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Gene Expression Analyses for Elucidating Mechanisms of Hormonal Action in Plants

  • George W. Bassel
  • Nicholas J. Provart
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 495)

Abstract

Analysis of large-scale gene expression data sets is proving to be a powerful tool for gene function prediction, cis-element discovery and hypothesis generation using Arabidopsis thaliana. Public initiatives led by the AtGenExpress Consortium and experiments conducted by individual researchers to document the transcriptome of Arabidopsis thaliana have led to a large numbers of data sets being made publicly available for data mining by so-called “electronic northerns”, co-expression analysis and other means. Given that approximately 50% genes in Arabidopsis have no function ascribed to them by “traditional” homology searches, and that only around 10% of the genes have had their function confirmed in the laboratory, these analyses can accelerate the identification of potential gene function with a mouse-click. This chapter covers the use of data mining tools available at the Bio-Array Resource (www.bar.utoronto.ca) for hypothesis generation in the context of plant hormone biology.

Key words

Gene expression analysis co-expression analysis data mining cis-element prediction, microarray gene function prediction Arabidopsis thaliana 

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Copyright information

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

Authors and Affiliations

  • George W. Bassel
    • 1
  • Nicholas J. Provart
    • 1
  1. 1.Department of Cell & Systems BiologyUniversity of TorontoTorontoCanada

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