Diese Doktorarbeit behandelt die Beobachtung, daß Koregulationsmuster in Genexpressionsdaten häufig Funktionsstrukturen der Zelle widerspiegeln. Zunächst werden simulierte Genexpressionsdaten und Expressionsdaten aus Hefeexperimenten mit Hilfe von Independent Component Analysis (ICA) und verwandten Faktormodellen untersucht. In einem eher theoretischen Zugang werden anschließend Beziehungen zwischen den Expressionsmustern und der biologischen Funktion der Gene aus einem Optimalitätsprinzip hergeleitet. Lineare Faktormodelle, beispielsweise ICA, zerlegen Genexpressionsmatrizen in statistische Komponenten: die Koeffizienten bezüglich der Komponenten können als Profile von verborgenen Variablen ("Expressionsmoden") interpretiert werden, deren Werte zwischen den Proben variieren. Im Gegensatz zu Clustermethoden beschreiben solche Faktormodelle eine überlagerung biologischer Effekte und die individuellen Reaktionen der einzelnen Gene: jedes Genprofil besteht aus einer überlagerung der Expressionsmoden, die so die gemeinsamen Schwankungen vieler Gene erklären. Die linearen Komponenten werden blind, also ohne zusätzliches biologisches Wissen, aus den Daten geschätzt, und die meisten der hier betrachteten Methoden erlauben es, nahezu schwach besetzte Komponenten zu rekonstruieren. Beim Ausdünnen einer Komponente werden Gene sichtbar, die stark auf die entsprechende Mode reagieren, ganz in Analogie zu Genen, die differentielle Expression zwischen einzelnen Proben zeigen. Verschiedene Faktormodelle werden in dieser Arbeit auf simulierte und experimentelle Expressionsdaten angewendet. Bei der Simulation von Expressionsdaten wird angenommen, daß die Genexpression von einigen unbeobachteten Variablen ("biologischen Expressionsmoden") abhängt, die den Zellzustand beschreiben und deren Einfluss auf die Gene sich durch nichtlineare Funktionen, die sogenannten Genprogramme, beschreiben läßt. Besteht Hoffnung, solche Expressionsmoden durch blinde Datenanalyse wiederzufinden? Die Tests in dieser Arbeit zeigen, daß die Moden mit ICA recht zuverlässig gefunden werden, selbst wenn die Daten verrauscht oder leicht nichtlinear sind und die Anzahl der wahren und der geschätzten Komponenten nicht übereinstimmt. Regressionsmodelle werden an Profile einzelner Gene angepasst, um ihre Expression durch Expressionsmoden aus Faktormodellen oder durch die Expression einzelner Transkriptionsfaktoren zu erklären. Nichtlineare Genprogramme werden mit Hilfe von nichtlinearer ICA ermittelt: solche effektiven Genprogramme könnten zur Beschreibung von Genexpression in großen Zellmodellen Verwendung finden. ICA und verwandte Methoden werden auf Expressionsdaten aus Zellzyklusexperimenten angewendet: neben biologisch interpretierbaren Moden werden experimentelle Artefakte identifiziert, die vermutlich Hybridisierungseffekte oder eine Verunreinigung der Proben widerspiegeln. Für einzelne Komponenten wird gezeigt, daß die koregulierten Gene gemeinsame biologische Funktionen besitzen und daß die entsprechenden Enzyme bevorzugt in bestimmten Bereichen des Stoffwechselnetzes zu finden sind. Die Expressionmechanismen scheinen also - als Ergebnis der Evolution - Funktionsbeziehungen zwischen den Genen widerzuspiegeln: es wäre unter ökonomischen Gesichtspunkten vermutlich ineffizient, wenn kooperierende Gene nicht auch koreguliert würden. Um diese teleologische Vorstellung von Genexpression zu formalisieren, wird in dieser Arbeit ein mathematisches Modell zur Analyse der optimalen differentiellen Expression (ANODE) vorgeschlagen: das Modell beschreibt Regulatoren, also beispielsweise Gene oder Enzyme, und die von ihnen gesteuerten Variablen, zum Beispiel metabolische Flüsse. Das Systemverhalten wird durch eine Fitnessfunktion bewertet, die beispielsweise vom bestimmten Stoffwechselflüssen abhängt und die es zu optimieren gilt. Dieses Optimalitätsprinzip definiert eine optimale Reaktion der Regulatoren auf kleine äußeren Störungen. Zur Berechnung optimaler Regulationsmuster braucht das zu regulierende System nur teilweise bekannt zu sein: es genügt, sein mögliches Verhalten in der Nähe des optimalen Zustandes sowie die lokale Form der Fitnesslandschaft zu kennen. Die Methode wird auf zeitabhängige Störungen erweitert: um die Antwort von Stoffwechselsystemen auf kleine oszillatorische Störungen zu beschreiben, werden frequenzabhängige Kontrollkoeffizienten definiert und durch Summations- und Konnektivitätstheoreme charakterisiert. Um die vorhergesagte Beziehung zwischen Expression und Funktion zu prüfen, werden Kontrollkoeffizienten für ein großes Stoffwechselnetz simuliert, und ihre statistischen Eigenschaften werden untersucht: die Struktur der Kontrollkoeffizientenmatrix bildet die Netztopologie ab, das bedeutet, chemische Reaktionen haben gewöhnlich einen geringen Einfluss auf weit entfernte Teile des Netzes. Außerdem hängen die Kontrollkoeffizienten innerhalb eines Teilnetzes nur schwach von der Modellierung des umgebenden Netzes ab. Verschiedene plausible Annahmen über sinnvolle Expressionsmuster lassen sich formal aus dem Optimalitätsprinzip herleiten: das Hauptergebnis ist eine allgemeine Beziehung zwischen dem Verhalten und der biologischen Funktion von Regulatoren, aus der sich zum Beispiel die Koregulation von Enzymen in Komplexen oder Funktionsmodulen ergibt. Die Funktionen der Gene werden in diesem Zusammenhang durch ihre linearen Einflüsse (die sogenannten Responsekoeffizienten) auf fitnessrelevante Zellvariable beschrieben. Für Stoffwechselenzyme werden aus den Theoremen der metabolischen Kontrolltheorie Summenregeln hergeleitet, die die Expressionsmuster mit der Struktur des Stoffwechselnetzes verknüpfen. Weitere Vorhersagen betreffen eine symmetrische Kompensation von Gendeletionen und eine Beziehung zwischen Genexpression und dem Fitnessverlust aufgrund von Deletionen. Wenn die optimale Steuerung durch eine Rückkopplung zwischen Zellvariablen und den Regulatoren verwirklicht ist, dann spiegeln sich funktionale Beziehungen auch in den Rückkopplungskoeffizienten wider. Daher ist zu erwarten, daß Gene mit ähnlicher Funktion durch Eingangssignale aus denselben Signalwegen gesteuert werden. Das Modell der optimalen Steuerung sagt voraus, daß Expressionsprofile aus Linearkombinationen von Responsekoeffizientenprofilen bestehen: Tests mit experimentellen Expressionsdaten und simulierten Kontrollkoeffizienten stützen diese Hypothese, und die gemeinsamen Komponenten, die aus diesen beiden Arten von Daten geschätzt werden, liefern ein anschauliches Bild der Stochwechselvorgänge, die zur Anpassung an unterschiedliche Umgebungen notwendig sind. Alles in allem werden in dieser Arbeit empirische Beziehungen zwischen der Expression and der Funktion von Genen bestätigt. Darüber hinaus werden solche Beziehungen aus theorischen Gründen vorhergesagt. Ein Hauptziel ist es, teleologische Aussagen über Genexpression auf explizite Annahmen zurückzuführen und dadurch klarer zu formulieren, und so einen theoretischen Rahmen für die Integration von Expressionsdaten und Funktionsannotationen zu liefern. Während andere Autoren die Expression mit Funktionskategorien der Gene oder topologisch definierten Stoffwechselwegen verglichen haben, schlage ich vor, die Funktionen von Genen durch ihre Responsekoeffizienten auszudrücken. Als ein Hauptergebnis dieser Arbeit werden allgemeine Beziehungen zwischen der Funktion, der optimalen Expression und dem Programm eines Gens vorhergesagt. Soweit die Optimalitätsannahme gilt, rechtfertigt das Modell die Verwendung von Expressionsdaten zur Funktionsannotation und zur Rekonstruktion von Stoffwechselwegen und liefert außerdem eine funktionsbezogene Interpretation für die linearen Komponenten in Expressionsdaten. Die Methoden aus dieser Arbeit sind nicht auf Genexpressionsdaten beschränkt: die Faktormodelle lassen sich auch auf Protein- und Metabolitdaten anwenden, und das Optimalitätsprinzip könnte ebenfalls auf andere Steuerungsmechanismen angewendet werden, beispielsweise auf die allosterische Steuerung von Enzymen. / This thesis is concerned with the observation that coregulation patterns in gene expression data often reflect functional structures of the cell. First, simulated gene expression data and expression data from yeast experiments are studied with independent component analysis (ICA) and with related factor models. Then, in a more theoretical approach, relations between gene expression patterns and the biological function of the genes are derived from an optimality principle. Linear factor models such as ICA decompose gene expression matrices into statistical components. The coefficients with respect to the components can be interpreted as profiles of hidden variables (called "expression modes") that assume different values in the different samples. In contrast to clusterings, such factor models account for a superposition of effects and for individual responses of the different genes: each gene profile consists of a superposition of the expression modes, which thereby account for the common variation of many genes. The components are estimated blindly from the data, that is, without further biological knowledge, and most of the methods considered here can reconstruct almost sparse components. Thresholding a component reveals genes that respond strongly to the corresponding mode, in comparison to genes showing differential expression among individual samples. In this work, different factor models are applied to simulated and experimental expression data. To simulate expression data, it is assumed that gene expression depends on several unobserved variables ("biological expression modes") which characterise the cell state and that the genes respond to them according to nonlinear functions called "gene programs". Is there a chance to reconstruct such expression modes with a blind data analysis? The tests in this work show that the modes can be found with ICA even if the data are noisy or weakly nonlinear, or if the numbers of true and estimated components do not match. Regression models are fitted to the profiles of single genes to explain their expression by expression modes from factor models or by the expression of single transcription factors. Nonlinear gene programs are estimated by nonlinear ICA: such effective gene programs may be used for describing gene expression in large cell models. ICA and similar methods are applied to expression data from cell-cycle experiments: besides biologically interpretable modes, experimental artefacts, probably caused by hybridisation effects and contamination of the samples, are identified. It is shown for single components that the coregulated genes share biological functions and the corresponding enzymes are concentrated in particular regions of the metabolic network. Thus the expression machinery seems to portray - as an outcome of evolution - functional relationships between the genes: regarding the economy of resources, it would probably be inefficient if cooperating genes were not coregulated. To formalise this teleological view on gene expression, a mathematical model for the analysis of optimal differential expression (ANODE) is proposed in this work: the model describes regulators, such as genes or enzymes, and output variables, such as metabolic fluxes. The system´s behaviour is evaluated by a fitness function, which, for instance, rates some of the metabolic fluxes in the cell and which is supposed to be optimised. This optimality principle defines an optimal response of regulators to small external perturbations. For calculating the optimal regulation patterns, the system to be controlled needs to be known only partially: it suffices to predefine its possible behaviour around the optimal state and the local shape of the fitness function. The method is extended to time-dependent perturbations: to describe the response of metabolic systems to small oscillatory perturbations, frequency-dependent control coefficients are defined and characterised by summation and connectivity theorems. For testing the predicted relation between expression and function, control coefficients are simulated for a large-scale metabolic network and their statistical properties are studied: the structure of the control coefficients matrix portrays the network topology, that is, chemical reactions tend to have little control on distant parts of the network. Furthermore, control coefficients within subnetworks depend only weakly on the modelling of the surrounding network. Several plausible assumptions about appropriate expression patterns can be formally derived from the optimality principle: the main result is a general relation between the behaviour of regulators and their biological functions, which implies, for example, the coregulation of enzymes acting in complexes or functional modules. In this context, the functions of genes are quantified by their linear influences (called ``response coefficients'') on fitness-relevant cell variables. For enzymes controlling metabolism, the theorems of metabolic control theory lead to sum rules that relate the expression patterns to the structure of the metabolic network. Further predictions concern a symmetric compensation for gene deletions and a relation between gene expression and the fitness loss caused by gene deletions. If optimal regulation is realised by feedback signals between the cell variables and the regulators, then functional relations are also portrayed in the linear feedback coefficients, so genes of similar function may be expected to share inputs from the same signalling cascades. According to the model of optimal regulation, expression profiles are linear combinations of response coefficient profiles: tests with experimental expression profiles and simulated control coefficients support this hypothesis, and the common components which are estimated from both kinds of data provide a vivid picture of the metabolic adaptations that are required in different environments. To summarise, empirical relations between gene expression and function have been confirmed in this work. Furthermore, such relations have been predicted on theoretical grounds. A main aim is to clarify teleological assertions about gene expression by deriving them from explicit assumptions, and thus to provide a theoretical framework for the integration of expression data and functional annotations. While other authors have compared expression to functional gene categories or topologically defined metabolic pathways, I propose to relate it to the response coefficients. A main result of this work is that general relations are predicted between a gene's function, its optimal expression behaviour, and its regulatory program. Where the assumption of optimality is valid, the model justifies the use of expression data for functional annotation and pathway reconstruction, and it provides a function-related interpretation for the linear components behind expression data. The methods from this work are not limited to gene expression data: the factor models are applicable to protein and metabolite data as well, and the optimality principle may also apply to other regulatory mechanisms, such as the allosteric control of enzymes.

Le cancer épithélial de l’ovaire est le cancer gynécologique le plus létal. La survie à 5 ans est de 30-40% chez les patientes atteintes d’une tumeur invasive (TOV), comparativement à 95% chez les patientes diagnostiquées pour une tumeur à faible potentiel de malignité ou borderline (LMP). Au laboratoire, l’analyse de l’expression des gènes de la micropuce à ADN U133 d’Affymetrix a révélé que la SERPINA1 est un gène dont l’expression varie entre les tumeurs LMP et TOV. La validation par Q-PCR nous a confirmé que cette antiprotéase est majoritairement surexprimée dans les tumeurs LMP, par rapport aux tumeurs bénignes (BOV) et aux tumeurs TOV. Nous avons donc surexprimé la SERPINA1 dans les lignées cellulaires invasives TOV 112D et TOV 1946 du cancer de l’ovaire et dérivé des clones stables. Les résultats obtenus nous indiquent que la surexpression de la SERPINA1 a un effet sur la capacité d’invasion et de migration cellulaire et non au niveau de la croissance cellulaire et la formation de structures tridimensionnelles. Les résultats issus de l’étude in vivo dans les souris SCID nous permettront de déterminer si la surexpression de la SERPINA1 a un effet sur la tumorigénèse ovarienne. Ainsi, la SERPINA1 demeure à notre avis un candidat d’intérêt pour tenter de mieux comprendre les différences biologiques entre les tumeurs LMP et TOV, ainsi que le rôle des protéases et de leurs inhibiteurs dans la progression tumorale du cancer de l’ovaire. / Epithelial ovarian cancer is the most lethal gynecologic cancer with a five-year survival rate of 30-40% in patients diagnosed with high-grade invasive disease (TOV). This is in stark contrast to the 95% five-year survival in patients diagnosed with low malignant potential (LMP) disease. It is therefore important to understand the biological differences between LMP and TOV. We have previously identified differential expression of SERPINA1 between serous LMP and TOV tumors through gene expression analysis using Affymetrix U133 DNA microarrays. Expression of this protease inhibitor in the majority of LMP tumors was confirmed and validated by Q-PCR. To study the effects of its overexpression on the invasive potential of ovarian cancer cell lines, SERPINA1 was cloned in the pcDNA3.1+ plasmid and stable clones were derived from two invasive ovarian cancer cell lines, TOV 112D and TOV 1946. Comparisons between clones and controls have shown no SERPINA1-dependent difference in cellular growth or spheroid formation. However, effects on cellular migration and invasion are observed in cells overexpressing SERPINA1. Results from an in vivo xenograft study in SCID mice will allow us to determine if SERPINA1 overexpression affects ovarian tumorigenesis. SERPINA1 remains an interesting candidate gene whose further characterization may lead to insights into its role, and the role of proteases and their inhibitors, in ovarian cancer disease progression.

Le cancer épithélial de l’ovaire est le cancer gynécologique le plus létal. La survie à 5 ans est de 30-40% chez les patientes atteintes d’une tumeur invasive(TOV), comparativement à 95% chez les patientes diagnostiquées pour une tumeur à faible potentiel de malignité (LMP). Au laboratoire, l’analyse de l’expression des gènes de la micropuce à ADN HuFL d’Affymetrix a révélé que Cks1 est un gène dont l’expression varie entre les tumeurs LMP et TOV. En effet, ce régulateur du cycle cellulaire est surexprimé dans les tumeurs TOV par rapport aux tumeurs LMP. Nous avons donc déplété Cks1 dans des lignées cellulaires tumorales invasives du cancer de l’ovaire dérivées au laboratoire, soit la TOV112D et la TOV1946, en utilisant des shRNAs sous le contrôle d’un répresseur inductible à la tétracycline. Puis, nous avons dérivé des clones stables inductibles à la tétracycline. Les résultats obtenus nous indiquent que la déplétion de Cks1 n’a pas d’effet sur la prolifération et la migration cellulaires, ni sur la formation de structures tridimensionnelles in vitro. Ainsi, nous pouvons conclure que Cks1 ne joue pas un rôle clé dans la progression tumorale par rapport aux paramètres testés. Or, des études supplémentaires seraient nécessaires pour expliquer les différences biologiques observées entre les deux types de tumeurs étudiées, et justifier cette variation observée de l’expression de Cks1. / Epithelial ovarian cancer is the most lethal gynecologic cancer with a five-year survival rate of only 30-40% in patients diagnosed with high-grade invasive disease (TOV). This contrasts with the 95% five-year survival in patients diagnosed with the low malignant potential (LMP)disease. Previously, we have identified differential expression of Cks1 between serous LMP and TOV tumors through gene expression analysis using Affymetrix HuFL DNA microarrays. Overexpression of this cell cycle regulator was observed in the TOV tumors, but not in the LMP samples. To study its role on the invasive potential of ovarian cancer cell lines, Cks1 was depleted in two tumoral invasive ovarian cancer cell lines established in our laboratory, TOV112D and TOV1946, using an inducible shRNA strategy. Then, tetracycline-inducible stable clones were derived and studied further. Comparisons between clones and controls have shown no Cks1-dependent effect on cellular growth, neither in migration capacity nor spheroid formation. Thus, we can conclude that Cks1 does not play a crucial role in the tested parameters for cancer progression, but further experiments could elucidate the biological differences observed between the two kinds of tumors studied.

O Brasil é o maior produtor mundial de maracujá azedo (Passiflora edulis f. flavicarpa) sendo esta a espécie de maior expressão comercial dentre as passifloras cultivadas. A bacteriose do maracujazeiro, causada por Xanthomonas axonopodis pv. passiflorae (Xap), é uma das doenças mais severas da cultura, acarretando grandes prejuízos aos produtores. Atualmente, é incipiente o conhecimento sobre a interação maracujá azedo-Xap. Diante disso, a identificação e a caracterização dos genes envolvidos no processo de defesa são passos importantes para dar suporte ao desenvolvimento de variedades resistentes. Assim, o objetivo deste trabalho foi identificar e caracterizar genes de maracujá azedo diferencialmente expressos durante a resposta de defesa à Xap, bem como mensurar a sua expressão. Para isso, foram construídas duas bibliotecas subtrativas de cDNA (forward e reverse) usando o método SSH a partir de transcritos de folhas, que foram inoculadas com o patógeno ou solução salina (controle). Após o sequenciamento dos clones, o processamento e a montagem das sequências, as unisequências foram anotadas através da Plataforma PLAZA e do programa computacional Blast2GO. Genes envolvidos em diversos processos biológicos foram selecionados para a validação das bibliotecas por PCR quantitativo. Usando a Plataforma PLAZA, 78 % (764) das unisequências mostraram similaridade com proteínas de Arabidopsis thaliana, enquanto 87 % (866) delas apresentaram similaridade com proteínas putativas de diversas espécies vegetais, quando se utilizou Blast2GO. Na biblioteca forward, foram identificadas 73 proteínas relacionadas à resposta de defesa, dentre as quais estão proteínas envolvidas na sinalização intracelular, na ativação da transcrição e regulação da expressão de genes de defesa, bem como proteínas de defesa, de resistência e relacionadas à patogênese (PRs). Dentre os 22 transcritos validados, 95 % foram diferencialmente expressos em pelo menos um dos três períodos avaliados; os genes mais expressos em resposta à infecção pelo patógeno são os que codificam as enzimas lipoxigenase, (+)-neomentol desidrogenase e quitinase, as quais participam diretamente nas respostas de defesa vegetal. Dos genes cuja expressão foi mais reprimida, dois codificam proteínas relacionadas à fotossíntese e dois codificam proteínas envolvidas na detoxificação da amônia e do H2O2. Nossos resultados sugerem que a planta utiliza um arsenal de transcritos para responder à infecção; entretanto, este arsenal não é eficiente para impedir a ação do patógeno e, consequentemente, o desenvolvimento da bacteriose nas condições estudadas. Nosso estudo é inédito e gerou informações sobre a reprogramação transcricional durante a interação maracujá azedo-Xap, o que constitui um importante passo para o melhor entendimento sobre este patossistema. / Brazil is the main producer of yellow passion fruit (Passiflora edulis f. flavicarpa) worldwide, which is the most widely commercialized crop among the cultivated passifloras. The bacterial leaf spot induced by Xanthomonas axonopodis pv. passiflorae (Xap) is one of the most severe diseases of the crop, causing great losses to producers. Currently, we understand very little about the yellow passion fruit-Xap interaction. Therefore, the identification and characterization of genes involved in the defense process are important steps to support the development of resistant varieties. Thus, the objective of this study was identify and characterize differentially expressed genes during the defense response to Xap, as well as to measure their expression. For that, we constructed two subtractive cDNA libraries (the forward and the reverse) by performing the SSH method from leaf transcripts, which were inoculated with the pathogen or saline solution (control). After sequencing the clones and sequence data processing, sequences were assembled into unique sequences, which were annotated using the PLAZA Platform and the computational program Blast2GO. Genes involved in several biological processes were selected to validate the libraries by quantitative PCR. When PLAZA was used for sequence similarity searches, 78 % (764) of the yellow passion fruit unique sequences showed similarity to proteins of Arabidopsis thaliana; when Blast2GO was used, 87 % (866) of the unique sequences showed similarities to putative proteins of several plant species. For the forward library, 73 proteins related to defense response were identified, such as those involved in intracellular signaling, transcription activation and regulation of defense gene expression, as well as defense and resistance proteins, and pathogenesis-related proteins (PRs). Of the 22 validated transcripts, 95 % were differentially expressed during at least one of the three periods evaluated; the genes up-regulated in response to the pathogen infection were those that code for the enzymes lipoxygenase, (+)-neomenthol dehydrogenase and chitinase, which participate directly in plant-defense responses. Out of down-regulated genes, two code for photosynthesis-related proteins, and two for ammonia and H2O2 detoxification. Our results suggest the plant uses an arsenal of transcripts to respond to infection; however, this arsenal is not effective to prevent pathogen action and consequently the occurrence of bacterial leaf spot under the evaluated conditions. The present study is the first to produce information on the transcriptional reprogramming during the passion fruit-Xap interaction, which represents an important step for a better understanding of this pathosystem.

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No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) tese_isabel_lopes_vighi.pdf: 2167536 bytes, checksum: ac573c14d5ef3a4795a4bf594d60bd85 (MD5) Previous issue date: 2016-03-10 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / O arroz (Oryza sativa L.) é o segundo cereal mais cultivado no mundo, sendo o Brasil o 9º maior produtor. No entanto sua produção é severamente influenciada por condições ambientais adversas, dentre as quais se destaca a salinidade e baixas temperaturas. O objetivo deste estudo foi avaliar respostas, bioquímicas e moleculares desencadeadas pela salinidade e por baixas temperaturas em plantas de arroz, com respostas contrastantes. Para atingir este objetivo foram realizados três estudos: No primeiro, foram quantificados os teores do ânion Superóxido (O2•−), Peróxido de hidrogênio (H2O2), Peroxidação lipídica (MDA), atividade enzimática e expressão gênica diferencial das isoformas das enzimas Superóxido dismutase (SOD), Catalase (CAT), Ascorbato peroxidase APX e Glutationa reduzida (GR) em genótipos com tolerância contrastante ao sal. Para o genótipo sensível (BRS Pampa), ocorreu aumento na atividade enzimática da SOD, CAT, APX e diminuição nos níveis de MDA. No genótipo tolerante (BRS Bojuru), também foi observado aumento da atividade das enzimas SOD e CAT, porém diminuição nos níveis de MDA. A regulação positiva das diferentes isoformas da SOD, CAT e APX demonstrou a sua contribuição para o aumento na atividade da enzima. No segundo estudo, foram quantificados os teores de H2O2, MDA, atividade enzimática e expressão gênica da CAT, bem como análise do promotor e cis elementos, nos mesmos dois genótipos contrastantes frente ao estresse por salinidade e baixa temperatura. O genótipo BRS Pampa (sensível) foi o que mostrou maior proteção contra danos oxidativos frente ao estresse por frio, bem como aumento na atividade da CAT e do número de transcritos das isoformas OSCATA e OSCATB. No terceiro estudo, avaliou-se o metabolismo da prolina em plantas de arroz, através do padrão de expressão dos genes envolvidos na biossíntese e catabolismo desse aminoácido e verificou-se a correlação com o conteúdo de prolina produzido em condições de estresse por salinidade e baixa temperatura. O conteúdo de prolina foi maior no genótipo BRS Bojuru (tolerante) frente às duas condições de estresse testadas. Sob estresse salino, os níveis de transcritos dos genes de biossíntese estão mais correlacionados com o conteúdo de prolina no genótipo tolerante, enquanto que em condições de baixa temperatura a correlação é maior no genótipo sensível. Os resultados obtidos permitem concluir que, sob estresse salino e por baixa temperatura, as plantas de arroz apresentam respostas diferenciais a nível bioquímico e molecular, sendo estas respostas dependentes do tempo, intensidade do estresse e composição genética dos genótipos. / Rice (Oryza sativa L.) is the second most cultivated cereal in the world, and Brazil is the 9th largest producer. However production is severely affected by adverse environmental conditions, among which the mains ones are the salinity and low temperatures. The aim of this study was to evaluate responses, biochemical and molecular triggered by salinity and low temperatures in rice plants with contrasting response. To achieve this goal there were three studies: In the first one, the anion content superoxide (O2•-) were quantified, hydrogen peroxide (H2O2), lipid peroxidation (MDA), enzyme activity and differential gene expression of isoforms of the enzyme superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase APX and reduced glutathione (GR) in genotypes with contrasting tolerance to salt. For the sensitive genotype (BRS Pampa), there was an increase in the enzymatic activity of SOD, CAT, APX and a decrease in MDA levels. In tolerant genotype (BRS Bojuru) was also observed an increased activity of enzymes SOD and CAT, but a decrease in MDA levels. The upregulation of the different isoforms of SOD, CAT and APX has demonstrated its contribution to the increase in the enzyme activity. In the second study, H2O2 levels were quantified, MDA, enzyme activity and gene expression of CAT, and promoter analysis and cis-elements, the same two contrasting genotypes against salinity stress and low temperature. The BRS Pampa genotype (sensitive) was the one that showed greater protection against oxidative damage compared to the stress by cold, as well as an increase in CAT activity and the number of transcripts OSCATA and OSCATB isoforms. In the third study evaluated the metabolism of proline in rice plants through the expression pattern of genes involved in biosynthesis and catabolism of amino-acid and was found to correlate with the proline content produced under stress by salinity and low temperature. The proline content was higher in BRS Bojuru genotype (tolerant) against the two tested stress conditions. Under salt stress, the biosynthesis gene transcript levels are more correlated with the proline content in tolerant genotype, whereas in low temperature conditions the correlation is highest in sensitive genotype. The results showed that under salt stress and low temperature, the rice plants have differential responses to biochemical and molecular level, which are dependent responses of time, stress intensity and genetic makeup of the genotypes.

Dans cette thèse, j'ai étudié le rôle des sRNAs dérivés de l'hôte et du virus lors de l'infection du colza (Brassica napus, Canola) par la souche UK1 du virus de la mosaïque du navet (TuMV-UK1). En utilisant un dérivé de TuMV fusionné avec un gène codant pour la protéine fluorescente verte (TuMV-GFP), deux cultivars de colza (‘Drakkar’ et ‘Tanto’) qui diffèrent par leur susceptibilité à ce virus ont été identifiés. Le profil transcriptionnel des foyers d'infection locale, dans les feuilles de Drakkar et de Tanto, par séquençage nouvelle génération (NGS) a révélé de nombreux gènes exprimés de manière différentielle. Les mêmes échantillons d'ARN provenant de feuilles de Drakkar et de Tanto, traitées par des virus ou utilisées en contrôle, ont également servi à établir le profil NGS des sRNAs (sRNAseq) et de leurs cibles potentielles d'ARN (PAREseq). Les analyses bioinformatiques et leur validation in vivo, ont permis d’identifier les événements de clivage de transcrits impliquant des micro ARN (miRNA) connus et encore inconnus. Fait important, les résultats indiquent que TuMV détourne la voie du RNA silencing de l’hôte avec des siRNAs issus de son propre génome (vsiRNA) pour cibler les gènes de l’hôtes. Le virus déclenche également le ciblage à grande échelle des ARN messagers (ARNm) de l’hôte par l’activation de la production de siRNAs secondaires en phase, à partir de locus PHAS. À leur tour, les vsiRNAs et les siRNAs dérivés de l'hôte (hsRNAs) ciblent et clivent l'ARN viral par le complexe RISC. Ces observations éclairent le rôle des siRNAs dérivés de l'hôte et du virus dans la coordination de l'infection virale. Un autre chapitre de cette thèse est consacré à l'analyse des maladies induites par des virus en utilisant comme modèle de plante Arabidopsis, infectée par un tobamovirus, le virus de la mosaïque du colza (ORMV). De plus, ces observations ont permis de proposer un modèle dans lequel cette guérison dépend d’un adressage important de vsiRNAs secondaires antiviraux depuis leur source de production jusqu’à leurs tissus de destination, et l'établissement d'un apport en vsiRNAs capable de bloquer l'activité VSR impliquée dans la formation des feuilles symptomatiques. / In this thesis, I investigated the role of host- and virus-derived sRNAs during infection of Rapeseed (Brassica napus, Canola) by the UK1 strain of Turnip mosaic virus (TuMV-UK1). By using a TuMV derivative tagged with a gene encoding green fluorescent protein (TuMV-GFP), two rapeseed cultivars (‘Drakkar’ and ‘Tanto’) that differ in susceptibility to this virus were identified. Transcriptional profiling of local infection foci in Drakkar and Tanto leaves by next generation sequencing (NGS) revealed numerous differentially expressed genes. The same RNA samples from mock- and virus- treated Drakkar and Tanto leaves were also used for the global NGS profiling of sRNAs (sRNAseq) and their potential RNA targets (PAREseq). The bioinformatic analysis and their in vivo validation led to the identification of transcript cleavage events involving known and yet unknown miRNAs. Importantly, the results indicate that TuMV hijacks the host RNA silencing pathway with siRNAs derived from its own genome (vsiRNAs) to target host genes. The virus also triggers the widespread targeting of host messenger RNAs (mRNAs) through activation of phased, secondary siRNA production from PHAS loci. In turn, both vsiRNAs and host-derived siRNAs (hsRNAs) target and cleave the viral RNA by the RISC-mediated pathway. These observations illuminate the role of host and virus-derived sRNAs in the coordination of virus infection. Another chapter of this thesis is dedicated to the analysis of virus-induced diseases by using Arabidopsis plants infected with the Oilseed rape mosaic tobamovirus (ORMV) as a model. Initially, the infected plants develop leaves with strong disease symptoms. However, at a later stage, disease-free, “recovered” leaves start to appear. Analysis of symptoms recovery led to the identification of a mechanism in which the VSR and virus derived-siRNAs play a central role. I used Arabidopsis mutants impaired in transcriptional and post-transcriptional silencing pathways (TGS and PTGS respectively) and a plant line carrying a promoter-driven GFP transgene silenced by PTGS (Arabidopsis line 8z2). Using various techniques able to monitor virus infection, small and long viral RNA molecules, VSR activity, as well as phloem-mediated transport with in these lines, this study led to the identification of genes required for disease symptoms and disease symptom recovery. Moreover, the observations allowed to propose a model in which symptoms recovery occurs upon robust delivery of antiviral secondary vsiRNAs from source to sink tissues, and establishment of a vsiRNA dosage able to block the VSR activity involved in the formation of disease symptoms.

Le cancer épithélial de l’ovaire est le cancer gynécologique le plus létal. La survie à 5 ans est de 30-40% chez les patientes atteintes d’une tumeur invasive (TOV), comparativement à 95% chez les patientes diagnostiquées pour une tumeur à faible potentiel de malignité ou borderline (LMP). Au laboratoire, l’analyse de l’expression des gènes de la micropuce à ADN U133 d’Affymetrix a révélé que la SERPINA1 est un gène dont l’expression varie entre les tumeurs LMP et TOV. La validation par Q-PCR nous a confirmé que cette antiprotéase est majoritairement surexprimée dans les tumeurs LMP, par rapport aux tumeurs bénignes (BOV) et aux tumeurs TOV. Nous avons donc surexprimé la SERPINA1 dans les lignées cellulaires invasives TOV 112D et TOV 1946 du cancer de l’ovaire et dérivé des clones stables. Les résultats obtenus nous indiquent que la surexpression de la SERPINA1 a un effet sur la capacité d’invasion et de migration cellulaire et non au niveau de la croissance cellulaire et la formation de structures tridimensionnelles. Les résultats issus de l’étude in vivo dans les souris SCID nous permettront de déterminer si la surexpression de la SERPINA1 a un effet sur la tumorigénèse ovarienne. Ainsi, la SERPINA1 demeure à notre avis un candidat d’intérêt pour tenter de mieux comprendre les différences biologiques entre les tumeurs LMP et TOV, ainsi que le rôle des protéases et de leurs inhibiteurs dans la progression tumorale du cancer de l’ovaire. / Epithelial ovarian cancer is the most lethal gynecologic cancer with a five-year survival rate of 30-40% in patients diagnosed with high-grade invasive disease (TOV). This is in stark contrast to the 95% five-year survival in patients diagnosed with low malignant potential (LMP) disease. It is therefore important to understand the biological differences between LMP and TOV. We have previously identified differential expression of SERPINA1 between serous LMP and TOV tumors through gene expression analysis using Affymetrix U133 DNA microarrays. Expression of this protease inhibitor in the majority of LMP tumors was confirmed and validated by Q-PCR. To study the effects of its overexpression on the invasive potential of ovarian cancer cell lines, SERPINA1 was cloned in the pcDNA3.1+ plasmid and stable clones were derived from two invasive ovarian cancer cell lines, TOV 112D and TOV 1946. Comparisons between clones and controls have shown no SERPINA1-dependent difference in cellular growth or spheroid formation. However, effects on cellular migration and invasion are observed in cells overexpressing SERPINA1. Results from an in vivo xenograft study in SCID mice will allow us to determine if SERPINA1 overexpression affects ovarian tumorigenesis. SERPINA1 remains an interesting candidate gene whose further characterization may lead to insights into its role, and the role of proteases and their inhibitors, in ovarian cancer disease progression.

Le cancer épithélial de l’ovaire est le cancer gynécologique le plus létal. La survie à 5 ans est de 30-40% chez les patientes atteintes d’une tumeur invasive(TOV), comparativement à 95% chez les patientes diagnostiquées pour une tumeur à faible potentiel de malignité (LMP). Au laboratoire, l’analyse de l’expression des gènes de la micropuce à ADN HuFL d’Affymetrix a révélé que Cks1 est un gène dont l’expression varie entre les tumeurs LMP et TOV. En effet, ce régulateur du cycle cellulaire est surexprimé dans les tumeurs TOV par rapport aux tumeurs LMP. Nous avons donc déplété Cks1 dans des lignées cellulaires tumorales invasives du cancer de l’ovaire dérivées au laboratoire, soit la TOV112D et la TOV1946, en utilisant des shRNAs sous le contrôle d’un répresseur inductible à la tétracycline. Puis, nous avons dérivé des clones stables inductibles à la tétracycline. Les résultats obtenus nous indiquent que la déplétion de Cks1 n’a pas d’effet sur la prolifération et la migration cellulaires, ni sur la formation de structures tridimensionnelles in vitro. Ainsi, nous pouvons conclure que Cks1 ne joue pas un rôle clé dans la progression tumorale par rapport aux paramètres testés. Or, des études supplémentaires seraient nécessaires pour expliquer les différences biologiques observées entre les deux types de tumeurs étudiées, et justifier cette variation observée de l’expression de Cks1. / Epithelial ovarian cancer is the most lethal gynecologic cancer with a five-year survival rate of only 30-40% in patients diagnosed with high-grade invasive disease (TOV). This contrasts with the 95% five-year survival in patients diagnosed with the low malignant potential (LMP)disease. Previously, we have identified differential expression of Cks1 between serous LMP and TOV tumors through gene expression analysis using Affymetrix HuFL DNA microarrays. Overexpression of this cell cycle regulator was observed in the TOV tumors, but not in the LMP samples. To study its role on the invasive potential of ovarian cancer cell lines, Cks1 was depleted in two tumoral invasive ovarian cancer cell lines established in our laboratory, TOV112D and TOV1946, using an inducible shRNA strategy. Then, tetracycline-inducible stable clones were derived and studied further. Comparisons between clones and controls have shown no Cks1-dependent effect on cellular growth, neither in migration capacity nor spheroid formation. Thus, we can conclude that Cks1 does not play a crucial role in the tested parameters for cancer progression, but further experiments could elucidate the biological differences observed between the two kinds of tumors studied.

La compréhension des mécanismes moléculaires impliqués dans la détermination du sexe chez les plantes à fleurs est primordiale d’un point de vue fondamental et appliqué. Des processus liés à la biosynthèse des hormones, tel que l’éthylène, ou la régulation de l’expression génique via des petits ARN et des facteurs de transcription ont été associés à l’unisexualisation des fleurs chez des espèces dioïques. Cependant, les déterminants contrôlant le sexe chez les plantes sont encore largement méconnus. Le palmier dattier, Phoenix dactylifera L, est une espèce dioïque dont le dimorphisme sexuel est observé très tôt au cours du développement des fleurs. Des gènes différentiellement exprimés (DEGs) ont été identifiés pendant les stades précoces du développement floral mâle et femelle. Pour cela, un transcriptome de référence rassemblant des données d’expression relatives aux deux sexes a été généré. L’analyse d'enrichissement GO des DEGs, a révélé des processus biologiques communs aux mâles et aux femelles, associés au développement reproducteur et à la réponse aux stimuli. Ce résultat indique que des mêmes processus peuvent solliciter des gènes différents au cours du développement floral précoce en fonction du sexe. Cette analyse a également mis en évidence que le développement des fleurs mâles requiert des processus biologiques spécifiques impliqués dans la régulation cellulaire et l'expression des gènes. En outre, deux DEGs femelles, une S-adenosylmethionine synthase et une Flap endonuclease et un DEG mâle, un élément transposable, ont été identifiés dans les régions non-recombinantes du génome du palmier dattier.Cette étude est la première analyse globale des processus biologiques associés à l’acquisition du dimorphisme sexuel. Elle contribue également à la compréhension de la détermination du sexe chez le palmier dattier, et plus largement à la connaissance de ces processus chez les espèces dioïques. / Unraveling molecular mechanisms involved in sex determination in flowering plants is of outstanding basic and applied interest. Several studies on dioecious species have highlighted the molecular basis of sex determination, such as cell death and ethylene biosynthesis pathway. Sex determination mechanisms in plants are, however, still largely unknown. The date palm, Phoenix dactylifera L, is a dioecious species where sexual dimorphism is observed very early in development of flowers. Differentially expressed genes (DEGs) were identified during the early stages of the male and female flower development. A reference transcriptome including male and female data was constructed to gain insight into this process in the dioecious palm Phoenix dactylifera L. Differentially expressed genes (DEG) were subsequently identified between males and females in the early flower development stages in which the first morphological gender difference occurs in date palms.Gene ontology enrichment analysis of DEG revealed biological processes shared between males and females involved in reproductive development and response to stimulus, indicating that same processes could require different genes during early flower development in date palm. This analysis also suggested that date palm triggers biological processes specifically involved in cellular regulation and gene expression to develop male flowers. Furthermore, two female DEGs related to DNA methylation S-adenosylmethionine synthase and DNA metabolism Flap endonuclease, and one male DEGs, a transposable element were found in non-recombinant date palm regions. This study provided the first insight into biological processes involved in sex determination in date palms and more widely to knowledge of this process in dioecious species.

O Brasil é o maior produtor mundial de maracujá azedo (Passiflora edulis f. flavicarpa) sendo esta a espécie de maior expressão comercial dentre as passifloras cultivadas. A bacteriose do maracujazeiro, causada por Xanthomonas axonopodis pv. passiflorae (Xap), é uma das doenças mais severas da cultura, acarretando grandes prejuízos aos produtores. Atualmente, é incipiente o conhecimento sobre a interação maracujá azedo-Xap. Diante disso, a identificação e a caracterização dos genes envolvidos no processo de defesa são passos importantes para dar suporte ao desenvolvimento de variedades resistentes. Assim, o objetivo deste trabalho foi identificar e caracterizar genes de maracujá azedo diferencialmente expressos durante a resposta de defesa à Xap, bem como mensurar a sua expressão. Para isso, foram construídas duas bibliotecas subtrativas de cDNA (forward e reverse) usando o método SSH a partir de transcritos de folhas, que foram inoculadas com o patógeno ou solução salina (controle). Após o sequenciamento dos clones, o processamento e a montagem das sequências, as unisequências foram anotadas através da Plataforma PLAZA e do programa computacional Blast2GO. Genes envolvidos em diversos processos biológicos foram selecionados para a validação das bibliotecas por PCR quantitativo. Usando a Plataforma PLAZA, 78 % (764) das unisequências mostraram similaridade com proteínas de Arabidopsis thaliana, enquanto 87 % (866) delas apresentaram similaridade com proteínas putativas de diversas espécies vegetais, quando se utilizou Blast2GO. Na biblioteca forward, foram identificadas 73 proteínas relacionadas à resposta de defesa, dentre as quais estão proteínas envolvidas na sinalização intracelular, na ativação da transcrição e regulação da expressão de genes de defesa, bem como proteínas de defesa, de resistência e relacionadas à patogênese (PRs). Dentre os 22 transcritos validados, 95 % foram diferencialmente expressos em pelo menos um dos três períodos avaliados; os genes mais expressos em resposta à infecção pelo patógeno são os que codificam as enzimas lipoxigenase, (+)-neomentol desidrogenase e quitinase, as quais participam diretamente nas respostas de defesa vegetal. Dos genes cuja expressão foi mais reprimida, dois codificam proteínas relacionadas à fotossíntese e dois codificam proteínas envolvidas na detoxificação da amônia e do H2O2. Nossos resultados sugerem que a planta utiliza um arsenal de transcritos para responder à infecção; entretanto, este arsenal não é eficiente para impedir a ação do patógeno e, consequentemente, o desenvolvimento da bacteriose nas condições estudadas. Nosso estudo é inédito e gerou informações sobre a reprogramação transcricional durante a interação maracujá azedo-Xap, o que constitui um importante passo para o melhor entendimento sobre este patossistema. / Brazil is the main producer of yellow passion fruit (Passiflora edulis f. flavicarpa) worldwide, which is the most widely commercialized crop among the cultivated passifloras. The bacterial leaf spot induced by Xanthomonas axonopodis pv. passiflorae (Xap) is one of the most severe diseases of the crop, causing great losses to producers. Currently, we understand very little about the yellow passion fruit-Xap interaction. Therefore, the identification and characterization of genes involved in the defense process are important steps to support the development of resistant varieties. Thus, the objective of this study was identify and characterize differentially expressed genes during the defense response to Xap, as well as to measure their expression. For that, we constructed two subtractive cDNA libraries (the forward and the reverse) by performing the SSH method from leaf transcripts, which were inoculated with the pathogen or saline solution (control). After sequencing the clones and sequence data processing, sequences were assembled into unique sequences, which were annotated using the PLAZA Platform and the computational program Blast2GO. Genes involved in several biological processes were selected to validate the libraries by quantitative PCR. When PLAZA was used for sequence similarity searches, 78 % (764) of the yellow passion fruit unique sequences showed similarity to proteins of Arabidopsis thaliana; when Blast2GO was used, 87 % (866) of the unique sequences showed similarities to putative proteins of several plant species. For the forward library, 73 proteins related to defense response were identified, such as those involved in intracellular signaling, transcription activation and regulation of defense gene expression, as well as defense and resistance proteins, and pathogenesis-related proteins (PRs). Of the 22 validated transcripts, 95 % were differentially expressed during at least one of the three periods evaluated; the genes up-regulated in response to the pathogen infection were those that code for the enzymes lipoxygenase, (+)-neomenthol dehydrogenase and chitinase, which participate directly in plant-defense responses. Out of down-regulated genes, two code for photosynthesis-related proteins, and two for ammonia and H2O2 detoxification. Our results suggest the plant uses an arsenal of transcripts to respond to infection; however, this arsenal is not effective to prevent pathogen action and consequently the occurrence of bacterial leaf spot under the evaluated conditions. The present study is the first to produce information on the transcriptional reprogramming during the passion fruit-Xap interaction, which represents an important step for a better understanding of this pathosystem.