Advertisement

Application of ESTs in Microarray Analysis

  • Weizhong Li
  • Lisa Olohan
  • Daryl Williams
  • Margaret Hughes
  • Andrew Gracey
  • Andrew Cossins
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 533)

Abstract

Microarray analyses provide information on the relative expression levels of large numbers of gene products (transcripts). As such they have been widely used to examine differences in gene expression across a variety of samples such as tissues and life-cycle stages. Due to a previous lack of sequence data, microarray analyses have typically centred on the study of well-characterised model organisms. However, the recent availability of large sets of expressed sequence tags (ESTs) generated for the purpose of gene discovery offers the opportunity to consider designing and applying microarray technology to a larger and more diverse set of species. Here we outline the array-design process involving the generation of an optimised set of oligoprobes from a minimally redundant but maximally representative list of sequences from raw EST data. We illustrate these principles by showing how we designed and fabricated a high-density oligoarray for the rainbow trout, a non-model species for which large numbers of ESTs, and a non-redundant assembly is available. This approach brings array technology within the reach of all investigators, even those with limited budgets.

Key words

Microarray oligoprobe expression profiling 

References

  1. 1.
    Hughes, T. R., Mao, M., Jones, A. R., Burchard, J., Marton, M. J., Shannon, K. W., Lefkowitz, S. M., Ziman, M., Schelter, J. M., Meyer, M. R., Kobayashi, S., Davis, C., Dai, H., He, Y. D., Stephaniants, S. B., Cavet, G., Walker, W. L., West, A., Coffey, E., Shoemaker, D. D., Stoughton, R., Blanchard, A. P., Friend, S. H., and Linsley, P. S. (2001) Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nat Biotechnol. 19, 342–47.PubMedCrossRefGoogle Scholar
  2. 2.
    Gracey, A. Y., Troll, J. V., and Somero, G. N. (2001) Hypoxia-induced gene expression profiling in the euryoxic fish Gillichthys mirabilis. Proc Natl Acad Sci USA 98, 1993–8.PubMedCrossRefGoogle Scholar
  3. 3.
    Podrabsy, J., and Somero, G. (2004) Changes in gene expression associated with acclimation to constant temperatures and fluctuating daily temperatures in an annual killifish Austrofundulus limnaeus. J Exp Biol 207, 2237–54.CrossRefGoogle Scholar
  4. 4.
    Carninci, P., Shibata, Y., Hayatsu, N., Sugahara, Y., Shibata, K., Itoh, M., Konno, H., Okazaki, Y., Muramatsu, M., and Hayashizaki, Y. (2000) Normalization and subtraction of cap-trapper-selected cDNAs to prepare full-length cDNA libraries for rapid discovery of new genes. Genome Res 10, 1617–30.PubMedCrossRefGoogle Scholar
  5. 5.
    Sagerstrom, C. G., Sun, B. I., and Sive, H. L. (1997) Subtractive cloning : Past; present; and future. Ann Rev Biochem 66, 751–83.PubMedCrossRefGoogle Scholar
  6. 6.
    Diatchenko, L., Lau, Y. F., Campbell, A. P., Chenchik, A., Moqadam, F., Huang, B., Lukyanov, S., Lukyanov, K., Gurskaya, N., Sverdlov, E. D., and Siebert, P. D. (1996) Suppression subtractive hybridization: a method for generating differentially regulated or tissue-specific cDNA probes and libraries. Proc Natl Acad Sci USA 93, 6025–30.PubMedCrossRefGoogle Scholar
  7. 7.
    Diatchenko, L., Lukyanov, S., Lau, Y. F. C., and Siebert, P. D. (1999) Suppression subtractive hybridization: a versatile method for identifying differentially expressed genes. Methods Enzymol 303, 349–80.PubMedCrossRefGoogle Scholar
  8. 8.
    Leparc, G. G., Tu¨chler, T., Striedner, G., Bayer, K., Sykacek, P., Hofacker, I. P., and Kreil, D. P. (2008) Model-based probe set optimization for high-performance microarrays. Nucleic Acids Res. doi:10.1093/nar/gkn1001Google Scholar
  9. 9.
    Kreil, D., Russell, R., and Russell, S. (2006) Microarray oligonucleotide probes. Methods Enzymol 410, 73–98.Google Scholar
  10. 10.
    Charbonnier, Y., Gettler, B., Francois, P., Bento, M., Renzoni, A., Vaudaux, P., Schlegel, W., and Schrenzel, J. (2005) A generic approach for the design of whole-genome oligoarrays, validated for genotyping, deletion mapping and gene expression analysis on Staphylococcus aureus. BMC Genomics 6, 95.PubMedCrossRefGoogle Scholar
  11. 11.
    Stenberg, J., Nilsson, M., and Landegren, U. (2005) ProbeMaker: an extensible framework for design of sets of oligonucleotide probes. BMC Bioinformatics 6, 229.PubMedCrossRefGoogle Scholar
  12. 12.
    Benson, D. A., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J., and Wheeler, D. L. (2006) GenBank. Nucleic Acids Res 1, D16–D20.CrossRefGoogle Scholar
  13. 13.
    Maglott, D., Ostell, J., Pruitt, K. D., and Tatusova, T. (2005) Entrez gene: gene-centered information at NCBI. Nucleic Acids Res 1, D54–D8.Google Scholar
  14. 14.
    Gerhard, D., Wagener, L., Feingold, E., Shenman, C., Grouse, L., Schuler, G., Klein, S., DOld, S., Rasooly, R., and Good, P. (2004) The status, quality, and expansion of the NIH full-length cDNA project: the Mammalian Gene Collection (MGC). Genome Res 41, 2121–27.Google Scholar
  15. 15.
    Apweiler, R., Bairoch, A., Wu, C.H., Barker, W.C., Boeckmann, B., Ferro, S., Gasteiger, E., Huang, H., Lopez, R., Magrane, M., Martin, M. J., Natale, D. A., O'Donovan, C., Redaschi, N., and Yeh, L.S. (2004) UniProt: the Universal Protein knowledgebase. Nucleic Acids Res 1, D115–D19.CrossRefGoogle Scholar
  16. 16.
    Dai, H., Meyer, M., Stepanients, S., Ziman, M., and Stoughton, R. (2002) Use of hybridisation kinetics for differentiating specific from non-specific binding to oligonucleotide microarrays. Nucleic Acids Res 30, e86.PubMedCrossRefGoogle Scholar
  17. 17.
    Churchill, G. (2002) Fundamentals of experimental design for cDNA microarrays. Nat Genet 32, 490–5.PubMedCrossRefGoogle Scholar
  18. 18.
    Wit, E., and McClure, J. (2004) Statistics for Microarrays: design, Analysis and Inference. Wiley Interscience, New York.Google Scholar
  19. 19.
    Speed, T. (Ed.) (2003) Statistical Analysis of Gene Expression Microarray Data. CRC Press, Chaman & Hall, Boca Raton.CrossRefGoogle Scholar
  20. 20.
    Quackenbush, J. (2001) Computational analysis of microarray data. Nat Rev Genet 2, 418–27.PubMedCrossRefGoogle Scholar
  21. 21.
    Churchill, G. A. (2004) Using ANOVA to analyze microarray data. Biotechniques 37, 173–75.PubMedGoogle Scholar
  22. 22.
    Berger, J., Hautaniemi, S., Järvinen, A.-K., Edgren, H., Mitra, S., and Astola, Optimized LOWESS normalization parameter selection for DNA microarray data. BMC Bioinformatics 5, 194.Google Scholar
  23. 23.
    Sutton, G. G., White, O., Adams, M. D. and Kerlavage, A. R. (1995) TIGR Assembler: a New Tool for Assembling Large Shotgun Sequencing Projects. Genome Sci Technol 1, 9–19.CrossRefGoogle Scholar
  24. 24.
    Wheeler, D. L., Church, D. M., Federhen, S., Lash, A. E., Madden, T. L., Pontius, J. U., Schuler, G. D., Schriml, L. M., Sequeira, E., Tatusova, T. A., and Wagner, L. (2003) Database resources of the National Center for Biotechnology. Nucleic Acids Res 31, 28–33.PubMedCrossRefGoogle Scholar
  25. 25.
    Rouillard, J. M., Zuker, M., and Gulari, E. (2003) OligoArray 2.0: design of oligonucleotide probes for DNA microarrays using a thermodynamic approach Nucleic Acids Res 31, 3057–62.PubMedCrossRefGoogle Scholar

Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Weizhong Li
    • 1
  • Lisa Olohan
    • 1
  • Daryl Williams
    • 1
  • Margaret Hughes
    • 1
  • Andrew Gracey
    • 2
  • Andrew Cossins
    • 1
  1. 1.Laboratory for Environmental Gene Regulation and Liverpool Microarray FacilitySchool of Biological Sciences, University of LiverpoolUK
  2. 2.Marine Environmental BiologyUniversity of Southern CaliforniaLos AngelesUSA

Personalised recommendations