Microbial genomic island discovery, visualization and analysis.

Détails

ID Serval
serval:BIB_EC3F894F1720
Type
Article: article d'un périodique ou d'un magazine.
Sous-type
Synthèse (review): revue aussi complète que possible des connaissances sur un sujet, rédigée à partir de l'analyse exhaustive des travaux publiés.
Collection
Publications
Titre
Microbial genomic island discovery, visualization and analysis.
Périodique
Briefings in bioinformatics
Auteur⸱e⸱s
Bertelli C., Tilley K.E., Brinkman FSL
ISSN
1477-4054 (Electronic)
ISSN-L
1467-5463
Statut éditorial
Publié
Date de publication
27/09/2019
Peer-reviewed
Oui
Volume
20
Numéro
5
Pages
1685-1698
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Résumé
Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale analyses of microbial genomes increases, such as for genomic epidemiology investigations of infectious disease outbreaks in public health, there is increased appreciation of the need to accurately predict and track GIs. Over the past decade, numerous computational tools have been developed to tackle the challenges inherent in accurate GI prediction. We review here the main types of GI prediction methods and discuss their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing. An assessment is provided of 20 GI prediction software methods that use sequence-composition bias to identify the GIs, using a reference GI data set from 104 genomes obtained using an independent comparative genomics approach. Finally, we present guidelines to assist researchers in effectively identifying these key genomic regions.
Mots-clé
antimicrobial resistance, genomic island, horizontal gene transfer, interactive visualization, microbial genomics
Pubmed
Web of science
Open Access
Oui
Création de la notice
06/03/2019 23:18
Dernière modification de la notice
10/02/2020 17:39
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