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. 2002 Jun;129(2):661-77.
doi: 10.1104/pp.002857.

Transcriptional profiling reveals novel interactions between wounding, pathogen, abiotic stress, and hormonal responses in Arabidopsis

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Transcriptional profiling reveals novel interactions between wounding, pathogen, abiotic stress, and hormonal responses in Arabidopsis

Yong Hwa Cheong et al. Plant Physiol. 2002 Jun.

Abstract

Mechanical wounding not only damages plant tissues, but also provides pathways for pathogen invasion. To understand plant responses to wounding at a genomic level, we have surveyed the transcriptional response of 8,200 genes in Arabidopsis plants. Approximately 8% of these genes were altered by wounding at steady-state mRNA levels. Studies of expression patterns of these genes provide new information on the interactions between wounding and other signals, including pathogen attack, abiotic stress factors, and plant hormones. For example, a number of wound-responsive genes encode proteins involved in pathogen response. These include signaling molecules for the pathogen resistance pathway and enzymes required for cell wall modification and secondary metabolism. Many osmotic stress- and heat shock-regulated genes were highly responsive to wounding. Although a number of genes involved in ethylene, jasmonic acid, and abscisic acid pathways were activated, many in auxin responses were suppressed by wounding. These results further dissected the nature of mechanical wounding as a stress signal and identified new genes that may play a role in wounding and other signal transduction pathways.

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Figures

Figure 1
Figure 1
A representative scatter plot of the expression level of 8,200 genes, showing the reproducibility between GeneChip experiments. Total RNA was prepared from the control sample at the 0 time point, and labeled samples were independently synthesized and hybridized to the arrays. Note that a high correlation is observed, indicating the results are reproducible.
Figure 2
Figure 2
Hierarchical cluster of the wounding-induced and -reduced genes using Spearman rank correlation, showing the early “signal gene clusters” and late “effector gene clusters.” Up-regulated gene clusters are indicated by red bars (signal gene clusters) or orange bars (effector gene clusters). Down-regulated gene clusters are indicated by the blue bar.
Figure 3
Figure 3
A hypothetical model for early wound-responsive transcription factors to activate late responsive genes in wounding signal transduction pathways.

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