>Magister Scientiae - MSc / Acute respiratory infections (ARI) continue to be the leading cause of acute illnesses worldwide and remain the most important cause of infant and young children mortality. Many viruses such as rhinoviruses, influenza viruses, parainfluenza viruses, respiratory syncytial viruses, adenoviruses and coronaviruses are deemed to be the etiological agents responsible for ARI’s in children. The recently discovered coronaviruses HCoV-HKU1 and HCoV-NL63 contribute significantly to the hospitalization of children with ARI’s. HCoV-NL63 was first identified in 2004, as the pathogen responsible for the hospitalization of a 7 month old child presenting with coryza, conjunctivitis and fever. Since then a significant amount of knowledge has been gained in the clinical spectrum on this virus, however HCoV-NL63 is still not well characterized on the molecular and proteomic level. This dissertation focuses on bringing about this characterization by cloning the HCoV-NL63 Nucleocapsid gene to be expressed in a bacterial system and transfecting the Nucleocapsid, Membrane and Envelope genes into a Mammalian cell culture system in order for its respective proteins to be expressed. With the use of Bioinformatic analytic tools certain characteristics of HCoV-NL63 Nucleocapsid, Membrane and Envelope proteins are able to be identified, as well as certain motifs and/or regions that are important in the functioning of these proteins. By comparing the results obtained for HCoV-NL63 N,M and E to other well studied coronavirus homologous will enlighten us on the potential role(s) of these proteins in determining HCoV-NL63 pathogenicity and infectivity. vi Although certain functions of these proteins can be deduced by the means of bioinformatics analysis, it is still imperative for it to be extensively characterized In Vitro. This will therefore form a fundamental step in the development of many other projects, which unfortunately fall outside the scope of this M.Sc thesis.

Les cellules cancéreuses sont caractérisées par des altérations de l'ADN causées par des facteurs exogènes, comme l'exposition à des agents environnementaux tels que le tabac ou les UV, ou par des mécanismes endogènes tels que les erreurs de polymérase lors de la réplication de l'ADN. L'analyse des causes et des conséquences de ces altérations permet de mieux comprendre les facteurs et mécanismes à l'origine du développement d'un cancer. Les technologies de séquençages à haut débit offrent l'opportunité d'étudier la nature précise de ces altérations à l'échelle du génome et permettent de révéler des signatures mutationnelles distinctes et spécifiques de cancérigènes, fournissant ainsi des hypothèses sur l'étiologie des cancers.L'objectif de ma thèse a consisté à développer des méthodes et des outils bioinformatiques accessibles et conviviaux permettant de faciliter l'analyse et l'interprétation des signatures mutationnelles à partir de données de séquençage à haut débit. L'application de ces outils et méthodes à des séries originales de tumeurs humaines et de systèmes expérimentaux de mutagénèse et carcinogénèse a permis de mieux caractériser la signature mutationnelle de l'acide aristolochique (AA) ainsi que d'autres cancérigènes d'intérêt / Cellular genomes accumulate alterations following exposures to exogenous factors, like environmental agents such as tobacco smoking or UV, or to endogenous mechanisms such as DNA replication errors. Analysing the causes and consequences of these changes allows a better understanding of the mechanisms underlying cancer development and progression. Next-generation sequencing (NGS) technologies provide the opportunity tostudy the nature of the resulting alterations on a genome-wide scale and started to reveal distinct mutational signatures specific to past carcinogenic exposures providing clues on cancer aetiology.The aim of my thesis was to develop user-friendly bioinformatic tools and methods for facilitating the analysis and interpretation of carcinogen-specific mutational signatures from NGS data. Applying these tools and methods to human tumours and experimental models of mutagenesis led to a better characterisation the mutational signature of aristolochic acid (AA), as well as other carcinogens of interest

Les promesses de la médecine de précision dépendent de nouvelles solutions technologiques pour le diagnostic. Dans l’aire post-génomique, les approches de biologie synthétique pour la médecine apportent de nouvelles façon de sonder, monitorer et interfacer la physiopathologie humaine. Émergeant en tant que champ scientifique mature dont la transition clinique s’accélère, la biologie synthétique peut être utilisée pour appliquer des principes d’ingénierie afin de concevoir et construire des systèmes biologiques comprenant des spécifications cliniques. Une application particulièrement intéressante est de développer des outils diagnostiques polyvalents, programmables et intelligents étroitement interconnectés avec la thérapie. Cette thèse présente de nouveaux concepts et approches d’ingénierie pour concevoir des dispositifs biosynthétiques capable d’interfacer les maladies humaines dans des échantillons cliniques en exploitant du traitement de signal au niveau biomoléculaire, à la lumière d’un besoin croissant en termes de capacités et de robustesse. Cette thèse s’intéresse en premier lieu à l’ingénierie de circuits synthétiques de gènes, reposant sur les portes logiques à integrases, pour intégrer des opérations modulaires et programmables de biodétéction de biomarqueur associées à des algorithmes de décisions au sein de population de bactéries. Elle s’intéresse ensuite à des méthodologies systématiques dites bottom-up, pour programmer des protocellules synthétiques microscopiques, capables d’exécuter des opérations de biodétéction médicale et de biocomputation. Nous décrivons le développement de méthodes simples de fabrications microfluidique associées à des solutions pour implémenter des opérations Booléenne complexes en utilisant de circuits biochimiques synthétiques. Cette contribution s’élargit aussi à la caractérisation de l’espace de conception de protocellules à l’aide d’approches de design assisté par ordinateur, ainsi que à l’analyse de preuves mathématiques et biologiques pour l’utilisation de protocellules comme des dispositifs universels de calcul. L’articulation des principes biologiques fondamentaux avec les implications médicales concernant les dispositifs biosynthétiques développés dans ce travail, a été jusqu’à la validation clinique, et initie de nouveaux modèles pour le développement de diagnostics de nouvelle génération. Ce travail prévoit que la biologie synthétique est en train de préparer le future de la médecine, en supportant et accélérant le développement de diagnostics avec de nouvelles capacités, apportant un progrès biotechnologique direct depuis le laboratoire de biologie clinique jusqu’au patient. / The promise for real precision medicine is contingent on novel technological solutions to diagnosis. In the post-genomic era, synthetic biology approaches to medicine provide new ways to probe, monitor and interface human pathophysiology. Emerging as a mature field increasingly transitioning to the clinics, synthetic biology can be used to apply engineering principles to design and build biological systems with clinical specifications. A particularly tantalizing application is to develop versatile, programmable and intelligent diagnostic devices closely interconnected with therapy. This thesis presents novel engineering concepts and approaches to design synthetic biological devices interfacing human diseases in clinical samples through biomolecular digital signal processing, in light of a need for dramatic improvements in capabilities and robustness. It addresses primarily the engineering of synthetic gene circuits through integrase based digital genetic amplifiers and logic gates, to integrate modular and programmable biosensing of biomarkers and diagnostic decision algorithms into bacteria. It then investigates systematic bottom-up methodologies to program microscale synthetic protocells performing medical biosensing and biocomputing operations. We demonstrate streamlined microfluidic fabrication methods and solutions to implement complex Boolean operation using integrated synthetic biochemical circuits. This contribution also extends to the characterization of protocell design space through novel computer assisted design frameworks, as well as the analysis of mathematical and biological evidence for universal protocellular biocomputing devices. The articulation of biological governing principles and medical implications for the synthetic devices developed in this work was further validated in the clinic, and initiates new models towards next-generation diagnostics. This work envisions that synthetic biology is preparing the future of medicine, supporting and speeding up the development of diagnostics with novel capabilities to bring direct improvement in biotechnologies from the clinical lab to the patient.

Magister Scientiae (Medical Bioscience) - MSc(MBS) / The human coronavirus NL63 was discovered in 2004 by a team of researchers in Amsterdam. Since its discovery it has been shown to have worldwide spread and affects mainly children, aged 0-5 years old, the immunocompromised and the elderly. Infection with HCoV-NL63 commonly results in mild upper respiratory tract infections and presents as the common cold, with symptoms including fever, cough, sore throat and rhinorrhoea. Lower respiratory tract findings are less common but may develop into more serious complications including bronchiolitis, pneumonia and croup. The primary function of the HCoV-NL63 nucleocapsid (N) protein is the formation of theprotective ribonucleocapsid core. For this particle to assemble, the N-protein undergoes N-N dimerization and then interacts with viral RNA. Besides the primary structural role of the Nprotein, it is also understood to be involved in viral RNA transcription, translation and replication, including several other physiological functions. The N-protein is also highly antigenic and elicits a strong immune response in infected patients. For this reason the N-protein may serve as a target for the development of diagnostic assays. We have used bioinformatic analysis to analyze the HCoV-NL63 N-protein and compared it to coronavirus N-homologues. This bioinformatic analysis provided the data to generate recombinant clones for expression in a bacterial system. We constructed recombinant clones of the N-protein of SARS-CoV and HCoV-NL63 and synthesized truncated clones corresponding to the N- and C-terminal of the HCoV-NL63 N-protein. These heterologously expressed proteins will serve the basis for several post-expression studies including characterizing the immunogenic epitope of the N-protein as well identifying any antibody crossreactivity between coronavirus species. / South Africa

Testes de paternidade geralmente são feitos analisando amostras de DNA do suposto pai, mãe e criança. Para realizar esse exame antes de a criança nascer era preciso recorrer à métodos invasivos, tais como amniocentese e biópsia de vilo corial. Com a descoberta de DNA fetal livre (fcfDNA) no soro e plasma materno, hoje é possível utilizar técnicas que usem esse fcfDNA diminuindo assim os riscos à saúde do feto e da mãe. Testes de pa- ternidade que analisam Short Tandem Repeats (STRs) do fcfDNA, embora possíveis, não são confiáveis, pois muitas vezes há degradação do DNA. Por sua vez, Single Nucleotide Polymorphisms (SNPs) têm sido demonstrados como bons candidatos para identificação humana e podem ser obtidos de fragmentos pequenos de DNA (ou seja, mesmo com o DNA degradado). No entanto, SNPs possuem um número limitado de alelos diferentes (entre dois e quatro). Micro-haplótipos são segmentos cromossomais menores do que 200 pb (pares de bases), contendo dois ou mais SNPs que formam pelo menos três haplótipos distintos. Ao utilizá-los como marcadores genéticos, aumentamos o número de possíveis alelos formados a partir dos SNPs. Como o fcfDNA possui um tamanho de aproximada- mente 145 pb, isso é suficiente para conter micro-haplótipos que podem ser sequenciados usando tecnologia de Sequenciamento de Nova Geração (NGS). O objetivo desse projeto é determinar a probabilidade de paternidade usando SNPs dentro de micro-haplótipos. Os micro-haplótipos foram escolhidos com base em literatura prévia e as frequências relativas destes foram calculadas com base nos grupos étnicos dos dados do 1000 Genomes. Dados brutos de sequenciamento de três amostras de DNA são analisados: o suposto pai, a mãe e o plasma materno (mistura de DNA livre da mãe e do feto). Em seguida, desenvolvemos scripts para obter e analisar os genótipos do suposto pai e da mãe, para cada um dos micro-haplótipos escolhidos. Combinando informação genotípica, frequências populacio- nais e frações fetais (plasma), desenvolvemos um método para calcular a probabilidade de paternidade em casos de não exclusão da mesma. / Paternity tests are usually done by analyzing DNA samples from the alleged father, the mother, and the child. To perform this exam before the birth, invasive methods such as am- niocentesis and chorionic villus sampling are usually necessary. Fortunately, the discovery of fetal cell-free DNA (fcfDNA) in maternal plasma and serum, and the development of te- chniques to analyze this fcfDNA have allowed researchers to reduce the health risk for both fetus and mother. Although paternity tests that analyze Short Tandem Repeats (STRs) from fcfDNA are possible, they are not reliable because DNA degradation often occurs. Single Nucleotide Polymorphisms (SNPs) have been demonstrated as good candidates for human identification and they can be obtained from small DNA fragments (even from de- graded DNA). However, SNPs have a limited number of different alleles (between two and four). Microhaplotypes are chromosomal segments smaller than 200 bp (base pairs) con- taining two or more SNPs that form at least three distinct haplotypes. By using them as genetic markers, we increased the number of possible alleles formed from the SNPs. Since fcfDNA has approximately 145 bp, this is sufficient to contain microhaplotypes that can be sequenced using Next Generation Sequencing (NGS) technology. The aim of this project is to determine the probability of paternity using SNPs within microhaplotypes. Microha- plotypes were chosen based on previous literature review. The haplotype frequencies were calculated based on the ethnic groups from 1000 Genomes database. Raw DNA sequence data from three DNA samples were analyzed: the alleged father, the mother, and the maternal plasma (mixture of mother and fcfDNA). Then, we developed scripts to analyse and obtain the genotypes of the alleged father and mother, for each microhaplotype. By combining genotypic information, population frequencies, and fetal fractions (plasma), we developed a method to calculate the probability of paternity in cases of non-exclusion.

<div> <div> <div> <p>Understanding protein-protein interactions (PPIs) in a cell is essential for learning protein functions, pathways, and mechanisms of diseases. This dissertation introduces the computational method to predict PPIs. In the first chapter, the history of identifying protein interactions and some experimental methods are introduced. Because interacting proteins share similar functions, protein function similarity can be used as a feature to predict PPIs. NaviGO server is developed for biologists and bioinformaticians to visualize the gene ontology relationship and quantify their similarity scores. Furthermore, the computational features used to predict PPIs are summarized. This will help researchers from the computational field to understand the rationale of extracting biological features and also benefit the researcher with a biology background to understand the computational work. After understanding various computational features, the computational prediction method to identify large-scale PPIs was developed and applied to Arabidopsis, maize, and soybean in a whole-genomic scale. Novel predicted PPIs were provided and were grouped based on prediction confidence level, which can be used as a testable hypothesis to guide biologists’ experiments. Since affinity chromatography combined with mass spectrometry technique introduces high false PPIs, the computational method was combined with mass spectrometry data to aid the identification of high confident PPIs in large-scale. Lastly, some remaining challenges of the computational PPI prediction methods and future works are discussed. </p> </div> </div> </div>

<p>Heterosis, or hybrid vigor, is a phenomenon observed in both plant and animal systems where hybrid offspring perform better when compared to their parents. For hybrid plants, this can result in increased biomass, crop yields, and vigor when compared to the inbred parents. Even though heterosis has been used in agriculture for over a century, the molecular mechanisms that result in hybrid vigor remain elusive even after years of investigation. A molecular understanding of heterosis is desirable because it will speed up the process of breeding compatible inbred lines for developing hybrid seeds, and it will provide us with the knowledge to potentially engineer inbred lines that can mimic the beneficial phenotypic effects of heterosis, eliminating the need for farmers to buy new hybrid seeds every year. The goal of this research project is to identify genes that are required for heterotic phenotypes in maize. Our working hypothesis is that a mutation in genes that are essential for heterosis will cause an altered heterotic phenotype in hybrid maize plants. To test this hypothesis, we applied combined approaches of EMS mutagenesis, trait phenotyping in field and controlled conditions, bulk segregant analysis, whole genome sequencing, and bioinformatics analysis. First, we applied a forward genetics approach to identify mutant hybrids with altered heterosis and detected potential causal genes <em>via</em> whole genome sequencing. We identified one mutation occurring in a protein coding gene (gene ID <em>Zm00001eb305590</em>) located in a region of interest on chromosome 7, whose genotypes across various samples assayed fit the observed segregation pattern of hybrid traits. This mutation leads to a moderate or high-level codon change, indicating that this gene may play a role in mediating heterosis in maize. By investigating this gene with further studies, the learned knowledge could speed up the process of hybrid maize breeding by selecting compatible inbred lines through sequencing or by engineering hybrids that have favorable alleles for this gene.</p>

<p>For many years, researchers have developed ways to diagnose degenerative disease in the retina by utilizing multiple gene analysis techniques. Retinitis pigmentosa (RP) disease can cause either partially or totally blindness in adults. For that reason, it is crucial to find a way to pinpoint the causes in order to develop a proper medication or treatment. One of the common methods is genome-wide analysis (GWA). However, it cannot fully identify the genes that are indirectly related to the changes in eye size. In this research, RNA sequencing (RNA-seq) analysis is used to link the phenotype to genotype, creating a pool of candidate genes that might associate with the RP. This will support future research in finding a therapy or treatment to cure such disease in human adults.</p> <p><br></p> <p>Using the Drosophila Genetic Reference Panel (DGRP) – a gene reference panel of fruit fly – two types of datasets are involved in this analysis: eye-size data and gene expression data with two replicates for each strain. This allows us to create a phenotype-genotype map. In other words, we are trying to trace the genes (genotype) that exhibit the RP disease guided by comparing their eye size (phenotype). The basic idea of the algorithm is to discover the best replicate combination that maximizes the correlation between gene expression and eye-size. Since there are 2N possible replicate combinations, where N is the number of selected strains, the original implementation of sequential algorithm was computationally intensive.</p> <p><br></p> <p>The original idea of finding the best replicate combination was proposed by Nguyen et al. (2022). In this research, however, we restructured the algorithms to distribute the tasks of finding the best replicate combination and run them in parallel. The implementation was done using the R programming language, utilizing doParallel and foreach packages, and able to execute on a multicore machine. The program was tested on both a laptop and a server, and the experimental results showed an outstanding improvement in terms of the execution time. For instance, while using 32 processes, the results reported up to 95% reduction in execution time when compared with the sequential version of the code. Furthermore, with the increment of computational capabilities, we were able to explore and analyze more extreme eye-size lines using three eye-size datasets representing different phenotype models. This further improved the accuracy of the results where the top candidate genes from all cases showed connection to RP.</p>

<p>Ancestry is a complex and layered concept, but it must be operationalized for its objective use in genetic studies. Critical decisions in research analyses, clinical practice, and forensic investigations are based on genetic ancestry inference. For example, in genetic association studies for clinical and applied research, investigators may need to isolate one population of interest from a worldwide dataset to avoid false positive results, or in human identification, ancestry inferences can help reveal the identity of unknown DNA evidence by narrowing down a suspect list. Many studies seek to improve ancestry inference for these reasons. The research presented here offers valuable resources for exploring and improving genetic ancestry inference and intelligence toward identity. </p> <p>First, analyses with ‘big data’ in genomics is a resource-intensive task that requires optimization. Therefore, this research introduces a suite of automated Snakemake workflows, <em>Iliad</em>, that was developed to give the research community an easy-to-learn, hands-off computational tool for genomic data processing of multiple data formats. <em>Iliad</em> can be installed and run on a Google Cloud Platform remote server instance in less than 20 minutes when using the provided installation code in the ReadTheDocs documentation. The workflows support raw data processing from various genetic data types including microarray, sequence, and compressed alignment data, as well as performing micro-workflows on variant call format (VCF) files to merge data or lift over variant positions. When compared to a similar workflow, <em>Iliad </em>completed processing one sample’s raw paired-end sequence reads to a human-legible VCF file in 7.6 hours which was three-times faster than the other workflow. This suite of workflows is paramount towards building reference population panels from human whole-genome sequence (WGS) data which is useful in many research studies including imputation, ancestry estimation, and ancestry informative marker (AIM) discovery.</p> <p>Second, there are persistent challenges in ancestry inference for individuals of the Middle East, especially with the use of AIMs. This research demonstrates a population genomics study pertaining to the Middle East, novel population data from Lebanon (n=190), and an unsupervised genetic clustering approach with WGS data from the 1000 Genomes Project and Human Genome Diversity Project. These efforts for AIM discovery identified two single nucleotide polymorphisms (SNPs) based on their high allelic frequency differences between the Middle East and populations in Eurasia, namely Europe and South/Central Asia. These candidate AIMs were evaluated with the most current and comprehensive AIM panel to date, the VISAGE Enhanced Tool (ET), using an external validation set of Middle Eastern WGS data (n=137). Instead of relying on pre-defined biogeographic ancestry labels to confirm the accuracy of validation sample ancestry inference, this research produced a deep, unsupervised ADMIXTURE analysis on 3,469 worldwide WGS samples with nearly 2 million independent SNPs (r2 < 0.1) which provided a genetic “ground truth”. This resulted in 136/137 validation samples as Middle East and provided valuable insights toward reference samples with varying co-ancestries that ultimately affects the classification of admixed individuals. Novel deep learning methods, specifically variational autoencoders, were introduced for visualizing one hundred percent of the genetic variance found using these AIMS in an alternative method to PCA and presents distinct population clusters in a robust ancestry space that remains static for the projection of unknown samples to aid in ancestry inference and human identification. </p> <p>Third, this research delves into a craniofacial study that makes improvements toward key intelligence information about physical identity by exploring the relationship between dentition and facial morphology with an advanced phenotyping approach paired with robust dental parameters used in clinical practice. Cone-beam computed tomography (CBCT) imagery was used to analyze the hard and soft tissue of the face at the same time. Low-to-moderate partial correlations were observed in several comparisons of dentition and soft tissue segments. These results included partial correlations of: i) inter-molar width and soft tissue segments nearest the nasal aperture, the lower maxillary sinuses, and a portion of the upper cheek, and ii) of lower incisor inclination and soft tissue segments overlapping the mentolabial fold. These results indicate that helpful intelligence information, potentially leading towards identity in forensic investigations, may be present where hard tissue structures are manifested in an observable way as a soft tissue phenotype. This research was a valuable preliminary study that paves the way towards the addition of facial hard tissue structures in combination with external soft tissue phenotypes to advance fundamental facial genetic research. Thus, CBCT scans greatly add to the current facial imagery landscape available for craniofacial research and provide hard and soft tissue data, each with measurable morphological variation among individuals. When paired with genetic association studies and functional biological experiments, this will ultimately lead to a greater understanding of the intricate coordination that takes place in facial morphogenesis, and in turn, guide clinical orthodontists to better treatment modalities with an emphasis on personalized medicine. Lastly, it aids intelligence methodologies when applied within the field of forensic anthropology.</p>

Les cellules endothéliales forment une couche semi-perméable entre le sang et les organes. La prolifération, la migration et la polarisation des cellules endothéliales sont essentielles à la formation de nouveaux vaisseaux à partir de vaisseaux préexistants, soit l’angiogenèse. Le facteur de croissance de l’endothélium vasculaire (VEGF) peut activer la synthase endothéliale du monoxyde d’azote (eNOS) et induire la production de monoxyde d’azote (NO) nécessaire pour la régulation de la perméabilité vasculaire et l’angiogenèse. β- caténine est une composante essentielle du complexe des jonctions d’ancrage ainsi qu’un régulateur majeur de la voie de signalisation de Wnt/β-caténine dans laquelle elle se joint au facteur de transcription TCF/LEF et module l’expression de nombreux gènes, dont certains sont impliqués dans l’angiogenèse. La S-nitrosylation (SNO) est un mécanisme de régulation posttraductionnel des protéines par l’ajout d’un groupement nitroso au niveau de résidus cystéines. Le NO produit par eNOS peut induire la S-nitrosylation de la β−caténine au niveau des jonctions intercellulaires et moduler la perméabilité de l’endothélium. Il a d’ailleurs été montré que le NO peut contrôler l’expression génique par la transcription. Le but de cette thèse est d’établir le rôle du NO au sein de la transcription des cellules endothéliales, spécifiquement au niveau de l’activité de β-caténine. Le premier objectif était de déterminer si la SNO de la β-caténine affecte son activité transcriptionnelle. Nous avons montré que le NO inhibe l’activité transcriptionnelle de β- caténine ainsi que la prolifération des cellules endothéliales induites par l’activation de la voie Wnt/β-caténine. Il est intéressant de constater que le VEGF, qui induit la production de NO via eNOS, réprime l’expression de AXIN2 qui est un gène cible de Wnt s’exprimant suite à la i i stimulation par Wnt3a et ce, dépendamment de eNOS. Nous avons identifié que la cystéine 466 de la β-caténine est un résidu essentiel à la modulation répressive de son activité transcriptionnelle par le NO. Lorsqu’il est nitrosylé, ce résidu est responsable de la perturbation du complexe de transcription formé de β-caténine et TCF-4 ce qui inhibe la prolifération des cellules endothéliales induite par la stimulation par Wnt3a. Puisque le NO affecte la transcription, nous avons réalisé l’analyse du transcriptome afin d’obtenir une vue d’ensemble du rôle du NO dans l’activité transcriptionnelle des cellules endothéliales. L’analyse différentielle de l’expression des gènes de cellules endothéliales montre que la répression de eNOS par siRNA augmente l’expression de gènes impliqués au niveau de la polarisation tels que : PARD3A, PARD3B, PKCZ, CRB1 et TJ3. Cette analyse suggère que le NO peut réguler la polarisation des cellules et a permis d’identifier des gènes responsables de l’intégrité des cellules endothéliales et de la réponse immunitaire. De plus, l’analyse de voies de signalisation par KEGG montre que certains gènes modulés par l’ablation de eNOS sont enrichis dans de nombreuses voies de signalisation, notamment Ras et Notch qui sont importantes lors de la migration cellulaire et la différenciation des cellules de têtes et de tronc (tip/stalk). Le regroupement des gènes exprimés chez les cellules traitées au VEGF (déplétées de eNOS ou non) révèle que le NO peut affecter l’expression de gènes contribuant au processus angiogénique, dont l’attraction chimiotactique. Notre étude montre que le NO module la transcription des cellules endothéliales et régule l’expression des gènes impliqués dans l’angiogenèse et la fonction endothéliale. / induce the production of nitric oxide (NO), which is critical for vascular permeability and angiogenesis. β-catenin is an essential component of the adherens junction as well as Wnt/β-catenin signaling pathway and it binds T-cell factor (TCF)/lymphoid enhancer factor, regulating expression of numerous genes including those involved in angiogenesis. S-nitrosylation (SNO) is a mechanism used by NO to regulate protein activity by adding a nitroso group to cysteine residues. eNOS derived-NO is capable to induce SNO of β-catenin at cell-cell junction and modulate endothelial permeability. Additionally, NO has been implicated in the transcriptional control of gene expression. Therefore, the goals of our studies were to investigate the regulatory roles of NO on transcription in endothelial cells, in particular to the modulation of the transcriptional activity of β-catenin. The objective of the first study is to investigate whether the SNO of β-catenin affect its transcriptional activity. We found that NO inhibits β-catenin transcriptional activity and endothelial cell proliferation induced by activation of Wnt/β-catenin signaling. Interestingly, VEGF, which can activate eNOS to produce NO in endothelial cells, repressed Wnt3a-induced expression of Wnt target gene AXIN2 in an eNOS-dependent manner. Moreover, we identified that Cys466 on β-catenin is a critical residue for the repressive effects of NO on β-catenin transcriptional activity. Furthermore, we showed that Cys466 is responsible for the disruption iv of β-catenin/TCF4 transcriptional complex, and NO-dependant inhibition of Wnt3a-simulated endothelial cell proliferation. Given the known effects of NO on transcription, whole transcriptome sequencing was performed in order to understand the transcriptional regulation of NO in endothelial cells. By analyzing gene differential expression in cells transfected with control and eNOS siRNA, we show that eNOS knockdown upregulates the expression of genes involved in cell polarization, such as PARD3A, PARD3B, PKCZ, CRB1 and TJ3. The up-regulation of these genes was confirmed by qRT-PCR analysis, suggesting that NO may regulate cell polarization. The analysis also showed that genes regulated by eNOS knockdown were involved in endothelial cell integrity and immune response. In addition, KEGG signaling pathway analysis showed that genes regulated by eNOS were enriched in many signal pathways including Ras signaling, which are important for endothelial cell migration. Moreover, clustering of differentially expressed genes in VEGF-treated cells and VEGF-treated eNOS-depleted cells revealed that NO may affect expression of genes in angiogenesis in response to VEGF, including those genes involved in chemotaxis. Our studies show that NO affects transcription in endothelial cells and regulates expression of genes involved in angiogenesis and endothelial cell function.