Ana T. Freitas

The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae

We present the YEAst Search for Transcriptional Regulators And Consensus Tracking (YEASTRACT; ) database, a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae. This database is a repository of 12 346 regulatory associations between transcription factors and target genes, based on experimental evidence which was spread throughout 861 bibliographic references. It also includes 257 specific DNA-binding sites for more than a hundred characterized transcription factors. Further information about each yeast gene included in the database was obtained from Saccharomyces Genome Database (SGD), Regulatory Sequences Analysis Tools and Gene Ontology (GO) Consortium. Computational tools are also provided to facilitate the exploitation of the gathered data when solving a number of biological questions as exemplified in the Tutorial also available on the system. YEASTRACT allows the identification of documented or potential transcription regulators of a given gene and of documented or potential regulons for each transcription factor. It also renders possible the comparison between DNA motifs, such as those found to be over-represented in the promoter regions of co-regulated genes, and the transcription factor-binding sites described in the literature. The system also provides an useful mechanism for grouping a list of genes (for instance a set of genes with similar expression profiles as revealed by microarray analysis) based on their regulatory associations with known transcription factors.

Current tools for the identification of miRNA genes and their targets

The discovery of microRNAs (miRNAs), almost 10 years ago, changed dramatically our perspective on eukaryotic gene expression regulation. However, the broad and important functions of these regulators are only now becoming apparent. The expansion of our catalogue of miRNA genes and the identification of the genes they regulate owe much to the development of sophisticated computational tools that have helped either to focus or interpret experimental assays. In this article, we review the methods for miRNA gene finding and target identification that have been proposed in the last few years. We identify some problems that current approaches have not yet been able to overcome and we offer some perspectives on the next generation of computational methods.

YEASTRACT: providing a programmatic access to curated transcriptional regulatory associations in Saccharomyces cerevisiae through a web services interface

The YEAst Search for Transcriptional Regulators And Consensus Tracking (YEASTRACT) information system (http://www.yeastract.com) was developed to support the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in June 2010, this database contains over 48 200 regulatory associations between transcription factors (TFs) and target genes, including 298 specific DNA-binding sites for 110 characterized TFs. All regulatory associations stored in the database were revisited and detailed information on the experimental evidences that sustain those associations was added and classified as direct or indirect evidences. The inclusion of this new data, gathered in response to the requests of YEASTRACT users, allows the user to restrict its queries to subsets of the data based on the existence or not of experimental evidences for the direct action of the TFs in the promoter region of their target genes. Another new feature of this release is the availability of all data through a machine readable web-service interface. Users are no longer restricted to the set of available queries made available through the existing web interface, and can use the web service interface to query, retrieve and exploit the YEASTRACT data using their own implementation of additional functionalities. The YEASTRACT information system is further complemented with several computational tools that facilitate the use of the curated data when answering a number of important biological questions. Since its first release in 2006, YEASTRACT has been extensively used by hundreds of researchers from all over the world. We expect that by making the new data and services available, the system will continue to be instrumental for yeast biologists and systems biology researchers.

The YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation in Saccharomyces cerevisiae

The YEASTRACT (http://www.yeastract.com) information system is a tool for the analysis and prediction of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in June 2013, this database contains over 200 000 regulatory associations between transcription factors (TFs) and target genes, including 326 DNA binding sites for 113 TFs. All regulatory associations stored in YEASTRACT were revisited and new information was added on the experimental conditions in which those associations take place and on whether the TF is acting on its target genes as activator or repressor. Based on this information, new queries were developed allowing the selection of specific environmental conditions, experimental evidence or positive/negative regulatory effect. This release further offers tools to rank the TFs controlling a gene or genome-wide response by their relative importance, based on (i) the percentage of target genes in the data set; (ii) the enrichment of the TF regulon in the data set when compared with the genome; or (iii) the score computed using the TFRank system, which selects and prioritizes the relevant TFs by walking through the yeast regulatory network. We expect that with the new data and services made available, the system will continue to be instrumental for yeast biologists and systems biology researchers.

YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae

The Yeast search for transcriptional regulators and consensus tracking (YEASTRACT) information system (www.yeastract.com) was developed to support the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in September 2007, this database contains over 30 990 regulatory associations between Transcription Factors (TFs) and target genes and includes 284 specific DNA binding sites for 108 characterized TFs. Computational tools are also provided to facilitate the exploitation of the gathered data when solving a number of biological questions, in particular the ones that involve the analysis of global gene expression results. In this new release, YEASTRACT includes DISCOVERER, a set of computational tools that can be used to identify complex motifs over-represented in the promoter regions of co-regulated genes. The motifs identified are then clustered in families, represented by a position weight matrix and are automatically compared with the known transcription factor binding sites described in YEASTRACT. Additionally, in this new release, it is possible to generate graphic depictions of transcriptional regulatory networks for documented or potential regulatory associations between TFs and target genes. The visual display of these networks of interactions is instrumental in functional studies. Tutorials are available on the system to exemplify the use of all the available tools.

Temporal logic patterns for querying dynamic models of cellular interaction networks

MOTIVATION Models of the dynamics of cellular interaction networks have become increasingly larger in recent years. Formal verification based on model checking provides a powerful technology to keep up with this increase in scale and complexity. The application of modelchecking approaches is hampered, however, by the difficulty for nonexpert users to formulate appropriate questions in temporal logic. RESULTS In order to deal with this problem, we propose the use of patterns, that is, high-level query templates that capture recurring biological questions and can be automatically translated into temporal logic. The applicability of the developed set of patterns has been investigated by the analysis of an extended model of the network of global regulators controlling the carbon starvation response in Escherichia coli. AVAILABILITY GNA and the model of the carbon starvation response network are available at http://www-helix.inrialpes.fr/gna.

An Efficient Algorithm for the Identification of Structured Motifs in DNA Promoter Sequences

We propose a new algorithm for identifying cis-regulatory modules in genomic sequences. The proposed algorithm, named RISO, uses a new data structure, called box-link, to store the information about conserved regions that occur in a well-ordered and regularly spaced manner in the data set sequences. This type of conserved regions, called structured motifs, is extremely relevant in the research of gene regulatory mechanisms since it can effectively represent promoter models. The complexity analysis shows a time and space gain over the best known exact algorithms that is exponential in the spacings between binding sites. A full implementation of the algorithm was developed and made available online. Experimental results show that the algorithm is much faster than existing ones, sometimes by more than four orders of magnitude. The application of the method to biological data sets shows its ability to extract relevant consensi

Evaluation of reduced susceptibility to quaternary ammonium compounds and bisbiguanides in clinical isolates and laboratory-generated mutants of Staphylococcus aureus

ABSTRACT The MICs and minimum bactericidal concentrations (MBCs) for the biocides benzalkonium chloride and chlorhexidine were determined against 1,602 clinical isolates of Staphylococcus aureus. Both compounds showed unimodal MIC and MBC distributions (2 and 4 or 8 mg/liter, respectively) with no apparent subpopulation with reduced susceptibility. To investigate further, all isolates were screened for qac genes, and 39 of these also had the promoter region of the NorA multidrug-resistant (MDR) efflux pump sequenced. The presence of qacA, qacB, qacC, and qacG genes increased the mode MIC, but not MBC, to benzalkonium chloride, while only qacA and qacB increased the chlorhexidine mode MIC. Isolates with a wild-type norA promoter or mutations in the norA promoter had similar biocide MIC distributions; notably, not all clinical isolates with norA mutations were resistant to fluoroquinolones. In vitro efflux mutants could be readily selected with ethidium bromide and acriflavine. Multiple passages were necessary to select mutants with biocides, but these mutants showed phenotypes comparable to those of mutants selected by dyes. All mutants showed changes in the promoter region of norA, but these were distinct from this region of the clinical isolates. Still, none of the in vitro mutants displayed fitness defects in a killing assay in Galleria mellonella larvae. In conclusion, our data provide an in-depth comparative overview on efflux in S. aureus mutants and clinical isolates, showing also that plasmid-encoded efflux pumps did not affect bactericidal activity of biocides. In addition, current in vitro tests appear not to be suitable for predicting levels of resistance that are clinically relevant.

A highly scalable algorithm for the extraction of cis-regulatory regions

In this paper we propose a new algorithm for identifying cis-regulatory modules in genomic sequences. In particular, the algorithm extracts structured motifs, defined as a collection of highly conserved regions with pre-specified sizes and spacings between them. This type of motifs is extremely relevant in the research of gene regulatory mechanisms since it can e! ectively represent promoter models. The proposed algorithm uses a new data structure, called box-link, to store the information about conserved regions that occur in a well-ordered and regularly spaced manner in the dataset sequences. The complexity analysis shows a time and space gain over previous algorithms that is exponential on the spacings between binding sites. Experimental results show that the algorithm is much faster than existing ones, sometimes by more than two orders of magnitude. The application of the method to biological datasets shows its ability to extract relevant consensi.

Advancing Eucalyptus genomics: identification and sequencing of lignin biosynthesis genes from deep-coverage BAC libraries

BackgroundEucalyptus species are among the most planted hardwoods in the world because of their rapid growth, adaptability and valuable wood properties. The development and integration of genomic resources into breeding practice will be increasingly important in the decades to come. Bacterial artificial chromosome (BAC) libraries are key genomic tools that enable positional cloning of important traits, synteny evaluation, and the development of genome framework physical maps for genetic linkage and genome sequencing.ResultsWe describe the construction and characterization of two deep-coverage BAC libraries EG_Ba and EG_Bb obtained from nuclear DNA fragments of E. grandis (clone BRASUZ1) digested with Hind III and BstY I, respectively. Genome coverages of 17 and 15 haploid genome equivalents were estimated for EG_Ba and EG_Bb, respectively. Both libraries contained large inserts, with average sizes ranging from 135 Kb (Eg_Bb) to 157 Kb (Eg_Ba), very low extra-nuclear genome contamination providing a probability of finding a single copy gene ≥ 99.99%. Libraries were screened for the presence of several genes of interest via hybridizations to high-density BAC filters followed by PCR validation. Five selected BAC clones were sequenced and assembled using the Roche GS FLX technology providing the whole sequence of the E. grandis chloroplast genome, and complete genomic sequences of important lignin biosynthesis genes.ConclusionsThe two E. grandis BAC libraries described in this study represent an important milestone for the advancement of Eucalyptus genomics and forest tree research. These BAC resources have a highly redundant genome coverage (> 15×), contain large average inserts and have a very low percentage of clones with organellar DNA or empty vectors. These publicly available BAC libraries are thus suitable for a broad range of applications in genetic and genomic research in Eucalyptus and possibly in related species of Myrtaceae, including genome sequencing, gene isolation, functional and comparative genomics. Because they have been constructed using the same tree (E. grandis BRASUZ1) whose full genome is being sequenced, they should prove instrumental for assembly and gap filling of the upcoming Eucalyptus reference genome sequence.