iNID: An Analytical Framework for Identifying Network Models for Interplays among Developmental Signaling in Arabidopsis

Abstract

Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involve complex interplays among signaling pathways activated by the internal and external factors (IEFs). However, decoding these complex interplays is still challenging. Here, we present a web-based platform that identifies key regulators and Network models delineating Interplays among Developmental signaling (iNID) in Arabidopsis. iNID provides a comprehensive resource of (1) transcriptomes previously collected under the conditions treated with a broad spectrum of IEFs and (2) protein and genetic interactome data in Arabidopsis. In addition, iNID provides an array of tools for identifying key regulators and network models related to interplays among IEFs using transcriptome and interactome data. To demonstrate the utility of iNID, we investigated the interplays of (1) phytohormones and light and (2) phytohormones and biotic stresses. The results revealed 34 potential regulators of the interplays, some of which have not been reported in association with the interplays, and also network models that delineate the involvement of the 34 regulators in the interplays, providing novel insights into the interplays collectively defined by phytohormones, light, and biotic stresses. We then experimentally verified that BME3 and TEM1, among the selected regulators, are involved in the auxin-brassinosteroid (BR)-blue light interplay. Therefore, iNID serves as a useful tool to provide a basis for understanding interplays among IEFs.

Organelle-targeted biosensors reveal distinct oxidative events during pattern-triggered immune responses

“…TAIR accession numbers of genes coding for antioxidant enzymes were retrieved from ( https://itservices.cas.unt.edu/∼rmittler/genelist.htm ) and their predicted subcellular localization was verified using the TAIR database ( https://www.arabidopsis.org/ ). Heat maps of expression profile were generated using the iNID web interface ( http://omics.sbmlab.com/inid/ ) with default parameters ( Choi et al, 2014 ). The transcriptome data sets analyzed are time-course experiments on the leaves of 5-week-old Arabidopsis plants collected 2, 6, and 24 h after inoculation with the bacterial strains Pst DC3000 and Pst DC3000 hrcC − (ME00331), or 1 and 4 h after treatment with flg22 and lipopolysaccharide (LPS) elicitors (GSE5615).…”

DiNAR: revealing hidden patterns of plant signalling dynamics using Differential Network Analysis in R

“…significance, node weight, min.node degree, cluster/gene IDInteractive: dynamic & static; log, TSV, GraphML YES AIM [3]OnlineStatic database NAp NO NAp ND ND NO CyLineUp [4]Cytoscape 3 pluginNoninteractive staticCytoscape YES NO Stat. significance (p value)Noninteractive static YES DyNet [5]Cytoscape 3 pluginSemi-interactive staticCondition specific NO YES (heatmap) ND Noninteractive static YES DyNetviewer [6]Cytoscape 3 pluginCoarse dynamictext YES YES Gene expression, SDText YES Diffany [7]Cytoscape 3 pluginNoninteractive staticCytoscape NO NO Edge weightNoninteractive static YES PCSF [8]R packageInteractive staticEdge list YES YES Functional enrichmentIgraph YES iNID [9]OnlineStatic NAp YES YES p values logFC ND NO exp. experimental, NAp not applicable, ND not possible to determine, SD standard deviation, technical operability accesibility at the time of testing, TSV tab separated values…”

“…Few solutions combining background knowledge and network analysis to enable visualisation of experimental data have so far been implemented in this area [3–9]. We developed an application to extend existing tools and further facilitate biological insight into dynamic rewiring events.…”

Gene duplication of type-B ARR transcription factors systematically extends transcriptional regulatory structures in Arabidopsis

“…Hormone-related genes are defined as the ones annotated with at least one of the following terms: for example, in the case of cytokinin, ‘response to cytokinin', ‘cytokinin biosynthetic process', ‘cytokinin metabolic process', ‘cytokinin transport', and ‘cytokinin-activated signaling pathway'. We then constructed the seven hormone signaling networks with those hormone-related genes based on KEGG pathway 35 , Science Signaling 36 37 38 , iNID 39 , and previous literatures 25 26 40 41 42 .…”

“…To identify hub-like molecules, we first calculated the number of interactors (degree) for each protein using PPIs in iNID 39 . We then estimated the empirical distribution of the degree by randomly sampling 100,000 proteins from the whole annotated proteins.…”