A genomic approach to identify regulatory nodes in the transcriptional network of systemic acquired resistance in plants.

Published

Journal Article

Many biological processes are controlled by intricate networks of transcriptional regulators. With the development of microarray technology, transcriptional changes can be examined at the whole-genome level. However, such analysis often lacks information on the hierarchical relationship between components of a given system. Systemic acquired resistance (SAR) is an inducible plant defense response involving a cascade of transcriptional events induced by salicylic acid through the transcription cofactor NPR1. To identify additional regulatory nodes in the SAR network, we performed microarray analysis on Arabidopsis plants expressing the NPR1-GR (glucocorticoid receptor) fusion protein. Since nuclear translocation of NPR1-GR requires dexamethasone, we were able to control NPR1-dependent transcription and identify direct transcriptional targets of NPR1. We show that NPR1 directly upregulates the expression of eight WRKY transcription factor genes. This large family of 74 transcription factors has been implicated in various defense responses, but no specific WRKY factor has been placed in the SAR network. Identification of NPR1-regulated WRKY factors allowed us to perform in-depth genetic analysis on a small number of WRKY factors and test well-defined phenotypes of single and double mutants associated with NPR1. Among these WRKY factors we found both positive and negative regulators of SAR. This genomics-directed approach unambiguously positioned five WRKY factors in the complex transcriptional regulatory network of SAR. Our work not only discovered new transcription regulatory components in the signaling network of SAR but also demonstrated that functional studies of large gene families have to take into consideration sequence similarity as well as the expression patterns of the candidates.

Full Text

Duke Authors

Cited Authors

  • Wang, D; Amornsiripanitch, N; Dong, X

Published Date

  • November 2006

Published In

Volume / Issue

  • 2 / 11

Start / End Page

  • e123 -

PubMed ID

  • 17096590

Pubmed Central ID

  • 17096590

Electronic International Standard Serial Number (EISSN)

  • 1553-7374

International Standard Serial Number (ISSN)

  • 1553-7366

Digital Object Identifier (DOI)

  • 10.1371/journal.ppat.0020123

Language

  • eng