Die Aufklärung der Mechanismen zur Kontrolle der Genexpression ist eines der wichtigsten Probleme der modernen Molekularbiologie. Detaillierte experimentelle Untersuchungen sind enorm aufwändig aufgrund der komplexen und kombinatorischen Wechselbeziehungen der beteiligten Moleküle. Infolgedessen sind bioinformatische Methoden unverzichtbar. Diese Dissertation stellt drei Methoden vor, die die Vorhersage der regulatorischen Elementen der Gentranskription verbessern. Der erste Ansatz findet Bindungsstellen, die von den Transkriptionsfaktoren erkannt werden. Dieser sucht statistisch überrepräsentierte kurze Motive in einer Menge von Promotersequenzen und wird erfolgreich auf das Genom der Bäckerhefe angewandt. Die Analyse der Genregulation in höheren Eukaryoten benötigt jedoch fortgeschrittenere Techniken. In verschiedenen Datenbanken liegen Hunderte von Profilen vor, die von den Transkriptionsfaktoren erkannt werden. Die Ähnlichkeit zwischen ihnen resultiert in mehrfachen Vorhersagen einer einzigen Bindestelle, was im nachhinein korrigiert werden muss. Es wird eine Methode vorgestellt, die eine Möglichkeit zur Reduktion der Anzahl von Profilen bietet, indem sie die Ähnlichkeiten zwischen ihnen identifiziert. Die komplexe Natur der Wechselbeziehung zwischen den Transkriptionsfaktoren macht jedoch die Vorhersage von Bindestellen schwierig. Auch mit einer Verringerung der zu suchenden Profile sind die Resultate der Vorhersagen noch immer stark fehlerbehafted. Die Zuhilfenahme der unabhängigen Informationsressourcen reduziert die Häufigkeit der Falschprognosen. Die dritte beschriebene Methode schlägt einen neuen Ansatz vor, die die Gen-Anotation mit der Regulierung von multiplen Transkriptionsfaktoren und den von ihnen erkannten Bindestellen assoziiert. Der Nutzen dieser Methode wird anhand von verschiedenen wohlbekannten Sätzen von Transkriptionsfaktoren demonstriert. / Understanding the mechanisms which control gene expression is one of the fundamental problems of molecular biology. Detailed experimental studies of regulation are laborious due to the complex and combinatorial nature of interactions among involved molecules. Therefore, computational techniques are used to suggest candidate mechanisms for further investigation. This thesis presents three methods improving the predictions of regulation of gene transcription. The first approach finds binding sites recognized by a transcription factor based on statistical over-representation of short motifs in a set of promoter sequences. A succesful application of this method to several gene families of yeast is shown. More advanced techniques are needed for the analysis of gene regulation in higher eukaryotes. Hundreds of profiles recognized by transcription factors are provided by libraries. Dependencies between them result in multiple predictions of the same binding sites which need later to be filtered out. The second method presented here offers a way to reduce the number of profiles by identifying similarities between them. Still, the complex nature of interaction between transcription factors makes reliable predictions of binding sites difficult. Exploiting independent sources of information reduces the false predictions rate. The third method proposes a novel approach associating gene annotations with regulation of multiple transcription factors and binding sites recognized by them. The utility of the method is demonstrated on several well-known sets of transcription factors. RNA interference provides a way of efficient down-regulation of gene expression. Difficulties in predicting efficient siRNA sequences motivated the development of a library containing siRNA sequences and related experimental details described in the literature. This library, presented in the last chapter, is publicly available at http://www.human-sirna-database.net

The study of cis-regulatory elements (CREs) will allow for increased understanding of regulation and lead to insight regarding the mechanisms governing growth, development, health, and disease. The aim of this study was to characterize the de novo in silico predictions of Arabidopsis CREs. Eight synthetic and 30 native promoter-constructs containing an eGFP/GUS reporter protein were generated for cold, genotoxic, heat, osmotic, and salt stress; the circadian clock; ABA signaling; root and epidermis tissue. Constructs were stably transformed into A. thaliana Col-0 and the effects of the CREs were evaluated by in planta stress or tissue assays using GUS expression levels. Results reveal a novel genotoxic element that specifically directs GUS expression in rosette leaves during genotoxic stress. Results also look promising for novel epidermis and root-specific elements. Results of these assays validate the de novo prediction pipeline's ability to identify novel and known CREs related to abiotic stress.

The study of cis-regulatory elements (CREs) will allow for increased understanding of regulation and lead to insight regarding the mechanisms governing growth, development, health, and disease. The aim of this study was to characterize the de novo in silico predictions of Arabidopsis CREs. Eight synthetic and 30 native promoter-constructs containing an eGFP/GUS reporter protein were generated for cold, genotoxic, heat, osmotic, and salt stress; the circadian clock; ABA signaling; root and epidermis tissue. Constructs were stably transformed into A. thaliana Col-0 and the effects of the CREs were evaluated by in planta stress or tissue assays using GUS expression levels. Results reveal a novel genotoxic element that specifically directs GUS expression in rosette leaves during genotoxic stress. Results also look promising for novel epidermis and root-specific elements. Results of these assays validate the de novo prediction pipeline's ability to identify novel and known CREs related to abiotic stress.

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Xylella fastidiosa é uma bactéria gram-negativa, não flagelada, agente causal de doenças de importância econômica como a doença de Pierce nas videiras e a clorose variegada dos citros (CVC) nas laranjeiras. O objetivo do presente trabalho foi realizar análises in silico das sequências promotoras dos genes deste fitopatógeno em uma tentativa de arrecadar novas evidências para o melhor entendimento da dinâmica de regulação transcricional de seus genes, incluindo aqueles envolvidos em mecanismos de patogenicidade e virulência. Para tanto, duas estratégias foram utilizadas para predição de elementos cis-regulatórios em regiões promotoras do genoma da cepa referência 9a5c, comprovadamente associada à CVC. A primeira, conhecida como phylogenetic footprinting, foi empregada para identificação de elementos regulatórios conservados em promotores de unidades transcricionais ortólogas, levando em consideração o conjunto de genes de X. fastidiosa e 7 espécies comparativas. O critério para identificação de unidades transcricionais ortólogas, isto é, unidades trancricionais oriundas de espécies distintas e cujos promotores compartilham elementos cis-regulatórios, foi paralelamente estudado utilizando-se informações regulatórias das bactérias modelos: Pseudomonas aeruginosa, Bacillus subtilis e Escherichia coli. Os resultados obtidos com análise de phylogenetic footprinting nos permitiu acessar a rede regulatória transcricional da espécie de forma compreensiva (global). Foram estabelecidas 2990 interações regulatórias, compreendendo 80 motivos distribuídos nos promotores de 56.8% das unidades transcricionais do genoma de X. fastidiosa. Na segunda estratégia recuperamos informações regulatórias experimentalmente validadas em E. coli e complementamos o conhecimento de dez regulons de X. fastidiosa, através de uma metodologia de scanning (varredura), dos quais algumas interações regulatórias já haviam sido previamente descritas por outros trabalhos. Destacamos os regulons de Fur e CRP, reguladores transcricionais globais, que se mostraram responsáveis pela modulação de genes relacionados a mecanismos de invasão e colonização do hospedeiro vegetal entre outros. Por fim, análises comparativas em regiões regulatórias correspondentes entre cepas foram realizadas e diferenças possivelmente associadas a particularidades fenotípicas foram identificadas entre 9a5c e J1a12, um isolado de citros não virulento, e 9a5c e Temecula1, um isolado de videira causador da doença de Pierce. / Xylella fastidiosa is a gram-negative, non-flagellated bacterium responsible for causing economically important diseases such as Pierce\'s disease in grapevines and Citrus Variegated Clorosis (CVC) in sweet orange trees. In the present work we performed in silico analysis on promoter sequences of protein-coding genes from this phytopathogen, including those involved in virulence and pathogenic mechanisms, in an attempt to better understand the underlying transcriptional regulatory dynamics. Two strategies for cis-regulatory elements prediction were applied on promoter sequences from 9a5c strain genome, a proven causal agent of CVC. The first one, known as phylogenetic footprinting, involved the prediction of regulatory motifs conserved on promoter sequences of orthologous transcription units from X. fastidiosa and a set of 7 comparatives species. The criteria to identify orthologous transcription units, i. e., those from different species and whose promoter sequences share at least one common regulatory motif, was studied based on regulatory information available for model organisms: Pseudomonas aeruginosa, Bacillus subtilis and Escherichia coli. The results obtained with the phylogenetic footprinting analysis permitted us to access the underlying transcriptional regulatory network from the species in a comprehensive manner (genome-wide), with a total of 2990 regulatory interactions corresponding to 80 predicted motifs distributed on promoter sequences of 56.8% of all transcription units. In the second strategy regulatory information from E. coli was recovered and used to expand the knowledge of ten regulons in X. fastidiosa, through a scanning process, of which some regulatory interactions were previously described by independent studies. We emphasize some genes related to host invasion and colonization present in the Fur and CRP regulons, two global transcription regulators. Lastly, comparative analysis on corresponding regulatory regions among strains were performed and differences possibly associated to phenotypic variation were identified between 9a5c and J1a12, a non-virulent strain isolated from orange trees, and between 9a5c and Temecula1, a strain associated to Pierce\'s disease on grapevines.