Die Genexpressionsmaschinerie in Chloroplasten und Mitochondrien und die ihrer prokaryotischen Vorläufer sind konserviert. Innerhalb eines bakteriellen Grundgerüsts entwickelte sich darüber hinaus ein komplexer RNA-Metabolismus. In der vorliegenden Arbeit wird eine neue Klasse kleiner RNAs (15-50nt) mit plastidärem und mitochondrialen Ursprung beschrieben. Diese kurzen RNAs überlappen mit Bindestellen von RNA-bindenden Proteinen, die mRNAs gegen exonukleolytischen Verdau beschützen. Diese stabilisierende Funktion wird vermutlich hauptsächlich von PPR (Pentatricopeptid repeat) Proteinen und verwandten Proteine bewerkstelligt. Die kleinen RNAs repräsentieren dabei minimale nuklease-resistente Bereiche, sogenannte RNA-Bindeprotein footprints. Solche footprints finden sich in fast jedem intergenischen Bereich, der Prozessierung aufweist. Durch transkriptomweite Untersuchungen von kleinen RNAs in Mutanten von RNA-Bindeproteinen konnte für diese eine Reihe von Bindestellen identifiziert werden. Nuklease-resistente kleine RNAs fehlen in entsprechenden Mutanten. Der Vergleich neu identifizierter Ziele einzelner RNA-Bindeproteine führte dabei zu neuen Erkenntnissen über den Mechanismus der RNA-Erkennung durch PPR Proteine. Im Gegensatz zu Plastiden befinden sich kleine RNAs in Mitochondrien überwiegend an den 3‘ Enden von Transkripten, deren Stabilität vermutlich maßgeblich von diesen RNA-Bindeproteinen beeinflusst wird. Für das chloroplastidäre Ribonukleoprotein CP31A konnte gezeigt werden, dass es an der Stabilisierung der ndhF mRNA beteiligt ist. Die Interaktion mit der ndhF mRNA, die eine zentrale Komponente des NDH-Komplexes kodiert, wird dabei über die 3‘ untranslatierte Region vermittelt. Zusätzlich konnte gezeigt werden, dass CP31A die Stabilität einiger antisense Transkripte beeinflusst. Weiterhin wurden zehn neue Cytidin Desaminierungungen durch die Analyse von RNA-Seq Datensätzen in der Modellpflanze Arabidopsis thaliana identifiziert. / Chloroplasts and mitochondria are of endosymbiotic origin. Their basic gene expression machineries are retained from their free-living prokaryotic progenitors. On top of this bacterial scaffold, a number of organelle-specific RNA processing steps evolved. In this thesis, a novel class of organelle-specific short (15-50nt) RNAs is described on a transcriptome-wide scale. The small RNAs are found at binding sites of PPR (Pentatricopeptide repeat) and PPR-like proteins, which protect mRNAs against exonucleolytic decay. The small RNAs represent minimal nuclease resistant RNAs, so called PPR footprints. Small RNAs were identified in almost every intergenic region subjected to intergenic processing. This finding suggests that accumulation of processed transcripts in plastids is mostly due to protection by highly specific RNA-binding proteins. Small RNA sequencing identified a number of nuclease insensitive sites missing in mutants of RNA-binding proteins. Analysis of multiple small RNAs representing target sites of single PPR proteins expands the knowledge of target specificity. In mitochondria, accumulations of small RNAs predicts that at least two thirds of mitochondrial mRNAs are stabilized by RNA-binding proteins binding in their 3’UTR. In sum, small organellar RNAs turned out to be instrumental in elucidating the hitherto enigmatic intercistronic processing of organellar RNAs and allowed novel insights into the function of the dominant family of organellar RNA binding proteins, the PPR proteins. A chloroplast ribonucleoprotein CP31A is shown to be involved in stabilization of an mRNA for a central component of the NDH-complex by interaction with its 3’UTR. In addition, CP31A represents the first factor described that influences the accumulation of chloroplast antisense transcripts. Finally, ten novel plastid C to U RNA-editing sites were identified in the model plant Arabidopsis thaliana, using a novel RNA-Seq based approach.

Text in English / Corridor disease is an economically important tick-borne disease of cattle in southern Africa. The disease is caused by Theileria parva and transmitted by the vectors, Rhipicephalus appendiculatus and R. zambeziensis. There is currently no vaccine to protect cattle against T. parva that is permitted in South Africa. To develop recombinant anti-tick vaccines against Corridor disease, comprehensive databases of genes expressed in the tick’s salivary glands are required. Therefore, in Chapters 2 and 3, mRNA from the salivary glands of R. appendiculatus and R. zambeziensis was sequenced and assembled using next generation sequencing technologies. Respectively, 12 761 and 13 584 non-redundant protein sequences were predicted from the sialotranscriptomes of R. appendiculatus and R. zambeziensis and uploaded to public sequence domains. This greatly expanded the number of sequences available for the two vectors, which will be invaluable resources for the selection of vaccine candidates in future. Further, in Chapter 3, differential gene expression analysis in R. zambeziensis revealed dynamic expression of secretory protein transcripts during feeding, suggestive of stringent transcriptional regulation of these proteins. Knowledge of these intricate expression profiles will further assist vaccine development in future. In Chapter 4, comparative sialotranscriptomic analyses were performed between R. appendiculatus and R. zambeziensis. The ticks have previously shown varying vector competence for T. parva and this chapter presents the search for correlates of this variance. Phylogenetic analyses were performed using these and other publically available tick transcriptomes, which indicated that R. appendiculatus and R. zambeziensis are closely related but distinct species. However, significant expression differences were observed between the two ticks, specifically of genes involved in tick immunity or pathogen transmission, signifying potential bioinformatic signatures of vector competence. Furthermore, nearly four thousand putative long non-coding RNAs (lncRNAs) were predicted in each of the two ticks. A large number of these showed differential expression and suggested a potential transcriptional regulatory function of lncRNA in tick blood feeding. LncRNAs are completely unexplored in ticks. Finally, in Chapter 5, concluding remarks are given on the potential impact the R. appendiculatus and R. zambeziensis sialotranscriptomes may have on future vaccine developments and some future research endeavours are discussed. / Life and Consumer Sciences / Ph. D. (Life Sciences)

Human complex diseases, like Diabetes and Cancer, affect many people worldwide today. Despite existing knowledge, many of these diseases are still not preventable. Complex diseases are known to be caused by a combination of genetic factors, as well as environmental and life style factors. The scope of this investigation covered the genomics of Type 1 Diabetes (T1D). There are 49 human genomic regions that are known to carry markers (disease-associated single nucleotide mutations) for T1D, and these were extensively studied in this research. The aim was to find out in how far this disease may be caused by problems in gene regulation rather than in gene coding. For this, the genetic factors associated with T1D, including the single point mutations and susceptibility regions, were characterised on the basis of their genomic attributes. Furthermore, mutations that occur in binding sites for transcription factors were analysed for change in the conspicuousness of their binding region, caused by allele substitution. This is called SNP (Single nucleotide polymorphism) sensitivity. From this study, it was found that the markers for T1D are mostly non-coding SNPs that occur in introns and non-coding gene transcripts, these are structures known to be involved in gene regulatory activity. It was also discovered that the T1D susceptibility regions contain an abundance of intronic, non-coding transcript and regulatory nucleotides, and that they can be split into three distinct groups on the basis of their structural and functional genomic contents. Finally, using an algorithm designed for this study, thirty-seven SNPs that change the representation of their surrounding region were identified. These regulatory mutations are non-associated T1D-SNPs that are mostly characterised by Cytosine to Thymine (C-T) transition mutations. They were found to be closer in average distance to the disease-associated SNPs than other SNPs in binding sites, and also to occur frequently in the binding motifs for the USF (Upstream stimulatory factor) protein family which is linked to problems in Type 2 diabetes.

No description available.

No description available.

The Transcription Start Site Associated non-coding RNAs (TSSaRNAs) have been predicted across the three domain of life. However, still, there are no reliable annotation efforts to identify their biological functions and their underline molecular machinery. Therefore, this project addresses the question of what are the potential functions of TSSaRNAs regarding their roles in addressing the cellular functions. To answer this question, we aimed to accurately identify TSSaRNAs in the model organism Halobacterium salinarum NRC-1 (an Archean microorganism) that incubated at the standard growth condition. Consequently, we aimed to investigate TSSaRNAs structural stability in the term of the thermodynamic energies. Moreover, we attempted to functionally annotate TSSaRNAs based on Rfam functional classification of non-coding RNAs. Based on the statistical approach we developed an algorithm to predict TSSaRNA using next-generation RNA sequencing data (RNA-Seq). To perform structural annotation of TSSaRNAs, we investigated the structural stability of TSSaRNAs by modeling the secondary structures by minimizing the thermodynamic free energy. We simulated TSSaRNAs tertiary structures based on the secondary structures constrain using the Rosetta-Common RNA tool. The structures of the minimum free energy supposed to be biophysically stable structures. To investigate the higher order structures of TSSaRNAs, we studied the hybridization between TSSaRNAs and their cognate genes as part of RNA based regulation system. Also, based on our hypothesis that TSSaRNAs may bind to protein to trigger their function, we have investigated the interaction between TSSaRNAs and Lsm protein which known as a chaperone protein that mediates RNA function and involved in RNA processing. Our pipeline to perform the functional annotation of TSSaRNAs aimed to classify TSSaRNAs into their corresponding Rfam families based on two steps: either through querying TSSaRNAs sequences against the co-variance models of Rfam families or by querying the Rfam sequences against the co-variance models of the consensus secondary structures in TSSaRNAs. The results showed that the prediction algorithm has succeeded to identify a total of 224 TSSaRNAs that expressed in the same strand of the mRNAs and 58 TSSaRNAs that expressed as antisense of the mRNAs. The identified TSSaRNAs molecules showed a median length of 25 nucleotides. Regarding the structural annotation of TSSaRNAs, the results showed that most of TSSaRNAs possessed thermodynamically stable secondary structures and their tertiary structures were capable of forming more complex structures through binding with other biomolecules. About the formation of higher-order structures, we have observed that most of TSSaRNAs (92.2%) were capable of hybridizing into their cognate genes also 55 TSSaRNAs indicated putative interactions with Lsm protein. Furthermore, the computation docking experiments demonstrated the TSSaRNAs-Lsm complexes associated with favorable binding energy of a median of -542900 kcal mole -¹. Regarding the functional annotation of TSSaRNAs, the results showed that the majority of TSSaRNAs (42.05%) considered as potential cis-acting regulators such as cis-regulatory element and sRNAs, but still, there are potential trans-acting regulators to regulate distant molecules such as CRISPR and antisense RNA. Moreover, the results indicated that TSSaRNAs could trigger more complex function as a catalytic function such as Riboswitch or to play a role in the defense against a virus such as CRISPR. As a conclusion; based on the results of this study we could state that TSSaRNAs have several potential functions opening the experimental validation perspective. / Os RNA não codificantes associados ao sítio de início da transcrição - em inglês, transcription start site associated non-coding RNAs (TSSaRNA) - foram observados nos três domínios da vida. No entanto, sem esforço confiável de anotação para identificar suas funções biológicas e seus mecanismos moleculares. Portanto, esse projeto levanta a questão de quais são as funções em potencial dos TSSaRNAs a respeito de seus papeis nas funções celulares. Para responder esta questão, nós objetivamos em identificar de forma eficaz os TSSaRNAs no organismo modelo Halobacterium salinarum NRC-1 (um microrganismo do domínio Arqueia) encubado em uma condição de crescimento padrão. Consequentemente, nós investigamos a estabilidade estrutural dos TSSaRNAs em relação a energias termodinâmicas. Ainda, fizemos a anotação funcional dos TSSaRNAs baseado na classificação funcional Rfam dos RNAs não-codificantes. Baseada em uma abordagem estatística nós desenvolvemos um algoritmo para predizer TSSaRNA usando dados de sequenciamento de RNA de nova geração (RNA-Seq). Para investigar a estabilidade estrutural dos TSSaRNAs nós modelamos as estruturas secundárias minimizando a energia livre termodinâmica para alcançar a estrutura mais estável biofisicamente. Nós simulamos estruturas terciárias de TSSaRNAs baseado nas restrições das estruturas secundárias usando a ferramenta Rosetta-Common RNA. As estruturas de energia livre mínima seriam supostamente estruturas estáveis biofisicamente. Para investigar as estruturas de ordem superior (quaternária) dos TSSaRNAs, nós estudamos a hibridização entre os TSSaRNAs e seus genes cognatos como parte de um possível sistema de regulação baseado em RNA. Ainda, baseada na hipótese que os TSSaRNAs podem ligar à proteína para habilitar sua função, nós investigamos a interação entre TSSaRNAs e proteína Lsm que é conhecida por ser uma proteína chaperone que media função do RNA e está envolvida no processamento do RNA. Nosso pipeline para executar a anotação funcional dos TSSaRNAs objetivou classificar as TSSaRNAs em suas correspondentes classes Rfam baseado em dois passos: por meio de consulta das sequências TSSaRNA em relação a modelos de covariância de famílias Rfam ou por consulta de sequências Rfam em relação a modelos de covariância das estruturas de secundárias de consenso das estruturas secundárias nos TSSaRNAs. Os resultados mostraram que o algoritmo de detecção teve sucesso em identificar um total de 224 TSSaRNAs que expressaram na mesma direção dos mRNAs e 58 TSSaRNAs que expressaram no sentido oposto (antisenso) dos mRNAs. As moléculas TSSaRNAs identificadas mostraram um comprimento mediano de 25 nucleotídeos. A respeito da anotação estrutural dos TSSaRNAs, os resultados mostraram que a maioria dos TSSaRNAs possuíam estruturas secundárias estáveis termodinamicamente e suas estruturas terciárias foram capazes de formar estruturas mais complexas por meio de vínculos com outras biomoléculas. Quanto à formação de estruturas de maior de estruturas de alta ordem nos observamos que a maioria dos TSSaRNAs (92.2%) são capazes, pelo menos em princípio, de hibridizar em seus genes cognatos e, também, 55 TSSaRNAs evidenciaram interagir com a proteína Lsm. Além disso, os experimentos computacionais de docking demonstratam os complexos TSSaRNAs-Lsm associados com energia de ligação favorável com uma média de - 542900 kcal mole -¹. Quanto à anotação funcional dos TSSaRNAs, os resultados mostraram que a maioria dos TSSaRNAs (42.05%) podem ser consideradas potenciais reguladores atuando em cis tais como elemento cis-regulamentar e sRNAs, mas ainda há pontenciais reguladores atuando em trans para regular moléculas em loci distantes, tais como CRISPR e RNA antisense. Além disso, os resultados mostraram que TSSaRNAs podem potencialmente ativar funções mais complexas como uma função catalítica, tal como Riboswitch ou executar um papel de defesa contra vírus, tal como CRISPR. Como conclusão; baseado nos resultados desse estudo, nós podemos afirmar que TSSaRNAs possuem várias funções em potencial abrindo a perspecitiva de validação experimental.