Bipolar disorder and schizophrenia are two severe psychiatric disorders characterized by a complex genetic basis, coupled to the influence of environmental factors. In this thesis, functional genomic analysis tools were used for the study of the underlying pathophysiology of these disorders, focusing on gene expression and function on a global scale with the application of high-throughput methods. Datasets from public databases regarding transcriptomic data of postmortem brain and skin fibroblast cells of patients with either schizophrenia or bipolar disorder were analyzed in order to identify differentially expressed genes. In addition, fibroblast cells of bipolar disorder patients obtained from the Biobank of the Neuropsychiatric Research Laboratory of Örebro University were cultured, RNA was extracted and used for microarray analysis. In order to gain deeper insight into the biological mechanisms related to the studied psychiatric disorders, the differentially expressed gene lists were subjected to pathway and target prioritization analysis, using proprietary tools developed by the group of Metabolic Engineering and Bioinformatics, of the National Hellenic Research Foundation, thus indicating various cellular processes as significantly altered. Many of the molecular processes derived from the analysis of the postmortem brain data of schizophrenia and bipolar disorder were also identified in the skin fibroblast cells. Additionally, through the use of machine learning methods, gene expression data from patients with schizophrenia were exploited for the identification of a subset of genes with discriminative ability between schizophrenia and healthy control subjects. Interestingly, a set of genes with high separating efficiency was derived from fibroblast gene expression profiling. This thesis suggests the suitability of skin fibroblasts as a reliable model for the diagnostic evaluation of psychiatric disorders and schizophrenia in particular, through the construction of promising machine-learning based classification models, exploiting gene expression data from peripheral tissues.

This thesis investigates the effect of Russian wheat aphid (RWA; Diuraphis noxia) infestation on the defence responses of the bread wheat line, PI 137739, on a molecular level. PI 137739 is known to contain the RWA resistance gene, Dn1. The study was conducted by utilising and combining a vast array of molecular biological techniques. Chapter 1 introduces the reader to a summary of the resistance responses observed within infested plants. A detailed description of the Russian wheat aphid follows and the genes responsible for RWA resistance in wheat is discussed. A brief report of research performed on the bread wheat genome is given and the biochemical defence responses of plants against insect infestation are discussed. This is followed by a concise description of resistance (R) genes and resistance gene categories in plants. The last discussion concerns microarray technology, a molecular tool utilised during this study. Chapter 2 aims at identifying genes involved in resistance against RWA infestation; specifically, genes containing the conserved nucleotide binding site¬leucine rich repeat (NBS-LRR) motif. Genomic, as well as complementary DNA (cDNA), was utilised in order to compare functional gene expression in wheat infested with the RWA. This was executed by employing PCR-based methods, single-pass sequencing and basic local alignment search tool (BLAST) analyses. Chapter 3 introduces suppression subtractive hybridisation (SSH) as a tool to further identify NBS-LRR or other resistance-related sequences in RWA infested wheat plants. SSH allows the comparative analysis of differential gene expression in RWA infested and uninfested wheat in order to identify resistance-¬related genes expressed in the infested, resistant wheat plants. The effect of RWA infestation on wheat resistance responses was examined further in chapter 4 through microarray analysis. The aim was the introduction and establishment of the microarray technique and to test the feasibility of using microarrays for differential gene expression and regulation studies. Microarray slides were assembled in order to monitor the up- and down¬regulation of genes at different time intervals - day 2, day 5 and day 8 - of RWA infestation. Clones isolated throughout this study were assembled on microarray slides and probed with control and RWA infested RNA. Differential gene regulation was assessed and further confirmed through Northern blot analyses, as well as quantitative real-time PCR. The thesis concludes with a general summary of the results obtained in chapter 5 and future prospects are outlined. / Thesis (PhD(Genetics))--University of Pretoria, 2005. / Genetics / unrestricted

Les microorganismes, par leurs fascinantes capacités d’adaptation liées à l’extraordinaire diversité de leurs capacités métaboliques, jouent un rôle fondamental dans tous les processus biologiques. Jusqu’à récemment, la mise en culture était l’étape préliminaire obligatoire pour réaliser l’inventaire taxonomique et fonctionnel des microorganismes au sein des environnements. Cependant ces techniques ne permettent d’isoler qu’une très faible fraction des populations microbiennes et tendent donc à être remplacées par des outils moléculaires haut-débit. Dans ce contexte, l’évolution des techniques de séquençage a laissé entrevoir de nouvelles perspectives en écologie microbienne mais l’utilisation directe de ces techniques sur des environnements complexes, constitués de plusieurs milliers d’espèces différentes, reste néanmoins encore délicate. De nouvelles stratégies de réduction ciblée de la complexité comme la capture de gènes ou les biopuces ADN représentent alors une bonne alternative notamment pour explorer les populations microbiennes même les moins abondantes. Ces stratégies à haut-débit reposent sur la détermination de sondes combinant à la fois une forte sensibilité, une très bonne spécificité et un caractère exploratoire. Pour concevoir de telles sondes plusieurs logiciels ont été développés : PhylGrid 2.0, KASpOD et ProKSpOD. Ces outils généralistes et polyvalents sont applicables à la sélection de sondes pour tout type de gènes à partir des masses de données produites à l’heure actuelle. L’utilisation d’architectures de calculs hautement parallèles et d’algorithmes innovants basés sur les k-mers ont permis de contourner les limites actuelles. La qualité des sondes ainsi déterminées a pu permettre leur utilisation pour la mise au point de nouvelles approches innovantes en écologie microbienne comme le développement de deux biopuces phylogénétiques, d’une méthode de capture de gènes en solution ainsi que d’un algorithme de classification des données métagénomiques. Ces stratégies peuvent alors être employées pour diverses applications allant de la recherche fondamentale pour une meilleure compréhension des écosystèmes microbiens, au suivi de processus de bioremédiation en passant par l’identification de tous types de pathogènes (eucaryotes, procaryotes et virus). / Microorganisms play a crucial role in all biological processes related to their huge metabolic potentialities. Until recently, the cultivation was a necessary step to appraise the taxonomic and functional diversity of microorganisms within environments. These techniques however allow surveying only a small fraction of microbial populations and tend to be consequently replaced by highthroughput molecular tools. While the evolution of sequencing technologies opened the door to unprecedented opportunities in microbial ecology, massive sequencing of complex environments, with thousands of species, still remains inconceivable. To overcome this limitation, strategies were developed to reduce the sample complexity such as gene capture or DNA microarrays.These high-throughput strategies rely on the selection of sensitive, specific and explorative probes. To design such probes several programs have been developed: PhylGrid 2.0, KASpOD and ProKSpOD. These multipurpose tools were implemented to design probes from the exponentially growing sequence datasets in microbial ecology. Using highly parallel computing architectures and innovative k-mers based strategies allowed overcoming major limitations in this field. The high quality probe sets were used to develop innovative strategies in microbial ecology including two phylogenetic microarrays, a gene capture approach and a taxonomic binning algorithm for metagenomic data. These approaches can be carried out for various applications including better understanding of microbial ecosystems, bioremediation monitoring or identification of pathogens (eukaryotes, prokaryotes and viruses).

The genus Candida includes several opportunistically pathogenic species which are common causative agents of the yeast infections in humans. Although current medical research is focused mostly on cancer, AIDS or Alzheimer disease, the problem of systemic candidiases cannot be neglected. These infections represent a real threat to the immunocompromissed patients, they are connected with a high mortality rate and expensive medication with poor prognosis. Pseudomonas aeruginosa could be an inspiration in a way of how to eliminate the pathogenic yeasts. The bacterium can inhibit growth of the most common yeast species of the genus Candida, C. albicans. This effect is based on production of toxic substances by the bacterium and on interaction of the bacterium with the C. albicans cell wall, which leads to the lysis of the yeast cells and which is not fully understood. Nevertheless, coexistence of these microorganisms is also possible and their relationship is affected by various factors. Knowledge of these inter- microbial interactions was obtained from studies of diseases and pathologies, during which C. albicans + P. aeruginosa coinfections occur. In this thesis I studied mechanisms of interaction between pathogenic yeast C. albicans and bacterium P. aeruginosa by a) C. albicans gene expression...

eDNA microarray technology has generated a tremendous amount of interest among biologists because of its promise to monitor the entire genome on a single chip, thus enabling researchers to have a better picture of the interaction among thousands of genes simultaneously. In the current study, this technology was used to print over 3,000 unknown genes from various silk glands of the black widow spider to profile their expression patterns and to identify novel candidates. Spiders are remarkable creatures because of their ability to make different silks, each with a specific function. Some of these silks have amazing mechanical properties, comparable to those of the finest synthetic materials. Several silk genes have been cloned from various spiders over the last few years, and the contribution of each of those genes in silk production has been identified. However, the majority of cellular and biochemical processes involved in silk manufacture remain a mystery. In our research, we attempt to identify genes that might be involved in silk assembly, on a global scale and investigate more about those genes and their interplay with other key biological molecules involved in silk manufacture. Our study showed that silking spiders for a certain period of time resulted in down-regulation of two important silk genes, ECP-1 and ECP-2. Both these genes are key molecules implicated for their role in maintaining the egg case architecture in the black widow spider.,-and we believe that these genes are also directly or indirectly involved in the manufacture of dragline silk. Microarray analyses also enable the discovery of several other interesting molecules, two of which could be accessory proteins involved in silk formation. Furthermore, in a separate study we also characterized a novel silk glue protein with unique ensemble repeats. In conclusion, we believe that the findings of this study will indeed be significant to silk researchers and material scientists alike and it will enhance our knowledge in understanding the mystery behind silk production.

No description available.

Nesta tese, apresentamos nossas estratégias para desenvolver um ambiente matemático e computacional para análises em larga-escala de dados de expressão gênica obtidos pela tecnologia de microarranjos de DNA. As análises realizadas visaram principalmente à identificação de marcadores moleculares de diagnóstico e prognóstico de cânceres humanos. Apresentamos o resultado de diversas análises implementadas através do ambiente desenvolvido, as quais conduziram a implementação de uma ferramenta computacional para a anotação automática de plataformas de microarranjos de DNA e de outra ferramenta destinada ao rastreamento da análise de dados realizada em ambiente R. Programação eXtrema (eXtreme Programming, XP) foi utilizada como técnica de planejamento e gerenciamento dos projetos de análise dados de expressão gênica. Todos os conjuntos de dados foram obtidos por nossos colaboradores, utilizando-se duas diferentes plataformas de microarranjos de DNA: a primeira enriquecida em regiões não-codificantes do genoma humano, em particular regiões intrônicas, e a segunda representando regiões exônicas de genes humanos. A primeira plataforma foi utilizada para avaliação do perfil de expressão gênica em tumores de próstata e rim humanos, sendo que análises utilizando SAM (Significance Analysis of Microarrays) permitiram a proposição de um conjunto de 49 sequências como potenciais biomarcadores de prognóstico de tumores de próstata. A segunda plataforma foi utilizada para avaliação do perfil de transcritos expressos em sarcomas, carcinomas epidermóide e carcinomas epidermóides de cabeça e pescoço. As análises com sarcomas permitiram a identificação de um conjunto de 12 genes relacionados à agressividade local e metástase. As análises com carcinomas epidermóides de cabeça e pescoço permitiram a identificação de 7 genes relacionados à metástase linfonodal. / In this PhD Thesis, we present our strategies to the development of a mathematical and computational environment aiming the analysis of large-scale microarray datasets. The analyses focused mainly on the identification of molecular markers for diagnosis and prognosis of human cancers. Here we show the results of several analyses implemented using this environment, which led to the development of a computational tool for automatic annotation of DNA microarray platforms and a tool for tracking the analysis within R environment. We also applied eXtreme Programming (XP) as a tool for planning and management of gene expression analyses projects. All data sets were obtained by our collaborators using two different microarray platforms. The first is enriched in non-coding human sequences, particularly intronic sequences. The second one represents exonic regions of human genes. Using the first platform, we evaluated gene expression profiles of prostate and kidney human tumors. Applying SAM to prostate tumor data revealed 49 potential molecular markers for prognosis of this disease. Gene expression in samples of sarcomas, epidermoid carcinomas and head and neck epidermoid carcinomas was investigated using the second platform. A set of 12 genes were identified as potential biomarkers for local aggressiveness and metastasis in sarcoma. In addition, the analyses of data obtained from head and neck epidermoid carcinomas allowed the identification of 7 potential biomarkers for lymph-nodal metastases.

INTRODUÇÃO: O aracnídeo Phoneutria nigriventer, também conhecido por aranha-armadeira, possui um veneno complexo, contendo vários peptídeos que ativam canais iônicos nas células. Dentre estes, só dois neuropeptídeos, Tx2-5 e Tx2-6, destacam-se por relaxar o músculo liso trabecular do corpo cavernoso, induzindo ereção peniana em camundongos e ratos. Este efeito tem sido associado à produção de oxido nítrico pela ativação de óxido nítrico sintases. No entanto, faltam estudos mais amplos para determinar o papel de Tx2-6 na indução da ereção. OBJETIVOS: Identificar os genes diferencialmente expressos no tecido erétil de camundongos após indução da ereção pela Tx2-6 utilizando microarranjos de oligonucleotídeos. Validação dos resultados obtidos nos microarranjos por PCR quantitativa e imuno-histoquímica. MATERIAIS E MÉTODOS: Camundongos machos e adultos da linhagem Swiss foram divididos em dois grupos: controle (n=10), inoculados pela via intracavernosa com 20 l de solução salina; e tratado (n=10), os quais receberam 0,006gg/animal do peptídeo Tx2-6 diluído em 20 l de salina pela via intracavernosa. Uma hora após o início da ereção no grupo tratado todos os animais foram sacrificados e retirou-se o pênis. Este último foi dividido em dois fragmentos, uma parte do material foi congelada em nitrogênio líquido e mantida a 80°C até a extração do RNA para os experimentos de microarranjos e PCR quantitativa; outra parte foi utilizada para avaliação imuno-histoquímica. RESULTADOS: No grupo tratado a ereção foi observada 30-45 minutos após aplicação de Tx2-6 e mantida durante 120 minutos. Os camundongos de grupo controle não apresentaram nenhum indício de ereção. Nos experimentos de microarranjos, onde foram analisados 34.000 genes representando o genoma total do camundongo, identificou-se 3.803 (12,3%) genes com expressão diferencial de pelo menos ±1,5 vez entre os grupos (1.823 genes superexpressos e 1.980 genes subexpressos no grupo tratado comparado ao controle). Os genes ednrb, sparc, fn1, sstr2, pdgfr foram selecionados para validação dos microarranjos por PCR quantitativa e confirmaram a superexpressão em relação aos controles. As proteínas Fn1, Sstr2 e Pdgfr resultaram aumentadas no grupo tratado após avaliação imuno-histoquímica. CONCLUSÕES: A inoculação de Tx2-6 pela via intracavernosa alterou o perfil de expressão gênica no tecido erétil de camundongos. O número de genes superexpressos foi similar ao de genes subexpressos. Serão necessários outros estudos para entender melhor as vias moleculares que Tx2-6 afeta na indução da ereção peniana. / INTRODUCTION: The Phoneutria nigriventer arachnid, also known as armed-spider, has a complex venom, composed by several peptides that affect cellular ionic channels. Among these, only two neuropeptides, Tx2-5 and Tx2-6 induce penile erection in mice and rats and this effect has been associated with the production of nitric oxide by the activation of nitric oxide synthases. Moreover, there is a scarcity of studies focusing on the role of Tx2-6 in the induction of erection. OBJECTIVES: To identify the differently expressed genes in the erectile tissue of mice after erection induction by Tx2-6 using oligonucleotide microarrays. To validate microarray results by quantitative PCR and immunohistochemistry. MATERIALS AND METHODS: Swiss adult male mice were divided in two groups: control (n=10) were injected intracavernously with 20 gl of saline solution; and treated (n=10) were injected intracavernously with 0.006gg/mouse of the Tx2-6 peptide diluted in 20 gl of saline solution. After checking the penile erection in the treated group, all mice were sacrificed one hour after the beginning of erection for the removal of the penis. Penile organ was divided into two fragments, one piece was immediately frozen in liquid-nitrogen and stored at -80°C until RNA extraction to make the microarray and quantitative PCR experiments; the other was reserved for immunohistochemistry analysis. RESULTS: In the treated group, erection was noticed 30-45 minutes after Tx2-6 inoculation and lasted for 120 minutes. Control mice did not present any sign of erection. Considering as differentially expressed genes with a ±1.5 fold expression difference, of the 34,000 genes on the microarray we identified 3,803 (12.3%) genes differentially expressed between the groups (1,823 genes up-regulated and 1,980 genes down-regulated in the treated group compared to controls). The ednrb, sparc, fn1, sstr2, pdgfr genes were selected for validation of microarray results by using quantitative PCR and confirmed the up-regulation when compared to controls. After immunohistochemistry analysis the Fn1, Sstr2 and Pdgfr proteins were found increased in the treated group. CONCLUSIONS: The intracavernous inoculation of Tx2-6 modified the gene expression profile of erectile tissue of mice. The number of upregulated and down-regulated genes was similar. Further studies are needed to understand the molecular pathways that Tx2-6 affect to induce penile erection.

This thesis consists of two parts. The first part focuses on high-dimensional classification problems in microarray experiments. The second part deals with forecasting problems with a large number of categories in predictors. Classification problems in microarray experiments refer to discriminating subjects with different biologic phenotypes or known tumor subtypes as well as to predicting the clinical outcomes or the prognostic stages of subjects. One important characteristic of microarray data is that the number of genes is much larger than the sample size. The penalized logistic regression method is known for simultaneous variable selection and classification. However, the performance of this method declines as the number of variables increases. With this concern, in the first study, we propose a new classification approach that employs the penalized logistic regression method iteratively with a controlled size of gene subsets to maintain variable selection consistency and classification accuracy. The second study is motivated by a modern microarray experiment that includes two layers of replicates. This new experimental setting causes most existing classification methods, including penalized logistic regression, not appropriate to be directly applied because the assumption of independent observations is violated. To solve this problem, we propose a new classification method by incorporating random effects into penalized logistic regression such that the heterogeneity among different experimental subjects and the correlations from repeated measurements can be taken into account. An efficient hybrid algorithm is introduced to tackle computational challenges in estimation and integration. Applications to a breast cancer study show that the proposed classification method obtains smaller models with higher prediction accuracy than the method based on the assumption of independent observations. The second part of this thesis develops a new forecasting approach for large-scale datasets associated with a large number of predictor categories and with predictor structures. The new approach, beyond conventional tree-based methods, incorporates a general linear model and hierarchical splits to make trees more comprehensive, efficient, and interpretable. Through an empirical study in the air cargo industry and a simulation study containing several different settings, the new approach produces higher forecasting accuracy and higher computational efficiency than existing tree-based methods.

The past few decades have witnessed a revolution in recombinant DNA and nucleic acid sequencing technologies. Recently however, technologies capable of massively high-throughout, genome-wide data collection, combined with computational and statistical tools for data mining, integration and modeling have enabled the construction of predictive networks that capture cellular regulatory states, paving the way for ‘Systems biology’. Consequently, protein interactions can be captured in the context of a cellular interaction network and emergent ‘system’ properties arrived at, that may not have been possible by conventional biology. The ability to generate data from multiple, non-redundant experimental sources is one of the important facets to systems biology. Towards this end, we have established a novel platform called ‘spotted cell microarrays’ for conducting image-based genetic screens. We have subsequently used spotted cell microarrays for studying multidimensional phenotypes in yeast under different regulatory states. In particular, we studied the response to mating pheromone using a cell microarray comprised of the yeast non-essential deletion library and analyzed morphology changes to identify novel genes that were involved in mating. An important aspect of the mating response pathway is large-scale spatiotemporal changes to the proteome, an aspect of proteomics, still largely obscure. In our next study, we used an imaging screen and a computational approach to predict and validate the complement of proteins that polarize and change localization towards the mating projection tip. By adopting such hybrid approaches, we have been able to, not only study proteins involved in specific pathways, but also their behavior in a systemic context, leading to a broader comprehension of cell function. Lastly, we have performed a novel metabolic starvation-based screen using the GFP-tagged collection to study proteome dynamics in response to nutrient limitation and are currently in the process of rationalizing our observations through follow-up experiments. We believe this study to have implications in evolutionarily conserved cellular mechanisms such as protein turnover, quiescence and aging. Our technique has therefore been applied towards addressing several interesting aspects of yeast cellular physiology and behavior and is now being extended to mammalian cells. / text