title: Synergy: a web resource for exploring gene regulation in Synechocystis sp. PCC6803.
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.
authors.affiliation: Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway.
authors.forename: Niklas
authors.initials: N
authors.lastname: Mähler
authors.affiliation: Department of Chemistry, Umeå University, Umeå, Sweden.
authors.forename: Otilia
authors.initials: O
authors.lastname: Cheregi
authors.affiliation: Department of Chemistry, Umeå University, Umeå, Sweden; Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden.
authors.forename: Christiane
authors.initials: C
authors.lastname: Funk
authors.affiliation: Department of Chemistry, Umeå University, Umeå, Sweden; Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden; Computational Life Science Cluster, Umeå University, Umeå, Sweden.
authors.forename: Sergiu
authors.initials: S
authors.lastname: Netotea
authors.affiliation: Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Ås, Norway; Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, Umeå, Sweden.
authors.forename: Torgeir R
authors.initials: TR
authors.lastname: Hvidsten
mesh_terms: D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D063990:Gene Ontology; D053263:Gene Regulatory Networks; D005798:Genes, Bacterial / Q000235:genetics; D020407:Internet; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D010802:Phylogeny; D015203:Reproducibility of Results; D046939:Synechocystis / Q000145:classification / Q000235:genetics*