A naturally occuring insertion of a single amino acid rewires transcriptional regulation by glucocorticoid receptor isoforms

In addition to guiding proteins to defined genomic loci, DNA can act as an allosteric ligand that influences protein structure and activity. Here we compared genome-wide binding, transcriptional regulation, and, using NMR, the conformation of two glucocorticoid receptor (GR) isoforms that differ by a single amino acid insertion in the lever arm, a domain that adopts DNA sequence-specific conformations. We show that these isoforms differentially regulate gene expression levels through two mechanisms: differential DNA binding and altered communication between GR domains. Our studies suggest a versatile role for DNA in both modulating GR activity and also in directing the use of GR isoforms. We propose that the lever arm is a "fulcrum" for bidirectional allosteric signaling, conferring conformational changes in the DNA reading head that influence DNA sequence selectivity, as well as conferring changes in the dimerization domain that connect functionally with remote regulatory surfaces, thereby influencing which genes are regulated and the magnitude of their regulation

Origin and diversification of the basic helix-loop-helix gene family in metazoans: insights from comparative genomics

BACKGROUND: Molecular and genetic analyses conducted in model organisms such as Drosophila and vertebrates, have provided a wealth of information about how networks of transcription factors control the proper development of these species. Much less is known, however, about the evolutionary origin of these elaborated networks and their large-scale evolution. Here we report the first evolutionary analysis of a whole superfamily of transcription factors, the basic helix-loop-helix (bHLH) proteins, at the scale of the whole metazoan kingdom. RESULTS: We identified in silico the putative full complement of bHLH genes in the sequenced genomes of 12 different species representative of the main metazoan lineages, including three non-bilaterian metazoans, the cnidarians Nematostella vectensis and Hydra magnipapillata and the demosponge Amphimedon queenslandica. We have performed extensive phylogenetic analyses of the 695 identified bHLHs, which has allowed us to allocate most of these bHLHs to defined evolutionary conserved groups of orthology. CONCLUSION: Three main features in the history of the bHLH gene superfamily can be inferred from these analyses: (i) an initial diversification of the bHLHs has occurred in the pre-Cambrian, prior to metazoan cladogenesis; (ii) a second expansion of the bHLH superfamily occurred early in metazoan evolution before bilaterians and cnidarians diverged; and (iii) the bHLH complement during the evolution of the bilaterians has been remarkably stable. We suggest that these features may be extended to other developmental gene families and reflect a general trend in the evolution of the developmental gene repertoires of metazoans

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/

Vitamin D receptor ChIP-seq in primary CD4+ cells: relationship to serum 25-hydroxyvitamin D levels and autoimmune disease

PMCID: PMC3710212This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Mitigating Anticipated Effects of Systematic Errors Supports Sister-Group Relationship between Xenacoelomorpha and Ambulacraria

Xenoturbella and the acoelomorph worms (Xenacoe-lomorpha) are simple marine animals with controversial affinities. They have been placed as the sister group of all other bilaterian animals (Nephrozoa hypothesis), implying their simplicity is an ancient characteristic [1, 2]; alternatively, they have been linked to the complex Ambulacraria (echinoderms and hemichordates) in a Glade called the Xenambulacraria [3,5], suggesting their simplicity evolved by reduction from a complex ancestor. The difficulty resolving this problem implies the phylogenetic signal supporting the correct solution is weak and affected by inadequate modeling, creating a misleading non-phylogenetic signal. The idea that the Nephrozoa hypothesis might be an artifact is prompted by the faster molecular evolutionary rate observed within the Acoelomorpha. Unequal rates of evolution are known to result in the systematic artifact of long branch attraction, which would be predicted to result in an attraction between long-branch acoelomorphs and the outgroup, pulling them toward the root [6]. Other biases inadequately accommodated by the models used can also have strong effects, exacerbated in the context of short internal branches and long terminal branches [7]. We have assembled a large and informative dataset to address this problem. Analyses designed to reduce or to emphasize misleading signals show the Nephrozoa hypothesis is supported under conditions expected to exacerbate errors, and the Xenambulacraria hypothesis is preferred in conditions designed to reduce errors. Our reanalyses of two other recently published datasets [1, 2] produce the same result. We conclude that the Xenacoelomorpha are simplified relatives of the Ambulacraria

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

FITBAR: a web tool for the robust prediction of prokaryotic regulons

<p>Abstract</p> <p>Background</p> <p>The binding of regulatory proteins to their specific DNA targets determines the accurate expression of the neighboring genes. The <it>in silico </it>prediction of new binding sites in completely sequenced genomes is a key aspect in the deeper understanding of gene regulatory networks. Several algorithms have been described to discriminate against false-positives in the prediction of new binding targets; however none of them has been implemented so far to assist the detection of binding sites at the genomic scale.</p> <p>Results</p> <p>FITBAR (Fast Investigation Tool for Bacterial and Archaeal Regulons) is a web service designed to identify new protein binding sites on fully sequenced prokaryotic genomes. This tool consists in a workbench where the significance of the predictions can be compared using different statistical methods, a feature not found in existing resources. The Local Markov Model and the Compound Importance Sampling algorithms have been implemented to compute the P-value of newly discovered binding sites. In addition, FITBAR provides two optimized genomic scanning algorithms using either log-odds or entropy-weighted position-specific scoring matrices. Other significant features include the production of a detailed genomic context map for each detected binding site and the export of the search results in spreadsheet and portable document formats. FITBAR discovery of a high affinity <it>Escherichia coli </it>NagC binding site was validated experimentally <it>in vitro </it>as well as <it>in vivo </it>and published.</p> <p>Conclusions</p> <p>FITBAR was developed in order to allow fast, accurate and statistically robust predictions of prokaryotic regulons. This feature constitutes the main advantage of this web tool over other matrix search programs and does not impair its performance. The web service is available at <url>http://archaea.u-psud.fr/fitbar</url>.</p

Contribution of CgPDR1-Regulated Genes in Enhanced Virulence of Azole-Resistant Candida glabrata

In Candida glabrata, the transcription factor CgPdr1 is involved in resistance to azole antifungals via upregulation of ATP binding cassette (ABC)-transporter genes including at least CgCDR1, CgCDR2 and CgSNQ2. A high diversity of GOF (gain-of-function) mutations in CgPDR1 exists for the upregulation of ABC-transporters. These mutations enhance C. glabrata virulence in animal models, thus indicating that CgPDR1 might regulate the expression of yet unidentified virulence factors. We hypothesized that CgPdr1-dependent virulence factor(s) should be commonly regulated by all GOF mutations in CgPDR1. As deduced from transcript profiling with microarrays, a high number of genes (up to 385) were differentially regulated by a selected number (7) of GOF mutations expressed in the same genetic background. Surprisingly, the transcriptional profiles resulting from expression of GOF mutations showed minimal overlap in co-regulated genes. Only two genes, CgCDR1 and PUP1 (for PDR1 upregulated and encoding a mitochondrial protein), were commonly upregulated by all tested GOFs. While both genes mediated azole resistance, although to different extents, their deletions in an azole-resistant isolate led to a reduction of virulence and decreased tissue burden as compared to clinical parents. As expected from their role in C. glabrata virulence, the two genes were expressed as well in vitro and in vivo. The individual overexpression of these two genes in a CgPDR1-independent manner could partially restore phenotypes obtained in clinical isolates. These data therefore demonstrate that at least these two CgPDR1-dependent and -upregulated genes contribute to the enhanced virulence of C. glabrata that acquired azole resistance

Regulatory targets of quorum sensing in Vibrio cholerae: evidence for two distinct HapR-binding motifs

The quorum-sensing pathway in Vibrio cholerae controls the expression of the master regulator HapR, which in turn regulates several important processes such as virulence factor production and biofilm formation. While HapR is known to control several important phenotypes, there are only a few target genes known to be transcriptionally regulated by HapR. In this work, we combine bioinformatic analysis with experimental validation to discover a set of novel direct targets of HapR. Our results provide evidence for two distinct binding motifs for HapR-regulated genes in V. cholerae. The first binding motif is similar to the motifs recently discovered for orthologs of HapR in V. harveyi and V. vulnificus. However, our results demonstrate that this binding motif can be of variable length in V. cholerae. The second binding motif shares common elements with the first motif, but is of fixed length and lacks dyad symmetry at the ends. The contributions of different bases to HapR binding for this second motif were demonstrated using systematic mutagenesis experiments. The current analysis presents an approach for systematically expanding our knowledge of the quorum-sensing regulon in V. cholerae and other related bacteria

An analysis of single amino acid repeats as use case for application specific background models

Background Sequence analysis aims to identify biologically relevant signals against a backdrop of functionally meaningless variation. Increasingly, it is recognized that the quality of the background model directly affects the performance of analyses. State-of-the-art approaches rely on classical sequence models that are adapted to the studied dataset. Although performing well in the analysis of globular protein domains, these models break down in regions of stronger compositional bias or low complexity. While these regions are typically filtered, there is increasing anecdotal evidence of functional roles. This motivates an exploration of more complex sequence models and application-specific approaches for the investigation of biased regions. Results Traditional Markov-chains and application-specific regression models are compared using the example of predicting runs of single amino acids, a particularly simple class of biased regions. Cross-fold validation experiments reveal that the alternative regression models capture the multi-variate trends well, despite their low dimensionality and in contrast even to higher-order Markov-predictors. We show how the significance of unusual observations can be computed for such empirical models. The power of a dedicated model in the detection of biologically interesting signals is then demonstrated in an analysis identifying the unexpected enrichment of contiguous leucine-repeats in signal-peptides. Considering different reference sets, we show how the question examined actually defines what constitutes the 'background'. Results can thus be highly sensitive to the choice of appropriate model training sets. Conversely, the choice of reference data determines the questions that can be investigated in an analysis. Conclusions Using a specific case of studying biased regions as an example, we have demonstrated that the construction of application-specific background models is both necessary and feasible in a challenging sequence analysis situation