The aetiology of common diseases is shaped by the effects of genetic and environmental factors. Big efforts have been devoted to unravel the genetic basis of disease with the hope that it will help to develop new therapeutic treatments and to achieve personalized medicine. With the development of high-throughput genotyping technologies, hundreds of association studies have described many loci associated to disease. However, the depiction of disease architecture remains incomplete. The aim of this work is to perform exhaustive comparisons across human populations to evaluate pressing questions. Our results provide new insights in the allele frequency of risk variants, their sharing across populations and the likely architecture of disease / La etiología de las enfermedades comunes está formada por factores genéticos y ambientales. Se ha puesto mucho empeño en describir sus bases genéticas. Este conocimiento será útil para desarrollar nuevas terapias y la medicina personalizada. Gracias a las técnicas de genotipado masivo, centenares de estudios de asociación han descrito una infinidad de genes asociados a enfermedad. Pese a ello, la arquitectura genética de las enfermedades no ha sido totalmente descrita. Esta tesis pretende llevar a cabo exhaustivas comparaciones entre poblaciones para responder diversas preguntas candentes. Nuestros resultados dan pistas sobre la frecuencia de los alelos de riesgo, su presencia entre poblaciones y la probable arquitectura de las enfermedades.

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Plus de 170 millions d'individus sont infectés par le VHC dans le monde et 37 millions par le VIH. La coinfection VIH/VHC est fréquente et représente un élément clé de la prise en charge des patients infectés par le VIH. Depuis l'arrivée des HAART, les maladies du foie sont devenues la cause principale de mortalité chez les patients coinfectés VIH/VHC. L'évolution naturelle et le pronostic de l'hépatite C sont plus sévères en cas de coinfection par le VIH du fait d'une fibrose accélérée et d'une évolution rapide vers la cirrhose et ses complications. Certains facteurs accélérant la fibrose hépatique sont clairs aujourd'hui comme: l'absence de recours au traitement anti-VHC, la réplication active du VHC et la consommation excessive d'alcool. De plus, il existe de plus en plus de preuves que les variants génétiques contribuent à la fibrose hépatique chez les patients monoinfectés par le VHC, mais cet aspect a été peu étudié dans la coinfection VIH/VHC.Durant ma thèse, j'ai eu accès aux données d'un échantillon de 494 patients coinfectés génotypés issu de la cohorte ANRS CO13 HEPAVIH. L'histoire naturelle du VIH et du VHC y est renseignée de manière très détaillée et le suivi clinique des patients permet d'avoir des informations précises sur l'état de fibrose hépatique. J'ai pu alors réaliser deux études d'association « génome-entier » pour identifier des polymorphismes associés à la sévérité de la fibrose à l'aide de données complètes de 292 patients. La première étude a mis en évidence une association entre la quantification de l'élasticité hépatique par Fibroscan® et un locus, également répliqué dans la monoinfection par le VHC. Cette association a permis d'identifier deux gènes impliqués dans des mécanismes de maintien de structure et de signalisation cellulaire (CAV3) mais aussi dans la réplication du VHC (RAD18). La seconde étude a identifié deux associations significatives en comparant deux groupes de scores METAVIR (F0F1F2 vs F3F4), en particulier dans le gène CTNND2 qui est impliqué dans un réseau d'interaction associé à des mécanismes moléculaires lié à des maladies hépatiques.Ces deux études sont en cours de publication dans des revues scientifiques internationales à comité de lecture. Ces nouvelles perspectives dans la compréhension des mécanismes de fibrose dans le contexte de la coinfection VIH/VHC pourraient aider à l'identification de nouvelles cibles pour la création de médicaments ou de tests diagnostiques afin d'améliorer les soins des patients. / Over 170 million people worldwide are infected by HCV and 37 million by HIV. Both viruses share the same modes of transmission, and HIV/HCV coinfection is common and represents a key element in the management of patients infected with HIV. Since the appearance of HAART, liver diseases have become the leading cause of death in HIV/HCV coinfected patients. The natural history and prognosis of hepatitis C are more severe in case of coinfection with HIV due to accelerated rate of fibrosis progression and rapid progression to cirrhosis and its complications. Factors accelerating liver fibrosis are known today such as the lack of recourse to anti-HCV treatment, active HCV replication and excessive alcohol consumption. There is increasing evidence that genetic variants contribute to liver fibrosis in HCV monoinfection, but this aspect has been little studied in HIV/HCV coinfection.I have exploited the genotype information from 494 coinfected patients from the cohort ANRS CO13 HEPAVIH. These patients are very-well documented regarding the history of their HIV/HCV infection and are very carefully followed-up, especially regarding the status of liver fibrosis. I have performed two genome-wide association studies to identify polymorphisms associated with the severity of fibrosis from complete data of 292 patients. The first study has dealt with the quantification of liver stiffness by Fibroscan® and an association with the 3p25 region has been identified, also replicated in monoinfection HCV. Two genes involved in cell signaling and structure of holding mechanisms (CAV3) but also in HCV replication (RAD18) appear as good candidates. The second study has unraveled two significant associations by comparing the METAVIR score group (F0F1F2 vs F3F4), especially in the CTNND2 gene implicated in a network of interactions with molecular mechanisms involved in liver diseases.These results are under publications in peer-review international scientific journals. These new insights into the molecular mechanisms of liver fibrosis in patients with HIV/HCV co- infection may help to define new targets for drug development or new diagnostic tests, to improve patient care.

Abstract Low back pain (LBP) is a highly prevalent musculoskeletal condition and the leading cause for workplace absenteeism. Lumbar disc degeneration (DD) is considered as a contributing factor to LBP. The role of genetic factors in the development of lumbar DD has been demonstrated to be significant, with heritability estimates ranging from 64% to 81%. Modic change (MC), a distinct phenotype of lumbar DD, is a subchondral and vertebral bone marrow change revealed only by magnetic resonance imaging (MRI). MC has been associated with LBP in both clinical samples and the general population. The genetic background of MC is largely unknown, and the heritability of MC has not previously been assessed. The aim of this study was to assess the heritability of MC using a twin study, identify predisposing genetic factors for MC in a family-based design using whole-exome sequencing and to identify genetic loci associated with MC using genome-wide association study (GWAS) meta-analysis. An additional aim was to study the prevalence, incidence and morphology of MC. The data consisted of two general population samples, the Northern Finland Birth Cohort 1966 (NFBC1966) and TwinsUK from the United Kingdom, as well as two Finnish families from the Oulu region. MC was found to be partly heritable with a heritability estimate of 30%. Two novel candidate genes, HSPG2 and MAML1, were found co-segregating with MC in two Finnish families. Both genes are important in the growth and differentiation of chondrocytes. Finally, a genetic locus on chromosome 9 was found to be significantly associated with MC using genome-wide meta-analysis of NFBC1966 and TwinsUK. These results showed that genetic factors play a role in the development of MC. In conclusion, this thesis increased the knowledge on the genetics of MC. However, the specific roles of these genes need to be studied further. / Tiivistelmä Alaselkäkivun kansaterveydellinen merkitys on suuri, sillä jopa 84% aikuisista kärsii siitä elämänsä aikana. Selkäkivun vuoksi Suomessa kertyy yli 2 miljoona sairauslomapäivää vuodessa. Välilevyrappeumaa pidetään merkittävänä tekijänä alaselkäkivun synnyssä ja perinnölliset tekijät selittävät välilevyrappeuman synnystä jopa 74%. Modic-muutokset ovat selkärangan välilevyjen päätelevyjen ja subkondraalisen luun muutoksia, jotka voidaan havaita ainoastaan magneettikuvauksella. Niitä pidetään välilevyrappeuman alatyyppinä. Modic-muutosten on osoitettu olevan yhteydessä alaselkäkipuun, mutta etiologia tunnetaan huonosti. Perinnöllisyyden osuutta Modic-muutoksien synnyssä ei ole aiemmin tutkittu ja niiden taustalla vaikuttavat geneettiset tekijät ovat pääasiassa tuntemattomia. Tämän tutkimuksen tavoitteena oli arvioida perinnöllisyyden osuutta Modic-muutoksissa kaksoisaineistossa, tunnistaa Modic-muutoksille altistavia geneettisiä muutoksia perheaineistossa käyttäen eksomisekvensointia ja tunnistaa genomin alueita, jotka assosioituvat Modic-muutoksiin. Tutkimus perustui kahteen väestöperäiseen aineistoon: Pohjois-Suomen Syntymäkohorttiin 1966 ja TwinsUK-kaksosaineistoon Yhdistyneistä kuningaskunnista sekä kahteen pohjois-suomalaiseen perheeseen. Tutkimuksessa osoitettiin, että Modic-muutokset ovat perinnöllisiä ja, että perinnölliset tekijät selittävät noin 30% niiden ilmenemisestä. Lisäksi tutkimuksessa tunnistettiin kaksi uutta alttiusgeeniä; HSPG2- ja MAML1-geenit. Molemmilla geeneillä on tärkeä rooli rustosolujen kasvamisessa ja erilaistumisessa. Tutkimuksessa myös tunnistettiin kromosomista 9 genomin alue, joka assosioituu Modic-muutoksiin. Väitöskirjassani osoitettiin, että perinnöllisillä tekijöillä on merkitystä Modic-muutosten synnyssä. Kokonaisuudessaan tämä väitöskirja kasvattaa ymmärrystä Modic-muutoksista, mutta lisätutkimusta aiheesta tarvitaan.

Statistical heterogeneity refers to differences among results of studies combined in a meta-analysis beyond that expected by chance. On the one hand, excessive heterogeneity can diminish power to discover genetic signals; on the other, moderate heterogeneity can reveal important biological differences among studies. Given its double-edged nature, this thesis dissects heterogeneity in genetic association meta-analyses from three vantage points. First, a novel multi-variant statistic, M is proposed to detect genome-wide (systematic) heterogeneity patterns in genetic association meta-analyses. This was motivated by the limited availability of appropriate methodology to measure the impact of heterogeneity across genetic signals, since traditional metrics (Q, I² and T²) measure heterogeneity at individual variants. Second, given that meta-analyses comprising small numbers of studies typically report imprecise summary effect estimates; GWAS-derived empirical heterogeneity priors are used to improve precision in estimation of average genetic effects and heterogeneity in smaller meta-analyses (e.g. ≤ 10 studies). Third, a critical evaluation of the Han-Eskin random-effects model shows how it can identify small effect heterogeneous loci overlooked by traditional fixed and random-effects methods. This work draws attention to the existence of genome-wide heterogeneity patterns, to reveal systematic differences among the ascertainment criteria of participating studies in a meta-analysis of coronary disease (CAD) risk. Furthermore, simulation studies with the Han-Eskin random-effects model revealed inflated genetic signals at small effect loci when heterogeneity levels were high. However, it did reveal an additional CAD risk variant overlooked by traditional meta-analysis methods. We therefore recommend a holistic approach to exploring heterogeneity in meta-analyses which assesses heterogeneity of genetic effects both at individual variants with traditional statistics and across multiple genetic signals with the M statistic. Furthermore, it is critically important to review forest plots for small effect loci identified using the Han-Eskin random-effects model amidst moderate-to-high heterogeneity (I² ≥ 40%).

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-05-05T18:05:07Z No. of bitstreams: 1 fabrizziocondedeoliveira.pdf: 6115188 bytes, checksum: 9810536208119e2012e4ee9015470c3e (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-06-07T15:41:26Z (GMT) No. of bitstreams: 1 fabrizziocondedeoliveira.pdf: 6115188 bytes, checksum: 9810536208119e2012e4ee9015470c3e (MD5) / Made available in DSpace on 2016-06-07T15:41:26Z (GMT). No. of bitstreams: 1 fabrizziocondedeoliveira.pdf: 6115188 bytes, checksum: 9810536208119e2012e4ee9015470c3e (MD5) Previous issue date: 2015-11-26 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Estudos de associação em escala genômica buscam encontrar marcadores moleculares do tipo SNP que estão associados direta ou indiretamente a um fenótipo em questão tais como, uma ou mais características do indivíduo ou, até mesmo, uma doença. O SNP pode ser a própria mutação causal ou pode estar correlacionado com a mesma por serem herdados juntos. Para identi car a região causadora ou promotora do fenótipo, a qual não é conhecida a priori, milhares ou milhões de SNPs são genotipados em amostras compostas de centenas ou milhares de indivíduos. Com isso, surge o desa o de selecionar os SNPs mais informativos no conjunto de dados genotípico, onde o número de atributos é, geralmente, muito superior ao número de indivíduos, com a possibilidade de que existam atributos altamente correlacionados e, ainda, podendo haver interações entre pares, trios ou combinações de SNPs de quaisquer ordens. Os métodos mais usados em estudos de associação em escala genômica utilizam o valor-p de cada SNP em testes estatísticos de hipóteses, baseados em regressão para fenótipos contínuos e baseados nos testes qui-quadrado ou similares em classi cação para fenótipos discretos, como ltro para selecionar os SNPs mais signi cativos. Entretanto, essa classe de métodos captura somente SNPs com efeitos aditivos, pois a relação adotada é linear. Na tentativa de superar as limitações de procedimentos já estabelecidos, este trabalho propõe um novo método de seleção de SNPs baseado em técnicas de Aprendizado de Máquina e Inteligência Computacional denominado SNP Markers Selector (SMS). O modelo é construído a partir de uma abordagem que divide o problema de seleção de SNPs em três fases distintas: a primeira relacionada à análise de relevância dos marcadores, a segunda responsável pela de nição do conjunto de marcadores relevantes que serão considerados por meio de uma estratégia de corte com base em um limite de relevância dos marcadores e, nalmente, uma fase para o re namento do processo de corte, geralmente para diminuir marcadores falsos-positivos. No SMS, essas três etapas, foram implementadas utilizando-se Florestas Aleatórias, Máquina de Vetores Suporte e Algoritmos Genéticos respectivamente. O SMS objetiva a criação de um uxo de trabalho que maximize o potencial de seleção do modelo através de etapas complementares. Assim, espera-se aumentar o potencial do SMS capturar efeitos aditivos e/ou não-aditivos com interação moderada entre pares e trios de SNPs, ou até mesmo, interações de ordens superiores com efeitos que sejam minimamente detectáveis. O SMS pode ser aplicado tanto em problemas de regressão (fenótipo contínuo) quanto de classi cação (fenótipo discreto). Experimentos numéricos foram realizados para avaliação do potencial da estratégia apresentada, com o método sendo aplicado em sete conjuntos de dados simulados e em uma base de dados real, onde a capacidade de produção de leite predita de vacas leiteiras foi medida como fenótipo contínuo. Além disso, o método proposto foi comparado com os métodos baseados no valor-p e com o Lasso Bayesiano apresentando, de forma geral, melhores resultados do ponto de vista de SNPs verdadeiros-positivos nos dados simulados com efeitos aditivos juntamente com interações entre pares e trios de SNPs. No conjunto de dados reais, baseado em 56.947 SNPs e um único fenótipo relativo à produção de leite, o método identi cou 245 QTLs associados à produção e à composição do leite e 90 genes candidatos associados à mastite, à produção e à composição do leite, sendo esses QTLs e genes identi cados por estudos anteriores utilizando outros métodos de seleção. Assim, o método demonstrou ser competitivo frente aos métodos utilizados para comparação em cenários complexos, com dados simulados ou reais, o que indica seu potencial para estudos de associação em escala genômica em humanos, animais e vegetais. / Genome-wide association studies have as main objective to discovery SNP type molecular markers associated directly or indirectly to a speci c phenotype related to one or more characteristics of an individual or even a disease. The SNP could be the causative mutation itself or correlated with the causative mutation due to common inheritance. Aiming to identify the causal or promoter region of the phenotype, which is unknown a priori, thousands or millions of SNPs are genotyped in samples composed of hundreds or thousands of individuals. Therefore, emerges the necessity to confront a challenge of selecting the most informative SNPs in genotype data set where the number of attributes are, usually, much higher than the number of individuals. Besides, the possibility of highly correlated attributes should be considered, as well as interactions between pairs, trios or combinations of high order SNPs. The most usual methods applied on genomewide association studies adopt the p-value of each SNP as a lter to select the SNPs most signi cant. For continuous phenotypes the statistical regression-based hypothesis test is used and the Chi-Square test or similar for classi cation of discrete phenotypes. However, this class of methods capture only SNPs with additive e ects, due to the linear relationship considered. In an attempt to overcome the limitations of established procedures, this work proposes a new SNPs selection method, named SNP Markers Selector (SMS), based on Machine Learning and Computational Intelligence strategies. The model is built considering an approach which divides the SNPs selection problem in three distinct phases: the rst related to the evaluation of the markers relevance, a second responsible for the de nition of the set of the relevant markers that will be considered by means of a cut strategy based on a threshold of markers relevance and, nally, a phase for the re nement of the cut process, usually to diminish false-positive markers. In the SMS, these three steps were implemented using Random Forests, Support Vector Machine and Genetic Algorithms, respectively. The SMS intends to create a work ow that maximizes the SNPs selection potential of the model due to the adoption of steps considered complementary. In this way, there is an increasing expectation on the performance of the SMS to capture additive e ects, moderate non-additive interaction between pairs and trios of SNPs, or even, higher order interactions with minimally detectable e ects. The SMS can be applied both in regression problems (continuous phenotype) as in classi cation problems (discrete phenotype). Numerical experiments were performed to evaluate the potential of the strategy, with the method being applied in seven sets of simulated data and in a real data set, where milk production capacity predicated of dairy cows was measured as continuous phenotype. Besides, the comparison of the proposed method with methods based on p-value and Lasso Bayesian technique indicate, in general, competitive results from the point of view of true-positive SNPs using simulated data set with additive e ects in conjunction with interactions of pairs and trios of SNPs. In the real data, based on 56,947 SNPs and a single phenotype of milk production, the method identi ed 245 QTLs associated with milk production and composition and 90 candidate genes associated with mastitis, milk production and composition, standing out that these QTLs and genes were identi ed by previous studies using other selection methods. Thus, the experiments showed the potential of the method in relation to other strategies when complex scenarios with simulated or real data are adopted, indicating that the work ow developed to guide the construction of the method should be considered for genome-wide asociation studies in humans, animals and plants.

Abstract Bronchiolitis is an infection of the small airways of the lung and is a common reason for infant hospitalizations. The most common causative pathogen is the respiratory syncytial virus (RSV). Genetic factors are thought to influence the risk of bronchiolitis, and better knowledge of bronchiolitis genetics will likely help to elucidate the disease process. Severe bronchiolitis in childhood may predispose to asthma. Therefore, an effective treatment of bronchiolitis may affect the present-day as well as lifelong respiratory health. In this project, we aimed to identify genetic loci of bronchiolitis susceptibility by a genome-wide association study (GWAS) and suitable follow-up studies, and to study a previously asthma-associated CDHR3 variant for association across five bronchiolitis populations by meta-analysis. We performed the GWAS on a Finnish-Swedish case-control population and identified several loci below the suggestive genome-wide significance level. Of these, three variants showed nominal associations in a replication population from the Netherlands. One of the loci affected KCND3 expression, and two others were intergenic variants with putative regulatory potential. In a follow-up study conducted on a GWAS sub population, we identified the NKG2D locus as a candidate of susceptibility to bronchiolitis. The genomic region encompassing NKG2D variants was reportedly associated with NKG2D mRNA and protein abundance. We validated the association between NKG2D genotypes and protein expression with flow cytometry. The association between NKG2D and bronchiolitis was supported by a Finnish replication study. The meta-analysis was performed on populations from Denmark, Finland, Sweden, Germany, and the Netherlands. A potential virus-specific role for the CDHR3 variant was detected in a population that comprised mostly RSV-negative cases. In conclusion, we identified new candidates of bronchiolitis susceptibility in GWAS and subsequent studies. We found the CDHR3 variant was a potential susceptibility factor in severe non-RSV bronchiolitis and asthma. Our preliminary results provide interesting starting points for further studies. In the future, better understanding of the disease mechanisms and the relationship of bronchiolitis and asthma could provide means to design new therapeutic options. / Tiivistelmä Bronkioliitti on viruksen aiheuttama alahengitystieinfektio, joka usein johtaa pienten lasten sairaalahoitoon. Yleisin bronkioliitin aiheuttaja lapsilla on respiratory syncytial -virus (RSV). Perintötekijöiden arvellaan altistavan bronkioliitille, joten uusi tieto altistavista geeneistä voi auttaa ymmärtämään taudin taustalla olevia biologisia mekanismeja. Lapsuusiän bronkioliitin ajatellaan voivan altistaa astmalle, joten bronkioliitin tehokas hoito voi vaikuttaa merkittävästi hengitysterveyteen myös pitkällä aikavälillä. Työssä pyrittiin selvittämään lapsuusajan bronkioliitille altistavia geneettisiä tekijöitä genominlaajuisella assosiaatiokartoituksella, joka toteutettiin suomalais-ruotsalaisessa tapaus-verrokkiväestössä. Löydökset pyrittiin varmentamaan soveltuvilla jatkotutkimuksilla. Lisäksi tarkastelimme astmalle altistavaa CDHR3-geenin polymorfismia viidessä eurooppalaisessa bronkioliittikohortissa käyttäen meta-analyysia. Assosiaatiokartoituksessa havaittiin useita mahdollisia bronkioliittialttiuteen vaikuttavia geenikohtia. Näistä kolme sai tukea hollantilaisessa väestössä tehdyssä assosiaatioanalyysissä, jossa testattiin assosiaatiokartoituksen lupaavimmat löydökset. Yksi altistavista polymorfismeista vaikutti KCND3-geenin ilmentymiseen, ja kaksi muuta olivat geenien välisiä, mahdollisesti geeninsäätelyyn osallistuvia variantteja. Assosiaatiokartoituksen osa-analyysissä NKG2D tunnistettiin mahdolliseksi bronkioliitille altistavaksi geeniksi. NKG2D-immuunireseptorin alentunut ilmentyminen voi tulostemme perusteella altistaa vakavalle bronkioliitille. Meta-analyysissä, jonka tutkimuskohortit olivat peräisin Tanskasta, Suomesta, Ruotsista, Saksasta ja Hollannista, todettiin mahdollinen yhteys CDHR3-geenin polymorfismin ja muun viruksen kuin RSV:n aiheuttaman bronkioliitin välillä. Toteutimme tässä työssä ensimmäisen genominlaajuisen bronkioliittialttiutta koskevan assosiaatiokartoituksen. Assosiaatiokartoituksessa, sitä seuranneissa jatkotutkimuksissa ja meta-analyysissä tunnistimme useita lupaavia alttiusgeenejä, mutta tuloksemme vaativat varmentamista suuremmissa tutkimusväestöissä.

Les études d’association pan-génomiques ont révélé plusieurs variants génétiques associés à des traits complexes. Les mesures érythrocytaires ont souvent fait l’objet de ce genre d’études, étant mesurées de façon routinière et précise. Comprendre comment les variations génétiques influencent ces phénotypes est primordial étant donné leur importance comme marqueurs cliniques et leur influence sur la sévérité de plusieurs maladies. En particulier, des niveaux élevés d’hémoglobine fœtal chez les patients atteints d’anémie falciforme est associé à une réduction des complications et une augmentation de l’espérance de vie. Néanmoins, la majorité des variants génétiques identifiés par ces études tombent à l’intérieur de régions génétiques non-codantes, augmentant la difficulté d’identifier des gènes causaux. L’objectif premier de ce projet est l’identification et la caractérisation de gènes influençant les traits complexes, et tout particulièrement les traits sanguins. Pour y arriver, j’ai tout d’abord développé une méthode permettant d’identifier et de tester l’effet de gènes knockouts sur les traits anthropométriques. Malgré un échantillon de grande taille, cette approche n’a révélé aucune association. Ensuite, j’ai caractérisé le méthylome et le transcriptome d’érythroblastes différentiés à partir de cellules souches hématopoïétiques et identifié plusieurs gènes potentiellement impliqués dans les programmes érythroïdes fœtaux et adultes. Par ailleurs, j’ai identifié plusieurs micro-ARNs montrant des motifs d’expression spécifiques entre les stages fœtaux et adultes et qui sont enrichis pour des cibles exprimées de façon opposée. Finalement, j’ai identifié plusieurs variants génétiques associés à l’expression de gènes dans les érythroblastes (eQTL). Cette étude a permis d’identifier des variants associés à l’expression du gène ATP2B4, qui encode le principal transporteur de calcium des érythrocytes. Ces variants, qui sont également associés à des traits sanguins et à la susceptibilité à la malaria, tombent dans un élément d’ADN spécifique aux cellules érythroïdes. La délétion de cet élément par le système CRISPR/Cas9 induit une forte diminution de l’expression du gène et une augmentation des niveaux de calcium intracellulaires. En conclusion, des échantillons de génotypages exhaustifs seront nécessaires pour étudier l’effet de gènes knockouts sur les traits complexes. Les érythroblastes montrent de grandes différences au niveau de leur méthylome et transcriptome entre les différents stages développementaux. Ces différences influencent potentiellement la régulation de l’hémoglobine fœtale et impliquent de nombreux micro-ARNs et régions régulatrices non-codantes. Finalement, l’exemple d’ATP2B4 montre qu’intégrer des études épigénomiques, transcriptomiques et des expériences d’édition de génome est une approche puissante pour caractériser des variants génétiques non-codants. Par ailleurs, ces résultats impliquent ATP2B4 dans l’hydratation des érythroblastes, qui est associé à la susceptibilité à la malaria et la sévérité de l’anémie falciforme. Cibler ATP2B4 de façon thérapeutique pourrait avoir un impact majeur sur ces maladies qui affectent des millions d’individus à travers le monde. / Genome-wide association studies (GWAS) have revealed several genetic variants associated with complex phenotypes. This is the case for red blood cell (RBC) traits, which are particularly amenable to GWAS as they are routinely and accurately measured. Understanding RBC trait variation is important given their significance as clinical markers and modifiers of disease severity. Notably, increased fetal hemoglobin (HbF) production in sickle cell disease (SCD) patients is associated with a higher life expectancy and decreased morbidity. Nonetheless, most variants identified through GWAS fall in non-coding regions of the human genome, increasing the difficulty of identifying causal links. The main goal of this project was to identify and characterize genes influencing complex traits, and in particular RBC phenotypes. First, I developed an approach to identify and test potential gene knockouts affecting anthropometric traits in a large sample from the general population, which did not yield significant associations. Then, I characterized the DNA methylome and transcriptome of erythroblasts differentiated ex vivo from hematopoietic progenitor stem cells (HPSC), and identified several genes potentially implicated in fetal and adult-stage erythroid programs. I also identified microRNAs (miRNA) that show specific developmental expression patterns and that are enriched in inversely expressed targets. Finally, I mapped expression quantitative trait loci (eQTL) in erythroblasts, and identify erythroid-specific eQTLs for ATP2B4, the main calcium ATPase of RBCs. These genetic variants are associated with RBC traits and malaria susceptibly, and overlap an erythroid-specific enhancer of ATP2B4. Deletion of this regulatory element using CRISPR/Cas9 experiments in human erythroid cells minimized ATP2B4 expression and increased intracellular calcium levels. In conclusion, large and comprehensive genotyping datasets will be necessary to test the role of rare gene knockouts on complex phenotypes. The transcriptomes and DNA methylomes of erythroblasts show substantial differences correlating with their developmental stages and that may be implicated in HbF production. These results also suggest a strong implication of erythroid enhancers and miRNAs in developmental stage specificity. Finally, characterizing the erythroid-specific enhancer of ATP2B4 suggest that integrating epigenomic, transcriptomic and gene editing experiments can be a powerful approach to characterize non-coding genetic variants. These results implicate ATP2B4 in erythroid cell hydration, which is associated with malaria susceptibility and SCD severity, suggesting that therapies targeting this gene could impact diseases affecting millions of individuals worldwide.

Cell functions are steered by complex interactions of gene products, like forming a temporary or stable complex, altering gene expression or catalyzing a reaction. Mapping these interactions is the key in understanding biological processes and therefore is the focus of numerous experiments and studies. Small-scale experiments deliver high quality data but lack coverage whereas high-throughput techniques cover thousands of interactions but can be error-prone. Unfortunately all of these approaches can only focus on one type of interaction at the time. This makes experimental mapping of the genome-wide network a cost and time intensive procedure. However, to overcome these problems, different computational approaches have been suggested that integrate multiple data sets and/or different evidence types. This widens the stringent definition of an interaction and introduces a more general term - functional association.  FunCoup is a database for genome-wide functional association networks of Homo sapiens and 16 model organisms. FunCoup distinguishes between five different functional associations: co-membership in a protein complex, physical interaction, participation in the same signaling cascade, participation in the same metabolic process and for prokaryotic species, co-occurrence in the same operon. For each class, FunCoup applies naive Bayesian integration of ten different evidence types of data, to predict novel interactions. It further uses orthologs to transfer interaction evidence between species. This considerably increases coverage, and allows inference of comprehensive networks even for not well studied organisms.  BinoX is a novel method for pathway analysis and determining the relation between gene sets, using functional association networks. Traditionally, pathway annotation has been done using gene overlap only, but these methods only get a small part of the whole picture. Placing the gene sets in context of a network provides additional evidence for pathway analysis, revealing a global picture based on the whole genome. PathwAX is a web server based on the BinoX algorithm. A user can input a gene set and get online network crosstalk based pathway annotation. PathwAX uses the FunCoup networks and 280 pre-defined pathways. Most runs take just a few seconds and the results are summarized in an interactive chart the user can manipulate to gain further insights of the gene set's pathway associations. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 2: Manuscript.</p>

The TRIB1 locus (8q24.13) is a novel locus associated with plasma TGs and CAD risk. Trib1 is a regulator of MAPK activity, and has been shown to regulate hepatic lipogenesis and VLDL production in mice. However, the functional relationship between common SNPs at the TRIB1 locus and plasma lipid traits is unknown; TRIB1 has not been identified as an eQTL. This cluster of SNPs falls within an intergenic region 25kb to 50kb downstream of the TRIB1 coding region. By phylogenetic footprinting analysis and DNA genotyping, we identified an evolutionarily conserved region (CNS1) within the risk locus that harbours two common SNPs in tight LD with GWAS risk SNPs and significantly associated with CAD. We investigated the regulatory function of CNS1 by luciferase reporter assays in HepG2 cells and demonstrate that this region has promoter activity. In addition, the rs2001844 risk allele significantly reduces luciferase activity, suggesting that altered expression of the EST-based gene may be associated with plasma TGs. We identified an EST within the risk locus directly downstream of CNS1. We performed 5'/3' RACE using HepG2 RNA, identified multiple variants of this EST-based gene, and confirmed its transcription start site within CNS1. We hypothesize that this EST is a long noncoding RNA due to low abundance, poor conservation, and absence of significant ORF. Over-expression of a short variant implicates its function in the regulation of target gene transcription, although the mechanism of action remains unknown. We conclude that the risk locus at 8q24.13 harbours a novel EST-based gene that may explain the relationship between GWAS SNPs at this locus and plasma lipid traits.