Transcriptional Profiling in Plants


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 2.

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, Copyright © 2007. Used with permission from ETH Zurich.

Figure 3.

Example of visualizations of microarray datasets using publicly available resources. MapMan ( overview of central metabolism gene expression changes in Columbia‐0 after 14 days of cold acclimation at 4°C (Hannah et al., ). Reproduced with permission from MapMan software.

Figure 4.

Example of visualizations of microarray datasets using publicly available resources. Electronic fluorescent protein (eFP) overview of APETALA1 expression in different plant organs ( Reproduced with permission of Nicholas Provart.



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Degenkolbe T, Hannah MA, Freund S et al. (2005) A quality‐controlled microarray method for gene expression profiling. Analytical Biochemistry 346: 217–224.

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Further Reading

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.

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.

Gentleman RC, Carey VJ, Bates DM et al. (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biology 5: R80.

Nettleton D (2006) A discussion of statistical methods for design and analysis of microarray experiments for plant scientists. Plant Cell 18: 2112–2121.

Zimmermann P, Schildknecht B, Craigon D et al. (2006) MIAME/Plant – adding value to plant microarrray experiments. Plant Methods 2: 1.

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.

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How to Cite close
Hannah, Matthew A, Hincha, Dirk, and Altmann, Thomas(Jul 2007) Transcriptional Profiling in Plants. In: eLS. John Wiley & Sons Ltd, Chichester. [doi: 10.1002/9780470015902.a0020129]