Transcriptional Profiling in Plants

Matthew A Hannah, Max‐Planck‐Institute of Molecular Plant Physiology, Potsdam‐Golm, Germany
Dirk Hincha, Max‐Planck‐Institute of Molecular Plant Physiology, Potsdam‐Golm, Germany
Thomas Altmann, University of Potsdam, Potsdam‐Golm, Germany

Published online: July 2007

DOI: 10.1002/9780470015902.a0020129

Full Article on Wiley Online Library

With appropriate design and data analysis, transcriptional profiling (i.e. the multiparallel analysis of expression of a large number of genes) is a reliable and powerful method to investigate developmental or physiological processes in plants, in particular the responses to genetic and environmental perturbation. Furthermore, its utility is broadened by the public availability of many experiments, which has led to the development of novel tools for determining gene function that are of direct and immediate use to the plant biology community.

Keywords: microarray; expression profiling; transcriptomics; data analysis; Arabidopsis

	Figure 1. Flowchart of the typical stages of a microarray experiment.
	Figure 2a. Example of visualizations of microarray datasets using publicly available resources. Heatmap of selected stress responsive genes in response to various abiotic and biotic stress treatments. From https://www.genevestigator.ethz.ch/at/, Copyright © 2007. Used with permission from ETH Zurich.
	Figure 2b. Example of visualizations of microarray datasets using publicly available resources. MapMan (http://gabi.rzpd.de/projects/MapMan/) overview of central metabolism gene expression changes in Columbia-0 after 14 days of cold acclimation at 4°C (Hannah et al., 2006). Reproduced with permission from MapMan software.
	Figure 2c. Example of visualizations of microarray datasets using publicly available resources. Electronic fluorescent protein (eFP) overview of APETALA1 expression in different plant organs (http://bbc.botany.utoronto.ca/). Reproduced with permission of Nicholas Provart.

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Further Reading
	other Performing a profiling experiment.
	Shi LM, Reid LH, Jones WD et al. (2006) The microarray quality control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nature Biotechnology 24: 1151–1161.
	van de Peppel J, Kemmeren P, van Bakel H et al. (2003) Monitoring global messenger RNA changes in externally controlled microarray experiments. EMBO Reports 4: 387–393.
	other Analysis of profiling data.
	Allison DB, Cui X, Page GP and Sabripour M (2006) Microarray data analysis: from disarray to consolidation and consensus. Nature Reviews Genetics 7: 55–65.
	Clarke JD and Zhu T (2006) Microarray analysis of the transcriptome as a stepping stone towards understanding biological systems: practical considerations and perspectives. The Plant Journal 45: 630–650.
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	Zimmermann P, Schildknecht B, Craigon D et al. (2006) MIAME/Plant – adding value to plant microarrray experiments. Plant Methods 2: 1.
	other Applications of transcript profiling in plants.
	Birnbaum K, Jung JW, Wang JY et al. (2005) Cell type-specific expression profiling in plants via cell sorting of protoplasts from fluorescent reporter lines. Nature Methods 2: 615–619.
	Brady SM, Long TA and Benfey PN (2006) Unraveling the dynamic transcriptome. Plant Cell 18: 2101–2111.
	Kliebenstein DJ, West MA, van Leeuwen H et al. (2006) Identification of QTLs controlling gene expression networks defined a priori. BMC Bioinformatics 7: 308.

Article Title:	Transcriptional Profiling in Plants
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