Detecting genomic islands using bioinformatics approaches

  title={Detecting genomic islands using bioinformatics approaches},
  author={Morgan G. I. Langille and William W. L. Hsiao and Fiona S. L. Brinkman},
  journal={Nature Reviews Microbiology},
Bacterial genomes contain clusters of genes that are acquired by horizontal transfer, called genomic islands (GIs). GIs are frequently associated with microbial adaptations that are of medical and environmental interest, and they have had a substantial impact on bacterial evolution. Therefore, there is growing interest in efficiently identifying GIs in newly sequenced bacterial genomes. Several computational methods for detecting GIs have been developed recently, presenting researchers with a… 
Computational methods for predicting genomic islands in microbial genomes
Patterns and architecture of genomic islands in marine bacteria
The results indicate that horizontal gene transfer mediated by phages, plasmids and other mobile genetic elements, and HR by site-specific recombinases play important roles in the mobility of clusters of genes between taxa and within closely related genomes, modulating the flexible pool of the genome.
Microbial genomic island discovery, visualization and analysis
The main types of GI prediction methods are reviewed and their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing are discussed.
Enabling genomic island prediction and comparison in multiple genomes to investigate bacterial evolution and outbreaks.
The developed IslandCompare is an open-source computational pipeline for GI prediction and comparison across several to hundreds of bacterial genomes, and contains a novel blast-based consistency step to improve cross-genome prediction consistency.
A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm
A novel method to predict GIs that is built upon mean shift clustering algorithm that does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach.
An Accurate Genomic Island Prediction Method for Sequenced Bacterialand Archaeal Genomes
The development of Genomic Island Hunter (GIHunter), an accurate software tool for GI detection that uses eight GI-associated features such as sequence composition, mobile gene information, and integrase and is shown to be more accurate than other approaches.
Discovering genomic islands using DNA sequence embedding
This thesis proposes to improve the boundary detection problem of GI by using a boundary fine-tuning method to attain better precision and presents a machine learning-based framework called TreasureIsland, that uses an unsupervised representation of DNA sequences to predict GI.
High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria
A new sliding window method, GIST, Genomic-island Identification by Signals of Transcription, is developed, which demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage.
An Integrative Approach for Genomic Island Prediction in Prokaryotic Genomes
It is reported, for the first time, that gene information and inter-genic distance are different between genomic islands and non-genomic islands, and it is concluded that the incorporation of geneInformation and intergenic distance could improve genomic island prediction accuracy.
EuGI: a novel resource for studying genomic islands to facilitate horizontal gene transfer detection in eukaryotes
The previously developed GI prediction tool, SeqWord Gene Island Sniffer (SWGIS), is modified to predict GIs in eukaryotic chromosomes and the EuGI database, which houses GIs identified in 66 different eUKaryotic species, and theEuGI web-resource, provide the first comprehensive resource for studying HGT in Eukaryotes.


Evaluation of genomic island predictors using a comparative genomics approach
The comparative genomics approach, IslandPick, was the most accurate, compared with a curated list of GIs, indicating that it has constructed suitable datasets, and the accuracy of several sequence composition-based GI predictors is evaluated.
Detection of genomic islands via segmental genome heterogeneity
This work applies an alternative ‘top–down’ approach where bacterial genomes are recursively divided into progressively smaller regions, each with uniform composition, based on a generalized divergence measure to quantify the compositional difference between segments in a hypothesis-testing framework.
The Association of Virulence Factors with Genomic Islands
It is shown quantitatively that GIs disproportionately contain more virulence factors than the rest of a given genome and that CRISPRs are also over-represented in GIs, which cement the significant role of GIs in the evolution of many pathogens.
Common themes in the genome strategies of pathogens.
  • J. Lawrence
  • Biology, Engineering
    Current opinion in genetics & development
  • 2005
Genomic islands in pathogenic and environmental microorganisms
Recent lessons that have been learned from pathogenicity islands in pathogenic microorganisms are discussed and how they apply to the role of genomic islands in commensal, symbiotic and environmental bacteria are discussed.
Evidence of a Large Novel Gene Pool Associated with Prokaryotic Genomic Islands
It is shown that genomic islands are frequently associated with a particular microbial adaptation, such as antibiotic resistance, pathogen virulence, or metal resistance, this suggests that microbes may have access to a larger “arsenal" of novel genes for adaptation than previously thought.
IslandPath: aiding detection of genomic islands in prokaryotes
IslandPath is a network service which incorporates multiple DNA signals and genome annotation features into a graphical display of a bacterial or archaeal genome, to aid the detection of genomic islands.
Detecting pathogenicity islands and anomalous gene clusters by iterative discriminant analysis.
A new computational method for the detection of horizontal gene transfer events
This paper introduces and discusses a novel computational method for identifying horizontal transfers that relies on a gene's nucleotide composition and obviates the need for knowledge of codon boundaries and can be easily extended to the case of clusters of horizontally transferred genes.
Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models
SIGI-HMM is a sensitive tool for the identification of GIs in microbial genomes that allows to interactively analyze genomes in detail and to generate or to test hypotheses about the origin of acquired genes.