Functional and Computational Analysis of RNA-binding Proteins and Their Roles in Cancer PDF Download
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Author: Yarden Katz
Publisher:
ISBN:
Category :
Languages : en
Pages : 241
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Book Description
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.
Author: Yarden Katz
Publisher:
ISBN:
Category :
Languages : en
Pages : 241
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Book Description
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.
Author: Elan A. Shatoff
Publisher:
ISBN:
Category : Molecular structure
Languages : en
Pages : 0
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Book Description
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.
Author: Gene W. Yeo
Publisher: Springer
ISBN: 3319290738
Category : Medical
Languages : en
Pages : 335
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Book Description
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.
Author: Xiao Li
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Gene W. Yeo
Publisher: Springer
ISBN: 1493912216
Category : Science
Languages : en
Pages : 474
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Book Description
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.
Author: Michael Uhl
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
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
Author: Jane Y. Wu
Publisher: Springer Science & Business Media
ISBN: 364231659X
Category : Medical
Languages : en
Pages : 256
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Book Description
Accumulating evidence supports the role of defects in post-transcriptional gene regulation in the development of cancer. RNA and Cancer examines the recent advances in our understanding of post-transcriptional gene regulation, especially RNA processing and its role in cancer development and treatment. A particular focus is mRNA splicing, but other topics such as microRNAs, mRNA stability, the perinucleolar compartment, and oligonucleotide therapeutics are also covered in detail. All chapters have been written by internationally renowned experts. The book is intended for all with an interest in gene regulation and cancer biology, and especially for those not directly working on RNA biology, including clinicians and medical students. It is hoped that it will stimulate further innovative research collaborations between RNA biologists and cancer researchers to the benefit of patients.
Author: Kiyoshi Nagai
Publisher: Oxford University Press, USA
ISBN:
Category : Medical
Languages : en
Pages : 302
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Book Description
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.
Author:
Publisher: Academic Press
ISBN: 0128171944
Category : Medical
Languages : en
Pages : 444
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Book Description
RNA-based Regulation in Human Health and Disease offers an in-depth exploration of RNA mediated genome regulation at different hierarchies. Beginning with multitude of canonical and non-canonical RNA populations, especially noncoding RNA in human physiology and evolution, further sections examine the various classes of RNAs (from small to large noncoding and extracellular RNAs), functional categories of RNA regulation (RNA-binding proteins, alternative splicing, RNA editing, antisense transcripts and RNA G-quadruplexes), dynamic aspects of RNA regulation modulating physiological homeostasis (aging), role of RNA beyond humans, tools and technologies for RNA research (wet lab and computational) and future prospects for RNA-based diagnostics and therapeutics. One of the core strengths of the book includes spectrum of disease-specific chapters from experts in the field highlighting RNA-based regulation in metabolic & neurodegenerative disorders, cancer, inflammatory disease, viral and bacterial infections. We hope the book helps researchers, students and clinicians appreciate the role of RNA-based regulation in genome regulation, aiding the development of useful biomarkers for prognosis, diagnosis, and novel RNA-based therapeutics. Comprehensive information of non-canonical RNA-based genome regulation modulating human health and disease Defines RNA classes with special emphasis on unexplored world of noncoding RNA at different hierarchies Disease specific role of RNA - causal, prognostic, diagnostic and therapeutic Features contributions from leading experts in the field
Author: Alexandros Armaos
Publisher:
ISBN:
Category :
Languages : en
Pages : 110
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Book Description
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.
