The advent of NGS (Next Generation Sequencing) technologies has resulted in an exponential increase in the number of complete genomes available in biological databases. This advance has allowed the development of several computational tools enabling analyses of large amounts of data in each of the various steps, from processing and quality filtering to gap filling and manual curation. The tools developed for gap closure are very useful as they result in more complete genomes, which will influence downstream analyses of genomic plasticity and comparative genomics. However, the gap filling step remains a challenge for genome assembly, often requiring manual intervention. Here, we present GapBlaster, a graphical application to evaluate and close gaps. GapBlaster was developed via Java programming language. The software uses contigs obtained in the assembly of the genome to perform an alignment against a draft of the genome/scaffold, using BLAST or Mummer to close gaps. Then, all identified alignments of contigs that extend through the gaps in the draft sequence are presented to the user for further evaluation via the GapBlaster graphical interface. GapBlaster presents significant results compared to other similar software and has the advantage of offering a graphical interface for manual curation of the gaps. GapBlaster program, the user guide and the test datasets are freely available at https://sourceforge.net/projects/gapblaster2015/. It requires Sun JDK 8 and Blast or Mummer.

With increased production of genomic data since the advent of next-generation sequencing (NGS), there has been a need to develop new bioinformatics tools and areas, such as comparative genomics. In comparative genomics, the genetic material of an organism is directly compared to that of another organism to better understand biological species. Moreover, the exponentially growing number of deposited prokaryote genomes has enabled the investigation of several genomic characteristics that are intrinsic to certain species. Thus, a new approach to comparative genomics, termed pan-genomics, was developed. In pan-genomics, various organisms of the same species or genus are compared. Currently, there are many tools that can perform pan-genomic analyses, such as PGAP (Pan-Genome Analysis Pipeline), Panseq (Pan-Genome Sequence Analysis Program) and PGAT (Prokaryotic Genome Analysis Tool). Among these software tools, PGAP was developed in the Perl scripting language and its reliance on UNIX platform terminals and its requirement for an extensive parameterized command line can become a problem for users without previous computational knowledge. Thus, the aim of this study was to develop a web application, known as PanWeb, that serves as a graphical interface for PGAP. In addition, using the output files of the PGAP pipeline, the application generates graphics using custom-developed scripts in the R programming language. PanWeb is freely available at http://www. computationalbiology.ufpa.br/panweb.

Seven genomes of Corynebacterium pseudotuberculosis biovar equi were sequenced on the Ion Torrent PGM platform, generating high-quality scaffolds over 2.35 Mbp. This bacterium is the causative agent of disease known as “pigeon fever” which commonly affects horses worldwide. The pangenome of biovar equi was calculated and two phylogenomic approaches were used to identify clustering patterns within Corynebacterium genus. Furthermore, other comparative analyses were performed including the prediction of genomic islands and prophages, and SNP-based phylogeny. In the phylogenomic tree, C. pseudotuberculosis was divided into two distinct clades, one formed by nitrate non-reducing species (biovar ovis) and another formed by nitrate-reducing species (biovar equi). In the latter group, the strains isolated from California were more related to each other, while the strains CIP 52.97 and 1/06-A formed the outermost clade of the biovar equi. A total of 1,355 core genes were identified, corresponding to 42.5% of the pangenome. This pangenome has one of the smallest core genomes described in the literature, suggesting a high genetic variability of biovar equi of C. pseudotuberculosis. The analysis of the similarity between the resistance islands identified a higher proximity between the strains that caused more severe infectious conditions (infection in the internal organs). Pathogenicity islands were largely conserved between strains. Several genes that modulate the pathogenicity of C. pseudotuberculosis were described including peptidases, recombination enzymes, micoside synthesis enzymes, bacteriocins with antimicrobial activity and several others. Finally, no genotypic differences were observed between the strains that caused the three different types of infection (external abscess formation, infection with abscess formation in the internal organs, and ulcerative lymphangitis). Instead, it was noted that there is a higher phenetic correlation between strains isolated at California compared to the other strains. Additionally, high variability of resistance islands suggests gene acquisition through several events of horizontal gene transfer.

The Next-Generation Sequencing (NGS) platforms provide a major approach to obtaining millions of short reads from samples. NGS has been used in a wide range of analyses, such as for determining genome sequences, analyzing evolutionary processes, identifying gene expression and resolving metagenomic analyses. Usually, the quality of NGS data impacts the final study conclusions. Moreover, quality assessment is generally considered the first step in data analyses to ensure the use of only reliable reads for further studies. In NGS platforms, the presence of duplicated reads (redundancy) that are usually introduced during library sequencing is a major issue. These might have a serious impact on research application, as redundancies in reads can lead to difficulties in subsequent analysis (e.g., de novo genome assembly). Herein, we present NGSReadsTreatment, a computational tool for the removal of duplicated reads in paired-end or single-end datasets. NGSReadsTreatment can handle reads from any platform with the same or different sequence lengths. Using the probabilistic structure Cuckoo Filter, the redundant reads are identified and removed by comparing the reads with themselves. Thus, no prerequisite is required beyond the set of reads. NGSReadsTreatment was compared with other redundancy removal tools in analyzing different sets of reads. The results demonstrated that NGSReadsTreatment was better than the other tools in both the amount of redundancies removed and the use of computational memory for all analyses performed. Available in https://sourceforge.net/projects/ngsreadstreatment/ .

Corynebacterium striatum commonly colonizes the normal skin and nasopharyngeal tract of humans; however, this potentially pathogenic bacterium has been identified as the causative agent of several nosocomial infections. The current study describes the draft genome of strain 1961 BR-RJ/09, isolated from the urine of a hospitalized patient from Brazil.