Abstract
Despite being a highly studied model organism, most genes of the cyanobacterium Synechocystis sp. PCC 6803 encode proteins with completely unknown function. To facilitate studies of gene regulation in Synechocystis, we have developed Synergy (http://synergy.plantgenie.org), a web application integrating co-expression networks and regulatory motif analysis. Co-expression networks were inferred from publicly available microarray experiments, while regulatory motifs were identified using a phylogenetic footprinting approach. Automatically discovered motifs were shown to be enriched in the network neighborhoods of regulatory proteins much more often than in the neighborhoods of non-regulatory genes, showing that the data provide a sound starting point for studying gene regulation in Synechocystis. Concordantly, we provide several case studies demonstrating that Synergy can be used to find biologically relevant regulatory mechanisms in Synechocystis. Synergy can be used to interactively perform analyses such as gene/motif search, network visualization and motif/function enrichment. Considering the importance of Synechocystis for photosynthesis and biofuel research, we believe that Synergy will become a valuable resource to the research community.
Highlights
Cyanobacteria are the only prokaryotic organisms that produce oxygen in the process of photosynthesis, and are the ancestors of higher plant chloroplasts
The popularity of the cyanobacteria phylum in photosynthesis and biotechnology research is reflected in the high number of sequenced cyanobacterial genomes available in Cyanobase [5] and other public databases [6]
This tool comprises a vast set of experimental data, and integrates microarray data obtained with different experimental platforms, its use is restricted to the visualization and analysis of gene expression clusters
Summary
Cyanobacteria are the only prokaryotic organisms that produce oxygen in the process of photosynthesis, and are the ancestors of higher plant chloroplasts. Light response in Synechocystis has been studied using gene co-expression networks [8,9,10] While these studies give insight into how cells react to single modifications, only the integration of multiple transcriptome data sets will allow a holistic understanding of the cellular response. The first meta-analysis of transcriptomics data in Synechocystis used a co-expression network inferred from 163 different environmental and genetic perturbations to identify a large number of genes (referred to as the Core Transcriptional Response) that are commonly regulated under most perturbations [9]. We have developed Synergy, a web resource for exploring Synechocystis gene regulation, which integrates co-expression network analysis with motif analysis. Considering the importance of Synechocystis as a model organism in biofuel production [2] and photosynthetic research [12, 13], we believe Synergy will become a valuable resource to many researchers
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