CircuitsDB: a database of mixed microRNA/transcription factor feed-forward regulatory circuits in human and mouse

<p>Abstract</p> <p>Background</p> <p>Transcription Factors (TFs) and microRNAs (miRNAs) are key players for gene expression regulation in higher eukaryotes. In the last years, a large amount of bioinformatic studies were devoted to the elucidation of transcriptional and post-transcriptional (mostly miRNA-mediated) regulatory interactions, but little is known about the interplay between them.</p> <p>Description</p> <p>Here we describe a dynamic web-accessible database, <monospace>CircuitsDB</monospace>, supporting a genome-wide transcriptional and post-transcriptional regulatory network integration, for the human and mouse genomes, based on a bioinformatic sequence-analysis approach. In particular, <monospace>CircuitsDB</monospace> is currently focused on the study of mixed miRNA/TF Feed-Forward regulatory Loops (FFLs), i.e. elementary circuits in which a master TF regulates an miRNA and together with it a set of Joint Target protein-coding genes. The database was constructed using an ab-initio oligo analysis procedure for the identification of the transcriptional and post-transcriptional interactions. Several external sources of information were then pooled together to obtain the functional annotation of the proposed interactions. Results for human and mouse genomes are presented in an integrated web tool, that allows users to explore the circuits, investigate their sequence and functional properties and thus suggest possible biological experiments.</p> <p>Conclusions</p> <p>We present <monospace>CircuitsDB</monospace>, a web-server devoted to the study of human and mouse mixed miRNA/TF Feed-Forward regulatory circuits, freely available at: <url>http://biocluster.di.unito.it/circuits/</url></p

The Estrogen Receptor α Signaling Pathway Controls Alternative Splicing in the Absence of Ligands in Breast Cancer Cells.

BACKGROUND: The transcriptional activity of estrogen receptor α (ERα) in breast cancer (BC) is extensively characterized. Our group has previously shown that ERα controls the expression of a number of genes in its unliganded form (apoERα), among which a large group of RNA-binding proteins (RBPs) encode genes, suggesting its role in the control of co- and post-transcriptional events. METHODS: apoERα-mediated RNA processing events were characterized by the analysis of transcript usage and alternative splicing changes in an RNA-sequencing dataset from MCF-7 cells after siRNA-induced ERα downregulation. RESULTS: ApoERα depletion induced an expression change of 681 RBPs, including 84 splicing factors involved in translation, ribonucleoprotein complex assembly, and 3'end processing. ApoERα depletion results in 758 isoform switching events with effects on 3'end length and the splicing of alternative cassette exons. The functional enrichment of these events shows that post-transcriptional regulation is part of the mechanisms by which apoERα controls epithelial-to-mesenchymal transition and BC cell proliferation. In primary BCs, the inclusion levels of the experimentally identified alternatively spliced exons are associated with overall and disease-free survival. CONCLUSION: Our data supports the role of apoERα in maintaining the luminal phenotype of BC cells by extensively regulating gene expression at the alternative splicing level

AP-2α regulates migration of GN-11 neurons via a specific genetic programme involving the Axl receptor tyrosine kinase

<p>Abstract</p> <p>Background</p> <p>Neuronal migration is a crucial process that allows neurons to reach their correct target location to allow the nervous system to function properly. AP-2α is a transcription factor essential for neural crest cell migration and its mutation results in apoptosis within this cell population, as demonstrated by genetic models.</p> <p>Results</p> <p>We down-modulated AP-2α expression in GN-11 neurons by RNA interference and observe reduced neuron migration following the activation of a specific genetic programme including the Adhesion Related Kinase (<it>Axl</it>) gene. We prove that <it>Axl </it>is able to coordinate migration per se and by ChIP and promoter analysis we observe that its transcription is directly driven by AP-2α via the binding to one or more functional AP-2α binding sites present in its regulatory region. Analysis of migration in AP-2α null mouse embryo fibroblasts also reveals an essential role for AP-2α in cell movement via the activation of a distinct genetic programme.</p> <p>Conclusion</p> <p>We show that AP-2α plays an essential role in cell movement via the activation of cell-specific genetic programmes. Moreover, we demonstrate that the AP-2α regulated gene <it>Axl </it>is an essential player in GN-11 neuron migration.</p

Docker4Circ: A Framework for the Reproducible Characterization of circRNAs from RNA-Seq Data.

Recent improvements in cost-effectiveness of high-throughput technologies has allowed RNA sequencing of total transcriptomes suitable for evaluating the expression and regulation of circRNAs, a relatively novel class of transcript isoforms with suggested roles in transcriptional and post-transcriptional gene expression regulation, as well as their possible use as biomarkers, due to their deregulation in various human diseases. A limited number of integrated workflows exists for prediction, characterization, and differential expression analysis of circRNAs, none of them complying with computational reproducibility requirements. We developed Docker4Circ for the complete analysis of circRNAs from RNA-Seq data. Docker4Circ runs a comprehensive analysis of circRNAs in human and model organisms, including: circRNAs prediction; classification and annotation using six public databases; back-splice sequence reconstruction; internal alternative splicing of circularizing exons; alignment-free circRNAs quantification from RNA-Seq reads; and differential expression analysis. Docker4Circ makes circRNAs analysis easier and more accessible thanks to: (i) its R interface; (ii) encapsulation of computational tasks into docker images; (iii) user-friendly Java GUI Interface availability; and (iv) no need of advanced bash scripting skills for correct use. Furthermore, Docker4Circ ensures a reproducible analysis since all its tasks are embedded into a docker image following the guidelines provided by Reproducible Bioinformatics Project

Docker4Circ: A Framework for the Reproducible Characterization of circRNAs from RNA-Seq Data

Recent improvements in cost-effectiveness of high-throughput technologies has allowed RNA sequencing of total transcriptomes suitable for evaluating the expression and regulation of circRNAs, a relatively novel class of transcript isoforms with suggested roles in transcriptional and post-transcriptional gene expression regulation, as well as their possible use as biomarkers, due to their deregulation in various human diseases. A limited number of integrated workflows exists for prediction, characterization, and differential expression analysis of circRNAs, none of them complying with computational reproducibility requirements. We developed Docker4Circ for the complete analysis of circRNAs from RNA-Seq data. Docker4Circ runs a comprehensive analysis of circRNAs in human and model organisms, including: circRNAs prediction; classification and annotation using six public databases; back-splice sequence reconstruction; internal alternative splicing of circularizing exons; alignment-free circRNAs quantification from RNA-Seq reads; and differential expression analysis. Docker4Circ makes circRNAs analysis easier and more accessible thanks to: (i) its R interface; (ii) encapsulation of computational tasks into docker images; (iii) user-friendly Java GUI Interface availability; and (iv) no need of advanced bash scripting skills for correct use. Furthermore, Docker4Circ ensures a reproducible analysis since all its tasks are embedded into a docker image following the guidelines provided by Reproducible Bioinformatics Project

Luminal long non-coding RNAs regulated by estrogen receptor alpha in a ligand-independent manner show functional roles in breast cancer

Estrogen Receptor alpha (ERα) activation by estrogenic hormones induces luminal breast cancer cell proliferation. However, ERα plays also important hormone-independent functions to maintain breast tumor cells epithelial phenotype. We reported previously by RNA-Seq that in MCF-7 cells in absence of hormones ERα down-regulation changes the expression of several genes linked to cellular development, representing a specific subset of estrogen-induced genes. Here, we report regulation of long non-coding RNAs from the same experimental settings. A list of 133 Apo-ERα-Regulated lncRNAs (AER-lncRNAs) was identified and extensively characterized using published data from cancer cell lines and tumor tissues, or experiments on MCF-7 cells. For several features, we ran validation using cell cultures or fresh tumor biopsies. AER-lncRNAs represent a specific subset, only marginally overlapping estrogen-induced transcripts, whose expression is largely restricted to luminal cells and which is able to perfectly classify breast tumor subtypes. The most abundant AER-lncRNA, DSCAM-AS1, is expressed in ERα+ breast carcinoma, but not in pre-neoplastic lesions, and correlates inversely with EMT markers. Down-regulation of DSCAM-AS1 recapitulated, in part, the effect of silencing ERα, i.e. growth arrest and induction of EMT markers. In conclusion, we report an ERα-dependent lncRNA set representing a novel luminal signature in breast cancer cells