Author:
Ferreira William,Lanes Gabriel,Azevedo Vasco,Santos Anderson
Abstract
AbstractMotivationBacterial genomes are being deposited into online databases at an increasing rate. Genome annotation represents one of the first efforts to understand organisms and their diseases. Some evolutionary relationships that are capable of being annotated only from genomes are conserved gene neighbourhoods (CNs), phylogenetic profiles (PPs), and gene fusions. At present, there is no standalone software that enables networks of interactions among proteins to be created using these three evolutionary characteristics with efficient and effective results.ResultsWe developed GENPPI software for the ab initio prediction of interaction networks using predicted proteins from a genome. In our case study, we employed 50 genomes of the genus Corynebacterium. Based on the PP relationship, GENPPI differentiated genomes between the ovis and equi biovars of the species Corynebacterium pseudotuberculosis and created groups among the other species analysed. If we inspected only the CN relationship, we could not entirely separate biovars, only species. Our software GENPPI was determined to be efficient because, for example, it creates interaction networks from the central genomes of 50 species/lineages with an average size of 2200 genes in less than 40 minutes on a conventional computer. Our software is compelling because the interaction networks that it creates reflect evolutionary relationships among species and were obtained in average nucleotide identity (ANI) analyses. Additionally, this software enables the user to define how he or she intends to explore the PP and CN characteristics through various parameters, enabling the creation of customized interaction networks. For instance, users can set parameters regarding the genus, metagenome, or pangenome. In addition to the parameterization of GENPPI, it is also the user’s choice regarding which set of genomes he or she is going to study.AvailabilityThe source code in the Common Lisp language, binary files for different operating systems, and GENPPI software tutorials are available at {{github.com/santosardr/genppi}}.Contactsantosardr@ufu.brSupplementary informationSupplementary data are available at Bioinformatics online.
Publisher
Cold Spring Harbor Laboratory