Avec la révolution moléculaire en biologie, une compréhension des mécanismes de la relation génotype-phénotype est devenue possible. Récemment, les progrès réalisés dans la synthèse et le séquençage de l’ADN ont permis le développement d’expériences de deep-mutational scanning capable de quantifier divers phénotypes pour un ensemble de génotypes sur toute la longueur d’un gène. Ces ensembles de données sont non seulement intéressants en eux-mêmes, mais permettent également de tester de manière rigoureuse des modèles phénotypiques quantitatifs. Nous avons utilisé cette technologie pour caractériser les cartes séquence-fitness de 3 systèmes bactériens modèles: un régulateur global, la CRP, une enzyme de résistance aux antibiotiques, la β-lactamase, et une petite voie métabolique constituée des enzymes AraA et AraB. Ces systèmes ont été choisis pour éclairer les rôles de différentes caractéristiques dans la formation de la relation génotype-fitness (réseaux de régulations, stabilité des protéines et flux métabolique). Nous constatons que la tendance globale des effets sur le fitness semble prévaloir sur les tendances spécifiques. Ceci nous conduit à penser qu’une grande partie de la relation entre le génotype et le fitness pourrait être expliquée à partir de la forme des fonctions de phénotype-fitness. Par ailleurs, nous voyons que la caractérisation de la relation génotype-fitness dans différents systèmes peut être un moyen puissant d’obtenir des informations sur les phénotypes pertinents. / With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep-mutational scanning experiments, capable of scoring comprehensive libraries of genotypes for a variety of phenotypes over the length of entire genes. Such datasets are not only interesting in themselves, but also allow rigorous testing of quantitative phenotypic models. We used this technology to characterise sequence-fitness maps for 3 model bacterial systems: a global regulator, CRP, an antibiotic-resistance enzyme, β-lactamase, and a small metabolic pathway, consisting of the enzymes AraA and AraB. These different systems were chosen to illuminate the roles of different mechanistic features in shaping the genotype-fitness relationship (regulatory wiring, protein stability and metabolic flux). We find that smooth patterns of fitness effects tend to prevail over idiosyncrasy, indicating that much of the genotype-fitness relationship could be understood from the global shape of smooth underlying phenotype-fitness functions. On the flip side, we see that characterising the genotype-fitness relationship in different systems can be a powerful way to glean phenotypic insights.

No description available.

A pigmentação dos olhos, cabelos e pele, bem como presença ou ausência de sardas, está entre os exemplos mais visíveis da variação fenotípica humana. O estudo da diversidade genética em genes de pigmentação tem beneficiado diferentes áreas do conhecimento, como a área da genética e antropologia forense, bem como a área relacionada a saúde e bemestar. Adicionalmente, a presença de estruturas secundárias na íris tem sido reportada como importante fator na percepção de cor de olho observada que um indivíduo pode ter referente a íris e também a fatores de risco para algumas doenças oculares, ainda que as bases genéticas envolvidas nestas características sejam pouco conhecidas. Os genes OCA2 e HERC2 representam dois genes associados à variação normal da pigmentação. Este trabalho avaliou a relação de polimorfismos nas regiões regulatórias e codificantes destes dois genes com os fenótipos de pigmentação e estruturas secundárias presentes na íris encontrados em uma amostra populacional de 340 indivíduos do estado de São Paulo, por meio de sequenciamento de nova geração. Análises de regressão logística e linear para as variáveis qualitativas e quantitativas da cor dos olhos e estruturas secundárias presentes na íris foram realizadas. 170 pontos de variação ao longo das regiões estudadas foram identificados, dos quais 18 estão associadas a pelo menos um fenótipo de pigmentação e estruturas secundárias presentes na íris. Destaca-se a existência de muitos polimorfismos que não se mostrara-se associados quando avaliados independentemente, porém foram associados quando analisados sob a ótica de interações epistáticas, considerada uma possível explicação para a variabilidade encontrada nestes fenótipos, principalmente aqueles intermediários, como a cor dos olhos verdes e mel. O uso de variáveis quantitativas para os olhos revelou pela primeira vez a associação do polimorfismo não sinônimo rs201872292 no gene HERC2 com olhos claros, independente do efeito do polimorfismo rs12913832. Ainda, a associação do polimorfismo rs58358300 localizado em um íntron do gene HERC2 com pigmentação da esclera, o que representa a primeira vez que um polimorfismo é associado a esta característica. Este foi o primeiro estudo no Brasil que se propôs a analisar polimorfismos genéticos em genes candidatos à variação normal da pigmentação humana com estruturas secundárias presentes na íris. Os resultados confirmam a hipótese de que polimorfismos dos genes OCA2 e HERC2 podem contribuir para a formação dos fenótipos clássicos de pigmentação de olhos, pele, cabelos e estruturas secundárias presentes na íris humana dos indivíduos da população brasileira. / The pigmentation of the eyes, hair and skin, as well as the presence or absence of freckles, are amongst the most visible examples of human phenotypic variation. The study of genetic diversity in pigmentation genes has contributed greatly to the fields of forensics genetics, anthropological genetics and public health. In addition, the presence of iris features has been reported to influence the perception of overall iris color and also consists in risk factors for ocular diseases, although very little is known about the genetic basis of these traits. The OCA2 and HERC2 genes have been associated with normal variation of pigmentation in diverse populations. The present study evaluated the relationship of polymorphisms in the regulatory and coding regions of these two genes with the pigmentation phenotypes and iris features found in a population sample of 340 individuals from the state of São Paulo, Brazil, through next-generation sequencing. Logistic and linear regression analyzes for the qualitative and quantitative variables were performed. A total of 170 points of variation throughout the studied regions were identified, of which 18 were associated with at least one pigmentation phenotype when analyzed as qualitative and/or quantitative variables and iris features. It is worth mentioning that many associations that were not observed when evaluated independently, were indeed associated when analyzed from the perspective of epistatic effects, which is considered a possible explanation for the variability found in these phenotypes, especially those presented as intermediate, such as green and hazel eye colors. The use of quantitative variables to evaluate the eye color, acquired from photographs, revealed for the first time the association of the nonsynonymous mutation rs201872292 in the HERC2 gene with light eyes, independently of the effect of the rs12913832 polymorphism. We highlight the association of the polymorphism rs58358300 located in an intron of the HERC2 gene with sclera pigmentation, which was the first time that a polymorphism is associated with this feature. This was the first study in Brazil to analyze genetic polymorphisms in candidate genes related to normal variation of human pigmentation and iris features by next-generation sequencing. The results confirm the hypothesis that OCA2 and HERC2 genes may contribute to classic pigmentation phenotypes of eyes, skin, hair, freckles and iris features in the Brazilian population.

Os estudos de associação de genoma inteiro têm encontrado alguns marcadores associados a doenças notoriamente hereditárias com herança complexa, mas, muitas vezes, estes marcadores somente explicam uma pequena parte da herdabilidade. Este relativo insucesso é atribuído, entre outras causas, à epistasia, ou seja, interação entre diferentes locos genéticos. A busca por epistasia é complexa e exige intensos recursos computacionais. Diversos métodos têm sido propostos para abordar este problema, incluindo métodos estatísticos tradicionais, busca estocástica e métodos heurísticos. Poucos destes métodos são capazes de processar as grandes massas de dados produzidas nos estudos caso-controle de genoma inteiro, e ainda menos métodos buscam conjuntos de três ou mais marcadores. A busca exaustiva de conjuntos de marcadores epistáticos é inviável hoje em dia para estes conjuntos, mas o algoritmo BOOST (WAN et al., 2010) mostrou que ela é relativamente fácil para pares de locos, em especial com o uso de placas gráficas como processadores (GPGPU). Partindo deste recente sucesso, propomos um algoritmo em fases para a busca de trios de locos que interagem, utilizando a busca de pares como passo inicial, uma abordagem ainda não utilizada. Outra ideia fundamental do algoritmo proposto é a extensão da concepção de trio de marcadores para um trio de blocos haplotípicos, onde cada bloco é formado por marcadores próximos entre si. Usando os dados do WTCCC, o Troost (de TRio+bOOST) sugeriu trios potencialmente epistáticos em todas a sete doenças. Quando submetidos à confirmação em amostra independente, os trios não puderam ser confirmados, exceto os trios para diabetes tipo 1 (T1D). Duzentos e oito trios foram confirmados para T1D, com baixos valores-P e genótipos combinados de risco com altas razões de chances. Os SNPs que compõem estes trios estão todos na região MHC, sabidamente associada à doença, exceto por um deles que está no cromossomo cinco e não havia sido previamente relacionado à T1D. / Genome-wide association studies have found some markers associated with diseases with complex inheritance. However, these markers explain only a fraction of the previously estimated heritability of the trait. This relative failure has been credited, among other causes, to epistasis, i.e. the interaction among genotypes at different loci. The search for epistasis is complex and requires intense computational resources. Many methods have been proposed to approach this problem, including traditional statistics, stochastic search, and heuristic methods. Few of them are capable of extracting, from the large amount of data produced in genome-wide case-control studies, useful information about sets of markers associated with the trait in question. Exhaustive search of sets of interacting markers is unfeasible nowadays for sets of three or more markers, but the BOOST algorithm (WAN et al., 2010) showed that the search is relatively easy for pairs of SNPs, in particular with the use of graphic cards for general processing (GPGPU). Starting from this recent success, we propose an algorithm in phases for the search for trios of interacting loci, using the search for pairs as the initial step, an approach not tried yet, to our knowledge. Another important idea of our algorithm is the extension of the concept of trio of markers to a trio of haplotypic blocks, where each block is formed by neighbor markers. Using data from WTCCC, the Troost (from TRio+bOOST) algorithm suggested potentially epistatic trios in all seven diseases. When submitted to a confirmation in an independent sample, the results could not be confirmed, except for type-1 diabetes (T1D). Two hundred eight trios were confirmed for T1D, with low p-values and risk combined genotypes with high odds ratio. The SNPs that form those trios are all in the MHC region, which is known to be strongly associated to T1D, except by one SNP in chromosome five that has not been previously associated with T1D.

Os estudos de associação de genoma inteiro têm encontrado alguns marcadores associados a doenças notoriamente hereditárias com herança complexa, mas, muitas vezes, estes marcadores somente explicam uma pequena parte da herdabilidade. Este relativo insucesso é atribuído, entre outras causas, à epistasia, ou seja, interação entre diferentes locos genéticos. A busca por epistasia é complexa e exige intensos recursos computacionais. Diversos métodos têm sido propostos para abordar este problema, incluindo métodos estatísticos tradicionais, busca estocástica e métodos heurísticos. Poucos destes métodos são capazes de processar as grandes massas de dados produzidas nos estudos caso-controle de genoma inteiro, e ainda menos métodos buscam conjuntos de três ou mais marcadores. A busca exaustiva de conjuntos de marcadores epistáticos é inviável hoje em dia para estes conjuntos, mas o algoritmo BOOST (WAN et al., 2010) mostrou que ela é relativamente fácil para pares de locos, em especial com o uso de placas gráficas como processadores (GPGPU). Partindo deste recente sucesso, propomos um algoritmo em fases para a busca de trios de locos que interagem, utilizando a busca de pares como passo inicial, uma abordagem ainda não utilizada. Outra ideia fundamental do algoritmo proposto é a extensão da concepção de trio de marcadores para um trio de blocos haplotípicos, onde cada bloco é formado por marcadores próximos entre si. Usando os dados do WTCCC, o Troost (de TRio+bOOST) sugeriu trios potencialmente epistáticos em todas a sete doenças. Quando submetidos à confirmação em amostra independente, os trios não puderam ser confirmados, exceto os trios para diabetes tipo 1 (T1D). Duzentos e oito trios foram confirmados para T1D, com baixos valores-P e genótipos combinados de risco com altas razões de chances. Os SNPs que compõem estes trios estão todos na região MHC, sabidamente associada à doença, exceto por um deles que está no cromossomo cinco e não havia sido previamente relacionado à T1D. / Genome-wide association studies have found some markers associated with diseases with complex inheritance. However, these markers explain only a fraction of the previously estimated heritability of the trait. This relative failure has been credited, among other causes, to epistasis, i.e. the interaction among genotypes at different loci. The search for epistasis is complex and requires intense computational resources. Many methods have been proposed to approach this problem, including traditional statistics, stochastic search, and heuristic methods. Few of them are capable of extracting, from the large amount of data produced in genome-wide case-control studies, useful information about sets of markers associated with the trait in question. Exhaustive search of sets of interacting markers is unfeasible nowadays for sets of three or more markers, but the BOOST algorithm (WAN et al., 2010) showed that the search is relatively easy for pairs of SNPs, in particular with the use of graphic cards for general processing (GPGPU). Starting from this recent success, we propose an algorithm in phases for the search for trios of interacting loci, using the search for pairs as the initial step, an approach not tried yet, to our knowledge. Another important idea of our algorithm is the extension of the concept of trio of markers to a trio of haplotypic blocks, where each block is formed by neighbor markers. Using data from WTCCC, the Troost (from TRio+bOOST) algorithm suggested potentially epistatic trios in all seven diseases. When submitted to a confirmation in an independent sample, the results could not be confirmed, except for type-1 diabetes (T1D). Two hundred eight trios were confirmed for T1D, with low p-values and risk combined genotypes with high odds ratio. The SNPs that form those trios are all in the MHC region, which is known to be strongly associated to T1D, except by one SNP in chromosome five that has not been previously associated with T1D.

Le paludisme tue un enfant toutes les 30 secondes en Afrique et 1 à 3 millions de personnes par an. Deux milliards d'individus sont exposés et on estime à 500 millions le nombre de cas cliniques survenant chaque année. Le paludisme étant une maladie multifactorielle, son évolution est soumise à l'influence d'effets environnementaux, à des variables telles que l'âge de l'individu, ainsi qu'à une combinaison de facteurs génétiques. De nombreux arguments sont en faveur d’un contrôle génétique de la résistance au paludisme, mais les gènes impliqués restent encore mal connus. Afin d’identifier de nouveaux gènes de résistance ou de susceptibilité au paludisme à Plasmodium falciparum, nous avons réalisé différentes études génétiques dans deux populations vivant en zone d’endémie palustre au Burkina Faso. Ainsi, des polymorphismes du gène IL12B situé dans une région chromosomique liée au paludisme (5q31-q33) ont été génotypés puis analysés. Nous n’avons pas décelé d’association allélique, mais ce travail a permis de confirmer l’existence d’une liaison génétique dans ce locus. Les données issues du génotypage du gène IL12B ainsi que celles d’études antérieures ont été utilisées pour évaluer les interactions génétiques entre la mutation provoquant l’hémoglobine C et 11 autres polymorphismes situés dans 5 gènes précédemment associés à la résistance au paludisme. En utilisant 3 phénotypes liés à l’infection palustre, nous avons ainsi pu observer 43 combinaisons multilocus significatives incluant des polymorphismes des gènes IL12B, IL4, TNF, NCR3 et LTA. Ces résultats d’interactions démontrent l’intérêt de développer ce type d’approches pour élucider le contrôle génétique de la résistance humaine au paludisme.Une approche par clonage positionnel, suivie d’une approche « gène candidat » nous a permis de mettre en évidence une liaison génétique entre la région 17p11-p13 et la parasitémie, puis une association allélique entre les gènes candidats HS3ST3A1 et HS3ST3B1 et la parasitémie. Ces gènes codent pour des isoenzymes transférant un groupement sulfate à des protéoglycanes afin de former des molécules d’héparane sulfates. L’implication potentielle de ces récepteurs, dans le contrôle génétique du paludisme suggère le rôle déterminant qu’ils pourraient jouer dans le déclenchement de l’infection, et fournit un nouveau terrain d’investigation pour l’identification de gènes contrôlant l’évolution de l’infection palustre. A notre connaissance, il s’agit de la première étude d’association entre un phénotype lié à l’infection palustre et des gènes impliqués dans la synthèse des héparane sulfates. / Malaria kills a child every 30 seconds in Africa and 1 to 3 million people per year. Two billion people are exposed and an estimated 500 million of clinical cases occur each year. Malaria being a multifactorial disease, its evolution is subject to the influence of environmental effects, variables such as age of the individual, and a combination of genetic factors. Many arguments are in favor of a genetic control of resistance to malaria, but the genes involved are still poorly understood. In order to identify new genes for resistance or susceptibility to Plasmodium falciparum, we performed genetic studies in two different populations living in malaria endemic area in Burkina Faso. Thus, polymorphisms of the IL12B gene located in a chromosomal region associated with malaria (5q31-q33) were genotyped and analyzed. We did not detect allelic association, but this work has confirmed the existence of a genetic linkage at this locus. Genotype data from IL12B gene and those of previous studies were used to evaluate interactions between the genetic mutation causing hemoglobin C and 11 other polymorphisms located in five genes previously associated with resistance to malaria. Using 3 phenotypes related to malaria infection, we were able to observe 43 significant multilocus combinations including IL12B gene polymorphisms, IL4, TNF, LTA and NCR3. These results demonstrate the interest to develop such approaches for elucidating the genetic control of human resistance to malaria. A positional cloning approach followed by a "candidate gene" approach allowed us to identify a genetic link between the region 17p11-p13 and parasitemia, and allelic association between candidate genes HS3ST3A1 and HS3ST3B1 and parasitemia. These genes encode isoenzymes transferring a sulfate group to proteoglycans to form molecules of heparan sulfates. The potential involvement of these receptors in the genetic control of malaria suggests the crucial role they might play in the onset of infection, and provides a new field of investigation for the identification of genes controlling the development of malaria infection. To our knowledge this is the first study of association between a phenotype associated with malaria infection and genes involved in the synthesis of heparan sulfates.

<p>The purpose of gene mapping is to understand the underlying genetics of simple and complex traits like plumage colour and growth. This thesis is based on a cross between the wild ancestor of the modern chicken, the red junglefowl, and a White Leghorn line selected for high egg mass. There are obvious phenotypic differences between these two breeds in several aspects such as growth, egg production and behaviour. These complex traits are often influenced by a number of genes or Quantitative Trait Loci (QTL) as well as environmental factors.</p><p>Identification of QTL regions involves testing of association between genetic markers and the phenotype of interest. The QTL identified in this study explain most of the difference in adult body weight between the red junglefowl and the White Leghorn, but less of the difference at earlier age. By applying a different method for detection of QTL, including gene interactions, epistasis, we can understand more of the genetics behind early growth. The allele coming from the red junglefowl is generally associated with lower weight, egg production and food consumption.</p><p>In this study we have also identified two genes explaining the difference in plumage colour in the cross. The <i>Extension</i> locus, encoded by the melanocortin receptor 1 (<i>MC1R</i>), controls the amount of pigment produced has shown to be associated with plumage colour. A mutation in the <i>MC1R</i> gene causes black pigmentation of the plumage. </p><p>We have also found association between the <i>PMEL17</i> gene, known to be involved in normal pigmentation, and the <i>Dominant white</i> phenotype present in the White Leghorn. After comparison of sequences from different alleles at the <i>Dominant white</i> locus, amino acid alteration caused by insertion and deletion in the transmembrane region of the <i>PMEL17</i> protein has been revealed. These mutations are associated with alleles representing different plumage colour variants.</p>

The purpose of gene mapping is to understand the underlying genetics of simple and complex traits like plumage colour and growth. This thesis is based on a cross between the wild ancestor of the modern chicken, the red junglefowl, and a White Leghorn line selected for high egg mass. There are obvious phenotypic differences between these two breeds in several aspects such as growth, egg production and behaviour. These complex traits are often influenced by a number of genes or Quantitative Trait Loci (QTL) as well as environmental factors. Identification of QTL regions involves testing of association between genetic markers and the phenotype of interest. The QTL identified in this study explain most of the difference in adult body weight between the red junglefowl and the White Leghorn, but less of the difference at earlier age. By applying a different method for detection of QTL, including gene interactions, epistasis, we can understand more of the genetics behind early growth. The allele coming from the red junglefowl is generally associated with lower weight, egg production and food consumption. In this study we have also identified two genes explaining the difference in plumage colour in the cross. The Extension locus, encoded by the melanocortin receptor 1 (MC1R), controls the amount of pigment produced has shown to be associated with plumage colour. A mutation in the MC1R gene causes black pigmentation of the plumage. We have also found association between the PMEL17 gene, known to be involved in normal pigmentation, and the Dominant white phenotype present in the White Leghorn. After comparison of sequences from different alleles at the Dominant white locus, amino acid alteration caused by insertion and deletion in the transmembrane region of the PMEL17 protein has been revealed. These mutations are associated with alleles representing different plumage colour variants.

<p>Leukotrienes are arachidonic acid derivatives long known for their inflammatory properties and their involvement with a number of human diseases, most notably asthma. Recently, leukotriene-based inflammation has also been implicated in atherosclerosis: ALOX5AP and LTA4H, two genes in the leukotriene biosynthesis pathway, have been associated with various cardiovascular disease (CVD) phenotypes. To assess the role of the leukotriene pathway in CVD pathogenesis, we performed genetic association studies of ALOX5AP and LTA4H in a non-familial data set of early onset coronary artery disease. Our results support a modest role for the leukotriene pathway in atherosclerosis pathogenesis, reveal important genomic interactions within the pathway, and suggest the importance of using pathway-based modeling for evaluating the genomics of atherosclerosis susceptibility. Motivated by this need, we investigated the statistical properties of a class of matrix-based statistics to assess epistasis. We simulated multiple two-variant disease models with haplotypes to gain an understanding of pathway interactions in terms of correlation patterns. Our goal was to detect an interaction between multiple disease-causing variants by means of their linkage disequlibrium (LD) patterns with other haplotype markers. The simulated models can be summarized into three categories: 1. No epistasis in the presence of marginal effects and LD; 2. Epistasis in the presence of LD and no marginal effects; and 3. Epistasis in the presence marginal effects and LD. We then assessed previously introduced single-gene methods that compare whole matrices of Single Nucleotide Polymorphism (SNP) LD between two samples. These methods include comparing two sets of principal components, a sum-of-squared-differences comparing pairwise LD, and a contrast test that controls for background LD. We also considered a partial least-square (PLS) approach for modeling gene-gene interactions. Our results indicate that these measures can be used to assess epistasis as well as marginal effects under certain disease models. Understanding and quantifying whole-gene variation and association to disease using multiple SNPs remains a difficult task. Providing a single statistical measure per gene will facilitate combining multiple types of genomic data at a gene-level and will serve as an alternative approach to assess epistasis in genome-wide association studies. The matrix-based measures can also be used in pathway ascertainment tools that require scores on a gene-level.</p> / Dissertation

No description available.