Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection.

Zhenhong Jiang,Xiaobao Dong,Fei He,Zhi-Gang Li,Ziding Zhang

doi:10.1038/srep35064

Abstract

Plant defense responses to pathogens involve massive transcriptional reprogramming. Recently, differential coexpression analysis has been developed to study the rewiring of gene networks through microarray data, which is becoming an important complement to traditional differential expression analysis. Using time-series microarray data of Arabidopsis thaliana infected with Pseudomonas syringae, we analyzed Arabidopsis defense responses to P. syringae through differential coexpression analysis. Overall, we found that differential coexpression was a common phenomenon of plant immunity. Genes that were frequently involved in differential coexpression tend to be related to plant immune responses. Importantly, many of those genes have similar average expression levels between normal plant growth and pathogen infection but have different coexpression partners. By integrating the Arabidopsis regulatory network into our analysis, we identified several transcription factors that may be regulators of differential coexpression during plant immune responses. We also observed extensive differential coexpression between genes within the same metabolic pathways. Several metabolic pathways, such as photosynthesis light reactions, exhibited significant changes in expression correlation between normal growth and pathogen infection. Taken together, differential coexpression analysis provides a new strategy for analyzing transcriptional data related to plant defense responses and new insights into the understanding of plant-pathogen interactions.

Highlights

Differential coexpression analysis is emerging as an important complement to the traditional differential expression analysis[16,17,18]
Lewis et al conducted a comparative analysis on the same transcriptional data for exploring the transcriptional dynamics during microbial-associated molecular pattern-triggered immunity induced by P. syringae pv. tomato DC3000 hrpA treatment and effector-triggered susceptibility caused by P. syringae pv. tomato DC3000 challenge[32]
GSE56094 is composed of 156 distinct samples from 13 time points in three conditions: mock treatments or infections by either virulent P. syringae pv tomato DC3000 or the corresponding nonpathogenic hrpA mutant, with four replicates for each condition[30,31,32]

Summary

Introduction

Differential coexpression analysis is emerging as an important complement to the traditional differential expression analysis[16,17,18]. Based on Fisher’s z-test, Fukushima et al explored tomato gene function via differential coexpression analysis[24] Later, they published an R package called DiffCorr to identify differential coexpression gene pairs[22]. They analyzed the expression changes of nuclear-encoded chloroplast-targeted Arabidopsis genes and showed that chloroplast was a key component of early immune responses[30]. To explore the biological significance of differential coexpression, we identified some potential TFs regulating differential coexpression in plant immune responses with the assistance of known Arabidopsis gene regulatory networks. We investigated differential coexpression in the context of metabolic pathways These results further indicated that the Arabidopsis gene network has been extensively rewired in response to infections by plant pathogens

Methods

Results

Conclusion