Genome-Wide Approaches To Study Rna Secondary Structure

The central hypothesis of molecular biology depicts RNA as an intermediary conveyor of genetic information. RNA is transcribed from DNA and translated to proteins, the molecular machines of the cell. However, many RNAs do not encode protein and instead function as molecular machines themselves. The most famous examples are ribosomal RNAs and transfer RNAs, which together form the core translational machinery of the cell. Many other non-coding RNAs have been discovered including catalytic and regulatory RNAs. In many cases RNA function is tightly linked to its secondary structure, which is the collection of hydrogen bonds between complimentary RNA sequences that drives these molecules into their three dimensional structure. Over the last decade, technology for determining the sequence of DNA and RNA has advanced rapidly, making transcriptome-wide expression profiling fast and widely available. In this dissertation, I discuss recent efforts to leverage this powerful technology to study, not just RNA expression, but several other aspects of RNA function. In particular, I focus on three tightly linked aspects of RNA biology: RNA-secondary structure, RNA cleavage, and regulatory small RNAs. I introduce a database for integrating, comparing, and contrasting techniques for determining RNA secondary structure including a technique developed in my dissertation laboratory. Additionally, I discuss a newly improved technology capable of detecting RNA cleavage events. Finally, I integrate RNA secondary structure probing and RNA cleavage detection to interrogate a family of genes important for eukaryotic small RNA-mediated silencing. These diverse analyses are just a few examples of the vast promises offered by adapting RNA-sequencing technology to probe RNA function across many cellular processes

Insights into RNA design from novel molecular tools

RNA, previously recognized merely as a messenger of genetic information, has been recently rediscovered as a versatile molecule with a central role in cellular regulation. These regulatory functions are enabled by its specific chemical makeup that allows it to fold into intricate and flexible structures. In stark contrast with DNA, RNA forms a variety of structural motifs that serve as efficient points of contact in molecular recognition. It is therefore clear, that dynamic RNA structures dictate the binding availability of interfaces that play important roles in molecular regulation inside living cells. As such, the need for tools that can accurately capture and predict RNA structure in vivo continues to be essential to understand RNA function. To this end, my dissertation focuses on the development of molecular tools to predict and characterize accessible RNA interfaces in their native environment. First, I established the usefulness of a fluorescence-based in vivo oligonucleotide hybridization approach to identify accessible interfaces by characterizing numerous RNA regions in several biologically relevant molecules in E. coli. I then described these RNA interactions using a biophysical model based on thermodynamic principles and incorporating large sets of data collected using this fluorescence-based system. This approach displayed improved prediction capabilities of RNA accessibility compared to un-optimized versions without incorporation of in vivo data. Finally, I detailed the development and application of a high throughput tool for the large-scale characterization of accessible interfaces within native RNAs in a single experiment. In this approach, in vivo oligonucleotide hybridization was coupled to transcriptional elongation control to allow analysis via next generation sequencing. This tool was used to obtain complete landscapes of functional structure for 72 regulatory molecules in a single experiment (>1000 regions). Altogether the results of this high throughput approach revealed a pattern indicating that RNA-RNA interaction sites are either highly accessible or highly protected, suggesting their binding status (e.g. actively bound or unbound). In addition, within bacterial small RNAs, our approached revealed the role of the global regulator Hfq as universal structural relaxer. The compendium of these tools provides a unique and fundamental perspective in the study of functional RNA structure, namely, the identification of dynamic structures. Furthermore, the information provided by these approaches significantly aids in the design of synthetic RNAs for a variety of purposes, including gene expression control.Chemical Engineerin

Computational Methods for Comparative Non-coding RNA Analysis: from Secondary Structures to Tertiary Structures

Unlike message RNAs (mRNAs) whose information is encoded in the primary sequences, the cellular roles of non-coding RNAs (ncRNAs) originate from the structures. Therefore studying the structural conservation in ncRNAs is important to yield an in-depth understanding of their functionalities. In the past years, many computational methods have been proposed to analyze the common structural patterns in ncRNAs using comparative methods. However, the RNA structural comparison is not a trivial task, and the existing approaches still have numerous issues in efficiency and accuracy. In this dissertation, we will introduce a suite of novel computational tools that extend the classic models for ncRNA secondary and tertiary structure comparisons. For RNA secondary structure analysis, we first developed a computational tool, named PhyloRNAalifold, to integrate the phylogenetic information into the consensus structural folding. The underlying idea of this algorithm is that the importance of a co-varying mutation should be determined by its position on the phylogenetic tree. By assigning high scores to the critical covariances, the prediction of RNA secondary structure can be more accurate. Besides structure prediction, we also developed a computational tool, named ProbeAlign, to improve the efficiency of genome-wide ncRNA screening by using high-throughput RNA structural probing data. It treats the chemical reactivities embedded in the probing information as pairing attributes of the searching targets. This approach can avoid the time-consuming base pair matching in the secondary structure alignment. The application of ProbeAlign to the FragSeq datasets shows its capability of genome-wide ncRNAs analysis. For RNA tertiary structure analysis, we first developed a computational tool, named STAR3D, to find the global conservation in RNA 3D structures. STAR3D aims at finding the consensus of stacks by using 2D topology and 3D geometry together. Then, the loop regions can be ordered and aligned according to their relative positions in the consensus. This stack-guided alignment method adopts the divide-and-conquer strategy into RNA 3D structural alignment, which has improved its efficiency dramatically. Furthermore, we also have clustered all loop regions in non-redundant RNA 3D structures to de novo detect plausible RNA structural motifs. The computational pipeline, named RNAMSC, was extended to handle large-scale PDB datasets, and solid downstream analysis was performed to ensure the clustering results are valid and easily to be applied to further research. The final results contain many interesting variations of known motifs, such as GNAA tetraloop, kink-turn, sarcin-ricin and t-loops. We also discovered novel functional motifs that conserved in a wide range of ncRNAs, including ribosomal RNA, sgRNA, SRP RNA, GlmS riboswitch and twister ribozyme

Killing The Messenger: Exploring Novel Triggers For Messenger Rna Decay In Eukaryotes

The lifecycle of messenger RNAs is regulated by multiple layers beyond their primary sequence. In addition to carrying the information for protein synthesis, mRNAs are decorated with RNA binding proteins, marked with covalent chemical modifications, and fold into intricate secondary structures. However, the full set of information encoded by these “epitranscriptomic” layers is only partially understood, and is often only characterized for select transcripts. Thus, it is crucial to develop and apply transcriptome-wide analytical tools to probe the location and functional relevance of epitranscriptome features. In this dissertation, I focus on applying such methods toward better understanding determinants of mRNA stability, through using 1) High Throughput Annotation of Modified Nucleotides, 2) nuclease-mediated probing of RNA secondary structure, and 3) detection of partial mRNA degradation from RNA sequencing. I observe that chemical modifications tend to mark uncapped and small RNA fragments derived from mRNAs in plants and humans, suggesting a link between modifications and mRNA stability. I then show this link is direct through showing differential stability at Arabidopsis transcripts that change modification status during long-term salt stress. By probing secondary structure, I show a link between structure, smRNA production, and co-translational RNA decay. Finally, I develop a new in silico method to detect partial RNA degradation in mouse oocytes, and identify sequence elements that appear to block complete exonucleolytic transcript cleavage during meiosis. I then identify putative RNA binding proteins that might mediate this partial decay. In summary, I apply transcriptome-wide sequencing-based methods to survey the effects of covalent modifications, secondary structure, and RNA binding proteins on mRNA stability

Probing of RNA structures in a positive sense RNA virus reveals selection pressures for structural elements.

In single stranded (+)-sense RNA viruses, RNA structural elements (SEs) play essential roles in the infection process from replication to encapsidation. Using selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq) and covariation analysis, we explore the structural features of the third genome segment of cucumber mosaic virus (CMV), RNA3 (2216 nt), both in vitro and in plant cell lysates. Comparing SHAPE-Seq and covariation analysis results revealed multiple SEs in the coat protein open reading frame and 3' untranslated region. Four of these SEs were mutated and serially passaged in Nicotiana tabacum plants to identify biologically selected changes to the original mutated sequences. After passaging, loop mutants showed partial reversion to their wild-type sequence and SEs that were structurally disrupted by mutations were restored to wild-type-like structures via synonymous mutations in planta. These results support the existence and selection of virus open reading frame SEs in the host organism and provide a framework for further studies on the role of RNA structure in viral infection. Additionally, this work demonstrates the applicability of high-throughput chemical probing in plant cell lysates and presents a new method for calculating SHAPE reactivities from overlapping reverse transcriptase priming sites

RNA systems biology: uniting functional discoveries and structural tools to understand global roles of RNAs

RNAs assume sophisticated structures that are active in myriad cellular processes. In this review, we highlight newly identified ribozymes, riboswitches, and small RNAs, some of which control the function of cellular metabolic and gene expression networks. We then examine recent developments in genome-wide RNA structure probing technologies that are yielding new insights into the structural landscape of the transcriptome. Finally, we discuss how these RNA ‘structomic’ methods can address emerging questions in RNA systems biology, from the mechanisms behind long non-coding RNAs to new bases for human diseases

PATTERNA: transcriptome-wide search for functional RNA elements via structural data signatures.

Establishing a link between RNA structure and function remains a great challenge in RNA biology. The emergence of high-throughput structure profiling experiments is revolutionizing our ability to decipher structure, yet principled approaches for extracting information on structural elements directly from these data sets are lacking. We present PATTERNA, an unsupervised pattern recognition algorithm that rapidly mines RNA structure motifs from profiling data. We demonstrate that PATTERNA detects motifs with an accuracy comparable to commonly used thermodynamic models and highlight its utility in automating data-directed structure modeling from large data sets. PATTERNA is versatile and compatible with diverse profiling techniques and experimental conditions

Probing The Function Of Long Noncoding RNAs In The Nucleus

The nucleus is a highly organized and dynamic environment where regulation and coordination of processes such as gene expression and DNA replication are paramount. In recent years, noncoding RNAs have emerged as key participants in the regulation of nuclear processes. There are a multitude of functional roles for long noncoding RNA (lncRNA), mediated through their ability to act as molecular scaffolds bridging interactions with proteins, chromatin, and other RNA molecules within the nuclear environment. In this review, we discuss the diversity of techniques that have been developed to probe the function of nuclear lncRNAs, along with the ways in which those techniques have revealed insights into their mechanisms of action. Foundational observations into lncRNA function have been gleaned from molecular cytology-based, single-cell approaches to illuminate both the localization and abundance of lncRNAs in addition to their potential binding partners. Biochemical, extraction-based approaches have revealed the molecular contacts between lncRNAs and other molecules within the nuclear environment and how those interactions may contribute to nuclear organization and regulation. Using examples of well-studied nuclear lncRNAs, we demonstrate that the emerging functions of individual lncRNAs have been most clearly deduced from combined cytology and biochemical approaches tailored to study specific lncRNAs. As more functional nuclear lncRNAs continue to emerge, the development of additional technologies to study their interactions and mechanisms of action promise to continually expand our understanding of nuclear organization, chromosome architecture, genome regulation, and disease states