Pervasive Chromatin-RNA Binding Protein Interactions Enable RNA-Based Regulation of Transcription.

Increasing evidence suggests that transcriptional control and chromatin activities at large involve regulatory RNAs, which likely enlist specific RNA-binding proteins (RBPs). Although multiple RBPs have been implicated in transcription control, it has remained unclear how extensively RBPs directly act on chromatin. We embarked on a large-scale RBP ChIP-seq analysis, revealing widespread RBP presence in active chromatin regions in the human genome. Like transcription factors (TFs), RBPs also show strong preference for hotspots in the genome, particularly gene promoters, where their association is frequently linked to transcriptional output. Unsupervised clustering reveals extensive co-association between TFs and RBPs, as exemplified by YY1, a known RNA-dependent TF, and RBM25, an RBP involved in splicing regulation. Remarkably, RBM25 depletion attenuates all YY1-dependent activities, including chromatin binding, DNA looping, and transcription. We propose that various RBPs may enhance network interaction through harnessing regulatory RNAs to control transcription.

A large-scale binding and functional map of human RNA-binding proteins.

Many proteins regulate the expression of genes by binding to specific regions encoded in the genome1. Here we introduce a new data set of RNA elements in the human genome that are recognized by RNA-binding proteins (RBPs), generated as part of the Encyclopedia of DNA Elements (ENCODE) project phase III. This class of regulatory elements functions only when transcribed into RNA, as they serve as the binding sites for RBPs that control post-transcriptional processes such as splicing, cleavage and polyadenylation, and the editing, localization, stability and translation of mRNAs. We describe the mapping and characterization of RNA elements recognized by a large collection of human RBPs in K562 and HepG2 cells. Integrative analyses using five assays identify RBP binding sites on RNA and chromatin in vivo, the in vitro binding preferences of RBPs, the function of RBP binding sites and the subcellular localization of RBPs, producing 1,223 replicated data sets for 356 RBPs. We describe the spectrum of RBP binding throughout the transcriptome and the connections between these interactions and various aspects of RNA biology, including RNA stability, splicing regulation and RNA localization. These data expand the catalogue of functional elements encoded in the human genome by the addition of a large set of elements that function at the RNA level by interacting with RBPs.

Expanded encyclopaedias of DNA elements in the human and mouse genomes.

The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.

RBP Image Database: A resource for the systematic characterization of the subcellular distribution properties of human RNA binding proteins.

RNA binding proteins (RBPs) are central regulators of gene expression implicated in all facets of RNA metabolism. As such, they play key roles in cellular physiology and disease etiology. Since different steps of post-transcriptional gene expression tend to occur in specific regions of the cell, including nuclear or cytoplasmic locations, defining the subcellular distribution properties of RBPs is an important step in assessing their potential functions. Here, we present the RBP Image Database, a resource that details the subcellular localization features of 301 RBPs in the human HepG2 and HeLa cell lines, based on the results of systematic immuno-fluorescence studies conducted using a highly validated collection of RBP antibodies and a panel of 12 markers for specific organelles and subcellular structures. The unique features of the RBP Image Database include: (i) hosting of comprehensive representative images for each RBP-marker pair, with ∼250,000 microscopy images; (ii) a manually curated controlled vocabulary of annotation terms detailing the localization features of each factor; and (iii) a user-friendly interface allowing the rapid querying of the data by target or annotation. The RBP Image Database is freely available at https://rnabiology.ircm.qc.ca/RBPImage/.

Resources for the Comprehensive Discovery of Functional RNA Elements.

Transcriptome-wide maps of RNA binding protein (RBP)-RNA interactions by immunoprecipitation (IP)-based methods such as RNA IP (RIP) and crosslinking and IP (CLIP) are key starting points for evaluating the molecular roles of the thousands of human RBPs. A significant bottleneck to the application of these methods in diverse cell lines, tissues, and developmental stages is the availability of validated IP-quality antibodies. Using IP followed by immunoblot assays, we have developed a validated repository of 438 commercially available antibodies that interrogate 365 unique RBPs. In parallel, 362 short-hairpin RNA (shRNA) constructs against 276 unique RBPs were also used to confirm specificity of these antibodies. These antibodies can characterize subcellular RBP localization. With the burgeoning interest in the roles of RBPs in cancer, neurobiology, and development, these resources are invaluable to the broad scientific community. Detailed information about these resources is publicly available at the ENCODE portal (https://www.encodeproject.org/).

Genome-wide identification of zero nucleotide recursive splicing in Drosophila.

Recursive splicing is a process in which large introns are removed in multiple steps by re-splicing at ratchet points--5' splice sites recreated after splicing. Recursive splicing was first identified in the Drosophila Ultrabithorax (Ubx) gene and only three additional Drosophila genes have since been experimentally shown to undergo recursive splicing. Here we identify 197 zero nucleotide exon ratchet points in 130 introns of 115 Drosophila genes from total RNA sequencing data generated from developmental time points, dissected tissues and cultured cells. The sequential nature of recursive splicing was confirmed by identification of lariat introns generated by splicing to and from the ratchet points. We also show that recursive splicing is a constitutive process, that depletion of U2AF inhibits recursive splicing, and that the sequence and function of ratchet points are evolutionarily conserved in Drosophila. Finally, we identify four recursively spliced human genes, one of which is also recursively spliced in Drosophila. Together, these results indicate that recursive splicing is commonly used in Drosophila, occurs in humans, and provides insight into the mechanisms by which some large introns are removed.

Pathway Commons at virtual cell: use of pathway data for mathematical modeling.

UNLABELLED: Pathway Commons is a resource permitting simultaneous queries of multiple pathway databases. However, there is no standard mechanism for using these data (stored in BioPAX format) to annotate and build quantitative mathematical models. Therefore, we developed a new module within the virtual cell modeling and simulation software. It provides pathway data retrieval and visualization and enables automatic creation of executable network models directly from qualitative connections between pathway nodes. AVAILABILITY AND IMPLEMENTATION: Available at Virtual Cell (http://vcell.org/). Application runs on all major platforms and does not require registration for use on the user's computer. Tutorials and video are available at user guide page.

Regulation of RNA editing by RNA-binding proteins in human cells.

Adenosine-to-inosine (A-to-I) editing, mediated by the ADAR enzymes, diversifies the transcriptome by altering RNA sequences. Recent studies reported global changes in RNA editing in disease and development. Such widespread editing variations necessitate an improved understanding of the regulatory mechanisms of RNA editing. Here, we study the roles of >200 RNA-binding proteins (RBPs) in mediating RNA editing in two human cell lines. Using RNA-sequencing and global protein-RNA binding data, we identify a number of RBPs as key regulators of A-to-I editing. These RBPs, such as TDP-43, DROSHA, NF45/90 and Ro60, mediate editing through various mechanisms including regulation of ADAR1 expression, interaction with ADAR1, and binding to Alu elements. We highlight that editing regulation by Ro60 is consistent with the global up-regulation of RNA editing in systemic lupus erythematosus. Additionally, most key editing regulators act in a cell type-specific manner. Together, our work provides insights for the regulatory mechanisms of RNA editing.

Allele-specific binding of RNA-binding proteins reveals functional genetic variants in the RNA.

Allele-specific protein-RNA binding is an essential aspect that may reveal functional genetic variants (GVs) mediating post-transcriptional regulation. Recently, genome-wide detection of in vivo binding of RNA-binding proteins is greatly facilitated by the enhanced crosslinking and immunoprecipitation (eCLIP) method. We developed a new computational approach, called BEAPR, to identify allele-specific binding (ASB) events in eCLIP-Seq data. BEAPR takes into account crosslinking-induced sequence propensity and variations between replicated experiments. Using simulated and actual data, we show that BEAPR largely outperforms often-used count analysis methods. Importantly, BEAPR overcomes the inherent overdispersion problem of these methods. Complemented by experimental validations, we demonstrate that the application of BEAPR to ENCODE eCLIP-Seq data of 154 proteins helps to predict functional GVs that alter splicing or mRNA abundance. Moreover, many GVs with ASB patterns have known disease relevance. Overall, BEAPR is an effective method that helps to address the outstanding challenge of functional interpretation of GVs.

Rapid and efficient uranium(VI) capture by phytic acid/polyaniline/FeOOH composites.

Uranium plays an indispensable role in nuclear energy, but there are limited land resources to meet the ever growing demand; therefore, a need exists to develop efficient materials for capturing uranium from water. Herein, we synthesize a promising adsorbent of phytic acid/polyaniline/FeOOH composites (PA/PANI/FeOOH) by oxidative polymerization. Phytic acid, acting asa gelator and dopant, plays an important role in the formation of polyaniline (PANI). The PA/PANI/FeOOH exhibites high adsorption capacity (qm=555.8mgg-1, T=298K), rapid adsorption rate (within 5min), excellent selectivity and cyclic stability. In addition, the results show that the adsorption isotherm is well fitted to the Langmuir isotherm model, and the adsorption kinetics agree with a pseudo-second order model. XPS analysis indicates that the removal of uranium is mainly attributed to abundant amine and imine groups on the surface of PA/PANI/FeOOH. Importantly, the removal of uranium from low concentrations of simulated seawater is highly efficient with a removal rate exceeding 92%. From our study, superior adsorption capacities, along with a low-cost, environmentally friendly and facile synthesis, reveal PA/PANI/FeOOH asa promising material for uranium capture.

Efficient removal of uranium(vi) from simulated seawater using amidoximated polyacrylonitrile/FeOOH composites.

The ability to recover uranium, an important nuclear fuel, from seawater provides the potential for long-term sustainable fuel supply for nuclear energy. In this work, novel amidoximated polyacrylonitrile/FeOOH (FeOOH-APAN) composites were synthesized and characterized by CHN analysis, Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), N2 adsorption-desorption, and X-ray photoelectron spectroscopy (XPS). In batch adsorption experiments, a variety of parameters were investigated in detail. The FeOOH-APAN composites exhibit high adsorption capacities (qL = 980.39 mg g-1, T = 298 K), superior to many other materials. In addition, they possess large Kd values (>104 mL g-1 at 25-400 mg L-1 U concentration), high removal rates (∼95% at 25-300 mg L-1, and ∼90% for ppb level simulated seawater), excellent selectivity and rapid capturing rates for uranium. XPS analysis shows that the removal of uranium is mainly related to amidoxime groups, involving the interaction with oxime oxygen and oxime nitrogen. In this paper, a more dominant binding mode is proposed, namely η2 coordination.

A benchmark for RNA-seq quantification pipelines.

Obtaining RNA-seq measurements involves a complex data analytical process with a large number of competing algorithms as options. There is much debate about which of these methods provides the best approach. Unfortunately, it is currently difficult to evaluate their performance due in part to a lack of sensitive assessment metrics. We present a series of statistical summaries and plots to evaluate the performance in terms of specificity and sensitivity, available as a R/Bioconductor package ( http://bioconductor.org/packages/rnaseqcomp ). Using two independent datasets, we assessed seven competing pipelines. Performance was generally poor, with two methods clearly underperforming and RSEM slightly outperforming the rest.

Mining functionally relevant gene sets for analyzing physiologically novel clinical expression data.

Gene set analyses have become a standard approach for increasing the sensitivity of transcriptomic studies. However, analytical methods incorporating gene sets require the availability of pre-defined gene sets relevant to the underlying physiology being studied. For novel physiological problems, relevant gene sets may be unavailable or existing gene set databases may bias the results towards only the best-studied of the relevant biological processes. We describe a successful attempt to mine novel functional gene sets for translational projects where the underlying physiology is not necessarily well characterized in existing annotation databases. We choose targeted training data from public expression data repositories and define new criteria for selecting biclusters to serve as candidate gene sets. Many of the discovered gene sets show little or no enrichment for informative Gene Ontology terms or other functional annotation. However, we observe that such gene sets show coherent differential expression in new clinical test data sets, even if derived from different species, tissues, and disease states. We demonstrate the efficacy of this method on a human metabolic data set, where we discover novel, uncharacterized gene sets that are diagnostic of diabetes, and on additional data sets related to neuronal processes and human development. Our results suggest that our approach may be an efficient way to generate a collection of gene sets relevant to the analysis of data for novel clinical applications where existing functional annotation is relatively incomplete.

Degenerate primer design via clustering.

This paper describes a new strategy for designing degenerate primers for a given multiple alignment of amino acid sequences. Degenerate primers are useful for amplifying homologous genes. However, when a large collection of sequences is considered, no consensus region may exist in the multiple alignment, making it impossible to design a single pair of primers for the collection. In such cases, manual methods are used to find smaller groups from the input collection so that primers can be designed for individual groups. Our strategy proposes an automatic grouping of the input sequences by using clustering techniques. Conserved regions are then detected for each individual group. Conserved regions are scored using a BlockSimilarity score, a novel alignment scoring scheme that is appropriate for this application. Degenerate primers are then designed by reverse translating the conserved amino acid sequences to the corresponding nucleotide sequences. Our program, DePiCt, was written in BioPerl and was tested on the Toll-Interleukin Receptor (TIR)and the non-TIR family of plant resistance genes. Existing programs for degenerate primer design were unable to find primers for these data sets.