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With increasing number of non-coding RNA families being identified, there is strong interest in developing computational methods to estimate sequence alignment and secondary structure. I developed TurboFold II, an algorithm that takes multiple, unaligned homologous RNA sequences, and outputs the predicted secondary structures and the structural alignment of the sequences. Secondary structure conservation information is incorporated in the alignment using a match score, calculated from estimated base pairing probabilities, to represent the secondary structural similarity between nucleotide positions in the two sequences. TurboFold II computes a multiple sequence alignment, based on a probabilistic consistency transformation and a hierarchically computed guide tree. TurboFold II has comparable alignment accuracy with MAFFT and higher accuracy than other tools. TurboFold II also has comparable structure prediction accuracy as the original TurboFold algorithm, which is one of the most accurate methods. I adapted the TurboFold II algorithm for prediction of RNA secondary structures to utilize base pairing probabilities guided by SHAPE experimental data. Results demonstrate that the SHAPE mapping data for a sequence improves structure prediction accuracy for other homologous sequences beyond the accuracy obtained by sequence comparison alone.I also developed TurboHomology, a method for secondary structure modeling and alignment for a newly discovered sequence of an RNA family with a known secondary structure and an existing multiple sequence alignment. TurboHomology achieves greater accuracy than TurboFold II by taking advantage of the known structure and alignment.
This volume provides protocols and procedures for determining and modeling RNA structure. Chapters guide the reader through protocols for RNA secondary structure prediction, single sequence modeling, Crumple, RNAstructure to model conserved secondary structures with multiple homologs, the prediction of bimolecular secondary structures with RNAstructure, STarMir, protocols for structure mapping, mapping data to constrain or restrain RNA secondary structure prediction with RNAstructure, unassigned NMR resonances, modeling protocols for Rosetta FARFAR, RNAComposer , ModeRNA, and MC-Fold. 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 tips on troubleshooting and avoiding known pitfalls. Authoritative and Practical, RNA Structure Determination: Methods and Protocols aims to ensure successful results in the further study of this vital field.
This volume provides protocols and procedures for determining and modeling RNA structure. Chapters guide the reader through protocols for RNA secondary structure prediction, single sequence modeling, Crumple, RNAstructure to model conserved secondary structures with multiple homologs, the prediction of bimolecular secondary structures with RNAstructure, STarMir, protocols for structure mapping, mapping data to constrain or restrain RNA secondary structure prediction with RNAstructure, unassigned NMR resonances, modeling protocols for Rosetta FARFAR, RNAComposer, ModeRNA, and MC-Fold. 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 tips on troubleshooting and avoiding known pitfalls. Authoritative and Practical, RNA Structure Determination: Methods and Protocols aims to ensure successful results in the further study of this vital field.
With the dramatic increase in RNA 3D structure determination in recent years, we now know that RNA molecules are highly structured. Moreover, knowledge of RNA 3D structures has proven crucial for understanding in atomic detail how they carry out their biological functions. Because of the huge number of potentially important RNA molecules in biology, many more than can be studied experimentally, we need theoretical approaches for predicting 3D structures on the basis of sequences alone. This volume provides a comprehensive overview of current progress in the field by leading practitioners employing a variety of methods to model RNA 3D structures by homology, by fragment assembly, and by de novo energy and knowledge-based approaches.
The existence of genes for RNA molecules not coding for proteins (ncRNAs) has been recognized since the 1950's, but until recently, aside from the critically important ribosomal and transfer RNA genes, most focus has been on protein coding genes. However, a long series of striking discoveries, from RNA's ability to carry out catalytic function, to discovery of riboswitches, microRNAs and other ribo-regulators performing critical tasks in essentially all living organisms, has created a burgeoning interest in this primordial component of the biosphere. However, the structural characteristics and evolutionary constraints on RNA molecules are very different from those of proteins, necessitating development of a completely new suite of informatic tools to address these challenges. In RNA Sequence, Structure, Function: Computational and Bioinformatic Methods, expert researchers in the field describe a substantial and relevant fraction of these methodologies from both practical and computational/algorithmic perspectives. Focusing on both of these directions addresses both the biologist interested in knowing more about RNA bioinformatics as well as the bioinformaticist interested in more detailed aspects of the algorithms. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results. Thorough and intuitive, RNA Sequence, Structure, Function: Computational and Bioinformatic Methods aids scientists in continuing to study key methods and principles of RNA bioinformatics.
Recent studies on the activities of RNA in the cell have revolutionized our understanding of the many roles played by this molecule. The first two editions of The RNA World (1993, 1999) shed light on the pre biotic era dominated by this versatile molecule, and provided an overview of the state of RNA research at the time. The new third edition of The RNA World updates this perspective, describing the vast array of newly discovered roles for RNA in the modern world. The updated original chapters are supplemented with new chapters on RNA protein complexes, snRNPs and snoRNPs, telomerase RNA, RNAi, microRNAs, noncoding RNA, and many other subjects. This book is essential reading for anyone interested in the biology of nucleic acids and gene regulation and a valuable resource for teaching these concepts
RNA exists at the heart of many important questions in biology today. Its diverse functionality is rooted in the wide range of structures RNA is able to form. The nucleotides in an RNA sequence possess the ability to form bonds with each other. Such bonding allows a strand of RNA to fold onto itself. In contrast to the iconic double helix structure of DNA, this results in intricate 3D conformations that vary with RNA sequence and in part allow the RNA to perform its cellular functions. The study of RNA's 2D folding pattern between bases in the sequence serves as an intermediate step to deciphering its complex final 3D formation. Determining this folding pattern, also called the secondary structure, remains a challenging task. In recent years, the advancement in DNA sequencing technology has popularized a number of chemical and enzymatic experiments that probe RNA molecules in a massively parallel fashion. These structure probing experiments can be performed both in vitro and in vivo and provide a wealth of information on RNA structure. The data coming from these experiments are typically quantified into a measure of reactivity per nucleotide. This reactivity is correlated with structure and thus this data is used to infer RNA structure. Combined with sequence information, these experimental datasets are typically incorporated into computational secondary structure prediction algorithms. Another class of psoralen-facilitated cross-linking experiments make use of psoralen's ability to form cross-links at interacting regions of RNA to directly probe base-pairing interactions in an RNA structure. These experiments provide direct structural information on an RNA and the resulting data have been particularly useful in uncovering alternative folding patterns for long RNA sequences. Despite the richness in experimental data, current data-driven secondary structure prediction methods suffer from major inaccuracies. In fact, while experimental protocols have been refined over the years, less progress has been made towards statistical characterization of structure probing data. This is even more true for the relatively new psoralen-facilitated cross-linking experiments. Further, most computational methods for structure prediction aim to predict a single optimal structure, whereas it is well-established that the same RNA sequence can exist in multiple conformations in nature. Thus, studying the entire Boltzmann ensemble of possible secondary structures for a given RNA can help uncover important underlying structures that would otherwise remain unknown. Additionally, prediction accuracy improves when abstract representations of RNA structures are used. The work done in this dissertation focuses on the development of computational tools to better utilize data coming from both types of experiments in the context of secondary structure prediction. First, we explored methods for improved signal extraction of structure probing data using signal processing techniques. We then developed a probabilistic model for characterization of structure probing data by analyzing statistical properties of such data. This model was incorporated into thermodynamics based secondary structure prediction algorithms for improved structure prediction. Finally, we studied the use of psoralen-facilitated cross-linking data to recover the structural landscape for a given RNA. We introduced a probabilistic model for these data and provide an extension of the previously developed structural landscape explorer, SLEQ. As these experiments are aimed at probing long RNAs, this extension makes use of abstract structural elements to help cluster similar structures and aggregate similar structural motifs.
This volume provides a wide spectrum of multidisciplinary approaches for studying RNA structure and dynamics, including detailed accounts of experimental and computational procedures. Chapters guide readers through cryo-electron microscopy, crystallography, isothermal titration calorimetry, small angle X-ray scattering, single-molecule Förster Energy transfer, X-ray free electron laser, atomic force microscopy, computational simulation, and prediction. 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 cutting-edge, RNA Structure and Dynamics aims to be a foundation for future studies and to be a source of inspiration for new investigations in the field.