RegCyanoDB: a database of regulatory interactions in cyanobacteria

Abstract

AbstractBackgroundCyanobacteria are photoautotrophic organisms with environmental, evolutionary, and industrial importance. Knowledge of its regulatory interactions are important to predict, optimise, and engineer their characteristics. However, at present, very few of their regulatory interactions are known. The regulatory interactions are known only for a few model organisms such as Escherichia coli due to technical and economical constraints, which are unlikely to change soon. Thus, mapping of regulatory interactions from well-studied organisms to less-studied organisms by using computational techniques is widely used. Reverse Best Hit (RBH), with appropriate algorithm parameters, is a simple and efficient method for detecting functional homologs.DescriptionWe predict the regulatory interactions in 30 strains of cyanobacteria using the known regulatory interactions from the best-studied organism, E. coli. RBH method with appropriate parameters is used to identify the functional homologs. An interaction is mapped to a cyanobacterial strain if functional homologs exist for a known transcription factor and its target gene. The confidence of the detected homologs and interactions are also provided. Since RBH is a conservative method, homolog-grouping is performed to recover lost putative interactions. A database of the predicted interactions from all the 30 strains of cyanobacteria is constructed.ConclusionRegcyanoDB contains 20,280 interactions with confidence levels for 30 cyanobacterial strains. The predicted regulatory interactions exhibit a scale free network topology as observed in model organisms. The interacting genes in E. coli and cyanobacteria are mostly found to have the same gene annotation. This database can be used for posing novel hypotheses and validation studies in wet-lab and computational domains.The database is available at http://www.che.iitb.ac.in/grn/RegCyanoDB/