No description available.

This project concerns an exploration of the presence and interactions of long non-coding RNA transcripts in an experimental atherosclerosis mouse model with relevance for human abdominal aortic aneurysm development. 187 long noncoding RNAs, two of them entirely novel, were found to be differentially expressed between angiotensin II treated (developing abdominal aortic aneurysms) and non-treated apolipoprotein E deficient mice (not developing aneurysms) harvested after the same period of time. These transcripts were also studied with regards to co-expression network connections. Eleven previously annotated and two novel long non-coding RNAs were present in two significantly disease correlated co-expression groups that were further profiled with respect to network properties, Gene Ontology terms and MetaCore© connections.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Oxidase Alternativa (AOX) em plantas à codificada por uma pequena famÃlia multigÃnica de origem nuclear (DNA genÃmico). Essa famÃlia multigÃnica foi bem estudada em mono e dicotiledÃneas sendo subdividida em duas subfamÃlias: Aox1 e Aox2. Os genes Aox1 sÃo encontrados em mono e eudicotiledÃneas apresentando expressÃo mais relacionada a condiÃÃes de estresses enquanto que os genes Aox2 sÃo encontrados apenas em eudicotiledÃneas com expressÃo constitutiva. VÃrios genes Aox1 e apenas hum gene Aox2 sÃo encontrados na maioria das eudicotiledÃneas estudadas. Nesse trabalho, caracterizou-se a famÃlia multigÃnica da Aox no gÃnero Medicago (Medicago truncatula e Medicago sativa) pertencente à ordem Fabales. Em Medicago truncatula, a famÃlia multigÃnica da Aox foi carcterizada atravÃs de busca por bioinformÃtica em bancos de dados identificando-se 4 genes Aox (Aox1, Aox2a, Aox2b1 e Aox2b2) no genoma dessa espÃcie revelando pela primeira vez uma duplicaÃÃo do gene Aox2b. OligonucleotÃdeos especÃficos desenhados para cada um dos genes foram usados para amplificaÃÃo por PCR, clonagem e seqÃenciamento parcial dos referidos genes em Medicago sativa. A expressÃo gÃnica foi estudada, atravÃs de RT-PCR semiquantitativa, em sementes durante a germinaÃÃo (0, 24 e 48 horas de apÃs embebiÃÃo) e em raÃzes e folhas de Medicago sativa crescidas em meio hidropÃnico de Hoagland e submetidas a diferentes condiÃÃes de estresse (0, 6, 12 e 24 hs apÃs tratamento): controle, Ãcido salicÃlico (0,5 mM), PEG (100 g/L), H2O2 (10 mM) e cisteÃna (0,5 mM). Os resultados revelaram que todos os 4 genes Aox foram detectados em sementes de Medicago sativa, entretanto os genes Aox1, 2b1 e 2b2 apresentaram aumento da expressÃo durante a germinaÃÃo enquanto que o Aox2a mostrou-se constitutivo. Em folhas os genes Aox1, 2a e 2b1 foram detectados em todas as condiÃÃes testadas jà o Aox2b2 foi detectado mais intensamente apenas nas condiÃÃes de estresse. De maneira semelhante ao observado durante a germinaÃÃo os genes Aox1, 2b1 e 2b2 tiveram expressÃo aumentada em resposta a todas as condiÃÃes de estresse. O Aox2a mostrou-se constitutivo, mas foi intensamente expresso. Em raÃzes, todos os genes foram detectados e um perfil semelhante de induÃÃo dos genes Aox1, 2b1 e 2b2 tambÃm foi observado com exceÃÃo do tratamento com PEG onde apenas Aox1 foi induzido. O Aox2a tambÃm se mostrou constitutivo, mas foi fracamente expresso. Com a finalidade de se compreender melhor a co-expressÃo dos genes Aox1, 2b1 e 2b2 em Medicago sativa os promotores foram clonados e seqÃenciados revelando regiÃes idÃnticas entre eles indicando o envolvimento de elementos cis comuns na regulaÃÃo. Esses resultados corroboram com a co-expressÃo induzida por estresse de Aox1/Aox2b observada anteriormente em feijÃo. Contudo, em Medicago sativa, observamos expressÃo diferencial entre tecidos: no tecido radicular os genes Aox1, Aox2a e 2b1 podem sem induzidos por estresses e/ou mostram uma caracterÃstica de expressÃo. Por outro lado, em folhas o gene Aox2b2 diferenciou por apresentar apenas caracterÃstica de gene induzido em condiÃÃes de estresse. / In plants, Alternative Oxidase (AOX) is enconded by small milti gene family located in genomc DNA. This multi gene family was studied in mono and dicots plants being clusterd in two subfamilies: Aox1 and Aox2. Aox1 gene are found in all angiosperms tÃxon presenting gene expression related to stress situations while Aox2 genes are found in dicots plants only and presenting a houkeeping expression. Many Aox1 genes e just one Aox2 are found in the most of dicots studied. However, in Fabales, as cowpea and soybean, is found a profile with two genes Aox2 (Aox2a , Aox2b) and one Aox1 gene. In this work was characterized a multi gene family of Aox genes in Medicago genus (Medicago truncatula e Medicago sativa) belonging to Fabales Order. Data mining in genBanks characterized four Aox genes (Aox1, Aox2a, Aox2b1 and Aox2b2) in Medicago truncatula genome revealing for first time a duplication of Aox2b genes. Specifics primers designed for each Aox gene and then were used to amplification by PCR, cloning and partial sequencing of these genes in Medicago sativa. Gene expression was carried out by semiquantitative RT-PCR in: germination seeds (0, 24, 48 hours of germination), roots and leaves from Medicago sativa grewth in Hoaglendâs medium and applied to disticts stress conditions (0, 6, 12 e 24 hs after treatment): control, salicylic acid (0,5mM), PEG (100g/L), H2O2 (10mM) e cisteÃne (0,5mM). The results revealed that all four Aox genes were detected in seed of Medicago sativa. However, Aox1, Aox2b1 and Aox2b2 genes presented high expression during germination while Aox2a showed constitutive expression. In leaves, Aox1, Aox2a and Aox2b1 were detected in all conditions tested, but Aox2b2 was observed more strong in stress situations only. Simirily observed in germination, Aox1, Aox2b1 and Aox2b2 increased transcripts levels in response to all stress conditions. Aox2a, one more time, had constitutive, but very strong expression. In roots, all genes were detected and a similar induction profile of Aox1, Aox2b1 and Aox2b2 were confirmed less to PEG treatment where just Aox1 was responsive. Aox2a had constitutive expression too, but it was weakly expressed. In order to understand the co-expresion of Aox1, Aox2b1 and Aox2b2 genes, the promoter regions were cloned and sequenced revealing close motifs among them suggesting th involviment of cis-elements in their regulation. Theses resuls corroborate with co-expression stress-induced of Aox1/Aox2b found in cowpea. However, in Medicago sativa, it was observed tissue-specific exression. Aox1, Aox2a and Aox2b1 with characteristics constitutive and induced in seeds germination and roots tissue while in leaves Aox2b2 differed by present stress-induced expression only.

Septinas compreendem uma conservada família de proteínas de ligação a nucleotídeo de guanina, capazes de formar filamentos. No entanto, apesar de sua importância em vários eventos celulares, ainda há pouca informação disponível no que diz respeita aos detalhes de suas funções moleculares e o mecanismo que conduz a formação de hetero-oligômeros. O objetivo desta tese foi a clonagem, co-expressão e cristalização de septinas e seus complexos (SEPT9-SEPT11-SEPT7; SEPT2-SEPT6-SEPT7-SEPT9; SEPT4-SEPT6-SEPT7 e SEPT4- SEPT8-SEPT7) seguidas por análise estrutural comparativa. Os cDNAs que codificam para as proteínas SEPT9, SEPT6, SEPT2, SEPT11, SEPT8, SEPT4, SEPT9GCα0 (resíduos 262-568) e SEPT9GC (resíduos 279-568) foram clonadas com sucesso em vetores de transferências ou de expressão. O complexo que foi melhor caracterizado, foi o composto por SEPT2-SEPT6-SEPT7-SEPT9GCα0, o qual foi confirmado por LC-MS/MS após digestão tríptica, revelando a produção in vitro de um complexo de septina tetramérico. Além disso, caracterizou-se o hetero dímero formado por SEPT7NGc-SEPT9GC. No entanto, as proteínas que foram mais plenamente investigadas foram as construções SEPT9GCα0 e SEPT9GC que foram estudados individualmente para caracterizações biofísicos e estruturais. SEPT9GCα0 apresentou-se bastante instável, porém, SEPT9GC foi eficientemente produzida e caracterizada. O estado oligomérico da proteína (monômero) foi confirmado por cromatografia de exclusão molecular. A proteína foi produzida na forma apo, e foi incapaz de hidrolisar GTP. A finidade de SEPT9GC pelos nucleotídeos GDP e GTPγS, foi avaliada por Calorimetria de Titulação Isotérmica -ITC, revelando que SEPT9GC possui uma maior afinidade por GTPγS, com Kd de 25,9 µM, o qual é dependente do íon Mg2+. Foram realizados estudos de cristalização dessa proteína, que resultou em cristais de alta resolução, com a proteína complexada a GDP e GTPγS. Interessantemente, a estrutura do complexo de SEPT9GC com o nucleotídeo GTPγS foi obtido por soaking de um cristal previamente obtido complexado com GDP. Este é o primeiro relatório da aplicação deste método para septinas. Finalmente, obtivemos três conjuntos de dados cristalográficos, dois para SEPT9GC-GDP, com resolução de 2.8 Å e 2.1Å e um conjunto de dados de SEPT9GC-GTPγS obtido a 2.8 Å. Dentre as principais características observadas na estrutura de SEPT9GC, tem-se a interface NC responsável pela polimerização dos filamentos, a qual se mostrou diferente dependendo do tipo de nucleotídeo ligado, com encurtamento do filamento na presença de GTPγS. Isso indica a comunicação entre as interfaces consecutivas G e NC ao longo do filamento. A mudança conformacional na interface envolve o rearranjo dos resíduos que são altamente conservados em todas as septinas, bem como alguns que são específicos do grupo de SEPT9 e podem ter implicações para a montagem de filamentos e de associação da membrana. / Septins belong to a highly conserved family of guanine nucleotide binding proteins, capable of forming filaments. Despite their importance for several critical cellular events including cell division, little information is available about their molecular functions and the mechanism which leads to the formation of hetero-oligomers. The aim of this thesis was the cloning, co-expression and crystallization of septins and their complexes (SEPT9-SEPT11-SEPT7; SEPT2-SEPT6-SEPT7-SEPT9; SEPT4-SEPT6-SEPT7 and SEPT4-SEPT8-SEPT7), followed by comparative structural analysis. The cDNAs coding for the proteins SEPT9, SEPT6, SEPT2, SEPT11, SEPT8, SEPT4, SEPT9GCα0 (residues 262-568) and SEPT9GC (residues 279-568) were successfully cloned into transferable or expression vectors. The best characterized complex was that composed of SEPT2-SEPT6-SEPT7-SEPT9GCα0, which was confirmed by LC-MS/MS analysis after triptic digestion, unveiling the in vitro production of a tetrameric septin complex. Additionally, we characterized the hetero-dimer formed by SEPT7NGc-SEPT9GC. However, the most fully investigated proteins were the constructs SEPT9GCα0 and SEPT9GC which were studied individually for biophysical and structural characterizations. SEPT9GCα0 was highly unstable contrasting with SEPT9GC that was efficiently produced and characterized. The presence of the oligomeric state of SEPT9GC (monomer) was confirmed by molecular exclusion chromatography. The protein was produced in the apo form and was capable of hydrolyzing GTP. The affinity of SEPT9GC for GDP and GTPγS nucleotides was evaluated by Isothermal Titration Calorimetry (ITC) revealing that SEPT9GC has a higher affinity for GTPγS, with a Kd of 25.9 µM, which is dependent on the presence of Mg2+. Crystallization studies of this protein were performed, obtaining high quality crystals of protein complexes with GDP and GTPγS. Interestingly, the structure of the complex of SEPT9GC with the nucleotide GTPγS was obtained by soaking a previously grown crystal of the GDP complex. This is the first report of the application of this method for septins. Finally, we have obtained three sets of crystallographic data, two for SEPT9GC-GDP, at resolutions of 2.8 Å and 2.1 Å, and one set of data for SEPT9GC-GTPγS at 2.8 Å. Among the main characteristics observed in the SEPT9GC structure is the NC interface responsible for filament polymerization, which is shown to vary according to the type of bound nucleotide, with foreshortening of the filament in the presence of GTPγS. This indicates communication between consecutive G and NC interfaces along the filament. The conformational change at the interface involves the rearrangement of residues which are highly conserved in all septins as well as several which are SEPT9 group specific and may have implications for filament assembly and membrane association.

Eimeria tenella is a eukaryotic, intracellular parasite that, along with six other Eimeria species, causes coccidiosis in chickens. This disease can result in weight loss or even death and is estimated to cause 2 billion euros of damages to the chicken industry each year. While much is known of the life cycle of E. tenella in the chicken, less is known about molecular mechanisms of infection and the chicken immune response. In this study, we produced a pipeline for dual RNA-sequencing analysis of a mixed chicken and E. tenella dataset.  We then carried out an analysis on an in vitro infection of the chicken macrophage HD-11 cell line.  This was followed by a differential expression analysis across six time points, 2, 4, 12, 24, 48, and 72 hours post-infection, in order to elucidate these mechanisms. The results showed clear patterns of expression for the chicken immune genes, with strong down-regulation of genes across the immune system at 24 hours and a repetition of early patterns at 72 hours, indicating that reinfection by a second generation of parasite cells was occurring. Several genes that may have important roles in the immune reaction of the chicken were identified, such as MRC2, ITGB3 and ITGA9, along with genes with known roles, such as TLR15. The expression of surface antigen genes in E. tenella was also examined, showing a clear upregulation in the late stages of merogony, suggesting important roles for merozoites. Finally, a co-expression analysis was carried out, showing considerable co-expression among the two organisms.  One of the gene co-expression networks identified appeared to be enriched with both infection specific genes from E. tenella and chicken immune genes. These results, along with the pipeline, will be used in further studies on E. tenella infections and bring us closer to the eventual goal of a vaccine for coccidiosis.

Coccidiosis caused by Eimeria parasites is a worldwide problem, affecting chickens and leading to great losses in the poultry industry. Current vaccines are costly and non-optimal, and the parasite has developed resistance to the anticoccidials in use. To be able to develop more efficient and cost-effective vaccines, further research into the immune response in poultry is needed. Here, we have analyzed immune chickens undergoing a secondary E. tenella infection using dual RNA-seq, as well as compared the immune response of the immune chickens to that of naïve chickens. Samples were taken from caecal tissue where the parasites replicate at six timepoints between 0 and 10 days post infection. The reads were put through a bioinformatic pipeline for preprocessing, mapping, counting and differential expression analysis. Using this we found 69 differentially expressed chicken genes (DEGs) in the secondary infections.The results show that DEGs are mainly found 1 and 2 days post infection (dpi), and a large proportion are interferon (IFN) stimulated genes. Compared to samples from naïve chickens, the immune chickens also expressed fewer cytokines and chemokines and the responses are lower at late time points (4 and 10 dpi). There are also lower counts of parasites in the immune chickens. These results show that immune chickens have a much faster response to E. tenellacompared to that of naïve chickens, and that there is a clear IFN-signature. We hypothesize that IFN-mediated inhibition of parasite replication is an important effector mechanism in protective immunity to Eimeria infection.

No description available.

No description available.

L’objectif de ce travail est de mettre au point une nouvelle approche automatique pour identifier les réseaux de gènes concourant à une même fonction biologique. Ceci permet une meilleure compréhension des phénomènes biologiques et notamment des processus impliqués dans les maladies telles que les cancers. Différentes stratégies ont été développées pour essayer de regrouper les gènes d’un organisme selon leurs relations fonctionnelles : génétique classique et génétique moléculaire. Ici, nous utilisons une propriété connue des réseaux de gènes fonctionnellement liés à savoir que ces gènes sont généralement co-régulés et donc co-exprimés. Cette co-régulation peut être mise en évidence par des méta-analyses de données de puces à ADN (micro-arrays) telles que Gemma ou COXPRESdb. Dans un travail précédent [Al Adhami et al., 2015], la topologie d’un réseau de co-expression de gènes a été caractérisé en utilisant deux paramètres de description des réseaux qui discriminent des groupes de gènes sélectionnés aléatoirement (modules aléatoires, RM) de groupes de gènes avec des liens fonctionnels connus (modules fonctionnels, FM), c’est-à-dire des gènes appartenant au même processus biologique GO. Dans le présent travail, nous avons cherché à généraliser cette approche et à proposer une méthode, appelée TopoFunc, pour améliorer l’annotation existante de la fonction génique. Nous avons d’abord testé différents descripteurs topologiques du réseau de co-expression pour sélectionner ceux qui identifient le mieux des modules fonctionnels. Puis, nous avons constitué une base de données rassemblant des modules fonctionnels et aléatoires, pour lesquels, sur la base des descripteurs sélectionnés, nous avons construit un modèle de discrimination LDA [Friedman et al., 2001] permettant, pour un sous-ensemble de gènes donné, de prédire son type (fonctionnel ou non). Basée sur la méthode de similarité de gènes travaillée par Wang et ses collègues [Wang et al., 2007], nous avons calculé un score de similarité fonctionnelle entre les gènes d’un module. Nous avons combiné ce score avec celui du modèle LDA dans une fonction de fitness implémenté dans un algorithme génétique (GA). À partir du processus biologique d’ontologie de gènes donné (GO-BP), AG visait à éliminer les gènes faiblement co-exprimés avec la plus grande clique de GO-BP et à ajouter des gènes «améliorant» la topologie et la fonctionnalité du module. Nous avons testé TopoFunc sur 193 GO-BP murins comprenant 50-100 gènes et avons montré que TopoFunc avait agrégé un certain nombre de nouveaux gènes avec le GO-BP initial tout en améliorant la topologie des modules et la similarité fonctionnelle. Ces études peuvent être menées sur plusieurs espèces (homme, souris, rat, et possiblement poulet et poisson zèbre) afin d’identifier des modules fonctionnels conservés au cours de l’évolution. / The aim of this work is to develop a new automatic approach to identify networks of genes involved in the same biological function. This allows a better understanding of the biological phenomena and in particular of the processes involved in diseases such as cancers. Various strategies have been developed to try to cluster genes of an organism according to their functional relationships : classical genetics and molecular genetics. Here we use a well-known property of functionally related genes mainly that these genes are generally co-regulated and therefore co-expressed. This co-regulation can be detected by microarray meta-analyzes databases such as Gemma or COXPRESdb. In a previous work [Al Adhami et al., 2015], the topology of a gene coexpression network was characterized using two description parameters of networks that discriminate randomly selected groups of genes (random modules, RM) from groups of genes with known functional relationship (functional modules, FM), e.g. genes that belong to the same GO Biological Process. We first tested different topological descriptors of the co-expression network to select those that best identify functional modules. Then, we built a database of functional and random modules for which, based on the selected descriptors, we constructed a discrimination model (LDA)[Friedman et al., 2001] allowing, for a given subset of genes, predict its type (functional or not). Based on the similarity method of genes worked by Wang and co-workers [Wang et al., 2007], we calculated a functional similarity score between the genes of a module. We combined this score with that of the LDA model in a fitness function implemented in a genetic algorithm (GA). Starting from a given Gene Ontology Biological Process (GO-BP), AG aimed to eliminate genes that were weakly coexpressed with the largest clique of the GO-BP and to add genes that "improved" the topology and functionality of the module. We tested TopoFunc on the 193 murine GO-BPs comprising 50-100 genes and showed that TopoFunc aggregated a number of novel genes to the initial GO-BP while improving module topology and functional similarity. These studies can be conducted on several species (humans, mice, rats, and possibly chicken and zebrafish) to identify functional modules preserved during evolution.

The amount of intramuscular fat can influence the sensory characteristics and nutritional value of beef, thus the selection of animals with adequate fat content for consumer becomes important. Intramuscular fat is a complex trait that is difficult to measure and there is growing knowledge about the genes and pathways that control the biological processes involved in fat deposition in muscle. MicroRNAs (miRNAs) are well conserved class of non-coding small RNAs that modulate gene expression of a range of functions in animal development and physiology. This study aimed to identify differentially expressed (DE) miRNAs, regulatory candidate genes and co-expression networks using mRNAs and miRNAs expression data from the Longissimus dorsi muscle of 30 Nelore steers with extreme genomic estimated breeding values (GEBV) for intramuscular fat (IMF) content. The differential expression analysis between the miRNA data from animals with extreme GEBV values for IMF identified six DE miRNAs. Functional annotation of target genes for these microRNAs indicates that PPARs signaling pathway is involved with IMF deposition. Regulatory candidate genes such as SDHAF4, FBXO17, ALDOA and PKM were identified by partial correlation with information theory (PCIT), phenotypic impact factor (PIF) and regulatory impact factor (RIF) approaches from integrated miRNAs-mRNAs expression data. Two DE miRNAs, bta-miR-143 and bta-miR-146b, upregulated in Low IMF group, were also correlated with regulatory candidate genes, which were functionally enriched for GO terms for fatty acids oxidation. Co-expression networks identified several modules related to immune system, protein metabolism, energy metabolism and glucose catabolism by weighted correlation network analysis (WGCNA), which showed possible interaction and regulation between mRNAs and miRNAs. This study contributes to our understanding of regulatory mechanisms of gene signaling networks involved in fat deposition process. Glucose metabolism and inflammation process were the main pathways found in integrative mRNAs-miRNAs analysis and showed to influence intramuscular fat content in beef cattle. / A quantidade de gordura intramuscular pode influenciar as características sensoriais e o valor nutricional da carne bovina, assim, a seleção de animais com conteúdo de gordura adequado para o consumidor torna-se importante. A gordura intramuscular é uma característica complexa, de difícil medição e há um conhecimento crescente sobre os genes e vias que controlam os processos biológicos envolvidos na deposição de gordura no músculo. MicroRNAs (miRNAs) são uma classe bem conservados de pequenos RNAs não-codificantes, que modulam a expressão gênica de uma gama de funções no desenvolvimento e fisiologia animal. Este estudo objetivou identificar miRNAs diferencialmente expressos (DE), genes reguladores candidatos e redes de co-expressão usando dados de expressão de mRNAs e miRNAs do músculo Longissimus dorsi de 30 novilhos Nelore com valores genéticos genômicos estimados (GEBV) extremos para conteúdo de gordura intramuscular (IMF). A análise de expressão diferencial entre os dados de miRNA de animais com valores extremos de GEBV para o IMF identificou seis miRNAs DE. A anotação funcional de genes alvos destes microRNAs indica que a via de sinalização de PPAR está envolvida com a deposição de IMF. Os genes reguladores candidatos, tais como SDHAF4, FBXO17, ALDOA e PKM foram identificados pelas abordagens de correlação parcial com teoria da informação (PCIT), fator de impacto fenotípico (PIF) e fator de impacto regulatório (RIF) a partir de dados integrados de expressão de mRNAs-miRNAs. Dois miRNAs, bta-miR-143 e bta-miR-146b, com alta expressão no grupo de baixo conteúdo de IMF, também foram correlacionados com genes reguladores candidatos, os quais foram funcionalmente enriquecidos para termos GO relacionados a oxidação de ácidos graxos. As redes de co-expressão identificaram vários módulos relacionados ao sistema imunológico, ao metabolismo das proteínas, ao metabolismo energético e ao catabolismo da glicose através da análise ponderada da rede de correlação (WGCNA), que mostrou possível interação e regulação entre mRNAs e miRNAs. Este estudo contribui com a compreensão dos possíveis mecanismos reguladores das redes de sinalização genética envolvidas no processo de deposição de gordura. O metabolismo da glicose e o processo de inflamação foram as principais vias encontrados na análise integrada de mRNA-miRNA e mostraram estar associadas ao conteúdo de gordura intramuscular em bovinos de corte.