Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis

PloS One
Katherine C H AmrineDario Cantu

Abstract

Intricate signal networks and transcriptional regulators translate the recognition of pathogens into defense responses. In this study, we carried out a gene co-expression analysis of all currently publicly available microarray data, which were generated in experiments that studied the interaction of the model plant Arabidopsis thaliana with microbial pathogens. This work was conducted to identify (i) modules of functionally related co-expressed genes that are differentially expressed in response to multiple biotic stresses, and (ii) hub genes that may function as core regulators of disease responses. Using Weighted Gene Co-expression Network Analysis (WGCNA) we constructed an undirected network leveraging a rich curated expression dataset comprising 272 microarrays that involved microbial infections of Arabidopsis plants with a wide array of fungal and bacterial pathogens with biotrophic, hemibiotrophic, and necrotrophic lifestyles. WGCNA produced a network with scale-free and small-world properties composed of 205 distinct clusters of co-expressed genes. Modules of functionally related co-expressed genes that are differentially regulated in response to multiple pathogens were identified by integrating differential gene express...Continue Reading

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Citations

Aug 22, 2015·Current Opinion in Plant Biology·Oliver Windram, Katherine J Denby
Jan 22, 2017·The Plant Journal : for Cell and Molecular Biology·Amit RaiMami Yamazaki
Aug 23, 2019·Acta Biochimica Et Biophysica Sinica·Xiaolan Rao, Richard A Dixon
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Aug 17, 2021·The Plant Journal : for Cell and Molecular Biology·Florent DelplaceDominique Roby

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Datasets Mentioned

BETA
GPL198

Software Mentioned

TOOL
R
Limma R
Limma
cutreeDynamic
db R package
WGCNA R package
gcrma
ArrayExpress
topGO

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