Finding RNA structure in the unstructured RBPome

BACKGROUND: RNA-binding proteins (RBPs) play vital roles in many processes in the cell. Different RBPs bind RNA with different sequence and structure specificities. While sequence specificities for a large set of 205 RBPs have been reported through the RNAcompete compendium, structure specificities are known for only a small fraction. The main limitation lies in the design of the RNAcompete technology, which tests RBP binding against unstructured RNA probes, making it difficult to infer structural preferences from these data. We recently developed RCK, an algorithm to infer sequence and structural binding models from RNAcompete data. The set of binding models enables, for the first time, a large-scale assessment of RNA structure in the RBPome. RESULTS: We re-validate and uncover the role of RNA structure in the RPBome through novel analysis of the largest-scale dataset to date. First, we show that RNA structure exists in presumably unstructured RNA probes and that its variability is correlated with RNA-binding. Second, we examine the structural binding preferences of RBPs and discover an overall preference to bind RNA loops. Third, we significantly improve protein-binding prediction using RNA structure, both in vitro and in vivo. Lastly, we demonstrate that RNA structural binding preferences can be inferred for new proteins from solely their amino acid content. CONCLUSIONS: By counter-intuitively demonstrating through our analysis that we can predict both the RNA structure of and RBP binding to these putatively unstructured RNAs, we transform a compendium of RNA-binding proteins into a valuable resource for structure-based binding models. We uncover the important role RNA structure plays in protein-RNA interaction for hundreds of RNA-binding proteins

Flexible microwave system to measure the electron number density and quantify the communications impact of electric thruster plasma plumes

An advanced microwave interferometric system operating in the Ku (12–18 GHz) band has been implemented for use in very large vacuum chambers to determine the effects of electromagnetic wave propagation through a plasma plume created by a space electric propulsion thruster. This diagnostic tool is used to nonintrusively obtain the local electron number density as well as provide information necessary for understanding impact to communications and other spacecraft electromagnetic systems. The use of a nonintrusive electromagnetic measurement provides highly accurate line integrated density and avoids problems caused by intrusive measurement techniques. If the plasma is symmetrical, local plasma density can also be determined accurately using well known inversion techniques. A network analyzer acts as a transmitter and receiver while a two axis positioning system maps the amplitude and phase variation of a transmitted signal over one plane of the plasma plume. The utilization of a 6 m×9 m vacuum chamber effectively minimizes plasma boundary effects, but the longer cable path lengths have required a frequency conversion circuit to reduce power loss and phase uncertainty at high frequencies. Two studies are presented: the first is a measurement of the local electron density in the plume of a 1 kW arcjet and the second is a measurement of attenuation in the plume of a stationary plasma thruster. Both the arcjet and SPT emit a steady state conical unmagnetized plasma that is radially symmetric. The arcjet peak density is 1015–1016 m−3 along centerline and the SPT peak density is 1016–1017 m−3 along centerline. © 1997 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71094/2/RSINAK-68-2-1189-1.pd

The RNA workbench: Best practices for RNA and high-throughput sequencing bioinformatics in Galaxy

RNA-based regulation has become a major research topic in molecular biology. The analysis of epigenetic and expression data is therefore incomplete if RNA-based regulation is not taken into account. Thus, it is increasingly important but not yet standard to combine RNA-centric data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq. Here, we present the RNA workbench, a comprehensive set of analysis tools and consolidated workflows that enable the researcher to combine these two worlds. Based on the Galaxy framework the workbench guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses that are independent of command-line knowledge. Currently, it includes more than 50 bioinformatics tools that are dedicated to different research areas of RNA biology including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-seq analysis and RNA target prediction. The workbench is developed and maintained by experts in RNA bioinformatics and the Galaxy framework. Together with the growing community evolving around this workbench, we are committed to keep the workbench up-to-date for future standards and needs, providing researchers with a reliable and robust framework for RNA data analysis

RF signal impact study of an SPT

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76213/1/AIAA-1996-2706-928.pd

RCAS: an RNA centric annotation system for transcriptome-wide regions of interest

In the field of RNA, the technologies for studying the transcriptome have created a tremendous potential for deciphering the puzzles of the RNA biology. Along with the excitement, the unprecedented volume of RNA related omics data is creating great challenges in bioinformatics analyses. Here, we present the RNA Centric Annotation System (RCAS), an R package, which is designed to ease the process of creating gene-centric annotations and analysis for the genomic regions of interest obtained from various RNA-based omics technologies. The design of RCAS is modular, which enables flexible usage and convenient integration with other bioinformatics workflows. RCAS is an R/Bioconductor package but we also created graphical user interfaces including a Galaxy wrapper and a stand-alone web service. The application of RCAS on published datasets shows that RCAS is not only able to reproduce published findings but also helps generate novel knowledge and hypotheses. The meta-gene profiles, gene-centric annotation, motif analysis and gene-set analysis provided by RCAS provide contextual knowledge which is necessary for understanding the functional aspects of different biological events that involve RNAs. In addition, the array of different interfaces and deployment options adds the convenience of use for different levels of users. RCAS is available at http://bioconductor.org/packages/release/bioc/html/RCAS.html and http://rcas.mdc-berlin.de

Plume characterization of the SPT-100

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76626/1/AIAA-1996-3298-655.pd

DLocalMotif: a discriminative approach for discovering local motifs in protein sequences

Motivation: Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery

The effectiveness of digital storytelling in the classrooms: a comprehensive study

In recent years the use of new technologies in educational systems has increased worldwide as digital cameras, personal computers, scanners, and easy-to-use software have become available to educators to harness the digital world. The impact of new technologies in educational contexts has been mostly positive as new technologies have given educators the opportunity to enhance their knowledge, skills, and therefore enhance the standard of education. Researchers have found that student engagement, achievement and motivation are enhanced through integration of such technologies. However, education systems still face many challenges: one of these challenges is how to enhance student engagement to provide better educational outcomes. It has become increasingly important to use innovative pedagogical models to engage learners. Digital storytelling is one of the innovative pedagogical approaches that can engage students in deep and meaningful learning. This research project aimed to create a constructivist learning environment with digital storytelling. The research investigated the pedagogical aspects of digital storytelling and the impact of digital storytelling on student learning when teachers and students use digital stories. A multi-site case study was conducted in one Australian school at primary and secondary levels. In selected classrooms, students and teachers had the opportunity to engage in innovative learning experiences based on digital storytelling. In order to enhance the reliability and validity of the research, multiple methods of data collection and analysis were used. Data was collected with qualitative and quantitative methods. An evaluation rubric was used to collect quantitative data, while interviews and observation were used to collect qualitative data. Data collection was guided by a mixed methods research design in order to evaluate if and how digital storytelling enhances teaching and learning outcomes. The findings from this study suggest that digital storytelling is a powerful tool to integrate instructional messages with learning activities to create more engaging and exciting learning environments. It is a meaningful approach for creating a constructivist learning environment based on novel principles of teaching and learning. Thus, this approach has the potential to enhance student engagement and provide better educational outcomes for learners

Chloroplast cold-resistance is mediated by the acidic domain of the RNA binding protein CP31A

Chloroplast RNA metabolism is characterized by long-lived mRNAs that undergo a multitude of post-transcriptional processing events. Chloroplast RNA accumulation responds to environmental cues, foremost light and temperature. A large number of nuclear-encoded RNA-binding proteins (RBPs) are required for chloroplast RNA metabolism, but we do not yet know how chloroplast RBPs convert abiotic signals into gene expression changes. Previous studies showed that the chloroplast ribonucleoprotein 31A (CP31A) is required for the stabilization of multiple chloroplast mRNAs in the cold, and that the phosphorylation of CP31A at various residues within its N-terminal acidic domain (AD) can alter its affinity for RNA in vitro. Loss of CP31A leads to cold sensitive plants that exhibit bleached tissue at the center of the vegetative rosette. Here, by applying RIP-Seq, we demonstrated that CP31A shows increased affinity for a large number of chloroplast RNAs in vivo in the cold. Among the main targets of CP31A were RNAs encoding subunits of the NDH complex and loss of CP31A lead to reduced accumulation of ndh transcripts. Deletion analyses revealed that cold-dependent RNA binding and cold resistance of chloroplast development both depend on the AD of CP31A. Together, our analysis established the AD of CP31A as a key mediator of cold acclimation of the chloroplast transcriptome

Determinants of promoter and enhancer transcription directionality in metazoans

Divergent transcription from promoters and enhancers is pervasive in many species, but it remains unclear if it is a general feature of all eukaryotic cis regulatory elements. To address this, here we define cis regulatory elements in C. elegans, D. melanogaster and H. sapiens and investigate the determinants of their transcription directionality. In all three species, we find that divergent transcription is initiated from two separate core promoter sequences and promoter regions display competition between histone modifications on the +1 and -1 nucleosomes. In contrast, promoter directionality, sequence composition surrounding promoters, and positional enrichment of chromatin states, are different across species. Integrative models of H3K4me3 levels and core promoter sequence are highly predictive of promoter and enhancer directionality and support two directional classes, skewed and balanced. The relative importance of features to these models are clearly distinct for promoters and enhancers. Differences in regulatory architecture within and between metazoans are therefore abundant, arguing against a unified eukaryotic model