Computation Tools for Prediction and Analysis of Genomic Islands

Abstract

The genomic island (GI) is a discrete cluster of genes in prokaryotic genomes acquired through horizontal gene transfer (HGT). GI includes genes having significant roles in genome evolution and adaptation to the changed environment. Genomic islands may be pathogenicity islands (PAIs), metabolic islands (MIs), secretion islands (SIs), symbiotic islands (SymIs), etc., according to the traits they carry. Major characteristics of GIs exhibit are sporadic distribution, large size, sequence composition, inserted adjacent or near to tRNA genes, and mobility genes. Prediction of genomic islands can be performed via experimental and/or computational methods. Sequence composition and comparative genomics are the two major approaches to predict GIs at the level of single genome and related genomes, respectively. Several computational tools have been designed and developed by researchers to predict the presence, type, transmission, and origin of genomic islands. Representatives of window-based programs are AlienHunter, Centroid, INDeGenIUS, Design-Island, and GI-SVM, whereas windowless methods include GC profile and MJSD. Among the available computational predictors GIPSy produced best results followed by Alien_Hunter, IslandViewer, predict Bias, GI Hunter, and Zisland Explorer. Till date except PAIs little information is available about other GIs like REIs, MIs, symbiotic islands, secretary islands, etc. PAIDB, IslandViewer, and InDeGenIUS software partially address these islands and need further exploration.