The chitinolytic activity of the Curtobacterium sp. isolated from field-grown soybean and analysis of its genome sequence

Curtobacterium sp. GD1 was isolated from leaves of conventionally grown soybean in Brazil. It was noteworthy that among all bacteria previously isolated from the same origin, only Curtobacterium sp. GD1 showed a strong chitinase activity. The enzyme was secreted and its production was induced by the presence of colloidal chitin in the medium. The chitinase was partially purified and characterized: molecular weight was approximately 37 kDa and specific activity 90.8 U/mg. Furthermore, Curtobacterium sp. GD1 genome was sequenced and analyzed. Our isolate formed a phylogenetic cluster with four other Curtobacterium spp. strains, with ANIb/ANIm ≥ 98%, representing a new, still non described Curtobacterium species. The circular genome visualization and comparison of genome sequences of strains forming new cluster indicated that most regions within their genomes were highly conserved. The gene associated with chitinase production was identified and the distribution pattern of glycosyl hydrolases genes was assessed. Also, genes associated with catabolism of structural carbohydrates such as oligosaccharides, mixed polysaccharides, plant and animal polysaccharides, as well as genes or gene clusters associated with resistance to antibiotics, toxic compounds and auxin biosynthesis subsystem products were identified. The abundance of putative glycosyl hydrolases in the genome of Curtobacterium sp. GD1 suggests that it has the tools for the hydrolysis of different polysaccharides. Therefore, Curtobacterium sp. GD1 isolated from soybean might be a bioremediator, biocontrol agent, an elicitor of the plant defense responses or simply degrader.

GCViT: a method for interactive, genome-wide visualization of resequencing and SNP array data

Background Large genotyping datasets have become commonplace due to efficient, cheap methods for SNP identification. Typical genotyping datasets may have thousands to millions of data points per accession, across tens to thousands of accessions. There is a need for tools to help rapidly explore such datasets, to assess characteristics such as overall differences between accessions and regional anomalies across the genome. Results We present GCViT (Genotype Comparison Visualization Tool), for visualizing and exploring large genotyping datasets. GCViT can be used to identify introgressions, conserved or divergent genomic regions, pedigrees, and other features for more detailed exploration. The program can be used online or as a local instance for whole genome visualization of resequencing or SNP array data. The program performs comparisons of variants among user-selected accessions to identify allele differences and similarities between accessions and a user-selected reference, providing visualizations through histogram, heatmap, or haplotype views. The resulting analyses and images can be exported in various formats. Conclusions GCViT provides methods for interactively visualizing SNP data on a whole genome scale, and can produce publication-ready figures. It can be used in online or local installations. GCViT enables users to confirm or identify genomics regions of interest associated with particular traits. GCViT is freely available at https://github.com/LegumeFederation/gcvit. The 1.0 version described here is available at 10.5281/zenodo.4008713.

NG-Circos: next-generation Circos for data visualization and interpretation

Circos plots are widely used to display multi-dimensional next-generation genomic data, but existing implementations of Circos are not interactive with limited support of data types. Here, we developed next-generation Circos (NG-Circos), a flexible JavaScript-based circular genome visualization tool for designing highly interactive Circos plots using 21 functional modules with various data types. To our knowledge, NG-Circos is the most powerful software to construct interactive Circos plots. By supporting diverse data types in a dynamic browser interface, NG-Circos will accelerate the next-generation data visualization and interpretation, thus promoting the reproducible research in biomedical sciences and beyond. NG-Circos is available at https://wlcb.oit.uci.edu/NG-Circos and https://github.com/YaCui/NG-Circos.

SEA version 3.0: a comprehensive extension and update of the Super-Enhancer archive

Super-enhancers (SEs) are critical for the transcriptional regulation of gene expression. We developed the super-enhancer archive version 3.0 (SEA v. 3.0, http://sea.edbc.org) to extend SE research. SEA v. 3.0 provides the most comprehensive archive to date, consisting of 164 545 super-enhancers. Of these, 80 549 are newly identified from 266 cell types/tissues/diseases using an optimized computational strategy, and 52 have been experimentally confirmed with manually curated references. We now support super-enhancers in 11 species including 7 new species (zebrafish, chicken, chimp, rhesus, sheep, Xenopus tropicalis and stickleback). To facilitate super-enhancer functional analysis, we added several new regulatory datasets including 3 361 785 typical enhancers, chromatin interactions, SNPs, transcription factor binding sites and SpCas9 target sites. We also updated or developed new criteria query, genome visualization and analysis tools for the archive. This includes a tool based on Shannon Entropy to evaluate SE cell type specificity, a new genome browser that enables the visualization of SE spatial interactions based on Hi-C data, and an enhanced enrichment analysis interface that provides online enrichment analyses of SE related genes. SEA v. 3.0 provides a comprehensive database of all available SE information across multiple species, and will facilitate super-enhancer research, especially as related to development and disease.

Transcriptome visualization and data availability at the Saccharomyces Genome Database

The Saccharomyces Genome Database (SGD; www.yeastgenome.org) maintains the official annotation of all genes in the Saccharomyces cerevisiae reference genome and aims to elucidate the function of these genes and their products by integrating manually curated experimental data. Technological advances have allowed researchers to profile RNA expression and identify transcripts at high resolution. These data can be configured in web-based genome browser applications for display to the general public. Accordingly, SGD has incorporated published transcript isoform data in our instance of JBrowse, a genome visualization platform. This resource will help clarify S. cerevisiae biological processes by furthering studies of transcriptional regulation, untranslated regions, genome engineering, and expression quantification in S. cerevisiae.

Chromatiblock: scalable whole-genome visualization of structural differences in prokaryotes

SummaryChromatiblock is a Python application for visualizing the presence, absence and arrangement of syntenic blocks across large numbers of complete bacterial genomes.AvailabilityChromatiblock is freely available under a GPL license, for macOS, GNU/Linux and and Microsoft Windows from https://github.com/mjsull/chromatiblock/[email protected]

Overview of Genomic Tools for Circular Visualization in the Nextgeneration Genomic Sequencing Era

After human genome sequencing and rapid changes in genome sequencing methods, we have entered into the era of rapidly accumulating genome-sequencing data. This has derived the development of several types of methods for representing results of genome sequencing data. Circular genome visualization tools are also critical in this area as they provide rapid interpretation and simple visualization of overall data. In the last 15 years, we have seen rapid changes in circular visualization tools after the development of the circos tool with 1-2 tools published per year. Herein we have summarized and revisited all these tools until the third quarter of 2018.

MakeHub: Fully automated generation of UCSC Genome Browser Assembly Hubs

Novel genomes are today often annotated by small consortia or individuals whose background is not from bioinformatics. This audience requires tools that are easy to use. This need had been addressed by several genome annotation tools and pipelines. Visualizing resulting annotation is a crucial step of quality control. The UCSC Genome Browser is a powerful and popular genome visualization tool. Assembly Hubs allow browsing genomes that are hosted locally via already available UCSC Genome Browser servers. The steps for creating custom Assembly Hubs are well documented and the required tools are publicly available. However, the number of steps for creating a novel Assembly Hub is large. In some cases the format of input files needs to be adapted which is a difficult task for scientists without programming background. Here, we describe the novel command line tool MakeHub that generates Assembly Hubs for the UCSC Genome Browser in a fully automated fashion. The pipeline also allows extending previously created Hubs by additional tracks.MakeHub is freely available for download from https://github.com/Gaius-Augustus/[email protected]