In prokaryotic organisms, a substantial fraction of adjacent genes are organized into operons-codirectionally organized genes in prokaryotic genomes with the presence of a common promoter and terminator. Although several available operon databases provide information with varying levels of reliability, very few resources provide experimentally supported results. Researchers at Indiana University believed that the biological community could benefit from having a new operon prediction database with operons predicted using next-generation RNA-seq datasets.
The researchers have created operomeDB, a database which provides an ensemble of all the predicted operons for bacterial genomes using available RNA-sequencing datasets across a wide range of experimental conditions. Although several studies have recently confirmed that prokaryotic operon structure is dynamic with significant alterations across environmental and experimental conditions, there are no comprehensive databases for studying such variations across prokaryotic transcriptomes. Currently this database contains nine bacterial organisms and 168 transcriptomes for which we predicted operons. User interface is simple and easy to use, in terms of visualization, downloading, and querying of data. In addition, because of its ability to load custom datasets, users can also compare their datasets with publicly available transcriptomic data of an organism.
Screenshot showing the selection of an operon in the operons track. Highlighted is the ecpBCDE operon in Escherichia coli K-12 genome encoding for the membrane and fimbria formation proteins. This view provides the name (database generated ID), position, type, and length of the operon. It also gives information such as the number of genes present in the operon and sequence of the region for the selected operon.
Availability – OperomeDB can be accessed at: http://sysbio.informatics.iupui.edu/operomeDB/#/