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Related Experiment Videos

Microarray expression profiling resources for plant genomics.

Willem Albert Rensink1, C Robin Buell

  • 1The Institute for Genomic Research, 9712 Medical Center Dr., Rockville, MD 20850, USA. wrensink@tigr.org

Trends in Plant Science
|November 9, 2005
PubMed
Summary
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This review highlights recent advances in plant genomic research using microarrays and gene expression databases. These tools accelerate the discovery of gene function by analyzing large-scale expression data from various plant species.

Area of Science:

  • Plant genomics
  • Functional genomics
  • Bioinformatics

Background:

  • Significant generation of plant genomic data, including sequence and functional annotation.
  • Diverse technologies like expressed sequence tags (ESTs), massively parallel signature sequencing (MPSS), and microarrays have been employed for gene expression studies.
  • Microarrays enable simultaneous functional data acquisition for numerous genes.

Purpose of the Study:

  • To review recent advancements in applying microarrays to plant genomic research.
  • To discuss the availability and utility of plant gene expression databases.
  • To highlight the role of these resources in functional gene discovery.

Main Methods:

  • Review of current literature on microarray applications in plant genomics.

Related Experiment Videos

  • Analysis of publicly available plant gene expression datasets, particularly from Arabidopsis.
  • Description of emerging microarray platforms for crop species.

    • Main Results:

    • Extensive microarray data for Arabidopsis is publicly accessible.
    • New microarray platforms are enabling genome-wide expression profiling in important crop species.
    • Public databases provide access to large-scale expression data.

    Conclusions:

    • Microarrays and associated public databases are crucial tools for plant genomic research.
    • These resources facilitate the functional discovery of genes in plants.
    • Continued development and accessibility of such data will advance plant science.