BACKGROUND: Metagenomics, the sequencing of DNA collected from an entire microbial community, enables the study of natural microbial consortia in their native habitats. Metagenomics studies produce huge volumes of data, including both the sequences themselves and metadata describing their abundance, assembly, predicted functional characteristics and environmental parameters. The ability to explore these data visually is critically important to meaningful biological interpretation. Current genomics applications cannot effectively integrate sequence data, assembly metadata, and annotation to support both genome and community-level inquiry. RESULTS: Elviz (Environmental Laboratory Visualization) is an interactive web-based tool for the visual exploration of assembled metagenomes and their complex metadata. Elviz allows scientists to navigate metagenome assemblies across multiple dimensions and scales, plotting parameters such as GC content, relative abundance, phylogenetic affiliation and assembled contig length. Furthermore Elviz enables interactive exploration using real-time plot navigation, search, filters, axis selection, and the ability to drill from a whole-community profile down to individual gene annotations. Thus scientists engage in a rapid feedback loop of visual pattern identification, hypothesis generation, and hypothesis testing. CONCLUSIONS: Compared to the current alternative of generating a succession of static figures, Elviz can greatly accelerate the speed of metagenome analysis. Elviz can be used to explore both user-submitted datasets and numerous metagenome studies publicly available at the Joint Genome Institute (JGI). Elviz is freely available at http://genome.jgi.doe.gov/viz and runs on most current web-browsers.

UNLABELLED: With the ubiquitous generation of complete genome assemblies for a variety of species, efficient tools for whole-genome alignment along with user-friendly visualization are critically important. Our VISTA family of tools for comparative genomics, based on algorithms for pairwise and multiple alignments of genomic sequences and whole-genome assemblies, has become one of the standard techniques for comparative analysis. Most of the VISTA programs have been implemented as Web-accessible servers and are extensively used by the biomedical community. In this manuscript, we introduce GenomeVISTA: a novel implementation that incorporates most features of the VISTA family--fast and accurate alignment, visualization capabilities, GUI and analytical tools within a stand-alone software package. GenomeVISTA thus provides flexibility and security for users who need to conduct whole-genome comparisons on their own computers. AVAILABILITY AND IMPLEMENTATION: Implemented in Perl, C/C++ and Java, the source code is freely available for download at the VISTA Web site: http://genome.lbl.gov/vista/.

SUMMARY: We have developed a web-based query tool, Whole-Genome rVISTA (WGRV), that determines enrichment of transcription factors (TFs) and associated target genes in sets of co-regulated genes. WGRV enables users to query databases containing pre-computed genome coordinates of evolutionarily conserved transcription factor binding sites in the proximal promoters (from 100 bp to 5 kb upstream) of human, mouse and Drosophila genomes. TF binding sites are based on position-weight matrices from the TRANSFAC Professional database. For a given set of co-regulated genes, WGRV returns statistically enriched and evolutionarily conserved binding sites, mapped by the regulatory VISTA (rVISTA) algorithm. Users can then retrieve a list of genes from the query set containing the enriched TF binding sites and their location in the query set promoters. Results are exported in a BED format for rapid visualization in the UCSC genome browser. Flat files of mapped conserved sites and their genomic coordinates are also available for analysis with stand-alone software. AVAILABILITY: http://genome.lbl.gov/cgi-bin/WGRVistaInputCommon.pl.

SUMMARY: Current genome browsers are designed for linear browsing of individual genomic regions, but the high-throughput nature of experiments aiming to elucidate the genetic component of human disease makes it very important to develop user-friendly tools for comparing several genomic regions in parallel and prioritizing them based on their functional content. We introduce VISTA Region Viewer (RViewer), an interactive online tool that allows for efficient screening and prioritization of regions of the human genome for follow-up studies. The tool takes as input genetic variation data from different biomedical studies, determines a number of various functional parameters for both coding and non-coding sequences in each region and allows for sorting and searching the results of the analysis in multiple ways. AVAILABILITY AND IMPLEMENTATION: The tool is implemented as a web application and is freely accessible on the Web at http://rviewer.lbl.gov CONTACT: [email protected]; [email protected].

UNLABELLED: We describe a general multiplatform exploratory tool called TreeQ-Vista, designed for presenting functional annotations in a phylogenetic context. Traits, such as phenotypic and genomic properties, are interactively queried from a user-provided relational database with a user-friendly interface which provides a set of tools for users with or without SQL knowledge. The query results are projected onto a phylogenetic tree and can be displayed in multiple color groups. A rich set of browsing, grouping and query tools are provided to facilitate trait exploration, comparison and analysis. AVAILABILITY: The program, detailed tutorial and examples are available online (http:/genome.lbl.gov/vista/TreeQVista).

BACKGROUND: Recent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With today's technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at http://genome.lbl.gov/vista/snpvista1. RESULTS: We have developed and present two modifications of an interactive visualization tool, SNP-VISTA, to aid in the analyses of the following types of data: A. Large-scale re-sequence data of disease-related genes for discovery of associated and/or causative alleles (GeneSNP-VISTA). B. Massive amounts of ecogenomics data for studying homologous recombination in microbial populations (EcoSNP-VISTA). The main features and capabilities of SNP-VISTA are: 1) mapping of SNPs to gene structure; 2) classification of SNPs, based on their location in the gene, frequency of occurrence in samples and allele composition; 3) clustering, based on user-defined subsets of SNPs, highlighting haplotypes as well as recombinant sequences; 4) integration of protein evolutionary conservation visualization; and 5) display of automatically calculated recombination points that are user-editable. CONCLUSION: The main strength of SNP-VISTA is its graphical interface and use of visual representations, which support interactive exploration and hence better understanding of large-scale SNP data by the user.

Bacterial response to nitric oxide (NO) is of major importance since NO is an obligatory intermediate of the nitrogen cycle. Transcriptional regulation of the dissimilatory nitric oxides metabolism in bacteria is diverse and involves FNR-like transcription factors HcpR, DNR, and NnrR; two-component systems NarXL and NarQP; NO-responsive activator NorR; and nitrite-sensitive repressor NsrR. Using comparative genomics approaches, we predict DNA-binding motifs for these transcriptional factors and describe corresponding regulons in available bacterial genomes. Within the FNR family of regulators, we observed a correlation of two specificity-determining amino acids and contacting bases in corresponding DNA recognition motif. Highly conserved regulon HcpR for the hybrid cluster protein and some other redox enzymes is present in diverse anaerobic bacteria, including Clostridia, Thermotogales, and delta-proteobacteria. NnrR and DNR control denitrification in alpha- and beta-proteobacteria, respectively. Sigma-54-dependent NorR regulon found in some gamma- and beta-proteobacteria contains various enzymes involved in the NO detoxification. Repressor NsrR, which was previously known to control only nitrite reductase operon in Nitrosomonas spp., appears to be the master regulator of the nitric oxides' metabolism, not only in most gamma- and beta-proteobacteria (including well-studied species such as Escherichia coli), but also in gram-positive Bacillus and Streptomyces species. Positional analysis and comparison of regulatory regions of NO detoxification genes allows us to propose the candidate NsrR-binding motif. The most conserved member of the predicted NsrR regulon is the NO-detoxifying flavohemoglobin Hmp. In enterobacteria, the regulon also includes two nitrite-responsive loci, nipAB (hcp-hcr) and nipC (dnrN), thus confirming the identity of the effector, i.e. nitrite. The proposed NsrR regulons in Neisseria and some other species are extended to include denitrification genes. As the result, we demonstrate considerable interconnection between various nitrogen-oxides-responsive regulatory systems for the denitrification and NO detoxification genes and evolutionary plasticity of this transcriptional network.

MOTIVATION: The power of multi-sequence comparison for biological discovery is well established. The need for new capabilities to visualize and compare cross-species alignment data is intensified by the growing number of genomic sequence datasets being generated for an ever-increasing number of organisms. To be efficient these visualization algorithms must support the ability to accommodate consistently a wide range of evolutionary distances in a comparison framework based upon phylogenetic relationships. RESULTS: We have developed Phylo-VISTA, an interactive tool for analyzing multiple alignments by visualizing a similarity measure for multiple DNA sequences. The complexity of visual presentation is effectively organized using a framework based upon interspecies phylogenetic relationships. The phylogenetic organization supports rapid, user-guided interspecies comparison. To aid in navigation through large sequence datasets, Phylo-VISTA leverages concepts from VISTA that provide a user with the ability to select and view data at varying resolutions. The combination of multiresolution data visualization and analysis, combined with the phylogenetic framework for interspecies comparison, produces a highly flexible and powerful tool for visual data analysis of multiple sequence alignments. AVAILABILITY: Phylo-VISTA is available at http://www-gsd.lbl.gov/phylovista. It requires an Internet browser with Java Plug-in 1.4.2 and it is integrated into the global alignment program LAGAN at http://lagan.stanford.edu

The explosion in genomic sequence available in public databases has resulted in an unprecedented opportunity for computational whole genome analyses. A number of promising comparative-based approaches have been developed for gene finding, regulatory element discovery and other purposes, and it is clear that these tools will play a fundamental role in analysing the enormous amount of new data that is currently being generated. The synthesis of computationally intensive comparative computational approaches with the requirement for whole genome analysis represents both an unprecedented challenge and opportunity for computational scientists. We focus on a few of these challenges, using by way of example the problems of alignment, gene finding and regulatory element discovery, and discuss the issues that have arisen in attempts to solve these problems in the context of whole genome analysis pipelines.

MOTIVATION: Protein fold recognition is an important approach to structure discovery without relying on sequence similarity. We study this approach with new multi-class classification methods and examined many issues important for a practical recognition system. RESULTS: Most current discriminative methods for protein fold prediction use the one-against-others method, which has the well-known 'False Positives' problem. We investigated two new methods: the unique one-against-others and the all-against-all methods. Both improve prediction accuracy by 14-110% on a dataset containing 27 SCOP folds. We used the Support Vector Machine (SVM) and the Neural Network (NN) learning methods as base classifiers. SVMs converges fast and leads to high accuracy. When scores of multiple parameter datasets are combined, majority voting reduces noise and increases recognition accuracy. We examined many issues involved with large number of classes, including dependencies of prediction accuracy on the number of folds and on the number of representatives in a fold. Overall, recognition systems achieve 56% fold prediction accuracy on a protein test dataset, where most of the proteins have below 25% sequence identity with the proteins used in training.

SUMMARY: VISTA is a program for visualizing global DNA sequence alignments of arbitrary length. It has a clean output, allowing for easy identification of similarity, and is easily configurable, enabling the visualization of alignments of various lengths at different levels of resolution. It is currently available on the web, thus allowing for easy access by all researchers. AVAILABILITY: VISTA server is available on the web at http://www-gsd.lbl.gov/vista. The source code is available upon request. CONTACT: [email protected]