Skip to main content
SpringerLink
Log in

Microarrays

An Overview

  • Protocol
Protocols for Nucleic Acid Analysis by Nonradioactive Probes

Part of the book series: Methods in Molecular Biology ((MIMB,volume 353))

Abstract

Gene expression microarrays are being used widely to address a myriad of complex biological questions. To gather meaningful expression data, it is crucial to have a firm understanding of the steps involved in the application of microarrays. The available microarray platforms are discussed along with their advantages and disadvantages. Additional considerations include study design, quality control and systematic assessment of microarray performance, RNA-labeling strategies, sample allocation, signal amplification schemes, defining the number of appropriate biological replicates, data normalization, statistical approaches to identify differentially regulated genes, and clustering algorithms for data visualization. In this chapter, the underlying principles regarding microarrays are reviewed, to serve as a guide when navigating through this powerful technology.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Liang, P. and Pardee, A. B. (2003) Analysing differential gene expression in cancer. Nat. Rev. Cancer 3, 869–876.

    Article  PubMed  CAS  Google Scholar 

  2. Miller, L. D., Long, P. M., Wong, L., Mukherjee, S., McShane, L. M., and Liu, E. T. (2002) Optimal gene expression analysis by microarrays. Cancer Cell 2, 353–361.

    Article  PubMed  CAS  Google Scholar 

  3. Roth, M. E., Feng, L., McConnell, K. J., et al. (2004) Expression profiling using a hexamer-based universal microarray. Nat. Biotechnol. 22, 418–426.

    Article  PubMed  CAS  Google Scholar 

  4. Fan, J. B., Yeakley, J. M., Bibikova, M., et al. (2004) A versatile assay for high-throughput gene expression profiling on universal array matrices. Genome Res. 14, 878–885.

    Article  PubMed  CAS  Google Scholar 

  5. Lockhart, D. J., Dong, H., Byrne, M. C., et al. (1996) Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat. Biotechnol. 14, 1675–1680.

    Article  PubMed  CAS  Google Scholar 

  6. Lipshutz, R. J., Fodor, S. P., Gingeras, T. R., and Lockhart, D. J. (1999) High density synthetic oligonucleotide arrays. Nat. Genet. 21(Suppl), 20–24.

    Article  PubMed  CAS  Google Scholar 

  7. 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 

  8. Schena, M., Heller, R. A., Theriault, T. P., Konrad, K., Lachenmeier, E., and Davis, R. W. (1998) Microarrays: biotechnology’s discovery platform for functional genomics. Trends Biotechnol. 16, 301–306.

    Article  PubMed  CAS  Google Scholar 

  9. Watson, A., Mazumder, A., Stewart, M., and Balasubramanian, S. (1998) Technology for microarray analysis of gene expression. Curr. Opin. Biotechnol. 9, 609–614.

    Article  PubMed  CAS  Google Scholar 

  10. Southern, E., Mir, K., and Shchepinov, M. (1999) Molecular interactions on microarrays. Nat. Genet. 21, 5–9.

    Article  PubMed  CAS  Google Scholar 

  11. Hess, K. R., Zhang, W., Baggerly, K. A., Stivers, D. N., and Coombes, K. R. (2001) Microarrays: handling the deluge of data and extracting reliable information. Trends Biotechnol. 19, 463–468.

    Article  PubMed  CAS  Google Scholar 

  12. Quackenbush, J. (2002) Microarray data normalization and transformation. Nat. Genet. 32(Suppl), 496–501.

    Article  PubMed  CAS  Google Scholar 

  13. Park, T., Yi, S. G., Kang, S. H., Lee, S., Lee, Y. S., and Simon, R. (2003) Evaluation of normalization methods for microarray data. BMC Bioinformatics 4, 33.

    Article  PubMed  Google Scholar 

  14. Wang, H. Y., Malek, R. L., Kwitek, A. E., et al. (2003) Assessing unmodified 70-mer oligonucleotide probe performance on glass-slide microarrays. Genome Biol. 4, R5.

    Article  PubMed  Google Scholar 

  15. Yuen, T., Wurmbach, E., Pfeffer, R. L., Ebersole, B. J., and Sealfon, S. C. (2002) Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays. Nucleic Acids Res. 30, e48.

    Article  PubMed  Google Scholar 

  16. Kuo, W. P., Jenssen, T. K., Butte, A. J., Ohno-Machado, L., and Kohane, I. S. (2002) Analysis of matched mRNA measurements from two different microarray technologies. Bioinformatics 18, 405–412.

    Article  PubMed  CAS  Google Scholar 

  17. Tan, P. K., Downey, T. J., Spitznagel, E. L., Jr., et al. (2003) Evaluation of gene expression measurements from commercial microarray platforms. Nucleic Acids Res. 31, 5676–5684.

    Article  PubMed  CAS  Google Scholar 

  18. Chuaqui, R. F., Bonner, R. F., Best, C. J., et al. (2002) Post-analysis follow-up and validation of microarray experiments. Nat. Genet. 32(Suppl), 509–514.

    Article  PubMed  CAS  Google Scholar 

  19. Eberwine, J., Yeh, H., Miyashiro, K., et al. (1992) Analysis of gene expression in single live neurons. Proc. Natl. Acad. Sci. USA 89, 3010–3014.

    Article  PubMed  CAS  Google Scholar 

  20. Randolph, J. B. and Waggoner, A. S. (1997) Stability, specificity and fluorescence brightness of multiply-labeled fluorescent DNA probes. Nucleic Acid Res. 25, 2923–2929.

    Article  PubMed  CAS  Google Scholar 

  21. Hughes, T. R., Mao, M., Jones, A. R., et al. (2001) Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nat. Biotechnol. 19, 342–347.

    Article  PubMed  CAS  Google Scholar 

  22. Peng, X., Wood, C. L., Blalock, E. M., Chen, K. C., Landfield, P. W., and Stromberg, A. J. (2003) Statistical implications of pooling RNA samples for microarray experiments. BMC Bioinformatics 4, 26.

    Article  PubMed  Google Scholar 

  23. Stears, R. L., Getts, R. C., and Gullans, S. R. (2000) A novel, sensitive detection system for high-density microarrays using dendrimer technology. Physiol. Genomics 3, 93–99.

    PubMed  CAS  Google Scholar 

  24. Wang, E., Miller, L. D., Ohnmacht, G. A., Liu, E. T., and Marincola, F. M. (2000) High-fidelity mRNA amplification for gene profiling. Nat. Biotech. 18, 457–459.

    Article  CAS  Google Scholar 

  25. Xiang, C. C., Chen, M., Ma, L., et al. (2003) A new strategy to amplify degraded RNA from small tissue samples for microarray studies. Nucleic Acids Res. 31, e53.

    Article  PubMed  Google Scholar 

  26. Kerr, M. K. and Churchill, G. A. (2001) Statistical design and the analysis of gene expression microarray data. Genet. Res. 77, 123–128.

    PubMed  CAS  Google Scholar 

  27. Churchill, G. A. (2002) Fundamentals of experimental design for cDNA microarrays. Nat. Genet. 32(Suppl), 490–495.

    Article  PubMed  CAS  Google Scholar 

  28. Dobbin, K., Shih, J. H., and Simon, R. (2003) Questions and answers on design of dual-label microarrays for identifying differentially expressed genes. J. Natl. Cancer Inst. 95, 1362–1369.

    PubMed  Google Scholar 

  29. Simon, R. M. and Dobbin, K. (2003) Experimental design of DNA microarray experiments. Biotechniques (Suppl), 16–21.

    Google Scholar 

  30. Yang, Y. H. and Speed, T. (2002) Design issues for cDNA microarray experiments. Nat. Rev. Genet. 3, 579–588.

    PubMed  CAS  Google Scholar 

  31. Talaat, A. M., Howard, S. T., Hale, W., 4th, Lyons, R., Garner, H., and Johnston, S. A. (2002) Genomic DNA standards for gene expression profiling in Mycobacterium tuberculosis. Nucleic Acids Res. 30, e104.

    Article  PubMed  Google Scholar 

  32. Desu, M. M. and Raghavarao, D. (eds.) (2003) Nonparametric Statistical Methods for Complete and Censored Data. Chapman & Hall/CRC Press, Boca Raton, FL.

    Google Scholar 

  33. Eickhoff, B., Korn, B., Schick, M., Poustka, A., and van der Bosch, J. (1999) Normalization of array hybridization experiments in differential gene expression analysis. Nucleic Acids Res. 27, e33.

    Article  PubMed  CAS  Google Scholar 

  34. Yue, H., Eastman, P. S., Wang, B. B., et al. (2001) An evaluation of the performance of cDNA microarrays for detecting changes in global mRNA expression. Nucleic Acids Res. 29, E41–1.

    Article  PubMed  CAS  Google Scholar 

  35. Badiee, A., Eiken, H. G., Steen, V. M., and Lovlie, R. (2003) Evaluation of five different cDNA labeling methods for microarrays using spike controls. BMC Biotechnol. 3, 23.

    Article  PubMed  Google Scholar 

  36. Benes, V. and Muckenthaler, M. (2003) Standardization of protocols in cDNA microarray analysis. Trends Biochem. Sci. 28, 244–249.

    Article  PubMed  CAS  Google Scholar 

  37. Cui, X. and Churchill, G. A. (2003) Statistical tests for differential expression in cDNA microarray experiments. Genome Biol. 4, 210.

    Article  PubMed  Google Scholar 

  38. Nadon, R. and Shoemaker, J. (2002) Statistical issues with microarrays: processing and analysis. Trends Genet. 18, 265–271.

    Article  PubMed  CAS  Google Scholar 

  39. Tusher, V. G., Tibshirani, R., and Chu, G. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98, 5116–5121.

    Article  PubMed  CAS  Google Scholar 

  40. Cleveland, W. S. (1979) Robust locally weighted regression and smoothing scatter-plots. J. Amer. Stat. Assoc. 74, 829–836.

    Article  Google Scholar 

  41. Yang, Y. H., Dudoit, S., Luu, P., et al. (2002) Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30, e15.

    Article  PubMed  Google Scholar 

  42. Eisen, M. B., Spellman, P. T., Brown, P. O., and Botstein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14,863–14,868.

    Article  PubMed  CAS  Google Scholar 

  43. Wen, X., Fuhrman, S., Michaels, G. S., et al. (1998) Large-scale temporal gene expression mapping of central nervous system development. Proc. Natl. Acad. Sci. USA 95, 334–339.

    Article  PubMed  CAS  Google Scholar 

  44. Soukas, A., Cohen, P., Socci, N. D., and Friedman, J. M. (2000) Leptin-specific patterns of gene expression in white adipose tissue. Genes Dev. 14, 963–980.

    PubMed  CAS  Google Scholar 

  45. Aronow, B. J., Toyokawa, T., Canning, A., et al. (2001) Divergent transcriptional responses to independent genetic causes of cardiac hypertrophy. Physiol. Genomics 6, 19–28.

    PubMed  CAS  Google Scholar 

  46. Dudoit, S., Gentleman, R. C., and Quackenbush, J. (2003) Open source software for the analysis of micorarray data. BioTechniques 34(Suppl), 45–51.

    Google Scholar 

  47. Saeed, A. I., Sharov, V., White, J., et al. (2003) TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34, 374–378.

    PubMed  CAS  Google Scholar 

  48. Gentleman, R. C., Carey, V. J., Bates, D. M., et al. (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80.

    Article  PubMed  Google Scholar 

  49. Saal, L. H., Troein, C., Vallon-Christersson, J., Gruvberger, S., Borg, A., and Peterson, C. (2002) BioArray Software Environment (BASE): a platform for comprehensive management and analysis of microarray data. Genome Biol. 3, SOFTWARE0003.

    Google Scholar 

  50. Sherlock, G. (2000) Analysis of large-scale gene expression data. Curr. Opin. Immunol. 12, 201–205.

    Article  PubMed  CAS  Google Scholar 

  51. Hughes, T. R. and Shoemaker, D. D. (2001) DNA microarrays for expression profiling. Curr. Opin. Chemical Biol. 5, 21–25.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Functional Genomics, The Institute for Genomic Research, Rockville, MD

    Norman H. Lee & Alexander I. Saeed

Authors
  1. Norman H. Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexander I. Saeed
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Gene Technologies, HortResearch Ltd., Mt. Albert, Auckland, New Zealand

    Elena Hilario

  2. Applied Science, Roche Diagnostics, Auckland, New Zealand

    John Mackay

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Humana Press Inc.

About this protocol

Cite this protocol

Lee, N.H., Saeed, A.I. (2007). Microarrays. In: Hilario, E., Mackay, J. (eds) Protocols for Nucleic Acid Analysis by Nonradioactive Probes. Methods in Molecular Biology, vol 353. Humana Press. https://doi.org/10.1385/1-59745-229-7:265

Download citation

  • DOI: https://doi.org/10.1385/1-59745-229-7:265

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-430-2

  • Online ISBN: 978-1-59745-229-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation