Whole-genome sequence analysis through online web interfaces: a review

Abstract

The recent development of whole-genome sequencing technologies paved the way for understanding the genomes of microorganisms. Every whole-genome sequencing (WGS) project requires a considerable cost and a massive effort to address the questions at hand. The final step of WGS is data analysis. The analysis of whole-genome sequence is dependent on highly sophisticated bioinformatics tools that the research personal have to buy. However, many laboratories and research institutions do not have the bioinformatics capabilities to analyze the genomic data and therefore, are unable to take maximum advantage of whole-genome sequencing. In this aspect, this study provides a guide for research personals on a set of bioinformatics tools available online that can be used to analyze whole-genome sequence data of bacterial genomes. The web interfaces described here have many advantages and, in most cases exempting the need for costly analysis tools and intensive computing resources.

Keywords: average nucleotide identitys; online web servers; single nucleotide polymorphisms; virulence factors; whole-genome sequencing.

Fig. 1.

General overview of high throughput sequencing workflow of a bacterial genome. Following genome assembly, online web interfaces can be utilized for the purpose of analyzing WGS. MLST, multilocus sequence typing; WGS, whole-genome sequencing.

Fig. 2.

General subsystem features and KEGG pathway of drug metabolism of Vibrio parahaemolyticus 3HP_AHPND genome through RAST server (Different colors in the subsystem category distribution indicates different subsystem features whereas KEGG pathway indicates the functions for V. parahaemolyticus 3HP_AHPND genome). KEGG, Kyoto Encyclopedia of Genes and Genomes.

Fig. 3.

CGE server workflow of classical MLST typing and SNP calling on selected Vibrio parahaemolyticus genomes. (A) Clinical V. parahaemolyticus genome RIMD 221063 was used as a reference for SNP calling. (B) The V. parahaemolyticus 3HP_AHPND genome was used for the in silco MLST analysis. MLST, multilocus sequence typing; SNP, single nucleotide polymorphism.

Fig. 4.

(A) The cano-wgMLST server workflow of wgMLST phylogeny and identification of highly discriminatory genes on 5 Vibrio parahaemolyticus genomes. (B) JSpeciesWS server workflow of ANI among 5 Vibrio parahaemolyticus genomes. ANI, average nucleotide identity; wgMLST, whole-genome multilocus sequence typing.

Fig. 5.

(A) Virulence factor analysis workflow of VFDB server. (B) Prophage analysis workflow of PHASTER server. (C) Cluster of orthologous group (COG) analysis workflow of WebMGA server. Vibrio parahaemolyticus genome 3HP_AHPND was used as a reference for all the applications.

Fig. 6.

Graphical illustration of chromosome I for 5 Vibrio parahaemolyticus genomes by GView server. Different colors in the genome map indicate different genomes. Clinical Vibrio parahaemolyticus genome RIMD 221063 was used as the reference for the genomic mapping.