RSAT: regulatory sequence analysis tools

The regulatory sequence analysis tools (RSAT, http://rsat.ulb.ac.be/rsat/) is a software suite that integrates a wide collection of modular tools for the detection of cis-regulatory elements in genome sequences. The suite includes programs for sequence retrieval, pattern discovery, phylogenetic footprint detection, pattern matching, genome scanning and feature map drawing. Random controls can be performed with random gene selections or by generating random sequences according to a variety of background models (Bernoulli, Markov). Beyond the original word-based pattern-discovery tools (oligo-analysis and dyad-analysis), we recently added a battery of tools for matrix-based detection of cis-acting elements, with some original features (adaptive background models, Markov-chain estimation of P-values) that do not exist in other matrix-based scanning tools. The web server offers an intuitive interface, where each program can be accessed either separately or connected to the other tools. In addition, the tools are now available as web services, enabling their integration in programmatic workflows. Genomes are regularly updated from various genome repositories (NCBI and EnsEMBL) and 682 organisms are currently supported. Since 1998, the tools have been used by several hundreds of researchers from all over the world. Several predictions made with RSAT were validated experimentally and published

RSAT 2011: regulatory sequence analysis tools

RSAT (Regulatory Sequence Analysis Tools) comprises a wide collection of modular tools for the detection of cis-regulatory elements in genome sequences. Thirteen new programs have been added to the 30 described in the 2008 NAR Web Software Issue, including an automated sequence retrieval from EnsEMBL (retrieve-ensembl-seq), two novel motif discovery algorithms (oligo-diff and info-gibbs), a 100-times faster version of matrix-scan enabling the scanning of genome-scale sequence sets, and a series of facilities for random model generation and statistical evaluation (random-genome-fragments, random-motifs, random-sites, implant-sites, sequence-probability, permute-matrix). Our most recent work also focused on motif comparison (compare-matrices) and evaluation of motif quality (matrix-quality) by combining theoretical and empirical measures to assess the predictive capability of position-specific scoring matrices. To process large collections of peak sequences obtained from ChIP-seq or related technologies, RSAT provides a new program (peak-motifs) that combines several efficient motif discovery algorithms to predict transcription factor binding motifs, match them against motif databases and predict their binding sites. Availability (web site, stand-alone programs and SOAP/WSDL (Simple Object Access Protocol/Web Services Description Language) web services): http://rsat.ulb.ac.be/rsat/

Paircomp, FamilyRelationsII and Cartwheel: tools for interspecific sequence comparison

BACKGROUND: Comparative sequence analysis is an effective and increasingly common way to identify cis-regulatory regions in animal genomes. RESULTS: We describe three tools for comparative analysis of pairs of BAC-sized genomic regions. Paircomp is a tool that does windowed (ungapped) comparisons of two sequences and reports all matches above a set threshold. FamilyRelationsII is a graphical viewer for comparisons that enables interactive exploration of several different kinds of comparisons. Cartwheel is a Web site and compute-cluster management system used to execute and store comparisons for display by FamilyRelationsII. These tools are specialized for the discovery of cis-regulatory regions in animal genomes. All tools and their source code are freely available at . CONCLUSION: These tools have been shown to effectively identify regulatory regions in echinoderms, mammals, and nematodes

RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding

International audienceGene regulatory regions contain short and degenerated DNA binding sites recognized by transcription factors (TFBS). When TFBS harbor SNPs, the DNA binding site may be affected, thereby altering the tran-scriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal variants in Genome-Wide Association Study (GWAS) studies. In this study, we describe improved versions of the programs Variation-tools designed to predict regulatory variants, and present four case studies to illustrate their usage and applications. In brief, Variation-tools facilitate i) obtaining variation information, ii) interconversion of variation file formats, iii) retrieval of sequences surrounding variants, and iv) calculating the change on predicted transcription factor affinity scores between alleles, using motif scanning approaches. Notably, the tools support the analysis of haplotypes. The tools are included within the well-maintained suite Regulatory Sequence Analysis Tools (RSAT, http://rsat.eu), and accessible through a web interface that currently enables analysis of five metazoa and ten plant genomes. Variation-tools can also be used in command-line with any locally-installed Ensembl genome. Users can input personal collections of variants and motifs, providing flexibility in the analysis

Comparative genomics exploration tools

Comparative Genomics focuses on elucidating the genetic differences between different species or different strains of the same species by the comparative analysis of DNA sequences to identify functional elements and regulatory regions. This thesis describes the design and development of two software tools to support comparative genomics research. These tools were specifically developed to support the analysis and assembly of sequence data produced from innovative new DNA sequencing technology from 454 Life Sciences using the PicoTiterPlate(TM) device. This technology will dramatically affect comparative genomics research. Currently available software tools were developed to handle traditional shotgun sequences averaging 500-1000 base pairs in length. These tools are inadequate to handle the unique characteristics of sequence reads generated by 454 Life Sciences. The goal of this research is to adapt currently available tools and develop new tools to be used for sequence reads generated by any sequencing technology, even those having different characteristics from the traditional shotgun sequences

MEMOFinder: combining _de_ _novo_ motif prediction methods with a database of known motifs

*Background:* Methods for finding overrepresented sequence motifs are useful in several key areas of computational biology. They aim at detecting very weak signals responsible for biological processes requiring robust sequence identification like transcription-factor binding to DNA or docking sites in proteins. Currently, general performance of the model-based motif-finding methods is unsatisfactory; however, different methods are successful in different cases. This leads to the practical problem of combining results of different motif-finding tools, taking into account current knowledge collected in motif databases.
*Results:* We propose a new complete service allowing researchers to submit their sequences for analysis by four different motif-finding methods for clustering and comparison with a reference motif database. It is tailored for regulatory motif detection, however it allows for substantial amount of configuration regarding sequence background, motif database and parameters for motif-finding methods.
*Availability:* The method is available online as a webserver at: http://bioputer.mimuw.edu.pl/software/mmf/. In addition, the source code is released on a GNU General Public License

Analysis tools for the interplay between genome layout and regulation

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes.Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation.SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information.We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation

TRED: a Transcriptional Regulatory Element Database and a platform for in silico gene regulation studies

In order to understand gene regulation, accurate and comprehensive knowledge of transcriptional regulatory elements is essential. Here, we report our efforts in building a mammalian Transcriptional Regulatory Element Database (TRED) with associated data analysis functions. It collects cis- and trans-regulatory elements and is dedicated to easy data access and analysis for both single-gene-based and genome-scale studies. Distinguishing features of TRED include: (i) relatively complete genome-wide promoter annotation for human, mouse and rat; (ii) availability of gene transcriptional regulation information including transcription factor binding sites and experimental evidence; (iii) data accuracy is ensured by hand curation; (iv) efficient user interface for easy and flexible data retrieval; and (v) implementation of on-the-fly sequence analysis tools. TRED can provide good training datasets for further genome-wide cis-regulatory element prediction and annotation, assist detailed functional studies and facilitate the decipher of gene regulatory networks (http://rulai.cshl.edu/TRED)