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Microarray and gene-clustering analysis.

Tsung-Hsien Tsai1, Denise M Milhorn, Shau-Ku Huang

  • 1Division of Allergy and Clinical Immunology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Methods in Molecular Biology (Clifton, N.J.)
|August 20, 2005
PubMed
Summary

DNA-chip technology enables comprehensive analysis of gene expression in human mast cells. This transcriptional profiling approach, combined with bioinformatics, offers a global view of immune responses and disease mechanisms.

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Area of Science:

  • Immunology
  • Molecular Biology
  • Genomics

Background:

  • Human mast cells are key players in innate immunity, releasing inflammatory mediators and cytokines.
  • Mast cell activation by antigen/immunoglobulin E (IgE) triggers complex signaling and gene expression pathways.

Purpose of the Study:

  • To review the application of DNA-chip technology for transcriptional profiling of activated human mast cells.
  • To discuss the integration of bioinformatics in analyzing mast cell gene expression data.

Main Methods:

  • Utilized complimentary deoxyribonucleic acid (DNA) oligonucleotide microarray (DNA-chip) technology for simultaneous gene expression monitoring.
  • Employed bioinformatics tools, including gene-clustering analyses (hierarchical clustering, self-organizing maps), for data interpretation.

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  • Described a laboratory protocol for array analysis of cultured cord blood-derived mononuclear cells.

    • Main Results:

    • DNA-chip technology allows for whole-genome scale identification of genes and their activity changes.
    • Transcriptional profiling reveals common gene expression patterns across experiments, aiding in understanding pathophysiologic changes.
    • Bioinformatics analysis is crucial for interpreting complex gene expression datasets.

    Conclusions:

    • DNA-chip technology provides powerful tools for studying mast cell biology and immune responses.
    • Transcriptional profiling combined with bioinformatics offers a global perspective on mast cell function.
    • The described techniques are broadly applicable to various array formats and gene expression studies.