Non-coding RNAs (ncRNAs) are a subset of RNAs that do not code for protein. They are divided into a number of different groups based on their function and targets. Small nucleolar RNAs (snoRNAs) are ncRNAs that have long been known to function as guides for ribosomal RNA (rRNA) modifying enzymes. They are classified into two major groups: box C/D snoRNAs and box H/ACA snoRNAs. Most box C/D snoRNAs direct the 2'-O-methylation of rRNA substrates, but some lack known targets and are therefore termed 'orphan snoRNAs'. Studies have implicated orphan snoRNAs in pre-mRNA processing and stability, but the functional consequence of snoRNA binding to mRNAs has not been fully determined. Saccharomyces cerevisiae had two orphan snoRNAs, snR4 and snR45, with no known function in ribosome synthesis. This project aimed to determine the targets of these snoRNAs, and investigate the effects of snoRNA binding to non-canonical target RNAs, as well as the underlying mechanism. Synthetic gene array screens with deletions of the SNR4 and SNR45 genes identified multiple positive and negative genetic interactions. In particular, deletion of either snoRNA gene was synthetic-lethal with mutation of the snoRNA-associated methyltransferase, Nop1 (Fibrillarin in humans), demonstrating that both have important functions. CLASH analyses of RNA-RNA interactions showed that these snoRNAs bind multiple mRNAs, while RNA sequencing and RT-qPCR revealed that snoRNA deletion altered mRNA abundance. Both orphan snoRNAs were well conserved between fungi, with a region of high conservation indicating a potential binding site. Associations were identified between snR4 and snR45 and multiple sequences within rRNA, including two recently identified sites of 18S rRNA acetylation. Work elsewhere showed that snR4 and snR45 function as guides for the acetyltransferase Kre33 using the region of high conservation, removing their 'orphan' status. Orphan snoRNAs have been implicated in human diseases, such as Prader Willi Syndrome and cancers. The work discussed in this thesis helps to elucidate the RNA interactions of yeast orphan snoRNAs. It has provided a greater understanding of the mechanisms involved, and may inform future work in combatting human disease.

Listeriosis is a potentially lethal disease caused by the Gram-positive facultative intracellular pathogen Listeria monocytogenes (L.m.). L.m. is found ubiquitously in the environment and infects humans via ingestion of contaminated food. Contaminated products are usually derived from ruminants and involve dairy products and different kinds of processed meat. Listeriosis is a potential lifethreatening disease with a total mortality rate of 20-30 %. The development of listeriosis may lead to meningitis and septicemia or other invasive diseases. Pregnant women are of increased risk of developing listeriosis and a materno-fetal infection commonly lead to spontaneous abortion or still-birth. Regulation of gene expression, and specifically virulence gene expression, is essential for pathogenic bacteria to be equipped for handling counteractions from the host as well as thriving in the often hostile environment. In pathogenic Listeria, virulence gene expression is under the control of the global virulence gene regulator PrfA. The expression of prfA is highly regulated at the transcriptional, post-transcriptional and post- translational level. We have identified a novel type of post-transcriptional regulation of prfA-mRNA by a trans-acting riboswitch element (SreA). By binding to the leader region of prfA-mRNA, SreA negatively regulates the expression of prfA. To our knowledge, this is the first description of a cis-acting riboswitch capable of functioning as a small RNA in trans, regulating targets on distant sites. To date, there have been around 100 sRNAs identified in Listeria monocytogenes, but experimental data is still limited. We have characterized a blood induced sRNA, Rli38, which is important for full virulence during oral infection of mice. Our data suggest that Rli38 regulates the expression of at least two proteins; OppD (Oligopeptide transport protein) and IsdG (heme degrading monooxygenase). Both of these proteins have been implicated in the infectious cycle of L.m. We speculate that the virulence phenotype of an ∆rli38 mutant is possibly mediated through the effect of these proteins. L.m. is a complex pathogen, able to infect and replicate in a variety of organs and cause several distinctive forms of disease. These qualities of L.m. generate difficulties in simulating human listeriosis in animal models, as entailed by the multitude of models used in the field. In this work, we have evaluated the use of an alternative animal model in studying listeriosis. Our results describe the differentiated virulence potential of wildtype bacteria and a ∆prfA mutant strain in the chicken embryo by live/death screening and organ colonization. Large differences in mean time to death were found between wild-type and the ∆prfA strain and ∆prfA cells displayed a considerable defect in colonization of the embryonal liver. The results presented in this thesis show that the chicken embryo infection model is a valuable and convenient tool in studying end-outcome and organ colonization of Listeria monocytogenes. Taken together, this thesis describes the characterization of two previously unknown sRNAs in the human pathogen Listeria monocytogenes and the use of an alternative infection model for simulating listeriosis.

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No. of bitstreams: 1 AnaCarolinaPereiraRocha_DISSERT.pdf: 5861142 bytes, checksum: 39f089afa48682089f4ef1bb8949e060 (MD5) Previous issue date: 2017-09-01 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / A diferencia??o das c?lulas-tronco mesenquimais humanas (CTMh) em osteoblasto segue um programa espec?fico de express?o g?nica, comprometendo-se inicalmente sob a influ?ncia das vias Wnt (Wingless pathway) e das BMPs (bone morphogenetic protein) que direcionam a c?lula a sua transforma??o em osteoblasto. Entretanto, as vias ativadas especificamente durante a fase inicial da diferencia??o s?o ainda pouco exploradas. Assim, o objetivo deste trabalho foi caracterizar o perfil transcricional do in?cio do processo de diferencia??o de CTMh, obtidas da veia do cord?o umbilical, em osteoblasto, a partir da t?cnica de RNA-Seq. A partir dos dados de transcriptoma, foi produzida uma lista ordenada de genes funcionalmente associados, obtida pela me?dia da expressa?o ge?nica tomada sobre genes vizinhos nesta lista, facilitando, assim, a sua interpretac?a?o biolo?gica. Para o estudo de ontologia g?nica e delineamento do perfil de express?o durante a osteog?nese, os processos metab?licos e fun??es moleculares significativamente alterados durante o decorrer do processo de diferencia??o foram analisados em diversas ferramentas (REVIGO, GOrila, PANTHER, LNCipedia e NONCODE) e descritos. Durante a indu??o ? diferencia??o das CTMh em osteoblasto, foi observado o aumento da express?o de genes caracter?sticos do fen?tipo osteobl?stico j? a partir do primeiro dia de diferencia??o. Foram identificados RNAs n?o codificantes, consoante a evolu??o da diferencia??o, bem como genes envolvidos na forma??o de rafts de membrana, j? a partir do terceiro dia de diferencia??o. Durante o terceiro dia de indu??o, genes envolvidos na regula??o da diferencia??o celular e em outros processos biol?gicos que precedem a diferencia??o, como ades?o celular, sinaliza??o e resposta ? fatores qu?micos externos j? apresentaram aumento em sua express?o. O estudo da express?o g?nica durante estes tr?s primeiros dias revelou ainda a diminui??o na express?o de genes envolvidos em processos biol?gicos de manuten??o de metabolismo basal, degrada??o de RNA e organiza??o do citoesqueleto, indicando assim que as mudan?as celulares que levam a c?lula a entrar em diferencia??o podem ter origem durante os tr?s primeiros dias de tratamento osteog?nico. / Human mesenchymal stem cells (hMSC) differentiation into osteoblast follows a specific gene expression program, committing itself initially under Wnt and BMPs pathways influence then differentiating into osteoblasts. However, specifically activated pathways during the first three days of differentiation are still poorly understood. Considering next generation sequencing technologies efficiency, and the lack of characterization in early hMSC differentiation process, in this work we used Illumina RNA-Seq to investigate the changes in these cells transcriptome. We used ex-vivo cultures of two human umbilical cord veins. Data from the complete transcriptome were analyzed in Transcriptogramer for the production of an ordered list of functionally associated genes, obtained by the mean of the gene expression taken on neighboring genes in this list, thus facilitating their biological interpretation. To study gene ontology and gene expression profile during osteogenesis, the metabolic processes and molecular functions significantly altered during the course of the differentiation process were analyzed in several tools (REVIGO, GOrila, PANTHER, LNCipedia and NONCODE) and properly described. During hMSC differentiation, an increase in expression of osteoblastic phenotype genes was observed as soon as the first day of differentiation started. Noncoding RNAs were also identified, depending on the evolution of the differentiation process, as well as genes involved in the formation of membrane rafts, on the third day of differentiation. During the third day of induction, cell differentiation regulation genes and other important genes on biological processes that precede differentiation, such as cell adhesion, signaling and external chemical factors response, have already increased expression. The study of gene expression during these first three days also revealed the decrease in the expression of groups of genes crucial to basal metabolism maintenance, RNA degradation and cytoskeleton organization, thus indicating that the cellular changes that lead the cell into differentiation may originate during the first three days of osteogenic treatment.

Skeletal muscle formation is among the most striking examples of cellular plasticity in animal tissue development, where mononucleated, lineage-restricted progenitor cells are epigenetically reprogrammed to produce multinucleated myofibers. While some mediators of epithelial-mesenchymal transition (EMT) have been shown to function in myogenesis, regulation of this process at the interface of multipotency and myogenic differentiation remains poorly understood. The long noncoding RNA (lncRNA) Meg3 is processed from the >200 kb Dlk1-Dio3 polycistron, and while many encoded miRNAs have been shown to regulate skeletal muscle differentiation, regeneration, and aging, the functional relevance of encoded lncRNAs in skeletal muscle remains elusive. Here, I demonstrate that Meg3 is enriched in proliferating post-natal myoblasts, where it epigenetically modulates aspects of cellular plasticity to facilitate myogenic differentiation in vitro, skeletal muscle regeneration in vivo, and safeguard myogenic identity. Chronic inhibition of Meg3 in C2C12 myoblasts compromised cytoarchitectural and transcriptomic cell-state transitions required for myogenic fusion and differentiation. These differentiation defects were primarily driven by TGFβ-dependent Snai2 activation, which correlated with irregular Ezh2 activity and abnormal epigenetic marks in differentiating C2C12 cells. Similarly, adenoviral Meg3 knockdown compromised muscle regeneration in vivo, which manifested as abnormal mesenchymal gene expression, fibrosis, and interstitial cell proliferation in the regenerating milieu. Comparison of Meg3-depleted C2C12 myoblasts and injured skeletal muscle to literature-derived gene sets suggest that Meg3-deficient samples deviate from controls towards abnormal transcriptional states, including immature satellite cell activation, muscle aging, and adoption of an osteoblast-like cell ontology. Thus, Meg3 regulates myoblast identity to maintain proper cell state transitions in postnatal myogenesis.

Análises de dados gerados em larga escala revelaram que os transcriptomas são mais extensos e complexos do que inferido previamente. Hoje é evidente que a maioria dos genomas de eucariotos são quase inteiramente transcritos e sob regulação atrelada a estágios de desenvolvimento. O controle da expressão gênica envolve RNAs não codificadores (ncRNAs) regulatórios, inclusive em processos pós-transcricionais. A regulação de expressão gênica em nível pós-transcricional é crucial em diferentes organismos, mas é particularmente central nos tripanossomatídeos. Os parasitos do gênero Leishmania (Ordem Kinetoplastidae, família Trypanosomatidae) provocam doenças infecto-parasitárias conhecidas como leishmanioses e em seu ciclo de vida apresenta-se sob três formas principais de desenvolvimento: promastigotas procíclicos, promastigotas metacíclicos e os amastigotas. Este trabalho teve como objetivo identificar e caracterizar computacionalmente ncRNAs putativos de Leishmania em diferentes estágios de desenvolvimento. A associação de abordagens em larga escala e ferramentas de bioinformática possibilitaram a identificação de 11.376 ncRNAs putativos em L. braziliensis e, em um estudo preliminar, de 37 ncRNAs putativos em L. donovani. Adicionalmente, o transcriptoma de L. braziliensis foi analisado comparativamente entre os três estágios de desenvolvimento do parasito. Em L. donovani, dos 37 ncRNAs putativos identificados, 34 estavam em UTRs (Untranslated Regions) e 3 em regiões intergênicas. Preditores de características específicas de ncRNAs foram utilizados e 32 ncRNAs putativos tiveram pelo menos uma predição positiva. Todos os candidatos estão conservados inteira ou parcialmente em pelo menos 3 espécies de Leishmania. Cinco ncRNAs de L. donovani foram confirmados por experimentos de Northern blotting. A análise do transcriptoma de L. braziliensis revelou uma diferença de expressão gênica entre os estágios de desenvolvimento que variou entre 52% e 71%, dependendo dos estágios comparados. Também foram definidos os limites das 5UTRs e 3UTRs de 81% e 38% das CDSs anotadas, respectivamente. Propusemos uma metodologia para identificação de ncRNAs putativos utilizando dados de sequenciamento de RNA-total. Essa metodologia identificou 11.376 ncRNAs putativos em L. braziliensis, sendo que todos os candidatos foram analisados por programas preditores de características específicas de ncRNAs e apresentaram pelo menos uma predição positiva, além de não possuírem semelhança com domínios proteicos conhecidos. A análise de conservação demonstrou que de 27% a 41% dos ncRNAs putativos identificados são conservados em outras espécies de Leishmania. Foram encontrados de 27% a 38% de ncRNAs putativos com regulação atrelada ao estágio de desenvolvimento, dependendo dos estágios comparados. Assim, além da identificação e descrição de ncRNAs em Leishmania foram encontrados candidatos com regulação atrelada ao desenvolvimento e padrões foram descortinados com o processo de análise proposto e executado. Portanto, esse trabalho contribui significativamente para ampliar a compreensão dos processos de regulação de expressão gênica em Leishmania e oferecerá à comunidade um conjunto grande e importante de informações sobre a organização genética do parasito, diferenças genéticas e regulatórias ao longo do desenvolvimento, além de informações do transcriptoma de forma global. / High-throughput data analyses indicated that transcriptomes are more extensive and complex than previously supposed. Currently, it is evident that most eukaryotic genomes are almost entirely transcribed and under regulation tied to developmental stages. Control of gene expression involves regulatory non-coding RNAs (ncRNAs), including post-transcriptional processes. Post-transcriptional regulation is particularly relevant for the regulation of gene expression in trypanosomatids, as compared to other organisms. Parasites of the genus Leishmania (Order Kinetoplastidae, family Trypanosomatidae) causes infectious-parasitic diseases known as leishmaniasis, and their life cycle comprises three development stages: procyclic promastigotes, metacyclic promastigotes and amastigotes. This study aimed to computationally identify and characterize Leishmania putative ncRNAs at different stages of development. Large-scale approaches combined with bioinformatics tools allowed the identification of 11,376 putative ncRNAs in L. braziliensis and, in a preliminary study, of 37 putative ncRNAs in L. donovani. In addition, the L. braziliensis the complete transcriptome was analyzed comparatively between the parasite development stages. In L. donovani, of the 37 putative ncRNAs identified, 34 were in UTRs (Untranslated Regions) and 3 in intergenic regions. Predictors of ncRNAs specific characteristics were used and 32 putative ncRNAs had at least one positive prediction. All candidates are conserved, partially or entirely, in at least three Leishmania species. Five L. donovani ncRNAs were confirmed by Northern blotting experiments. Analysis of the L. braziliensis transcriptome revealed differences in gene expression levels between developmental stages, ranging from 52% to 71%, depending on the compared stages. The boundaries of the 5\'UTRs and 3\'UTRs were also defined for 81% and 38% of the annotated CDSs, respectively. We developed a methodology for the identification of putative ncRNAs using total RNA sequencing data. This methodology allowed the identification of 11,376 putative ncRNAs in L. braziliensis, and all candidates were analyzed by predictive programs of ncRNAs specific characteristics and presented at least one positive prediction, in addition to bearing no similarity to known protein domains. The analysis showed that from 27% to 41% of the putative ncRNAs identified are conserved in other Leishmania species. We found 27% to 38% of putative ncRNAs with regulation associated to the developmental stage, depending on the compared stages. Consequently, besides identification and characterization of ncRNAs in Leishmania, candidates with developmental-related regulation were found and patterns were uncovered with the proposed and implemented analysis. Thus, this work contributes significantly to improve understanding of gene expression regulation processes in Leishmania and will offer to the community important information about the parasite genetics and regulatory differences along the development, besides of L. braziliensis transcriptome information.

Non-coding RNAs (ncRNAs) are transcripts that function directly as RNA molecule without ever being translated to protein. The transcriptional output of eukaryotic cells is diverse, pervasive, and multi-layered. It consists of spliced as well as unspliced transcripts of both protein-coding messenger RNAs and functional ncRNAs. However, it also contains degradable non-functional by-products and artefacts - certainly a reason why ncRNAs have long been wrongly disposed as transcriptional noise. Today, RNA-controlled regulatory processes are broadly recognized for a variety of ncRNA classes. The thermoresponsive ROSE ncRNA (repression of heat shock gene expression) is only one example of a regulatory ncRNA acting at the post-transcriptional level via conformational changes of its secondary structure. Bioinformatics helps to identify novel ncRNAs in the bulk of genomic and transcriptomic sequence data which are produced at ever increasing rates. However, ncRNA annotation is unfortunately not part of generic genome annotation pipelines. Dedicated computational searches for particular ncRNAs are veritable research projects in their own right. Despite best efforts, ncRNAs across the animal phylogeny remain to a large extent uncharted territory. This thesis describes a comprehensive collection of exploratory bioinformatic field studies designed to de novo predict ncRNA genes in a series of computational screens and in a multitude of newly sequenced genomes. Non-coding RNAs can be divided into subclasses (families) according to peculiar functional, structural, or compositional similarities. A simple but eligible and frequently applied criterion to classify RNA species is length. In line, the thesis is structured into two parts: We present a series of pilot-studies investigating (1) the short and (2) the long ncRNA repertoire of several model species by means of state-of-the-art bioinformatic techniques. In the first part of the thesis, we focus on the detection of short ncRNAs exhibiting thermodynamically stable and evolutionary conserved secondary structures. We provide evidence for the presence of short structured ncRNAs in a variety of different species, ranging from bacteria to insects and higher eukaryotes. In particular, we highlight drawbacks and opportunities of RNAz-based ncRNA prediction at several hitherto scarcely investigated scenarios, as for example ncRNA prediction in the light of whole genome duplications. A recent microarray study provides experimental evidence for our approach. Differential expression of at least one-sixth of our drosophilid RNAz predictions has been reported. Beyond the means of RNAz, we moreover manually compile sophisticated annotation of short ncRNAs in schistosomes. Obviously, accumulating knowledge about the genetic material of malaria causing parasites which infect millions of humans world-wide is of utmost scientific interest. Since the performance of any comparative genomics approach is limited by the quality of its input alignments, we introduce a novel light-weight and performant genome-wide alignment approach: NcDNAlign. Although the tool is optimized for speed rather than sensitivity and requires only a minor fraction of CPU time compared to existing programs, we demonstrate that it is basically as sensitive and specific as competing approaches when applied to genome-wide ncRNA gene finding and analysis of ultra-conserved regions. By design, however, prediction approaches that search for regions with an excess of mutations that maintain secondary structure motifs will miss ncRNAs that are unstructured or whose structure is not well conserved in evolution. In the second part of the thesis, we therefore overcome secondary structure prediction and, based on splice site detection, develop novel strategies specifically designed to identify long ncRNAs in genomic sequences - probably the open problem in current RNA research. We perform splice site anchored gene-finding in drosophilids, nematodes, and vertebrate genomes and, at least for a subset of obtained candidate genes, provide experimental evidence for expression and the existence of novel spliced transcripts undoubtedly confirming our approach. In summary, we found evidence for a large number of previously undescribed RNAs which consolidates the idea of non-coding RNAs as an abundant class of regulatory active transcripts. Certainly, ncRNA prediction is a complex task. This thesis, however, rationally advises how to unveil the RNA complement of newly sequenced genomes. Since our results have already established both subsequent computational as well as experimental studies, we believe to have enduringly stimulated the field of RNA research and to have contributed to an enriched view on the subject.

Small nucleolar RNAs (snoRNAs) are one of the most abundant and evolutionary ancient group of small non-coding RNAs. Their main function is to target chemical modifications of ribosomal RNAs (rRNAs) and small nuclear (snRNAs). They fall into two classes, box C/D snoRNAs and box H/ACA snoRNAs, which are clearly distinguished by conserved sequence motifs and the type of modification that they govern. The box H/ACA snoRNAs are responsible for targeting pseudouridylation sites and the box C/D snoRNAs for directing 2’-O-methylation of ribonucleotides. A subclass that localize to the Cajal bodies, termed scaRNAs, are responsible for methylation and pseudouridylation of snRNAs. In addition an amazing diversity of non-canonical functions of individual snoRNAs arose. The modification patterns in rRNAs and snRNAs are retained during evolution making it even possible to project them from yeast onto human. The stringent conservation of modification sites and the slow evolution of rRNAs and snRNAs contradicts the rapid evolution of snoRNA sequences. Recent studies that incorporate high-throughput sequencing experiments still identify undetected snoRNAs even in well studied organisms as human. The snoRNAbase, which has been the standard database for human snoRNAs has not been updated ince 2006 and misses these new data. Along with the lack of a centralized data collection across species, which incorporates also snoRNA class specific characteristics the need to integrate distributed data from literature and databases into a comprehensive snoRNA set arose. Although several snoRNA studies included pro forma target predictions in individual species and more and more studies focus on non-canonical functions of subclasses a systematic survey on the guiding function and especially functional homologies of snoRNAs was not available. To establish a sound set of snoRNAs a computational snoRNA annotation pipeline, named snoStrip that identifies homologous snoRNAs in related species was employed. For large scale investigation of the snoRNA function, state-of-the-art target pedictions were performed with our software RNAsnoop and PLEXY. Further, a new measure the Interaction Conservation Index (ICI) was developed to evaluate the conservation of snoRNA function. The snoStrip pipeline was applied to vertebrate species, where the genome sequence has been available. In addition, it was used in several ncRNA annotation studies (48 avian, spotted gar) of newly assembled genomes to contribute the snoRNA genes. Detailed target analysis of the new vertebrate snoRNA set revealed that in general functions of homologous snoRNAs are evolutionarily stable, thus, members of the same snoRNA family guide equivalent modifications. The conservation of snoRNA sequences is high at target binding regions while the remaining sequence varies significantly. In addition to elucidating principles of correlated evolution it was possible, with the help of the ICI measure, to assign functions to previously orphan snoRNAs and to associate snoRNAs as partners to known but so far unexplained chemical modifications. As further pattern redundant guiding became apparent. For many modification sites more than one snoRNA encodes the appropriate antisense element (ASE), which could ensure constant modification through snoRNAs that have different expression patterns. Furthermore, predictions of snoRNA functions in conjunction with sequence conservation could identify distant homologies. Due to the high overall entropy of snoRNA sequences, such relationships are hard to detect by means of sequence homology search methods alone. The snoRNA interaction network was further expanded through novel snoRNAs that were detected in data from high-throughput experiments in human and mouse. Through subsequent target analysis the new snoRNAs could immediately explain known modifications that had no appropriate snoRNA guide assigned before. In a further study a full catalog of expressed snoRNAs in human was provided. Beside canonical snoRNAs also recent findings like AluACAs, sno-lncRNAs and extraordinary short SNORD-like transcripts were taken into account. Again the target analysis workflow identified undetected connections between snoRNA guides and modifications. Especially some species/clade specific interactions of SNORD-like genes emerged that seem to act as bona fide snoRNA guides for rRNA and snRNA modifications. For all high confident new snoRNA genes identified during this work official gene names were requested from the HUGO Gene Nomenclature Committee (HGNC) avoiding further naming confusion.

The genome can be considered the blueprint for an organism. Composed of DNA, it harbours all organism-specific instructions for the synthesis of all structural components and their associated functions. The role of carriers of actual molecular structure and functions was believed to be exclusively assumed by proteins encoded in particular segments of the genome, the genes. In the process of converting the information stored genes into functional proteins, RNA – a third major molecule class – was discovered early on to act a messenger by copying the genomic information and relaying it to the protein-synthesizing machinery. Furthermore, RNA molecules were identified to assist in the assembly of amino acids into native proteins. For a long time, these - rather passive - roles were thought to be the sole purpose of RNA. However, in recent years, new discoveries have led to a radical revision of this view. First, RNA molecules with catalytic functions - thought to be the exclusive domain of proteins - were discovered. Then, scientists realized that much more of the genomic sequence is transcribed into RNA molecules than there are proteins in cells begging the question what the function of all these molecules are. Furthermore, very short and altogether new types of RNA molecules seemingly playing a critical role in orchestrating cellular processes were discovered. Thus, RNA has become a central research topic in molecular biology, even to the extent that some researcher dub cells as “RNA machines”. This thesis aims to contribute towards our understanding of RNA-related phenomena by applying Bioinformatics means. First, we performed a genome-wide screen to identify sites at which the chemical composition of DNA (the genotype) critically influences phenotypic traits (the phenotype) of the model plant Arabidopsis thaliana. Whole genome hybridisation arrays were used and an informatics strategy developed, to identify polymorphic sites from hybridisation to genomic DNA. Following this approach, not only were genotype-phenotype associations discovered across the entire Arabidopsis genome, but also regions not currently known to encode proteins, thus representing candidate sites for novel RNA functional molecules. By statistically associating them with phenotypic traits, clues as to their particular functions were obtained. Furthermore, these candidate regions were subjected to a novel RNA-function classification prediction method developed as part of this thesis. While determining the chemical structure (the sequence) of candidate RNA molecules is relatively straightforward, the elucidation of its structure-function relationship is much more challenging. Towards this end, we devised and implemented a novel algorithmic approach to predict the structural and, thereby, functional class of RNA molecules. In this algorithm, the concept of treating RNA molecule structures as graphs was introduced. We demonstrate that this abstraction of the actual structure leads to meaningful results that may greatly assist in the characterization of novel RNA molecules. Furthermore, by using graph-theoretic properties as descriptors of structure, we indentified particular structural features of RNA molecules that may determine their function, thus providing new insights into the structure-function relationships of RNA. The method (termed Grapple) has been made available to the scientific community as a web-based service. RNA has taken centre stage in molecular biology research and novel discoveries can be expected to further solidify the central role of RNA in the origin and support of life on earth. As illustrated by this thesis, Bioinformatics methods will continue to play an essential role in these discoveries. / Das Genom eines Organismus enthält alle Informationen für die Synthese aller strukturellen Komponenten und deren jeweiligen Funktionen. Lange Zeit wurde angenommen, dass Proteine, die auf definierten Abschnitten auf dem Genom – den Genen – kodiert werden, die alleinigen Träger der molekularen - und vor allem katalytischen - Funktionen sind. Im Prozess der Umsetzung der genetischen Information von Genen in die Funktion von Proteinen wurden RNA Moleküle als weitere zentrale Molekülklasse identifiziert. Sie fungieren dabei als Botenmoleküle (mRNA) und unterstützen als Trägermoleküle (in Form von tRNA) die Zusammenfügung der einzelnen Aminosäurebausteine zu nativen Proteine. Diese eher passiven Funktionen wurden lange als die einzigen Funktionen von RNA Molekülen angenommen. Jedoch führten neue Entdeckungen zu einer radikalen Neubewertung der Rolle von RNA. So wurden RNA-Moleküle mit katalytischen Eigenschaften entdeckt, sogenannte Ribozyme. Weiterhin wurde festgestellt, dass über proteinkodierende Abschnitte hinaus, weit mehr genomische Sequenzbereiche abgelesen und in RNA Moleküle transkribiert werden als angenommen. Darüber hinaus wurden sehr kleine und neuartige RNA Moleküle identifiziert, die entscheidend bei der Koordinierung der Genexpression beteiligt sind. Diese Entdeckungen rückten RNA als Molekülklasse in den Mittelpunkt moderner molekularbiologischen Forschung und führten zu einer Neubewertung ihrer funktionellen Rolle. Die vorliegende Promotionsarbeit versucht mit Hilfe bioinformatorischer Methoden einen Beitrag zum Verständnis RNA-bezogener Phänomene zu leisten. Zunächst wurde eine genomweite Suche nach Abschnitten im Genom der Modellpflanze Arabidopsis thaliana vorgenommen, deren veränderte chemische Struktur (dem Genotyp) die Ausprägung ausgewählter Merkmale (dem Phänotyp) entscheidend beeinflusst. Dabei wurden sogenannte Ganz-Genom Hybridisierungschips eingesetzt und eine bioinformatische Strategie entwickelt, Veränderungen der chemischen Struktur (Polymorphismen) anhand der veränderten Bindung von genomischer DNA aus verschiedenen Arabidopsis Kultivaren an definierte Proben auf dem Chip zu detektieren. In dieser Suche wurden nicht nur systematisch Genotyp-Phänotyp Assoziationen entdeckt, sondern dabei auch Bereiche identifiziert, die bisher nicht als proteinkodierende Abschnitte annotiert sind, aber dennoch die Ausprägung eines konkreten Merkmals zu bestimmen scheinen. Diese Bereiche wurden desweiteren auf mögliche neue RNA Moleküle untersucht, die in diesen Abschnitten kodiert sein könnten. Hierbei wurde ein neuer Algorithmus eingesetzt, der ebenfalls als Teil der vorliegenden Arbeit entwickelt wurde. Während es zum Standardrepertoire der Molekularbiologen gehört, die chemische Struktur (die Sequenz) eines RNA Moleküls zu bestimmen, ist die Aufklärung sowohl der Struktur als auch der konkreten Funktion des Moleküls weitaus schwieriger. Zu diesem Zweck wurde in dieser Arbeit ein neuer algorithmischer Ansatz entwickelt, der mittels Computermethoden eine Zuordnung von RNA Molekülen zu bestimmten Funktionsklassen gestattet. Hierbei wurde das Konzept der Beschreibung von RNA-Sekundärstrukturen als Graphen genutzt. Es konnte gezeigt werden, dass diese Abstraktion von der konkreten Struktur zu nützlichen Aussagen zur Funktion führt. Des weiteren konnte demonstriert werden, dass graphen-theoretisch abgeleitete Merkmale von RNA-Molekülen einen neuen Zugang zum Verständnis der Struktur-Funktionsbeziehungen ermöglichen. Die entwickelte Methode (Grapple) wurde als web-basierte Anwendung der wissenschaftlichen Welt zur Verfügung gestellt. RNA hat sich als ein zentraler Forschungsgegenstand der Molekularbiologie etabliert und neue Entdeckungen können erwartet werden, die die zentrale Rolle von RNA bei der Entstehung und Aufrechterhaltung des Lebens auf der Erde weiter untermauern. Bioinformatische Methoden werden dabei weiterhin eine essentielle Rolle spielen.

Non-coding RNAs (ncRNAs) are transcripts that function directly as RNA molecule without ever being translated to protein. The transcriptional output of eukaryotic cells is diverse, pervasive, and multi-layered. It consists of spliced as well as unspliced transcripts of both protein-coding messenger RNAs and functional ncRNAs. However, it also contains degradable non-functional by-products and artefacts - certainly a reason why ncRNAs have long been wrongly disposed as transcriptional noise. Today, RNA-controlled regulatory processes are broadly recognized for a variety of ncRNA classes. The thermoresponsive ROSE ncRNA (repression of heat shock gene expression) is only one example of a regulatory ncRNA acting at the post-transcriptional level via conformational changes of its secondary structure. Bioinformatics helps to identify novel ncRNAs in the bulk of genomic and transcriptomic sequence data which are produced at ever increasing rates. However, ncRNA annotation is unfortunately not part of generic genome annotation pipelines. Dedicated computational searches for particular ncRNAs are veritable research projects in their own right. Despite best efforts, ncRNAs across the animal phylogeny remain to a large extent uncharted territory. This thesis describes a comprehensive collection of exploratory bioinformatic field studies designed to de novo predict ncRNA genes in a series of computational screens and in a multitude of newly sequenced genomes. Non-coding RNAs can be divided into subclasses (families) according to peculiar functional, structural, or compositional similarities. A simple but eligible and frequently applied criterion to classify RNA species is length. In line, the thesis is structured into two parts: We present a series of pilot-studies investigating (1) the short and (2) the long ncRNA repertoire of several model species by means of state-of-the-art bioinformatic techniques. In the first part of the thesis, we focus on the detection of short ncRNAs exhibiting thermodynamically stable and evolutionary conserved secondary structures. We provide evidence for the presence of short structured ncRNAs in a variety of different species, ranging from bacteria to insects and higher eukaryotes. In particular, we highlight drawbacks and opportunities of RNAz-based ncRNA prediction at several hitherto scarcely investigated scenarios, as for example ncRNA prediction in the light of whole genome duplications. A recent microarray study provides experimental evidence for our approach. Differential expression of at least one-sixth of our drosophilid RNAz predictions has been reported. Beyond the means of RNAz, we moreover manually compile sophisticated annotation of short ncRNAs in schistosomes. Obviously, accumulating knowledge about the genetic material of malaria causing parasites which infect millions of humans world-wide is of utmost scientific interest. Since the performance of any comparative genomics approach is limited by the quality of its input alignments, we introduce a novel light-weight and performant genome-wide alignment approach: NcDNAlign. Although the tool is optimized for speed rather than sensitivity and requires only a minor fraction of CPU time compared to existing programs, we demonstrate that it is basically as sensitive and specific as competing approaches when applied to genome-wide ncRNA gene finding and analysis of ultra-conserved regions. By design, however, prediction approaches that search for regions with an excess of mutations that maintain secondary structure motifs will miss ncRNAs that are unstructured or whose structure is not well conserved in evolution. In the second part of the thesis, we therefore overcome secondary structure prediction and, based on splice site detection, develop novel strategies specifically designed to identify long ncRNAs in genomic sequences - probably the open problem in current RNA research. We perform splice site anchored gene-finding in drosophilids, nematodes, and vertebrate genomes and, at least for a subset of obtained candidate genes, provide experimental evidence for expression and the existence of novel spliced transcripts undoubtedly confirming our approach. In summary, we found evidence for a large number of previously undescribed RNAs which consolidates the idea of non-coding RNAs as an abundant class of regulatory active transcripts. Certainly, ncRNA prediction is a complex task. This thesis, however, rationally advises how to unveil the RNA complement of newly sequenced genomes. Since our results have already established both subsequent computational as well as experimental studies, we believe to have enduringly stimulated the field of RNA research and to have contributed to an enriched view on the subject.

The concept of the gene has been constantly challenged by new discoveries in the life sciences. Recent challenging observations include the high frequency of alternative splicing events and the common transcription of non-protein-coding-RNAs (ncRNAs) from the genome. The latter has long been considered noise in biological systems. Multiple lines of evidence from genomic studies indicate that alternative splicing and ncRNA play important roles in expanding proteome diversity in eukaryotes. Here, the aim is to find the link between alternative splicing and ncRNAs by studying the expression profile of the spliceosomal snRNAs (U snRNA). Spliceosomal snRNAs are essential for pre-mRNA splicing in eukaryotes. They participate in splice site selection, recruitment of protein factors and catalyzing the splicing reaction. Because of this, both the abundance and diversity of U snRNAs were expected to be large. In our study we deeply analyzed the U snRNA population in primates using a combination of bioinformatical, biochemical and high throughput sequencing approaches. This transcriptome profiling has revealed that human, chimpanzee and rhesus have similar U snRNA populations, i.e. the vast majority of U snRNAs originate from few well-defined gene loci and the heterogeneity observed in U snRNA populations was largely due to the presence of SNPs at these loci. It seems that the gene loci that could potentially encode a significantly heterogeneous population of U snRNAs are mostly silent. Only few minority transcripts were detected in our study, and among them three U1-like snRNAs might play a role in the regulation of alternative splicing by recognizing non-canonical splicing sites. Mutations of U snRNA have been shown to impact the splicing process. Therefore, our study provides a reference to study the biological significance of SNPs in U snRNA genes and their association with diseases.