YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia

Abstract

BackgroundYersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity.DescriptionTo facilitate the ongoing and future research of Yersinia, especially those generally considered non-pathogenic species, a well-defined repository and analysis platform is needed to hold the Yersinia genomic data and analysis tools for the Yersinia research community. Hence, we have developed the YersiniaBase, a robust and user-friendly Yersinia resource and analysis platform for the analysis of Yersinia genomic data. YersiniaBase has a total of twelve species and 232 genome sequences, of which the majority are Yersinia pestis. In order to smooth the process of searching genomic data in a large database, we implemented an Asynchronous JavaScript and XML (AJAX)-based real-time searching system in YersiniaBase. Besides incorporating existing tools, which include JavaScript-based genome browser (JBrowse) and Basic Local Alignment Search Tool (BLAST), YersiniaBase also has in-house developed tools: (1) Pairwise Genome Comparison tool (PGC) for comparing two user-selected genomes; (2) Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomics analysis of Yersinia genomes; (3) YersiniaTree for constructing phylogenetic tree of Yersinia. We ran analyses based on the tools and genomic data in YersiniaBase and the preliminary results showed differences in virulence genes found in Yersinia pestis and Yersinia pseudotuberculosis compared to other Yersinia species, and differences between Yersinia enterocolitica subsp. enterocolitica and Yersinia enterocolitica subsp. palearctica.ConclusionsYersiniaBase offers free access to wide range of genomic data and analysis tools for the analysis of Yersinia. YersiniaBase can be accessed at http://yersinia.um.edu.my.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-014-0422-y) contains supplementary material, which is available to authorized users.

Occurrence and Genetic Correlations of Yersinia spp. Isolated from Commensal Rodents in Northeastern Poland

“…The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Maximum Composite Likelihood method [29] and are in the units of the number of base substitutions per site. This analysis involved 44 nucleotide sequences.…”

Draft Genome Sequences of Yersinia frederiksenii, Yersinia intermedia, and Yersinia kristensenii Strains from Brazil

“…The genomes ranged between 4.8 and 5.0 Mb in size for Yersinia frederiksenii , between 4.9 and 5.1 Mb in size for Yersinia intermedia , and between 4.6 and 4.8 Mb in size for Yersinia kristensenii , as described for Yersinia spp. (3.7 Mb to greater than 5.0 Mb) ( 11 ). The number of contigs per assembly for each isolate ranged between 78 and 145.…”

Prevention and Control of Pathogens Based on Big-Data Mining and Visualization Analysis

“…At present, many deficiencies exist in relevant studies: studies on just one specific genus or species of pathogenic bacteria (Ang et al, 2014;Choo et al, 2014a;Choo et al, 2014b;Heydari et al, 2014a;Heydari et al, 2014b;Tan et al, 2015), or studies focusing totally on micro-organisms (such as bacteria) (Marcos et al, 2006;Uchiyama, 2007). So thus far, the depth and precision of data mining has not met the tailored needs of scientific research and clinical practice.…”