PhysBinder : improving the prediction of transcription factor binding sites by flexible inclusion of biophysical properties

The most important mechanism in the regulation of transcription is the binding of a transcription factor (TF) to a DNA sequence called the TF binding site (TFBS). Most binding sites are short and degenerate, which makes predictions based on their primary sequence alone somewhat unreliable. We present a new web tool that implements a flexible and extensible algorithm for predicting TFBS. The algorithm makes use of both direct (the sequence) and several indirect readout features of protein-DNA complexes (biophysical properties such as bendability or the solvent-excluded surface of the DNA). This algorithm significantly outperforms state-of-the-art approaches for in silico identification of TFBS. Users can submit FASTA sequences for analysis in the PhysBinder integrative algorithm and choose from >60 different TF-binding models. The results of this analysis can be used to plan and steer wet-lab experiments. The PhysBinder web tool is freely available at http://bioit.dmbr.ugent.be/physbinder/index.php

Low nucleosome occupancy is encoded around functional human transcription factor binding sites

<p>Abstract</p> <p>Background</p> <p>Transcriptional regulation of genes in eukaryotes is achieved by the interactions of multiple transcription factors with arrays of transcription factor binding sites (TFBSs) on DNA and with each other. Identification of these TFBSs is an essential step in our understanding of gene regulatory networks, but computational prediction of TFBSs with either consensus or commonly used stochastic models such as Position-Specific Scoring Matrices (PSSMs) results in an unacceptably high number of hits consisting of a few true functional binding sites and numerous false non-functional binding sites. This is due to the inability of the models to incorporate higher order properties of sequences including sequences surrounding TFBSs and influencing the positioning of nucleosomes and/or the interactions that might occur between transcription factors.</p> <p>Results</p> <p>Significant improvement can be expected through the development of a new framework for the modeling and prediction of TFBSs that considers explicitly these higher order sequence properties. It would be particularly interesting to include in the new modeling framework the information present in the nucleosome positioning sequences (NPSs) surrounding TFBSs, as it can be hypothesized that genomes use this information to encode the formation of stable nucleosomes over non-functional sites, while functional sites have a more open chromatin configuration.</p> <p>In this report we evaluate the usefulness of the latter feature by comparing the nucleosome occupancy probabilities around experimentally verified human TFBSs with the nucleosome occupancy probabilities around false positive TFBSs and in random sequences.</p> <p>Conclusion</p> <p>We present evidence that nucleosome occupancy is remarkably lower around true functional human TFBSs as compared to non-functional human TFBSs, which supports the use of this feature to improve current TFBS prediction approaches in higher eukaryotes.</p

A distance difference matrix approach to identifying transcription factors that regulate differential gene expression

A distance difference matrix method is presented for identifying transcription factor binding sites of secondary factors responsible for the different responses of the target genes of one transcription factor

ConTra v3 : a tool to identify transcription factor binding sites across species, update 2017

Transcription factors are important gene regulators with distinctive roles in development, cell signaling and cell cycling, and they have been associated with many diseases. The ConTra v3 web server allows easy visualization and exploration of predicted transcription factor binding sites (TFBSs) in any genomic region surrounding coding or non-coding genes. In this updated version, with a completely re-implemented user interface using latest web technologies, users can choose from nine reference organisms ranging from human to yeast. ConTra v3 can analyze promoter regions, 5'-UTRs, 3'-UTRs and introns or any other genomic region of interest. Thousands of position weight matrices are available to choose from for detecting specific binding sites. Besides this visualization option, additional new exploration functionality is added to the tool that will automatically detect TFBSs having at the same time the highest regulatory potential, the highest conservation scores of the genomic regions covered by the predicted TFBSs and strongest co-localizations with genomic regions exhibiting regulatory activity. The ConTra v3 web server is freely available at http://bioit2.irc.ugent.be/contra/v3

A new generation of JASPAR, the open-access repository for transcription factor binding site profiles

JASPAR is the most complete open-access collection of transcription factor binding site (TFBS) matrices. In this new release, JASPAR grows into a meta-database of collections of TFBS models derived by diverse approaches. We present JASPAR CORE—an expanded version of the original, non-redundant collection of annotated, high-quality matrix-based transcription factor binding profiles, JASPAR FAM—a collection of familial TFBS models and JASPAR phyloFACTS—a set of matrices computationally derived from statistically overrepresented, evolutionarily conserved regulatory region motifs from mammalian genomes. JASPAR phyloFACTS serves as a non-redundant extension to JASPAR CORE, enhancing the overall breadth of JASPAR for promoter sequence analysis. The new release of JASPAR is available at

αT-catenin in restricted brain cell types and its potential connection to autism

BACKGROUND: Recent genetic association studies have linked the cadherin-based adherens junction protein alpha-T-catenin (αT-cat, CTNNA3) with the development of autism. Where αT-cat is expressed in the brain, and how its loss could contribute to this disorder, are entirely unknown. METHODS: We used the αT-cat knockout mouse to examine the localization of αT-cat in the brain, and we used histology and immunofluorescence analysis to examine the neurobiological consequences of its loss. RESULTS: We found that αT-cat comprises the ependymal cell junctions of the ventricles of the brain, and its loss led to compensatory upregulation of αE-cat expression. Notably, αT-cat was not detected within the choroid plexus, which relies on cell junction components common to typical epithelial cells. While αT-cat was not detected in neurons of the cerebral cortex, it was abundantly detected within neuronal structures of the molecular layer of the cerebellum. Although αT-cat loss led to no overt differences in cerebral or cerebellar structure, RNA-sequencing analysis from wild type versus knockout cerebella identified a number of disease-relevant signaling pathways associated with αT-cat loss, such as GABA-A receptor activation. CONCLUSIONS: These findings raise the possibility that the genetic associations between αT-cat and autism may be due to ependymal and cerebellar defects, and highlight the potential importance of a seemingly redundant adherens junction component to a neurological disorder

Genome-wide computational analysis reveals cardiomyocyte-specific transcriptional cis-regulatory motifs that enable efficient cardiac gene therapy

Gene therapy is a promising emerging therapeutic modality for the treatment of cardiovascular diseases and hereditary diseases that afflict the heart. Hence, there is a need to develop robust cardiac-specific expression modules that allow for stable expression of the gene of interest in cardiomyocytes. We therefore explored a new approach based on a genome-wide bioinformatics strategy that revealed novel cardiac-specific cis-acting regulatory modules (CS-CRMs). These transcriptional modules contained evolutionary-conserved clusters of putative transcription factor binding sites that correspond to a "molecular signature" associated with robust gene expression in the heart. We then validated these CS-CRMs in vivo using an adeno-associated viral vector serotype 9 that drives a reporter gene from a quintessential cardiac-specific a-myosin heavy chain promoter. Most de novo designed CS-CRMs resulted in a > 10-fold increase in cardiac gene - expression. The most robust CRMs enhanced cardiac-specific transcription 70- to 100-fold. Expression was sustained and restricted to cardiomyocytes. We then combined the most potent CS-CRM4 with a synthetic heart and muscle-specific promoter (SPc5-12) and obtained a significant 20-fold increase in cardiac gene expression compared to the cytomegalovirus promoter. This study underscores the potential of rational vector design to improve the robustness of cardiac gene therapy

ConTra: a promoter alignment analysis tool for identification of transcription factor binding sites across species

Transcription factors (TFs) are key components in signaling pathways, and the presence of their binding sites in the promoter regions of DNA is essential for their regulation of the expression of the corresponding genes. Orthologous promoter sequences are commonly used to increase the specificity with which potentially functional transcription factor binding sites (TFBSs) are recognized and to detect possibly important similarities or differences between the different species. The ConTra (conserved TFBSs) web server provides the biologist at the bench with a user-friendly tool to interactively visualize TFBSs predicted using either TransFac (1) or JASPAR (2) position weight matrix libraries, on a promoter alignment of choice. The visualization can be preceded by a simple scoring analysis to explore which TFs are the most likely to bind to the promoter of interest. The ConTra web server is available at http://bioit.dmbr.ugent.be/ConTra/index.php

ConTra v2: a tool to identify transcription factor binding sites across species, update 2011

Transcription factors are important gene regulators with distinctive roles in development, cell signaling and cell cycling, and they have been associated with many diseases. The ConTra v2 web server allows easy visualization and exploration of predicted transcription factor binding sites in any genomic region surrounding coding or non-coding genes. In this new version, users can choose from nine reference organisms ranging from human to yeast. ConTra v2 can analyze promoter regions, 5′-UTRs, 3′-UTRs and introns or any other genomic region of interest. Hundreds of position weight matrices are available to choose from, but the user can also upload any other matrices for detecting specific binding sites. A typical analysis is run in four simple steps of choosing the gene, the transcript, the region of interest and then selecting one or more transcription factor binding sites. The ConTra v2 web server is freely available at http://bioit.dmbr.ugent.be/contrav2/index.php

Next-generation muscle-directed gene therapy by in silico vector design

There is an urgent need to develop the next-generation vectors for gene therapy of muscle disorders, given the relatively modest advances in clinical trials. These vectors should express substantially higher levels of the therapeutic transgene, enabling the use of lower and safer vector doses. In the current study, we identify potent muscle-specific transcriptional cisregulatory modules (CRMs), containing clusters of transcription factor binding sites, using a genome-wide data-mining strategy. These novel muscle-specific CRMs result in a substantial increase in muscle-specific gene transcription (up to 400-fold) when delivered using adeno-associated viral vectors in mice. Significantly higher and sustained human micro-dystrophin and follistatin expression levels are attained than when conventional promoters are used. This results in robust phenotypic correction in dystrophic mice, without triggering apoptosis or evoking an immune response. This multidisciplinary approach has potentially broad implications for augmenting the efficacy and safety of muscle-directed gene therapy