γBOriS: Identification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning

Abstract

The biology of bacterial cells is, in general, based on the information encoded on circular chromosomes. Regulation of chromosome replication is an essential process which mostly takes place at the origin of replication (oriC). Identification of high numbers of oriC is a prerequisite to enable systematic studies that could lead to insights of oriC functioning as well as novel drug targets for antibiotic development. Current methods for identyfing oriC sequences rely on chromosome-wide nucleotide disparities and are therefore limited to fully sequenced genomes, leaving a superabundance of genomic fragments unstudied. Here, we present γBOriS (Gammaproteobacterial oriCSearcher), which accurately identifies oriC sequences on gammaproteobacterial chromosomal fragments by employing motif-based DNA classification. Using γBOriS, we created BOriS DB, which currently contains 25,827 oriC sequences from 1,217 species, thus making it the largest available database for oriC sequences to date.

Integrating LASSO Feature Selection and Soft Voting Classifier to Identify Origins of Replication Sites

“…For prokaryotic ORIs, an Ori-Finder system based on Z-curve method is constructed by Gao et al [ 10 , 11 ] to identify ORIs in bacterial and archaea genomes. Subsequently, a method based on motif [ 12 ] was proposed to identify the ORIs in Gammaproteobacteria. Based on the accumulation of experimental biological data, a recent review has summarized the development of computational methods for the identification of eukaryotic ORIs [ 13 ].…”