Discovery of Core Biotic Stress Responsive Genes in Arabidopsis by Weighted Gene Co-Expression Network Analysis

<div><p>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 <i>Arabidopsis thaliana</i> 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 expression testing with functional enrichment analyses of gene ontology terms, known disease associated genes, transcriptional regulators, and <i>cis</i>-regulatory elements. The significance of functional enrichments was validated by comparisons with randomly generated networks. Network topology was then analyzed to identify intra- and inter-modular gene hubs. Based on high connectivity, and centrality in meta-modules that are clearly enriched in defense responses, we propose a list of 66 target genes for reverse genetic experiments to further dissect the Arabidopsis immune system. Our results show that statistical-based data trimming prior to network analysis allows the integration of expression datasets generated by different groups, under different experimental conditions and biological systems, into a functionally meaningful co-expression network.</p></div

Gene Ontology (GO) term enrichments in modules identified by WGCNA and in randomly generated modules.

<p>(<b>A</b>) Molecular function and (<b>B</b>) biological process GO terms. Line plots represent the number of enriched modules as a function of the number of enriched terms in a module. Red symbols represent the observed counts, and red lines represent the best smooth of the data points. The black lines and symbols represent the mean number of enriched modules for modules with any given number of enriched GO terms in 100 random replicates. The boxplot represents the number of total modules with at least one enriched term in all 100 random permutations of the network. Red symbols represent the number of modules with at least one enriched term in the natural network. Real BP data included eight modules enriched for up to 274 terms, which were not shown in the figure.</p

Characterization of the disease response hub genes extracted from the Arabidopsis co-expression network.

<p>(<b>A</b>) Unweighted network showing the connectivity (TOM > 0.1) between the 46 hub genes identified in the LTDL, PB, TOOL, and LT meta-modules and 20 extended hub genes (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118731#pone.0118731.s012" target="_blank">S7 Table</a>). Nodes are visualized as circles and correlations between nodes as lines (edges). Node size is proportional to degree of unweighted connectivity; the colors of the nodes correspond to modular assignments. The inner circle represents the disease response-related meta-module hub connectivity. The outer circle represents the extended hub genes found to have TOM > 0.1 connections with > 75% of the original hubs. (<b>B</b>) Gene Ontology-annotated hierarchy of the top 5% enriched biological processes in the 66 hub genes. Boxes represent direct assignments of GO terms to hub genes, and ellipses represent parent terms assigned by topGO during analysis. (<b>C</b>) Boxplot showing the distribution of gene expression fold changes (log₂) of the hub nodes in each microarray. The modules associated to each of the genes are provided in the multi-color bar. Red and blue dots represent comparisons in which genes were up- and down-regulated, respectively. For details refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118731#pone.0118731.s012" target="_blank">S7 Table</a>.</p

Summary of experiments included in this study.

<p>¹ Number of ATH1 arrays that were hybridized with cDNA from pathogen-infected samples</p><p>² BB: bacterial biotrophs; BH: bacterial hemibiotrophs; BN: bacterial necrotrophs; FB: fungal biotrophs; FN: fungal necrotrophs; OB: oomycete biotrophs; PR: protist.</p><p>³ Values in parenthesis correspond to the number of arrays for each pathogen.</p><p>Summary of experiments included in this study.</p

Graphical representation of the TOOL meta-module.

<p>Nodes of the unweighted network (TOM > 0.1) are visualized as circles and correlations between nodes as lines (edges). Node size is proportional to degree of unweighted connectivity; the colors of the edge of the nodes correspond to module membership; edge width and opacity are proportional to TOM and adjacency values between the two connected nodes, respectively. The central color of each node is based on the mean expression log₂ fold-change (up-regulation in red, down-regulation in blue) in response to necrotrophs (left) and biotrophs (right). The shape of the network is based on a force-directed graph calculation which creates a shape based on centrality computed with Cytoscape v. 2.8 [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0118731#pone.0118731.ref029" target="_blank">29</a>]. Intra-modular hub genes are numbered according to their ranked unweighted connectivity.</p

Graphical visualization of the Arabidopsis co-expression network.

<p>(A) Dendrogram of all differentially expressed probesets clustered based on a dissimilarity measure (1—TOM). Each line of the dendrogram corresponds to a probeset. The first multi-color bar below the dendrogram shows the 205 modules identified using the dynamic cutting method with each gene color-coded based on module assignment. The second and third multi-color bars highlight the modules enriched (<i>P</i>-value < 0.01) in molecular function (MF) and biological process (BP) GO terms. Each line corresponds to genes in modules enriched in GO terms, while line colors identify module membership. Module gene members are not always adjacent to each other because WGCNA modules do not comprise only leaves with their direct ancestors. (<b>B</b>) Circular tree showing hierarchical clustering of the 205 module eigengenes. Modules that are enriched in genes associated with hormones (ET: ethylene, JA: jasmonic acid, SA: salicylic acid, and ABA: abscisic acid) and that are part of higher-order (meta) modules discussed in the text are highlighted. (<b>C</b>) Hierarchical cluster tree showing the relationship between the TOOL, LTDL, and LT meta-modules based on correlations between their respective eigengenes. Hormone enrichment is also depicted in the tree.</p

Additional file 1: Table S1. of A new polymorphism on chromosome 6 associated with bolting tendency in sugar beet

Information on 192 SNPs used in the study. (XLSX 37 kb

Additional file 2: Table S2. of A new polymorphism on chromosome 6 associated with bolting tendency in sugar beet

Sequences of the designed primers and TaqMan probes for detection of the SNP183. (DOC 28 kb

Scrophularia buergeriana Miq.

原著和名: ゴマノハグサ科名: ゴマノハグサ科 = Scrophulariaceae採集地: 埼玉県 北埼玉郡 北川辺町 伊賀袋 (埼玉県 北埼玉郡 北川辺町 伊賀袋)採集日: 1991/7/4採集者: 古瀬 義整理番号: JH027336国立科学博物館整理番号: TNS-VS-97733

Data_Sheet_1_Molecular Profiling of Pierce’s Disease Outlines the Response Circuitry of Vitis vinifera to Xylella fastidiosa Infection.XLSX

<p>Pierce’s disease is a major threat to grapevines caused by the bacterium Xylella fastidiosa. Although devoid of a type 3 secretion system commonly employed by bacterial pathogens to deliver effectors inside host cells, this pathogen is able to influence host parenchymal cells from the xylem lumen by secreting a battery of hydrolytic enzymes. Defining the cellular and biochemical changes induced during disease can foster the development of novel therapeutic strategies aimed at reducing the pathogen fitness and increasing plant health. To this end, we investigated the transcriptional, proteomic, and metabolomic responses of diseased Vitis vinifera compared to healthy plants. We found that several antioxidant strategies were induced, including the accumulation of gamma-aminobutyric acid (GABA) and polyamine metabolism, as well as iron and copper chelation, but these were insufficient to protect the plant from chronic oxidative stress and disease symptom development. Notable upregulation of phytoalexins, pathogenesis-related proteins, and various aromatic acid metabolites was part of the host responses observed. Moreover, upregulation of various cell wall modification enzymes followed the proliferation of the pathogen within xylem vessels, consistent with the intensive thickening of vessels’ secondary walls observed by magnetic resonance imaging. By interpreting the molecular profile changes taking place in symptomatic tissues, we report a set of molecular markers that can be further explored to aid in disease detection, breeding for resistance, and developing therapeutics.</p