression by differential display, in Methods in Enzymology, Vogt, P. K., ed., Academic Press, New York, pp/ 304–321.

    Google Scholar 

  18. Williams, J.G., Kubelik, A. R., Rafalski, J.A and Tingey, S. V. (1990) DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Res., 18, 6531–6535.

    Article  PubMed  CAS  Google Scholar 

  19. Liang, P., Zhu, W., Zhang, X., Guo, Z., O’Connell, R., Averboukh, L. Wang, F. and Pardee, A. B. (1994). Differential display using one-base anchored oligo-dT primer. Nucleic Acids Res., 22, 5763–5764.

    Article  PubMed  CAS  Google Scholar 

  20. Liang, P., Editor. (1998) Current progress in differential display methods and applications.methods in: A Companion to Methods in Enzymology, Academic Press, New York, pp.

    Google Scholar 

  21. Yu, J., Zhang, L., Hwang, P.M., Rago, C., Kinzler, K. and Vogelstein, B. (1999) Identification and classification of p53-regulated genes. Proc. Natl. Acad. Sci. USA 96, 14,517–14,522.

    CAS  Google Scholar 

  22. Cho, Y., Meade, J., Walden, J., Guo, Z. and Liang, P. (2001) Multi-color Fluorescent Differential Display. Biotechniques, 30, 562–572.

    PubMed  CAS  Google Scholar 

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Correspondence to Shitao Yang or Peng Liang.

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Yang, S., Liang, P. Global analysis of gene expression by differential display. Mol Biotechnol 27, 197–208 (2004). https://doi.org/10.1385/MB:27:3:197

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