A expressão de antígenos restritos a tecidos (TRAs do inglês tissue restricted antigens) no timo pelas células epiteliais medulares (mTECs de medullary thymic epithelial cells) é essencial para a tolerância central das células T. Devido à sua heterogeneidade em termos de representação de autoantígenos, esse fenômeno foi denominado como expressão gênica promíscua (PGE de promiscuous gene expression), no qual o gene Aire (de autoimmune regulator) desempenha um papel como principal regulador transcricional positivo sobre um grande conjunto de TRAs dependentes de Aire. A proteína Aire tem a capacidade de interagir com seqüências específicas de DNA desempenhando um papel como regulador direto. Neste estudo utilizamos o método dos cDNA microarrays para acessar a PGE em células mTEC CD80+ murinas cultivadas in vitro. O agrupamento hierárquico dos dados permitiu a observação de que os genes de TRAs foram diferencialmente expressos. Para testar essa hipótese, inicialmente silenciamos o gene Aire pelo método de RNA interferente (RNAi) nas células mTEC. O agrupamento hierárquico dos dados de cDNA microarray mostrou um conjunto de genes de TRAs dependentes de Aire, os quais foram reprimidos após o silenciamento deste último. Redes gênicas reconstruídas desses dados permitiram a identificação de um nó gênico (Gucy2d) estabelecendo regulação positiva sobre genes downstream nas células mTEC normais. Entretanto, sob efeito do silenciamento de Aire, Gucy2d passou a ser um repressor. Esses resultados evidenciaram que genes da PGE estão conectados em rede, que um nó gênico pode atuar como intermediário no seu controle e que Aire na rede PGE desempenha seu controle como regulador upstream. / The expression of tissue restricted antigens (TRAs) in thymus by medullary thymic epithelial cells (mTECs) is essential for the central selftolerance of T cells. Due to heterogeneity of autoantigen representation this phenomenon has been termed promiscuous gene expression (PGE), in which the autoimmune regulator (Aire) gene plays a role as main positive transcriptional regulator on a large set of Aire-dependent TRAs. Aire protein is able in binding to specific DNA sequence motifs and plays a role as a direct regulator. Here we used the cDNA microarray method to access PGE in murine CD80+ mTECs cultured in vitro. Hierarchical clustering of the data allowed observation that TRA genes were differentially expressed. To further investigate the control of PGE, we hypothesize that TRA genes establish networks contributing it selves to modulate their transcriptional levels. Aire in this case plays a role as upstream positive modulator. To test this hypothesis, initially we silenced Aire by gene knockdown (RNA interference) in mTECs. Hierarchical clustering of cDNA microarray data showed a set of Airedependent TRAs genes, which were down regulated after Aire silencing. Gene networks reconstructed from these data allowed the identification of a gene node (Gucy2d) establishing positive regulation upon downstream genes in normal mTECs. Nevertheless, under silencing of Aire, Gucy2d has become a repressor. These finding evidentiate that, genes features in PGE are connected in network; a gene node may act as intermediate in their control and that Aire in PGE network plays a role as an upstream regulator.

A expressão de antígenos restritos a tecidos (TRAs do inglês tissue restricted antigens) no timo pelas células epiteliais medulares (mTECs de medullary thymic epithelial cells) é essencial para a tolerância central das células T. Devido à sua heterogeneidade em termos de representação de autoantígenos, esse fenômeno foi denominado como expressão gênica promíscua (PGE de promiscuous gene expression), no qual o gene Aire (de autoimmune regulator) desempenha um papel como principal regulador transcricional positivo sobre um grande conjunto de TRAs dependentes de Aire. A proteína Aire tem a capacidade de interagir com seqüências específicas de DNA desempenhando um papel como regulador direto. Neste estudo utilizamos o método dos cDNA microarrays para acessar a PGE em células mTEC CD80+ murinas cultivadas in vitro. O agrupamento hierárquico dos dados permitiu a observação de que os genes de TRAs foram diferencialmente expressos. Para testar essa hipótese, inicialmente silenciamos o gene Aire pelo método de RNA interferente (RNAi) nas células mTEC. O agrupamento hierárquico dos dados de cDNA microarray mostrou um conjunto de genes de TRAs dependentes de Aire, os quais foram reprimidos após o silenciamento deste último. Redes gênicas reconstruídas desses dados permitiram a identificação de um nó gênico (Gucy2d) estabelecendo regulação positiva sobre genes downstream nas células mTEC normais. Entretanto, sob efeito do silenciamento de Aire, Gucy2d passou a ser um repressor. Esses resultados evidenciaram que genes da PGE estão conectados em rede, que um nó gênico pode atuar como intermediário no seu controle e que Aire na rede PGE desempenha seu controle como regulador upstream. / The expression of tissue restricted antigens (TRAs) in thymus by medullary thymic epithelial cells (mTECs) is essential for the central selftolerance of T cells. Due to heterogeneity of autoantigen representation this phenomenon has been termed promiscuous gene expression (PGE), in which the autoimmune regulator (Aire) gene plays a role as main positive transcriptional regulator on a large set of Aire-dependent TRAs. Aire protein is able in binding to specific DNA sequence motifs and plays a role as a direct regulator. Here we used the cDNA microarray method to access PGE in murine CD80+ mTECs cultured in vitro. Hierarchical clustering of the data allowed observation that TRA genes were differentially expressed. To further investigate the control of PGE, we hypothesize that TRA genes establish networks contributing it selves to modulate their transcriptional levels. Aire in this case plays a role as upstream positive modulator. To test this hypothesis, initially we silenced Aire by gene knockdown (RNA interference) in mTECs. Hierarchical clustering of cDNA microarray data showed a set of Airedependent TRAs genes, which were down regulated after Aire silencing. Gene networks reconstructed from these data allowed the identification of a gene node (Gucy2d) establishing positive regulation upon downstream genes in normal mTECs. Nevertheless, under silencing of Aire, Gucy2d has become a repressor. These finding evidentiate that, genes features in PGE are connected in network; a gene node may act as intermediate in their control and that Aire in PGE network plays a role as an upstream regulator.

The DNA microarray is a powerful tool to study expression levels of thousands of genes simultaneously. Often, cDNA libraries representing expressed genes of an organism are available, along with expressed sequence tags (ESTs). ESTs are widely used as the probes for microarrays. Designing custom microarrays, rich in genes relevant to the experimental objectives, requires selection of probes based on their sequence. We have designed a probe selection method, called GeneSieve, to select EST probes for custom microarrays. To assign annotations to the ESTs, we cluster them into contigs using PHRAP. The larger contig sequences are then used for similarity search against known proteins in model organism such as Arabidopsis thaliana. We have designed three different methods to assign annotations to the contigs: bidirectional hits (BH), bidirectional best hits (BBH), and unidirectional best hits (UBH). We apply these methods to pine and potato EST sets. Results show that the UBH method assigns unambiguous annotations to a large fraction of contigs in an organism. Hence, we use UBH to assign annotations to ESTs in GeneSieve. To select a single EST from a contig, GeneSieve assigns a quality score to each EST based on its protein homology (PH), cross hybridization (CH), and relative length (RL). We use this quality score to rank ESTs according to seven different measures: length, 3' proximity, 5' proximity, protein homology, cross hybridization, relative length, and overall quality score. Results for pine and potato EST sets indicate that EST probes selected by quality score are relatively long and give better values for protein homology and cross hybridization. Results of the GeneSieve protocol are stored in a database and linked with sequence databases and known functional category schemes such as MIPS and GO. The database is made available via a web interface. A biologist is able to select large number of EST probes based on annotations or functional categories in a quick and easy way. / Master of Science

Avaliamos as causas moleculares da deficiência de C3 ou de FI em 07 pacientes, chegando a caracterizar a causa molecular em cinco deles. As mutações encontradas em cada um dos pacientes foram: C3def3 - C364G troca Arg102Gly; G2481C (Val807); A4956G (Val1632); FIdef2 - G693A, troca Gly162Asp; FIdef3 e -4 - C767T, troca Arg187Stop; FIdef6 e -7 - Inserção 1382<font face=\"Symbol\">DAT, códon de parada prematura 13 bases a montante. Além disso, analisamos se a ausência dessas proteínas levava a alterações na expressão gênica em fibroblastos de pele de pacientes deficientes de C3 ou de FI em relação a indivíduos normais e saudáveis através de ensaios com microarranjos de cDNA. Confirmamos uma tendência à alteração da expressão através de PCR em tempo real dos genes CHNRB1, CAV1, PSMB1, PI4K2B e MASP1 nos deficientes de C3; dos genes SPRY2, PSMA5, PGM2L1, GOLPH3 e JAKMIP3 nos deficientes de FI e o gene ETV6 nos dois grupos de pacientes. Dessa forma, podemos sugerir que deficiências das proteínas C3 e FI podem possivelmente influenciar a expressão de outros genes neste tipo de célula. / We investigated C3 and Factor I deficiency in 07 patients and could characterize the molecular basis in five of them. The mutations found were: C3def3 - C364G change Arg102Gly; G2481C (Val807); A4956G (Val1632); FIdef2 - G693A, change Gly162Asp; FIdef3 e -4 - C767T, change Arg187Stop; FIdef6 e -7 - insertion 1382<font face=\"Symbol\">DAT, Stop codon generation after 13 bp. Furthermore, we analyzed if the absence of these proteins cause alterations in gene expression profiles in skin fibroblasts from C3 and FI deficients compared to fibroblasts from normal individuals by cDNA microarrays. We confirmed a tendency of altered gene expression by Real Time PCR atCHNRB1, CAV1, PSMB1, PI4K2B and MASP1 genes on C3 deficients, SPRY2, PSMA5, PGM2L1, GOLPH3 and JAKMIP3 on FI deficient and ETV6 gene in both groups. Thus, we concluded that C3 and FI deficiencies could affect gene expression profiles in skin fibroblasts.

Avaliamos as causas moleculares da deficiência de C3 ou de FI em 07 pacientes, chegando a caracterizar a causa molecular em cinco deles. As mutações encontradas em cada um dos pacientes foram: C3def3 - C364G troca Arg102Gly; G2481C (Val807); A4956G (Val1632); FIdef2 - G693A, troca Gly162Asp; FIdef3 e -4 - C767T, troca Arg187Stop; FIdef6 e -7 - Inserção 1382<font face=\"Symbol\">DAT, códon de parada prematura 13 bases a montante. Além disso, analisamos se a ausência dessas proteínas levava a alterações na expressão gênica em fibroblastos de pele de pacientes deficientes de C3 ou de FI em relação a indivíduos normais e saudáveis através de ensaios com microarranjos de cDNA. Confirmamos uma tendência à alteração da expressão através de PCR em tempo real dos genes CHNRB1, CAV1, PSMB1, PI4K2B e MASP1 nos deficientes de C3; dos genes SPRY2, PSMA5, PGM2L1, GOLPH3 e JAKMIP3 nos deficientes de FI e o gene ETV6 nos dois grupos de pacientes. Dessa forma, podemos sugerir que deficiências das proteínas C3 e FI podem possivelmente influenciar a expressão de outros genes neste tipo de célula. / We investigated C3 and Factor I deficiency in 07 patients and could characterize the molecular basis in five of them. The mutations found were: C3def3 - C364G change Arg102Gly; G2481C (Val807); A4956G (Val1632); FIdef2 - G693A, change Gly162Asp; FIdef3 e -4 - C767T, change Arg187Stop; FIdef6 e -7 - insertion 1382<font face=\"Symbol\">DAT, Stop codon generation after 13 bp. Furthermore, we analyzed if the absence of these proteins cause alterations in gene expression profiles in skin fibroblasts from C3 and FI deficients compared to fibroblasts from normal individuals by cDNA microarrays. We confirmed a tendency of altered gene expression by Real Time PCR atCHNRB1, CAV1, PSMB1, PI4K2B and MASP1 genes on C3 deficients, SPRY2, PSMA5, PGM2L1, GOLPH3 and JAKMIP3 on FI deficient and ETV6 gene in both groups. Thus, we concluded that C3 and FI deficiencies could affect gene expression profiles in skin fibroblasts.

<p>During the development and lifecycle of multicellular organisms, cells have to die, and this occurs by a process called programmed cell death or PCD, which can be separated from necrosis or accidental cell death (Pennell and Lamb, 1997). Senescence is the terminal phase in the development of an organism, organ, tissue or cell, where nutrients are remobilized from the senescing parts of the plant into other parts, and the cells of the senescing organ or tissue undergo PCD if the process is not reversed in time. Leaf senescence involves cessation of photosynthesis, loss of pigments and proteins, nutrient remobilization, and degradation of the plant cells (Smart, 1994). Initiation of leaf senescence is triggered by a wide range of endogenous and environmental factors, that through unknown pathways controls the process, and regulates the expression of senescence-associated genes (SAGs) (Buchanan-Wollaston, 1997). Autumn leaf senescence in deciduous trees is regulated by photoperiod and temperature, and is an attractive experimental system for studies on senescence in perennial plants.</p><p>We have studied the process of autumn senescence in a free-growing aspen (Populus tremula) by following changes in pigment, metabolite and nutrient content, photosynthesis, and cell and organelle integrity. All data were combined in a cellular timetable of autumn senescence in aspen. The senescence process started on September 11 with degradation of pigments and other leaf constituents, and once initiated, progressed steadily without being affected by the environment. Chloroplasts were rapidly degraded, and mitochondria took over energy production after chlorophyll levels had dropped by 50%. At the end of remobilization, around 29th of September, some cells were still metabolically active and had chlorophyll-containing plastids. Over 80% of nitrogen and phosphorus was remobilized, and a sudden change in the 15N of the cellular content on September 29, indicated that volatile compounds may have been released.</p><p>We have also studied gene expression in autumn leaves by analysing EST sequences from two different cDNA libraries, one from autumn leaves of a field-grown aspen and the other from young, but fully expanded leaves of a green-house grown aspen. In the autumn leaf library, ESTs encoding metallothioneins, proteases, stress-related proteins and proteins involved in respiration and breakdown of macromolecules were abundant, while genes coding for photosynthetic proteins were massively downregulated. We have also identified homologues to many known senescence-associated genes in annual plants.</p><p>By using Populus cDNA microarrays, we could follow changes in gene expression during the autumn over four years in the same free-growing aspen tree. We also followed changes in chlorophyll content to monitor the progression of leaf senescence. We observed a major shift in gene expression, occuring at different times the four years, that reflected a metabolic shift from photosynthetic competence to energy generation by mitochondrial respiration. Even though autumn senescence was initiated almost at the same date each year, the transcriptional timetables were different from year to year, especially for 2004, which indicates that there is no strict correlation between the transcriptional and the cellular timetables of leaf senescence.</p>

During the development and lifecycle of multicellular organisms, cells have to die, and this occurs by a process called programmed cell death or PCD, which can be separated from necrosis or accidental cell death (Pennell and Lamb, 1997). Senescence is the terminal phase in the development of an organism, organ, tissue or cell, where nutrients are remobilized from the senescing parts of the plant into other parts, and the cells of the senescing organ or tissue undergo PCD if the process is not reversed in time. Leaf senescence involves cessation of photosynthesis, loss of pigments and proteins, nutrient remobilization, and degradation of the plant cells (Smart, 1994). Initiation of leaf senescence is triggered by a wide range of endogenous and environmental factors, that through unknown pathways controls the process, and regulates the expression of senescence-associated genes (SAGs) (Buchanan-Wollaston, 1997). Autumn leaf senescence in deciduous trees is regulated by photoperiod and temperature, and is an attractive experimental system for studies on senescence in perennial plants. We have studied the process of autumn senescence in a free-growing aspen (Populus tremula) by following changes in pigment, metabolite and nutrient content, photosynthesis, and cell and organelle integrity. All data were combined in a cellular timetable of autumn senescence in aspen. The senescence process started on September 11 with degradation of pigments and other leaf constituents, and once initiated, progressed steadily without being affected by the environment. Chloroplasts were rapidly degraded, and mitochondria took over energy production after chlorophyll levels had dropped by 50%. At the end of remobilization, around 29th of September, some cells were still metabolically active and had chlorophyll-containing plastids. Over 80% of nitrogen and phosphorus was remobilized, and a sudden change in the 15N of the cellular content on September 29, indicated that volatile compounds may have been released. We have also studied gene expression in autumn leaves by analysing EST sequences from two different cDNA libraries, one from autumn leaves of a field-grown aspen and the other from young, but fully expanded leaves of a green-house grown aspen. In the autumn leaf library, ESTs encoding metallothioneins, proteases, stress-related proteins and proteins involved in respiration and breakdown of macromolecules were abundant, while genes coding for photosynthetic proteins were massively downregulated. We have also identified homologues to many known senescence-associated genes in annual plants. By using Populus cDNA microarrays, we could follow changes in gene expression during the autumn over four years in the same free-growing aspen tree. We also followed changes in chlorophyll content to monitor the progression of leaf senescence. We observed a major shift in gene expression, occuring at different times the four years, that reflected a metabolic shift from photosynthetic competence to energy generation by mitochondrial respiration. Even though autumn senescence was initiated almost at the same date each year, the transcriptional timetables were different from year to year, especially for 2004, which indicates that there is no strict correlation between the transcriptional and the cellular timetables of leaf senescence.

Η τεχνολογία των μικροσυστοιχιών επιτρέπει τη μέτρηση των επιπέδων έκφρασης χιλιάδων γονιδίων ταυτόχρονα σε ένα μόνο πείραμα δημιουργώντας έτσι ένα τεράστιο σύνολο δεδομένων για ανάλυση. Για να είναι δυνατή η εξαγωγή σημαντικής πληροφορίας για το υπό μελέτη βιολογικό σύστημα, έχουν χρησιμοποιηθεί διάφορες μέθοδοι προεπεξεργασίας και ανάλυσης των δεδομένων. Στις μεθόδους προεπεξεργασίας των δεδομένων συμπεριλαμβάνονται και οι μέθοδοι κανονικοποίησης. Σκοπός της κανονικοποίησης είναι η ελαχιστοποίηση των συστηματικών σφαλμάτων που εντοπίζονται στα εκτιμώμενα επίπεδα έκφρασης των γονιδίων, έτσι ώστε οι εμφανιζόμενες διαφορές τους να οφείλονται κυρίως σε βιολογικούς παράγοντες. Επίσης, η κανονικοποίηση καθιστά εφικτή τη σύγκριση των επιπέδων έκφρασης δεδομένων από περισσότερες της μίας μικροσυστοιχίες. Στην παρούσα διπλωματική εργασία παρατίθεται μια ανασκόπηση των μεθόδων κανονικοποίησης για δεδομένα γονιδιακής έκφρασης cDNA μικροσυστοιχιών καθώς και μια σύγκριση των αναλυόμενων μεθόδων κανονικοποίησης. / Microarray technology allows the measurement of gene expression levels of thousands of genes simultaneously in a single experiment, therefore creating a vast set of data for analysis. In order to be able to extract the most essential information for the biological system under examination in a specific microarray, various methods are used for data pre-processing and analysis. These data pre-processing methods also include normalization methods. The purpose of normalization is the minimization of the systematic errors that are found in the estimated gene expression levels, so as the observed biological differences be due mainly to biological factors. Furthermore, the normalization makes possible the comparison of gene expression levels of data from more than one microarrays. In the present thesis a review of the normalization methods for gene expression microarray data is presented, as well as a comparison between the analysed normalization methods.

Para avanzar en el entendimiento de las vías de señalización moleculares involucradas en la progresión de cáncer tumoral, se construyo una plataforma personalizada de cDNAs, la cual contiene genes de vías de señalización representativas para investigar la respuesta dinámica temporal a hormonas (progesterona y estradiol) empleando como modelo la línea celular T47D-MTVL e inhibidores específicos de las vías de señalización. Adicionalmente, se realizó un análisis de los perfiles de expresión de un grupo de tumores de mama encontrando buena correlación con los datos clínico-histopatológicos y mostrando como fenotipos específicos correlacionan con mal pronóstico. Los genes más significativos capaces de discriminar entre los fenotipos de tumor fueron determinados, y probados sobre un nuevo grupo de muestras, asignándolas a los subtipos predichos. El análisis de las vías de señalización de los genes más significativos de cada fenotipo fue realizado para elucidar las vías moleculares más representativas afectadas en cada clase de tumor.

Cette thèse de doctorat s’inscrit dans le développement et l’utilisation de méthodes mathématiques et informatiques qui exploitent les données temporelles d’expression des gènes issues de puces à ADN afin de rationaliser et de modéliser les réseaux de régulation génique. Dans cette optique, nous nous sommes principalement intéressés aux données d’expression des gènes de la drosophile (Drosophila melanogaster) pendant son développement, du stade embryonnaire au stade adulte. Nous avons également étudié des données concernant le développement d’autres eucaryotes supérieurs, la réponse d’une bactérie soumises à différents stress et le cycle cellulaire d’une levure. Ce travail a été réalisé selon trois volets principaux :la détection des stades de développement et des perturbations, les classifications de profils d’expression et la modélisation de réseaux de régulation.<p><p>Premièrement, l’observation des données d’expression utilisées nous a conduits à approfondir l’étude des phénomènes survenant lors des changements de stades de développement de la drosophile. Dans ce but, deux méthodes de détection automatique de ces changements ont été développées et appliquées aux données temporelles disponibles sur le développement d’eucaryotes supérieurs. Elles ont également été appliquées à des données temporelles relatives à des perturbations externes de bactéries. Cette étude à montré qu’une formulation mathématique simple permettait de retrouver les instants expérimentaux où une perturbation ou un changement de stade de développement est observé, à partir uniquement des profils d’expression. Par ailleurs, la réponse à une perturbation externe s’avère non distinguable d’une succession de stades de développement, sur la base des seuls profils temporels d’expression.<p><p>Deuxièmement, en raison des dimensions du problème constitué par les données d’expression de plusieurs milliers de gènes et de l’impossibilité de distinguer le rôle dans la régulation des gènes qui présentent des profils d’expression similaires, il s’est avéré nécessaire de classifier les gènes selon leurs profils d’expression. En nous basant sur les résultats obtenus lors de la détection des stades de développement, la démarche suivie est de regrouper les gènes qui présentent des profils temporels d’expression aux comportements similaires non seulement au cours de la série temporelle complète, mais également dans chacun des stades de développement. Dans cette optique, trois distances ont été proposées et utilisées dans une classification hiérarchique des données d’expression de la drosophile.<p><p>Troisièmement, des structures de modèles linéaires et non linéaires ainsi que des méthodes d’estimation et de réduction paramétriques ont été développées et utilisées pour reproduire les données d’expression du développement de la drosophile. Les résultats de ce travail ont montré qu’avec une structure de modèle linéaire simple, la reproduction des profils expérimentaux était excellente et que, dans ce cas, le réseau de régulation génique de la drosophile pouvait se contenter d’une faible connectivité (en moyenne 3 connexions par classe de gènes) et ce, sans hypothèse a priori. Toutefois, les modèles linéaires ont ensuite sérieusement été remis en question par des analyses de robustesse aux perturbations paramétriques et de stabilité des profils après extrapolation dans le temps. Dès lors, quatre structures de modèles non linéaires et cinq méthodes de réduction paramétrique ont été proposées et utilisées pour concilier les critères de reproduction des données, de robustesse et de stabilité des réseaux identifiés. En outre, ces méthodes de modélisation ont été appliquées à un sous-ensemble de 20 gènes impliqués dans le développement musculaire de la drosophile et pour lesquels 36 interactions ont été validées expérimentalement, ainsi qu’à des profils synthétiques bruités. Nous avons pu constater que plus de la moitié des connexions et non-connexions sont retrouvées par trois modèles non linéaires. Les résultats de cette étude ont permis d’éliminer certaines structures de modèle et méthodes de réduction et ont mis en lumière plusieurs directions futures à suivre dans la démarche de modélisation des réseaux de régulation génique. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished