Ribonucleic acid (RNA) is an essential molecule, which carries out a wide variety of functions within the cell, from its crucial involvement in protein synthesis to catalysing biochemical reactions and regulating gene expression. Such diverse functional repertoire is indebted to complex structures that RNA can adopt and its flexibility as an interacting molecule. It has become possible to experimentally measure these two crucial aspects of RNA regulatory role with such technological advancements as next-generation sequencing (NGS). NGS methods can rapidly obtain the nucleotide sequence of many molecules in parallel. Designing experiments, where only the desired parts of the molecule (or specific parts of the transcriptome) are sequenced, allows to study various aspects of RNA biology. Analysis of NGS data is insurmountable without computational methods. One such experimental method is RNA structure probing, which aims to infer RNA structure from sequencing chemically altered transcripts. RNA structure probing data is inherently noisy, affected both by technological biases and the stochasticity of the underlying process. Most existing methods do not adequately address the issue of noise, resorting to heuristics and limiting the informativeness of their output. In this thesis, a statistical pipeline was developed for modelling RNA structure probing data, which explicitly captures biological variability, provides automated bias-correcting strategies, and generates a probabilistic output based on experimental measurements. The output of our method agrees with known RNA structures, can be used to constrain structure prediction algorithms, and remains robust to reduced sequence coverage, thereby increasing sensitivity of the technology. Another recent experimental innovation maps RNA-protein interactions at very high temporal resolution, making it possible to study rapid binding events happening on a minute time scale. In this thesis, a non-parametric algorithm was developed for identifying significant changes in RNA-protein binding time-series between different conditions. The method was applied to novel yeast RNA-protein binding time-course data to study the role of RNA degradation in stress response. It revealed pervasive changes in the binding to the transcriptome of the yeast transcription termination factor Nab3 and the cytoplasmic exoribonuclease Xrn1 under nutrient stress. This challenged the common assumption of viewing transcriptional changes as the major driver of changes in RNA expression during stress and highlighted the importance of degradation. These findings inspired a dynamical model for RNA expression, where transcription and degradation rates are modelled using RNA-protein binding time-series data.

xiv, 78 p. : ill. (some col.) A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / Myotonic Dystrophy (DM) is a genetic disorder with multisystemic symptoms that is caused by expression (as RNA) of expanded repeats of CTG or CCTG in the genome. It is hypothesized that the protein MBNL1 (M[barbelow]uscleb[barbelow]lin[barbelow]d-l[barbelow]ike-1) is sequestered to the expanded CUG or CCUG RNAs. MBNL1 regulates the alternative splicing of a variety of pre-mRNAs and its mis-localization results in mis-splicing of a subset of pre-mRNAs that are linked to the symptoms found in DM patients. I initially demonstrated that MBNL1 can bind short structured CUG and CCUG repeats with high affinity and specificity in vitro . Next, I was able to determine and articulate the first structure of a binding site of MBNL1 in an endogenous pre-mRNA that it regulates. I found that MBNL1 binds a stem-loop in the cardiac troponin T (cTNT) pre-mRNA. The stem-loop contains two mismatches and resembles both CUG and CCUG repeats. I determined that MBNL1 regulated exon 5 by directly competing with the essential splicing factor U2AF65 for binding upstream of exon 5. When U2AF65 is prevented from binding, factors in the spliceosome can no longer be recruited and the following exon is skipped. Furthermore, I found that MBNL1 and U2AF65 compete by binding mutually exclusive RNA structures. I also characterized a potential therapeutic approach for DM. Current data suggest that if MBNL1 is released from sequestration, disease symptoms may be alleviated. Using a targeted screen of small molecules known to bind structured nucleic acids, I identified the small molecule pentamidine as a compound that disrupted MBNL1 binding to CUG repeats in vitro . I showed in cell culture that pentamidine was able to reverse the mis-splicing of two pre-mRNAs affected in DM. Pentamidine also significantly reduced the formation of RNA foci in tissue culture cells, which are characteristic of DM. MBNL1 was released from the foci in the treated cells. Furthermore, pentamidine partially rescued splicing defects of two pre-mRNAs in mice expressing expanded CUG repeats. This dissertation includes three previously published co-authored publications. / Committee in charge: Kenneth Prehoda, Chairperson, Chemistry; J. Andrew Berglund, Advisor, Chemistry; Victoria DeRose, Member, Chemistry; Peter von Hippel, Member, Chemistry; Alice Barkan, Outside Member, Biology

Le génome du virus de l’Hépatite C est constitué d’un ARN monocaténaire linéaire de polarité positive (+). Les interactions ARN-ARN prennent une place essentielle dans la régulation du cycle viral.La synthèse de l’ARN est réalisée par l’ARN-polymérase ARN-dépendante (RdRp) codée par le virus. Elle serait initiée à l’extrémité 3’ des molécules à répliquer. Un ARN génomique complémentaire de polarité négative (-) est d’abord synthétisé. Il sert ensuite de matrice pour la production des brins génomiques. Les mécanismes qui président au recrutement de la polymérase et à l’initiation de la synthèse d’ARN restent, aujourd’hui, mal connus.Les structures ARN présentes aux extrémités 3’ et leurs rôles ont donc étés étudiés au cours des travaux de cette thèse. Au niveau de l’extrémité 3’ de l’ARN (+), la dimérisation a été montrée indispensable à la réplication du virus in cellulo. Ces travaux ont par la suite permis de caractériser par gel retard et cryo-microscopie la dimérisation des ARN génomiques en solution. Au niveau de l’extrémité 3’ de l’ARN (-), la dimérisation de deux molécules a également pu être caractérisée par des approches biochimiques et biophysiques. Par ailleurs la présence d’un G-quadruplex introduit un remaniement conformationnel qui se révèle indispensable à une synthèse performante de l’ARN. De manière similaire au brin génomique, la dynamique structurale résultante de ces interactions semble donc nécessaire à une réplication efficace de l’ARN par la RdRp.Les résultats obtenus soulignent l’importance de la dimérisation et des variations conformationnelles prisent aux extrémités 3’ pour la réplication de l’ARN. Ces données ouvrent alors la voie vers de nouvelles perspectives quant à la compréhension des mécanismes qui président au fonctionnement de la polymérase du VHC. / The hepatitis C virus genome consists of a linear positive sens (+) single-stranded RNA. RNA-RNA interactions play an essential role in the regulation of the viral cycle.RNA synthesis is performed by the RNA-dependent RNA-polymerase (RdRp) encoded by the virus. It would be initiated at the 3 'end of the molecule to be replicated. A complementary genomic RNA of negative polarity (-) is first synthesized. It then serves as a matrix for the production of genomic strands. The mechanisms that govern the recruitment of the polymerase and the initiation of RNA synthesis remain poorly understood today.The RNA structures found at the 3 'ends and their roles have therefore been studied during the work of this thesis. At the 3 'end of the (+) RNA, dimerization was shown to be essential for replication of the virus in cellulo. This work made it possible to characterize by gel shift assay and cryo-microscopy the dimerization of the genomic RNAs in solution. At the 3 'end of (-) RNA, the dimerization of two molecules could also be characterized by biochemical and biophysical approaches. Moreover, the presence of a G-quadruplex introduces a conformational reshuffle which proves to be indispensable for an efficient RNA synthesis. Similarly to the genomic strand, the resulting structural dynamics of these interactions appear to be necessary for efficient RNA replication by the RdRp.The results obtained here underline the importance of dimerization and conformational variations at the 3 'ends for RNA replication. These data then open the way to new perspectives on understanding the mechanisms that govern the functioning of HCV polymerase.

The Hepatitis Delta Virus (HDV) is an RNA pathogen that uses the host DNA-dependent RNA polymerase II (RNAP II) to replicate. Previous studies identified the right terminal domain of genomic polarity (R199G) of HDV RNA as an RNAP II promoter, but the features required for HDV RNA to be used as an RNA promoter were unknown. In order to identify the structural features of an HDV RNA promoter, I analyzed 473,139 sequences representing 2,351 new R199G variants generated by high-throughput sequencing of a viral population replicating in 293 cells. To complement this analysis, I also analyzed the same region from HDV sequences isolated from various hosts. Base pair covariation analysis indicates a strong selection for the rod-like conformation. Several selected RNA motifs were identified, including a GC-rich stem, a CUC/GAG motif and a uridine at the initiation site of transcription. In addition, a polarization of purine/pyrimidine content was identified, which might represent a motif favourable for the binding of the host Polypyrimidine tract-binding protein-associated-splicing-factor (PSF), p54 and Paraspeckle Protein 1 (PSP1). Previously, it was shown that R199G binds both RNAP II and PSF, that PSF increased the HDV levels during in vitro transcription and that p54 binds R199G. In the present study, I showed that PSP1 also associates with HDV RNA and I investigated whether these proteins are required for HDV replication. My results show that knockdown of PSF, p54 and PSP1 resulted in a decrease of HDV accumulation. These proteins are highly concentrated in paraspeckles, which are nuclear structures involved in storage of transcripts generated by RNAP II. I found that upon viral replication in 293 cells, PSP1 appeared as bigger foci present outside of the nucleus, while PSF and p54 foci remained in the nucleus. NEAT1 is a long non-coding RNA essential for the formation of paraspeckles. Upon HDV replication, I found an increase of the intensity and size of NEAT1 foci that correlates with an increase of NEAT1 transcripts. Altogether, these data suggest that HDV replication results in an alteration of the paraspeckles structures, providing foundation for further investigation of the paraspeckles role in HDV cycle. Overall, the present study addresses the importance of the HDV RNA structure and of the host paraspeckle proteins for HDV replication.

Avec l’explosion de la quantité de données biologiques disponible, développer de nouvelles méthodes de traitements efficaces est une problématique majeure en bioinformatique. De nombreuses structures biologiques sont modélisées par des structures arborescentes telles que les structures secondaires d’ARN et l’architecture des plantes. Ces structures contiennent des motifs répétés au sein même de leur structure mais également d’une structure à l’autre. Nous proposons d’exploiter cette propriété fondamentale afin d’améliorer le stockage et le traitement de tels objets.En nous inspirant du principe de filtres sur les séquences, nous définissons dans cette thèse une méthode de filtrage sur les arborescences ordonnées permettant de rechercher efficacement dans une base de données un ensemble d’arborescences ordonnées proches d’une arborescence requête. La méthode se base sur un découpage de l’arborescence en graines et sur une recherche de graines communes entre les structures. Nous définissons et résolvons le problème de chainage maximum sur des arborescences. Nous proposons dans le cas des structures secondaires d’ARN une définition de graines (l−d) centrées.Dans un second temps, en nous basant sur des techniques d’instanciations utilisées, par exemple, en infographie et sur la connaissance des propriétés de redondances au sein des structures biologiques, nous présentons une méthode de compression permettant de réduire l’espace mémoire nécessaire pour le stockage d’arborescences non-ordonnées. Après une détermination des redondances nous utilisons une structure de données plus compacte pour représenter notamment l’architecture de la plante, celle-ci pouvant contenir des informations topologiques mais également géométriques. / The explosion of available biological data urges the need for bioinformatics methods. Manybiological structures are modeled by tree structures such as RNA secondary structure and plantsarchitecture. These structures contain repeating units within their structure, but also betweendifferent structures. We propose to exploit this fundamental property to improve storage andtreatment of such objects.Following the principle of sequence filtering, we define a filtering method on ordered treesto efficiently retrieve in a database a set of ordered trees close from a query. The method isbased on a decomposition of the tree into seeds and the detection of shared seeds between thesestructures. We define and solve the maximum chaining problem on trees. We propose for RNAsecondary structure applications a definition of (l−d) centered seed.Based on instantiation techniques used for instance in computer graphics and the repetitivenessof biological structures, we present a compression method which reduces the memoryspace required for plant architecture storage. A more compact data structure is used in order torepresent plant architecture. The construction of this data structure require the identification ofinternal redundancies and taking into account both topological and geometrical informations.

A crucial step of the viral life cycle of Kaposi’s Sarcoma Herpesvirus (KSHV) lytic infection is the triggering of a massive RNA decay event termed “Host Shutoff”. Host Shutoff is driven by the viral endonuclease SOX which leads to the destruction of over 70% of the total transcriptome. This process cripples cellular gene expression and allows for viral reprograming of the cell for the purpose of viral replication. Co-evolution has led to the host developing a multitude of antiviral defenses aimed at preserving certain cellular RNAs linked to antiviral responses. One such defense are RNA secondary structures located within the 3’UTR of select host transcripts that protect them from SOX degradation. This structure, known as the SOX Resistant Element or SRE, has previously been isolated to a 200-nucleotide region found within the 3’UTR of the host transcript Interleukin-6. In this thesis, I sought to further define the structure of the IL-6 and other SREs using SHAPE-MaP to generate chemically-probed RNA structural models. Through this work, I demonstrated that the IL-6 SRE confers a form of active resistance to SOX cleavage, and based on structural analyses, likely acts as a scaffold for the recruitment of a protective ribonucleoprotein complex. This research highlights the importance of RNA secondary structures in influencing mRNA fate during viral infection and establishes the groundwork for understanding how these structural features can facilitate escape of cellular transcripts from viral endonucleases.

No description available.

No description available.

Indiana University-Purdue University Indianapolis (IUPUI) / Non-coding RNAs across the genome have been associated with various biological processes, ranging from regulation of splicing to remodeling of chromatin. Amongst the repertoire of non-coding sequences lies a critical species of RNAs called long non-coding RNAs (lncRNAs). LncRNAs significantly contribute to a large spectrum of human phenotypes, including cancers, Heart failure, Diabetes, and Alzheimer’s disease. This dissertation emphasizes the need to characterize the functional role of lncRNAs to improve our understanding of human diseases. This work consolidates a resource from multiple computational genomics and natural language processing-based approaches to advance our ability to functionally annotate hundreds of lncRNAs and their interactions, providing a one-stop lncRNA functional annotation and dynamic interaction network and multi-facet omics data visualization platform. RNA interactions are vital in various cellular processes, from transcription to RNA processing. These interactions dictate the functional scope of the RNA. However, the multifaceted functional nature of RNA stems from its ability to form secondary structures. Therefore, this work establishes a computational method to characterize RNA secondary structure by integrating SHAPE-seq and long-read sequencing to enhance further our understanding of RNA structure in modulating the post-transcriptional regulatory processes and deciphering the influence at several layers of biological features, ranging from structure composition to consequent protein occupancy. This study will potentially impact the research community by providing methods, web interfaces, and computational pipelines, improving our functional understanding of long non-coding RNAs. This work also provides novel integration methods of technologies like Oxford Nanopore-based long-read sequencing, RNA structure-probing methods, and machine learning. The approaches developed in this dissertation are scalable and adaptable to investigate further the functional and regulatory role of RNA and its structure. Overall, this study accelerates the development of RNA-based diagnostics and the identification of therapeutic targets in human disease.

Non-protein-coding RNAs play critical regulatory roles in cellular life. Many ncRNAs fold into specific structures in order to perform their biological functions. Some of the RNAs, such as riboswitches, can even fold into alternative structural conformations in order to participate in different biological processes. In addition, these RNAs can transit dynamically between different functional structures along folding pathways on their energy landscapes. These alternative functional structures are usually energetically favored and are stable in their local energy landscapes. Moreover, conformational transitions between any pair of alternate structures usually involve high energy barriers, such that RNAs can become kinetically trapped by these stable and local optimal structures. We have proposed a suite of computational approaches for analyzing and discovering regulatory RNAs through studying folding pathways, alternative structures and energy landscapes associated with conformational transitions of regulatory RNAs. First, we developed an approach, RNAEAPath, which can predict low-barrier folding pathways between two conformational structures of a single RNA molecule. Using RNAEAPath, we can analyze folding iii pathways between two functional RNA structures, and therefore study the mechanism behind RNA functional transitions from a thermodynamic perspective. Second, we introduced an approach, RNASLOpt, for finding all the stable and local optimal structures on the energy landscape of a single RNA molecule. We can use the generated stable and local optimal structures to represent the RNA energy landscape in a compact manner. In addition, we applied RNASLOpt to several known riboswitches and predicted their alternate functional structures accurately. Third, we integrated a comparative approach with RNASLOpt, and developed RNAConSLOpt, which can find all the consensus stable and local optimal structures that are conserved among a set of homologous regulatory RNAs. We can use RNAConSLOpt to predict alternate functional structures for regulatory RNA families. Finally, we have proposed a pipeline making use of RNAConSLOpt to computationally discover novel riboswitches in bacterial genomes. An application of the proposed pipeline to a set of bacteria in Bacillus genus results in the re-discovery of many known riboswitches, and the detection of several novel putative riboswitch elements.