Download or read book Functional and Computational Analysis of RNA binding Proteins and Their Roles in Cancer written by Yarden Katz and published by . This book was released on 2014 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is concerned with mRNA processing in mammalian cells and proceeds in two parts. In the first part, I introduce a computational framework for inferring the abundances of mRNA isoforms using high-throughput RNA sequencing data. This framework was applied to study the targets of the ubiquitous splicing factor hnRNP H in human cells. In the second part, I describe an experimental study of the Musashi (hnRNP-like) family of RNA-binding proteins in stem cells and cancer cells, which incorporates computational analyses that rely heavily on the framework developed in part one. In sum, this work provides a computational framework of general use in global analyses of RNA processing and its protein regulators, as well as functional insights into a family of poorly understood RNA-binding proteins. Several related analyses and techniques developed as part of the thesis are described in Appendix A-C. Appendix A describes a study of activity-dependent gene expression and mRNA processing in the mouse olfactory bulb. It uses computational techniques developed in part one of the thesis. Appendix B describes a technique for quantitative visualization of alternative splicing from RNA sequencing data and its integration into a genome browser. Appendix C describes a method for clonal analysis of neural stem cell growth and differentiation in culture using live imaging and `microdot' plates, developed as part of the work presented in part one of the thesis.

Download or read book Computational Analysis of the Interplay Between RNA Structure and Function written by Elan A. Shatoff and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: RNA is ubiquitous in the cellular environment, and it can function in innumerable ways with a variety of interaction partners. A RNA molecule's structure, in particular the set of base pairing interactions between the nucleotides of the molecule known as secondary structure, can help determine its function. Since most proteins can only bind to either single stranded or double stranded RNA, RNA secondary structure can also help determine where and how RNA-protein binding interactions occur. In this work I investigate computational models for RNA-protein interactions in a variety of different contexts. In Chapter 2 I probe the effect of single nucleotide variations on RNA-protein binding as mediated by RNA secondary structure. Single nucleotide variations are single nucleotide changes in an organism's genome that can often cause disease, and may do so through a number of different mechanisms. In this work we propose that sequence changes can affect accessibility to protein binding sites through changes in secondary structure, even when these sequence changes occur tens of nucleotides outside of protein binding sites. We find that single nucleotide variations can have a many fold effect on the binding affinity of proteins for RNA, and characterize the genome-wide effect of single nucleotide variations on HuR binding. HuR is a single-stranded RNA binding protein that binds to AU-rich sequences, and has links to diseases such as cancer. We also find an asymmetry in this effect for HuR, indicating that this effect may be under selection. Following the previous work, which utilizes a model incorporating single stranded RNA binding proteins into RNA secondary structure folding, I introduce a model for incorporating double stranded RNA binding proteins (dsRBPs) into RNA secondary structure partition function calculations in Chapter 3. The dsRBPs are an important but understudied class of proteins that have uses in a wide range of processes. We implement our model in the ViennaRNA package, and validate it by calculating a number of experimental observables for transactivation response element RNA-binding protein. We find that RNA secondary structure can have a many fold effect on the effective binding affinity of dsRBPs, and show that calculated affinities for pre-miRNA-like constructs correlate with experimentally measured processing rates. Our model provides a novel method for interrogating the interplay between dsRBPs and RNA secondary structure. In Chapter 4 I study RNA-protein interactions in a different context, and investigate the role of Shine-Dalgarno (SD) sequences in translation in the Bacteroidetes. The Bacteroidetes are a phylum of bacteria known to rarely use SD sequences, but after performing a survey of SD usage in the phylum we find that certain ribosomal protein genes utilize them, particularly rpsU. A cryo-electron microscopy structure of the ribosome from Flavobacterium johnsoniae, a member of the Bacteroidetes, also shows that S21, which is encoded by the ribosomal open reading frame rpsU, sequesters the anti-Shine-Dalgarno (ASD) sequence. In our survey of SD sequences we also find covariation between the SD sequence of rpsU and the ASD sequence. These observations suggest an autoregulatory model for S21 in the Bacteroidetes.

Download or read book Computational Analysis of RNA binding Protein Target site Selection and Function written by Xiao Li and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Systems Biology of RNA Binding Proteins written by Gene W. Yeo and published by Springer. This book was released on 2014-09-08 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: After transcription in the nucleus, RNA binding proteins (RBPs) recognize cis-regulatory RNA elements within pre-mRNA sequence to form mRNA-protein (mRNP) complexes. Similarly to DNA binding proteins such as transcription factors that regulate gene expression by binding to DNA elements in the promoters of genes, RBPs regulate the fate of target RNAs by interacting with specific sequences or RNA secondary structural features within the transcribed RNA molecule. The set of functional RNA elements recognized by RBPs within target RNAs and which control the temporal, functional and spatial dynamics of the target RNA define a putative “mRNP code”. These cis-regulatory RNA elements can be found in the 5’ and 3’ untranslated regions (UTRs), introns, and exons of all protein-coding genes. RNA elements in 5’ and 3’ UTRs are frequently involved in targeting RNA to specific cellular compartments, affecting 3’ end formation, controlling RNA stability and regulating mRNA translation. RNA elements in introns and exons are known to function as splicing enhancers or silencers during the splicing process from pre-mRNA to mature mRNA. This book provides case studies of RNA binding proteins that regulate aspects of RNA processing that are important for fundamental understanding of diseases and development. Chapters include systems-level perspectives, mechanistic insights into RNA processing and RNA Binding proteins in genetic variation, development and disease. The content focuses on systems biology and genomics of RNA Binding proteins and their relation to human diseases.

Download or read book Computational Analysis and Prediction of RNA protein Interactions written by Michael Uhl and published by . This book was released on 2022* with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: This dissertation is about the computational analysis and prediction of RNA-protein interactions. Ribonucleic acids (RNAs) and proteins both are essential for the control of gene expression in our cells. Gene expression is the process by which a functional gene product, namely a protein or an RNA, is produced from a gene, starting from the gene region on the DNA with the transcription of an RNA. Once regarded primarily as a messenger to transmit the protein information, recent years have seen RNA moving further into the biomedical spotlight, thanks to its increasingly uncovered roles in regulating gene expression. In addition, RNA has showcased its therapeutic potential, as famously demonstrated by the groundbreaking success of RNA vaccines in the COVID-19 pandemic. However, RNAs rarely function on their own: In humans, more than 1,500 different RNA-binding proteins (RBPs) are involved in controlling the various stages of an RNA's life cycle, creating a highly complex regulatory interplay between RNAs and proteins. It is therefore of fundamental importance to study these RNA-protein interactions, in order to deepen our understanding of gene expression. Over the last decade, CLIP-seq has become the dominant experimental method to identify the set of cellular RNA binding sites for an RBP of interest. However, analysing the resulting CLIP-seq data can be challenging, as there are many analysis steps and CLIP-seq protocol variants available, each requiring specific adaptations to the analysis workflow. Consequently, there is a need for analysis guidelines, providing easy access to tools, as well as the constant improvement of tools and workflows to increase the accuracy of the analysis results. The first set of works included in this thesis (publications P1, P4, and P5) deals with these topics, by providing a review article on CLIP-seq data analysis, as well as two articles on how to further improve CLIP-seq data analysis. Publication P1 supplies readers with an overview of tools and protocols, as well as guidelines to conduct a successful analysis, drawing largely from our own experience with analysing CLIP-seq data. Publication P4 demonstrates the issues current binding site identification tools have with CLIP-seq data from RBPs that bind to processed RNAs, and that the integration of RNA processing information improves the resulting binding site quality. On top of this, publication P5 presents Peakhood, the first tool that utilizes RNA processing information in order to increase the quality of RBP binding sites identified from CLIP-seq data. A natural drawback of experimental methods is that a target RNA needs to be sufficiently expressed in the observed cells for an RNA-protein interaction to be detected. Hence, since gene expression is a dynamic process that differs between cell types, time points, and conditions, a CLIP-seq experiment cannot recover the complete set of cellular RBP binding sites. This creates a demand for computational methods which can learn the binding properties of an RBP from existing CLIP-seq data, in order to predict RBP binding sites on any given target RNA. Besides interacting with proteins, RNAs can also interact with other RNAs, further increasing the amount of possible regulatory interactions between RNAs and proteins. In this regard, long non-coding RNAs (lncRNAs), a large class of non-protein-coding RNAs whose functions are still vastly unexplored, have become especially important, as it has been shown that they can engage in RNA-RNA interactions, whose regulatory mechanisms also include RNA-protein interactions. As such mechanistic studies are typically slow and expensive, computational tools that combine RNA-protein and RNA-RNA interaction predictions to infer potential mechanisms could be of great help, e.g., by screening a set of target RNAs and proteins and suggesting plausible mechanisms for experimental validation. The second set of works included in this thesis (publications P2 and P3) thus deals with the computational prediction of RNA-protein interactions, RNA-RNA interactions and the functional mechanisms that can be inferred from these interactions. Publication P2 introduces MechRNA, the first tool to infer functional mechanisms of lncRNAs based on their predicted interactions with RBPs and other RNAs, as well as gene expression data. We demonstrated MechRNA's capability to identify formerly described lncRNA mechanisms and experimentally validated one prediction, underlining its value for functional lncRNA studies. Finally, publication P3 presents RNAProt, a flexible and performant RBP binding site prediction tool based on recurrent neural networks. Compared to other popular deep learning methods, RNAProt achieves state-of-the-art predictive performance, as well as superior runtime efficiency. In addition, it is more feature-rich than any other available method, including the support of user-defined predictive features. We further showed that its visualizations agree with known RBP binding preferences, and demonstrated that its additional predictive features can increase the specificity of predictions

Download or read book RNA Processing written by Gene W. Yeo and published by Springer. This book was released on 2016-06-02 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ribonucleic acid (RNA) binding proteins currently number in the thousands and defects in their function are at the heart of diseases such as cancer and neurodegeneration. RNA binding proteins have become implicated in the intricate control of surprisingly diverse biological settings, such as circadian rhythm, stem cell self-renewal, oncogenesis and germ cell development. This book surveys a range of genome-wide and systems approaches to studying RNA binding proteins, the importance of RNA binding proteins in development, cancer and circadian rhythm.

Download or read book Computational Analysis and Annotation of Structurally Functional RNAs written by Milad Miladi and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: This work is a dissertation about computational methodologies and analyses of ribonucleic acid (RNA) molecules based on their sequence and structure properties. RNA is an essential molecule of living cells that acts as the career of the proteins genetic information and also as a regulatory functional element that contributes to cellular mechanisms. While only less than 3% of the human genome is encoding for known proteins, more than 85% of the genome is getting transcribed into RNA. Alone for the human genome, tens of thousands of non-coding RNA genes exist bearing pervasive functions. Despite the important roles of RNAs, functional and the regulatory mechanisms of a large number of the non-coding and protein-coding RNAs is either unknown or poorly understood. To solve this challenge, computational methodologies are a vital asset for a scalable and systematic analysis and annotation of RNAs with unknown functions. RNAs are polymer molecules that fold into complex structures within the cells. For a functional RNA, its folded structure often plays an important role and is better conserved than the polymer sequence through evolution. Therefore, it is essential to consider both the sequence and structure information for the task of annotation and discovery of functional RNAs using the computational approaches. Comparative methodologies utilise the evolutionary conservation information of both sequence and structure. They are pivot assets for providing reliable structure prediction and annotation of functional RNAs. Over the past decade, millions of RNA sequences have been obtained using techniques such as genomic screens and high-throughput sequencing experiments. These techniques produce up to several thousands or even millions of sequences and can be applied over all the domains of life. Analysing these large collections of sequences, for the evaluation and annotation of functional RNAs, demands efficient optimisation algorithms with sufficiently accurate models. Additionally, since the cells rely on heterogeneous molecules and mechanisms to function, integrative analysis of biological data is commonly required nowadays. Therefore, computational approaches based on techniques such as machine learning are needed to provide comprehensive strategies with high efficiencies also at different levels of the data. This thesis addresses some substantial challenges for the evaluation and annotation of functional RNAs by presenting novel contributions using computational analysis, optimisation algorithms, comparative methodologies, clustering approaches. The personal contributions are presented in the form of six works that are encompassed as six publications from three domains for the tasks of annotation, discovery, and analysis of functional RNAs. SPARSE and Pankov are two novel contributed algorithms for the problem of simultaneous alignment and folding (SA&F) of RNAs. SPARSE achieves a quadratic complexity without sequence-based heuristics by utilising a strong sparsification over the ensemble of possible secondary structure formations. The second SA&F algorithm Pankov, enables a fast simultaneous alignment and folding of RNAs while cohering to the nearest-neighbour thermodynamics principle of the standard RNA folding model. Pankov provides the most accurate SA&F probabilistic energy model until today, by mapping the nearest-neighbour principle to a Markov scheme using conditional in-loop probabilities. RNAscClust and GraphClust2 are presented for scalable clustering of RNA sequences based on sequence and structure. The RNAscClust methodology enables a linear-time clustering of paralogous RNAs based on their sequence and structure. Both tools are machine learning approaches that utilise graph kernel and locality-sensitive hashing schemes to support the clustering of input entries in an asymptotically linear time. RNAscClust incorporates orthogonal structure conservation to enhance the clustering and annotation performance. GraphClust2 is an integrative approach for the accessible and scalable clustering of RNAs to identify structurally conserved non-coding RNAs and motifs. GraphClust2 outperforms its predecessor and importantly supports diverse sources of genomic and experimental data in an accessible fashion. GraphClust2 bridges the gap between high-throughput sequencing experiments and the structure-based methodologies for functional RNA discovery. The final topic covered by this thesis is the mutational analysis of RNA secondary structure and function. A large-scale compilation and statistical analysis of somatic cancer synonymous mutations is presented. The analysis and experiments reveal that the synonymous mutations, despite not changing encoded protein sequence, can have substantial impacts on the gene expression levels and considerably disrupt the local secondary structure of mRNAs. Finally, MutaRNA is presented as an accessible web-based solution for evaluating the impact of mutation on the RNA secondary structure and visualising the complex impacts of the mutation on the intra-molecular interactions potentials in an intuitive manner

Download or read book Long Non Coding RNAs in Cancer written by Alfons Navarro and published by Humana. This book was released on 2022-06-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents techniques needed for the study of long non-coding RNAs (lncRNAs) in cancer from their identification to functional characterization. Chapters guide readers through identification of lncRNA expression signatures in cancer tissue or liquid biopsies by RNAseq, single Cell RNAseq, Phospho RNAseq or Nanopore Sequencing techniques; validation of lncRNA signatures by Real time PCR, digital PCR or in situ hybridization; and functional analysis by siRNA or CRISPR based methods for lncRNA silencing or overexpression. Lipid based nanoparticles for delivery of siRNAs in vivo, lncRNA-protein interactions, viral lncRNAs and circRNAs are also treated in this volume. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and practical, Long Non-Coding RNAs in Cancer aims to provide a collection of laboratory protocols, bioinformatic pipelines, and review chapters to further research in this vital field.

Download or read book Computational Characterization of Protein RNA Interactions and Implications for Phase Separation written by Alexandros Armaos and published by . This book was released on 2020 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite what was previously considered, the role of RNA is not only to carry the geneticinformation from DNA to proteins. Indeed, RNA has proven to be implicated in morecomplex cellular processes. Recent evidence suggests that transcripts have a regulatoryrole on gene expression and contribute to the spatial and temporal organization of theintracellular environment. They do so by interacting with RNA-binding proteins (RBPs)to form complex ribonucleoprotein (RNP) networks, however the key determinants thatgovern the formation of these complexes are still not well understood. In this work, I willdescribe algorithms that I developed to estimate the ability of RNAs to interact withproteins. Additionally, I will illustrate applications of computational methods to proposean alternative model for the function of Xist lncRNA and its protein network.Finally, I will show how computational predictions can be integrated with highthroughput approaches to elucidate the relationship between the structure of the RNA andits ability to interact with proteins. I conclude by discussing open questions and futureopportunities for computational analysis of cell's regulatory network.Overall, the underlying goal of my work is to provide biologists with new insights intothe functional association between RNAs and proteins as well as with sophisticated toolsthat will facilitate their investigation on the formation of RNP complexes.

Download or read book Comprehensive Discovery and Analysis of RNA Binding Protein dependent Post transcriptional Events in Mammalian Systems written by Stephanie C. Huelga and published by . This book was released on 2014 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nascent transcripts produced by RNA polymerase II in eukaryotic cells are subject to extensive processing prior to the generation of a functional messenger RNA (mRNA). These RNAs are generally found coated with RNA binding proteins (RBPs), which act in concert to regulate RNA processing events, including splicing, polyadenylation, and RNA stability. The aggregate effect of various RBPs on a given RNA transcript eventually dictates its fate, a phenomenon referred to as the RNP code. The precise control of RNA processing by RBPs is incredibly important for cellular homeostasis, defects of which lead to numerous accounts of human genetic diseases in many tissues. With the emergence of genome-wide methods for detecting direct binding of RBPs on target RNAs, coupled with technologies to measure changes in various aspects of RNA processing, global rules and insights for individual RBPs have been revealed. However, few studies have combined regulatory changes for more than one RBP to better understand their combinatorial effects on RNA targets. Additionally, despite the importance of RBPs, we still do not have the complete repertoire of which proteins bind to RNA, and which of these bind simultaneously with other RBPs to constitute the "RBP-RNA interactome". Here, I conduct genome-wide RNA processing analyses in mammalian cells, integrating regulation and binding information for multiple RBPs, including disease-related RBPs, the highly abundant heterogeneous nuclear ribonucleoparticle (hnRNP) proteins, and many previously uncharacterized RBPs. This battery of computational and experimental assays provides insight into the unique roles of hundreds of individual RBPs, as well as the extent of coordinated regulation between RBPs. I also describe a systematic approach to identifying the proteins that interact with RNA simultaneously with hnRNP proteins. Not limited to only mRNA-bound proteins, my strategy identifies thousands of hnRNP protein interactors, including putative novel proteins that interact with mRNA and pre-mRNA, and have biochemical and statistical attributes of known RBPs. My findings expand the repertoire of RNA-interacting RBPs and provide a resource for the study of human simultaneous RBP-RBP interactomes. This comprehensive analysis of RBPs investigates their specific roles in the regulation of RNA processing yielding interesting findings for the RNA biology field and insights into how misregulation can impact human disease.

Download or read book Genomic and Precision Medicine written by Geoffrey S. Ginsburg and published by Academic Press. This book was released on 2022-04-09 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic and Precision Medicine: Oncology, Third Edition focuses on the applications of genome discovery as research points to personalized cancer therapies. Each chapter is organized to cover the application of genomics and personalized medicine tools and technologies to a) Risk Assessment and Susceptibility, b) Diagnosis and Prognosis, c) Pharmacogenomics and Precision Therapeutics, and d) Emerging and Future Opportunities in the field. Provides a comprehensive volume written and edited by oncology genomic specialists for oncology health providers Includes succinct commentary and key learning points that will assist providers with their local needs for implementation of genomic and personalized medicine into practice Presents an up-to-date overview on major opportunities for genomic and personalized medicine in practice Covers case studies that highlight the practical use of genomics in the management of patients

Download or read book Molecular Biology of The Cell written by Bruce Alberts and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Biological Sequence Analysis written by Richard Durbin and published by Cambridge University Press. This book was released on 1998-04-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

Download or read book RNA protein Interactions written by Kiyoshi Nagai and published by Oxford University Press, USA. This book was released on 1994 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of RNA-protein interactions is crucial to understanding the mechanisms and control of gene expression and protein synthesis. The realization that RNAs are often far more biologically active than was previously appreciated has stimulated a great deal of new research in this field. Uniquely, in this book, the world's leading researchers have collaborated to produce a comprehensive and current review of RNA-protein interactions for all scientists working in this area. Timely, comprehensive, and authoritative, this new Frontiers title will be invaluable for all researchers in molecular biology, biochemistry and structural biology.

Download or read book RNA RNA Interactions written by Frank J. Schmidt and published by Humana Press. This book was released on 2014-10-29 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this volume expert researchers in the field detail many of the methods which are now commonly used to study RNA. These methods are presented as a guidebook to scientists who are experienced with RNA research and want to brush up on a new technique. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Thorough and intuitive, RNA-RNA Interactions: Methods and Protocols guides scientists investigating biological systems and studying RNA.

Download or read book Protein Nucleic Acid Interactions written by Phoebe A. Rice and published by Royal Society of Chemistry. This book was released on 2008-05-22 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides both in-depth background and up-to-date information in this area. The chapters are organized by general themes and principles, written by experts who illustrate topics with current findings. Topics covered include: - the role of ions and hydration in protein-nucleic acid interactions - transcription factors and combinatorial specificity - indirect readout of DNA sequence - single-stranded nucleic acid binding proteins - nucleic acid junctions and proteins, - RNA protein recognition - recognition of DNA damage. It will be a key reference for both advanced students and established scientists wishing to broaden their horizons.

Download or read book Handbook of RNA Biochemistry written by Roland K. Hartmann and published by John Wiley & Sons. This book was released on 2015-06-22 with total page 1370 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a highly acclaimed handbook and ready reference. Unmatched in its breadth and quality, around 100 specialists from all over the world share their up-to-date expertise and experiences, including hundreds of protocols, complete with explanations, and hitherto unpublished troubleshooting hints. They cover all modern techniques for the handling, analysis and modification of RNAs and their complexes with proteins. Throughout, they bear the practising bench scientist in mind, providing quick and reliable access to a plethora of solutions for practical questions of RNA research, ranging from simple to highly complex. This broad scope allows the treatment of specialized methods side by side with basic biochemical techniques, making the book a real treasure trove for every researcher experimenting with RNA.