CodaChrome: a tool for the visualization of proteome conservation across all fully sequenced bacterial genomes

PanViz: interactive visualization of the structure of functionally annotated pangenomes

Summary

PanViz is a novel, interactive, visualization tool for pangenome analysis. PanViz allows visualization of changes in gene group (groups of similar genes across genomes) classification as different subsets of pangenomes are selected, as well as comparisons of individual genomes to pangenomes with gene ontology based navigation of gene groups. Furthermore it allows for rich and complex visual querying of gene groups in the pangenome. PanViz visualizations require no external programs and are easily sharable, allowing for rapid pangenome analyses.

Availability and Implementation

PanViz is written entirely in JavaScript and is available on https://github.com/thomasp85/PanViz . A companion R package that facilitates the creation of PanViz visualizations from a range of data formats is released through Bioconductor and is available at https://bioconductor.org/packages/PanVizGenerator .

Contact

thomasp85@gmail.com.

Supplementary information

Supplementary data are available at Bioinformatics online.

Visualization of consensus genome structure without using a reference genome

BACKGROUND

Standard graphical tools for whole genome comparison require a reference genome. However, any reference is also subject to annotation biases and rearrangements, and may not serve as the standard except for those of extensively studied model species. To fully exploit the rapidly accumulating sequence data from the recent sequencing technologies, genome comparison without any reference has been anticipated.

RESULTS

We introduce a circular genome visualizer to compare complete genomes of closely related species. This tool visualizes the position of orthologous gene clusters rather than actual sequences or their features, thereby achieving the comparative view without using a single reference genome. The essential information is the matrix of orthologous gene clusters whose positions (not sequences) are color-coded in circular graphics. As a demonstration, comparison of 14 Lactobacillus paracasei strains and one L. casei strain revealed not only large-scale rearrangements but also genomic islands that are strain-specific. Comparison of 73 Helicobacter pylori strains confirmed their genetic consistency and also revealed the three general patterns of large-scale genome inversions.

CONCLUSIONS

From the ample sequence information in the GenBank/ENA/DDBJ repository, we can reconstruct a genomic consensus for particular species. By visualizing multiple strains at a glance, we can identify conserved as well as strain-specific regions in multiply sequenced genomes. Positional consistency for orthologous genes provides information orthogonal to major sequence features such as the GC content or sequence similarity of marker genes. The positional comparison is therefore useful for identifying large-scale genome rearrangements or gene transfers.

Rice-Infecting Pseudomonas Genomes Are Highly Accessorized and Harbor Multiple Putative Virulence Mechanisms to Cause Sheath Brown Rot

Sheath rot complex and seed discoloration in rice involve a number of pathogenic bacteria that cannot be associated with distinctive symptoms. These pathogens can easily travel on asymptomatic seeds and therefore represent a threat to rice cropping systems. Among the rice-infecting Pseudomonas, P. fuscovaginae has been associated with sheath brown rot disease in several rice growing areas around the world. The appearance of a similar Pseudomonas population, which here we named P. fuscovaginae-like, represents a perfect opportunity to understand common genomic features that can explain the infection mechanism in rice. We showed that the novel population is indeed closely related to P. fuscovaginae. A comparative genomics approach on eight rice-infecting Pseudomonas revealed heterogeneous genomes and a high number of strain-specific genes. The genomes of P. fuscovaginae-like harbor four secretion systems (Type I, II, III, and VI) and other important pathogenicity machinery that could probably facilitate rice colonization. We identified 123 core secreted proteins, most of which have strong signatures of positive selection suggesting functional adaptation. Transcript accumulation of putative pathogenicity-related genes during rice colonization revealed a concerted virulence mechanism. The study suggests that rice-infecting Pseudomonas causing sheath brown rot are intrinsically diverse and maintain a variable set of metabolic capabilities as a potential strategy to occupy a range of environments.