Since the completion of the sequencing of the human genome at the turn of the century, genomics has revolutionized the study of biology and medicine by providing high-throughput and quantitative methods for measuring molecular activities. Microarray and next generation sequencing emerged as important inflection points where the rate of data generation skyrocketed. The high dimensionality nature and the rapid growth in the volume of data precipitated a unique computational challenge in massive data analysis and interpretation. Noise and signal structure in the data varies significantly across types of data and technologies; thus, the context of the data generation process itself plays an important role in detecting key and oftentimes subtle signals. In this dissertation, we discuss four areas where contextualizing the data aids discoveries of disease-causing variants, complex relationships in the human microecology, interplay between gene and environment, and genetic regulation of gene expression. These studies, each in its own unique way, have helped made possible discoveries and expanded the horizon of our understanding of the human body, in health and disease.

The aim of this thesis is to apply recently developed technologies for genomic variation analyses, and to ensure quality of the generated information for use in preclinical cancer research. Faster access to a patients’ full genomic sequence for a lower cost makes it possible for end users such as clinicians and physicians to gain a more complete understanding of the disease status of a patient and adjust treatment accordingly. Correct biological interpretation is important in this context, and can only be provided through fast and simple access to relevant high quality data. Therefore, we here propose and validate new bioinformatic strategies for biomarker selection for prediction of response to cancer therapy. We initially explored the use of bioinformatic tools to select interesting targets for toxicity in carboplatin and paclitaxel on a smaller scale. From our findings we then further extended the analysis to the entire exome to look for biomarkers as targets for adverse effects from carboplatin and gemcitabine. To investigate any bias introduced by the methods used for targeting the exome, we analyzed the mutation profiles in cancer patients by comparing whole genome amplified DNA to unamplified DNA. In addition, we applied RNA-seq to the same patients to further validate the variations obtained by sequencing of DNA. The understanding of the human cancer genome is growing rapidly, thanks to methodological development of analysis tools. The next step is to implement these tools as a part of a chain from diagnosis of patients to genomic research to personalized treatment. / <p>QC 20121105</p>

Exome sequencing, the process of sequencing the set of all known exons simultaneously using next-generation sequencing technology, has dramatically changed the landscape of genetic research and genetic testing. The incredible volume of data produced by these experiments creates challenges in: 1) annotating the affects of observed variants, 2) filtering to remove noise, 3) identifying plausible disease-causing variants, and 4) validating experimental results. Here we will present a series of bioinformatic tools and techniques intended to address these challenges with exome sequencing and associated validation experiments. First, we will present the Automated Sequence Analysis Pipeline (ASAP), a tool for the efficient and automated management, detection and annotation of Sanger sequencing-based genetic testing and variant validation. This pipeline is extended to annotate exome-sequencing derived variants. Exome sequencing experiments produce a great number of variants that do not cause a patient's disease. One of the biggest challenges in exome sequencing experiments is sorting through these false positives to discover the true disease-causing variants. We have developed several techniques to aid in the reduction of these errors. The techniques described include: 1) the construction of a catalog of systematic errors by reprocessing thousands of publically available exomes, 2) a tool for the filtering of variants based on family structure and disease assumptions, and 3) a tool for discovering regions of autozygosity from the exomes of several affected patients in consanguineous pedigrees. Classes of variants that are undiscoverable using current analysis techniques gives rise to false negatives in exome sequencing experiments. We will present a tool, the Retrotransposon Insertion Detector for Exomes (RIDE) that uses the characteristic anomalies present in sequence alignments to detect the insertion of repetitive elements. The process of identifying a the cause of a patient's disease using exome sequencing data has been equated to finding a needle in a stack of needles. Only through the proper annotation of variants and the reduction of the error rates associated with exome sequencing experiments can this task be achieved in an efficient manner.

Submitted by Leonardo Cavalcante (leo.ocavalcante@gmail.com) on 2018-04-23T22:50:06Z No. of bitstreams: 1 Arquivototal.pdf: 7015058 bytes, checksum: 0d8c1dd0bc2f42ab36a2d917f1dc6a05 (MD5) / Made available in DSpace on 2018-04-23T22:50:06Z (GMT). No. of bitstreams: 1 Arquivototal.pdf: 7015058 bytes, checksum: 0d8c1dd0bc2f42ab36a2d917f1dc6a05 (MD5) Previous issue date: 2015-07-06 / A part of the populations in Northeastern Brazil are relatively isolated geographically and these populations maintain the tradition of consanguineous marriages for generations. These two factors (isolation and inbreeding) increase the risk of birth of people with autosomal recessive intellectual disabilities. The objective of this study was to determine the genetic causes of intellectual disabilities in two large consanguineous families of Paraiba backlands. In 2012, we conducted an epidemiological study to investigate the contribution of genetic factors in determining the deficiencies in six municipalities of Paraíba previously selected by presenting high consanguinity rate. Families who had patients with neurodegenerative disorders and/or intellectual disabilities (ID) were invited by community health agents for a first screening realized by biologists in order to select patients with deficiency probably caused by genetic mutations. In total, 276 patients were screened, of which, 109 were selected for medical evaluation with neurologists. After medical evaluation, two families with multiple affected individuals in two different forms of autosomal recessive intellectual disability were selected for clinical and genetic research. We performed the linkage study using SNPs array analysis to determine homozygous regions. Subsequently, the whole exome sequencing (WES) of one affected individual of each family was sequenciated. Potentially deleterious variants detected in regions of homozigosity-by descent which were not present in Brazilian population controls or in exomes of global online databases were subject to further scrutiny and segregation analysis by Sanger sequencing. Family A has seven adult siblings with syndromic ID. Phenotype includes tall forehead, prognatism, prominent chin, very large and overhanging nose tip. Homozigosity-by-descent analysis found a 4.0 Mb region in 19q13.32-q13.33 (lod score: 3.24). WES disclosed a homozygous variant (c.418C>T, p.Arg140Trp) in mediator complex subunit 25 (MED25), predicted as deleterious by Provean, Mutation Taster, PolyPhen-2 and SIFT. MED25 is a component of the Mediator complex, involved in regulation of transcription of nearly all RNA polymerase II-dependent genes. Deleterious mutations in MED12, MED17, MED23 and recently after our publication another mutation in the MED25 have been associated with ID. Family B has nine affected adults descending from four closely related first-cousin couples affected by severe non-syndromic ID. Homozigosity-by-descent analysis disclosed a 20.7 Mb region in 8q12.3-q21.2 (lod score: 3.11). WES identified a homozygous deleterious variant in inositol monophosphatase1 gene (IMPA1), consisting of a 5 bp duplication (c.489_493dupGGGCT) leading to frameshift (p.Ser165Trpfs*10). IMPA1 gene product is responsible for the final step of biotransformation of inositol triphosphate and diacylglycerol, two second messengers, and up to now, despite its many physiological functions, no clinical phenotype has been assigned to this gene dysfunction. From this study, it was possible to develop diagnostic test by restriction enzyme and therapeutic perspective for cases associated with IMPA1. / Uma parte das populações do Nordeste brasileiro está relativamente isolada geograficamente e mantêm, há várias gerações, a tradição de casamentos consanguíneos. Esses dois fatores associados (isolamento e endocruzamento) elevam o risco de nascimento de pessoas com deficiência intelectual com herança genética autossômica recessiva. O objetivo deste trabalho foi determinar as causas genéticas da deficiência intelectual em duas grandes famílias consanguíneas do sertão paraibano. Em 2012, nosso grupo de pesquisa realizou um estudo epidemiológico para determinar a contribuição de fatores genéticos na determinação das deficiências em seis municípios do sertão paraibano selecionados previamente por apresentarem elevada taxa de consanguinidade. As famílias que apresentavam repetições de indivíduos com doenças neurodegenerativas e/ou deficiência intelectual (DI) foram convocadas pelos agentes comunitários de saúde para uma primeira triagem, realizada pelos biólogos geneticistas, a fim de selecionar pacientes que apresentavam deficiência por prováveis causas genéticas. No total, foram triados 276 pacientes, sendo que, 109 foram selecionados para avaliação médica com neurologistas. Após a avaliação médica, duas famílias com múltiplos indivíduos acometidos por duas diferentes formas de DI de herança autossômica recessiva foram selecionadas para investigação clínico-genética. O estudo de ligação para determinar regiões em homozigose foi realizado com o uso da técnica de array de SNPs. Posteriormente, foi feito o sequenciamento do exoma completo de um indivíduo afetado de cada família. Variantes potencialmente deletérias detectadas em regiões em homozigose e que não estavam presentes em controles brasileiros e em banco de dados mundiais, foram objetos de uma análise mais aprofundada e feito a análise de co-segregação através do sequenciamento de Sanger. A primeira família estudada, a família A, possui sete adultos com DI sindrômica. O fenótipo inclui testa alta, prognatismo, queixo proeminente e ponta do nariz saliente, além da DI grave. O estudo de ligação apontou duas regiões com LOD scores máximos = 3,234, uma região de 26 Mb no cromossomo 2 (2p12 - q11.2) e uma região de 4,0 Mb no cromossomo 19 (19q13.32 - q13.33). O sequenciamento do exoma revelou uma variante em homozigose (c.418C>T, p.Arg140Trp) no gene MED25 (subunidade 25 do complexo mediador), predita como deletéria por diferentes softwares (Polyphen, Provean, Mutation Taster e SIFT). O complexo mediador está envolvido na regulação da transcrição de quase todos os genes dependentes da RNA polimerase II. Mutações deletérias nos genes MED12, MED17, MED23 e, recentemente, outra mutação no MED25, têm sido associadas com DI. Já a segunda família estudada, a família B, possui nove adultos afetados, descendentes de quatro relações consanguíneas entre primos de primeiro grau, com DI grave não-sindrômica. O estudo de ligação apontou uma região de 20,7 Mb no cromossomo 8 (8q12.3-q21.2) com LOD score = 3,11. O sequenciamento do exoma identificou uma variante deletéria em homozigose no gene inositol monofosfatase1 (IMPA1), que consiste em uma duplicação de 5 pares de bases (c.489_483dupGGGCT), levando a uma mutação do tipo frameshift (p.Ser165Trpfs*10). O produto do gene IMPA1 é uma enzima responsável pela etapa final da biotransformação dos segundos mensageiros inositol trifosfato e diacilglicerol, e até o momento, apesar de apresentar importantes funções fisiológicas, não havia fenótipo clínico atribuído a esse gene. A partir deste estudo, foi possível desenvolver teste diagnóstico com triagem por enzima de restrição e perspectiva de tratamento terapêutico para os casos associados ao IMPA1.

Les myopathies congénitales sont des maladies neuromusculaires dont le diagnostic est établi grâce aux données cliniques, histologiques et génétique. Cependant, le diagnostic génétique est manquant pour la moitié des patients, ce qui suggère de nouveaux gènes impliqués. Le but de mon projet était d'identifier de nouveaux gènes de myopathies congénitales et de valider l'impact des mutations trouvées. En utilisant une stratégie d'analyse de séquençage d'exomes de patients déjà exclus pour les gènes connus, nous avons mis en évidence deux nouveaux gènes impliqués dans les myopathies congénitales. Des mutations récessives dans le gène PYROXD1, codant pour une oxydoréductase, causent une myopathie apparaissant à l'enfance avec des défauts spécifiques en histologie. Grâce à un modèle animal, nous avons montré que les mutations impactaient l'activité enzymatique de la protéine. Des mutations dominantes ou récessives dans le gène CACNA1S causent une myopathie avec un phénotype similaire pour toutes les mutations. Les études fonctionnelles ont montré que les mutations causaient un défaut dans le couplage excitation-contraction. / Congenital myopathies are neuromuscular diseases diagnosed by clinical, histological and genetic data. However, the genetic diagnosis is missing for half of the patients, suggesting new genes involved. The goal of my project was to identify new genes of congenital myopathies and validate the impact of the mutations. Using a strategy of analyzing DNA sequencing of patients already excluded for known genes, we have identified two new genes involved in congenital myopathies. Recessive mutations in the PYROXD1 gene, encoding an oxidoreductase, cause a myopathy with childhood-onset and a histology specific spectra. Functionnal studies showed that the mutations have an effect on the enzymatic activity of the protein. We showed that dominant or recessive mutations in the CACNA1S gene cause a neonatal onset myopathy with a similar phenotype for all found mutations.

abstract: Rapid advancements in genomic technologies have increased our understanding of rare human disease. Generation of multiple types of biological data including genetic variation from genome or exome, expression from transcriptome, methylation patterns from epigenome, protein complexity from proteome and metabolite information from metabolome is feasible. "Omics" tools provide comprehensive view into biological mechanisms that impact disease trait and risk. In spite of available data types and ability to collect them simultaneously from patients, researchers still rely on their independent analysis. Combining information from multiple biological data can reduce missing information, increase confidence in single data findings, and provide a more complete view of genotype-phenotype correlations. Although rare disease genetics has been greatly improved by exome sequencing, a substantial portion of clinical patients remain undiagnosed. Multiple frameworks for integrative analysis of genomic and transcriptomic data are presented with focus on identifying functional genetic variations in patients with undiagnosed, rare childhood conditions. Direct quantitation of X inactivation ratio was developed from genomic and transcriptomic data using allele specific expression and segregation analysis to determine magnitude and inheritance mode of X inactivation. This approach was applied in two families revealing non-random X inactivation in female patients. Expression based analysis of X inactivation showed high correlation with standard clinical assay. These findings improved understanding of molecular mechanisms underlying X-linked disorders. In addition multivariate outlier analysis of gene and exon level data from RNA-seq using Mahalanobis distance, and its integration of distance scores with genomic data found genotype-phenotype correlations in variant prioritization process in 25 families. Mahalanobis distance scores revealed variants with large transcriptional impact in patients. In this dataset, frameshift variants were more likely result in outlier expression signatures than other types of functional variants. Integration of outlier estimates with genetic variants corroborated previously identified, presumed causal variants and highlighted new candidate in previously un-diagnosed case. Integrative genomic approaches in easily attainable tissue will facilitate the search for biomarkers that impact disease trait, uncover pharmacogenomics targets, provide novel insight into molecular underpinnings of un-characterized conditions, and help improve analytical approaches that use large datasets. / Dissertation/Thesis / Doctoral Dissertation Molecular and Cellular Biology 2015

Deficiência intelectual (DI), associada ou não a outras alterações congênitas, é a razão mais frequente de procura por aconselhamento genético pelas famílias. Até alguns anos atrás, a realização de cariótipo, triagem para doenças metabólicas e fra(x) elucidavam apenas &sim;40% dos casos de pacientes com DI idiopática. Com o surgimento de arrays genômicos, as causas moleculares por trás de outros &sim;20% dos quadros de DI foram elucidadas; porém, mesmo com esse avanço, muitos pacientes ainda permanecem sem causa molecular clara que justifique o fenótipo. O sequenciamento do exoma (WES) é hoje um dos recursos disponíveis para o diagnóstico e possível elucidação das causas genéticas por trás da deficiência intelectual idiopática, abrindo caminho também à identificação de novos genes. O presente trabalho realizou o sequenciamento de exoma de 8 probandos que tinham em comum a deficiência intelectual esporádica, acompanhada ou não de outros sinais clínicos, e de seus genitores não afetados (trios). Esses pacientes foram previamente triados para a síndrome do X frágil, e submetidos a exame de array CGH para investigação de perdas e ganhos de segmentos cromossômicos, ambos com resultados negativos. O objetivo desse estudo foi detectar alterações e possivelmente novos genes associados com a DI, usando pipelines de padrões de herança mendeliano. Treze alterações em 9 genes foram detectadas por sequenciamento de exoma e confirmadas por sequenciamento Sanger: 8 mutações bialélicas em genes recessivos (TBC1D24, ADAMTSL2, NALCN, VPS13B), uma ligada ao X (MID1), e 4 alterações de novo (RYR2, GABBR2, CDK13, DDX3X); 5 dessas alterações ainda não haviam sido descritas nos bancos de dados consultados, caracterizando mutações novas. Dos 8 trios, em 5 identificamos alterações moleculares provavelmente responsáveis pelos quadros apresentados; dois desses casos foram em genes recessivos (mutações homozigotas ou em heterozigose composta) e potencialmente teriam sido detectados mesmo se apenas os probandos houvessem sido sequenciados. Para as alterações em heterozigose, porém, a avaliação dos genitores e constatação de status de novo da mutação foram importantes para avaliar o impacto da variante. Esse trabalho resultou em uma taxa de diagnóstico de 62,5%; mesmo considerando o pequeno tamanho da amostra, esse valor está bem acima dos 15-30% relatados na literatura quando essa metodologia é utilizada para o estudo de casos esporádicos de DI. Em dois casos, mutações foram identificadas em genes que só foram descritos como mutados recentemente e que ainda não são considerados genes de deficiência intelectual no OMIM: o gene CDK13 foi descrito como mutado em pacientes de uma única coorte com malformação cardíaca congênita (sindrômica ou não), porém sua contribuição para coortes de DI ainda não foi investigada. O gene GABBR2, identificado mutado em heterozigose em um dos nossos pacientes, já havia sido considerado um candidato potencial para DI, mas apenas 2 trabalhos detectaram mutações nesse gene entre pacientes com DI e epilepsia. Os resultados aqui apresentados substanciam o papel desses genes como implicados na DI sindrômica de herança autossômica dominante, e devem contribuir para serem considerados genes OMIM de deficiência intelectual / Intellectual disability (ID), associated or not with other congenital abnormalities, is the most frequent reason for families to seek genetic counseling. Until some years ago, karyotyping, metabolic disease and FRAXA screening elucidated only &sim;40% of patients with idiopathic ID. Importantly, with the introduction of genomic arrays, the molecular cause behind a further &sim;20% of ID cases was determined; however, despite this improvement, many patients are still not provided with a clear molecular explanation and cause for their phenotype. Nowadays, whole exome sequencing (WES) is one of the methods available for diagnosis and a further means of possible elucidation of the genetic causes of idiopathic intellectual disability; in many cases this method also allows identification of genes that have not been previously related to ID. In the present project, we sequenced the exome (WES) of 8 sporadic patients that all had ID, with or without other clinical signs, and their unaffected parents (trios); these patients had been previously screened for fragile X syndrome and for losses and gains of chromosomal segments by array CGH, both with negative results. The objective of this study was to detect mutations and possibly new genes associated with ID, using pipelines for Mendelian inheritance patterns. Thirteen mutations in 9candidate genes were detected by exome sequencing and confirmed by Sanger sequencing, among them 8 biallelic mutations in autossomal recessive genes (TBC1D24, ADAMTSL2, NALCN, VPS13B), one mutation in an X-linked gene (MID1), and 4 de novo alterations (RYR2, GABBR2, CDK13, DDX3X); 5 of these mutations had not been described in the databases consulted characterizing new variants. Of the 8 trios, we obtained a probable diagnosis of the molecular alteration responsible for the presented phenotypes in 5. Two of these cases were in recessive genes (homozygous mutations or compound heterozygous), and the mutations would probably have been detected even if only the probands had been sequenced. However, for the heterozygous mutations, the assessment of the parents and the confirmation of the de novo status of the mutation was important to evaluate the impact of the variant. This work resulted in a diagnosis rate of 62.5%; even considering the small sample size, this value is well above the average of 15-30% reported in the literature when the methodology used for the study of ID sporadic cases is considered. In two cases, mutations were detected in genes only recently described as mutated and which are not considered yet as OMIM ID genes. The CDK13 gene had already been described as mutated in a single cohort of patients with syndromic congenital heart defects, but its contribution to ID cohorts has not been established. The GABBR2 gene, where a heterozygous mutation was identified in the patient, had already been considered a potential candidate for ID; there are only 2 studies that detected mutations in this gene among patients with ID and epilepsy. This contribution may pave the way to establishing GABBR2 and CDK13 as causations of ID and acceptance by OMIM

Bien que l’hétérogénéité des désordres génétiques nous limite dans l’identification du gène causal avec les approches diagnostiques conventionnelles, le séquençage de l’exome a permis d’accroitre le nombre de diagnostics moléculaires posés récemment. Par contre, le grand nombre de variants identifiés par cette méthode pose un défi significatif dans l’interprétation clinique de ses variants. Nous avons donc élaboré PhenoVar, un logiciel qui intègre les données phénotypiques et génotypiques pour retourner une courte liste de diagnostics potentiels. Nous voulons valider cette approche par phénotype au niveau clinique et montrer qu’elle peut être efficace pour diagnostiquer des patients atteints de maladies génétiques rares. Pour ce faire, le séquençage de l’exome a été effectué sur une cohorte de 51 patients. Ceux-ci présentent des dysmorphismes avec ou sans désordres neurodéveloppementaux dont l’étiologie reste indéterminée après plusieurs analyses conventionnelles. Suite au séquençage de l’exome, un pipeline d’analyse bio-informatique nous a permis de filtrer les variations pour garder seulement les variations rares, codantes, ayant une bonne qualité et pour éliminer les artéfacts de séquençage. Ensuite, pour analyser ces variations filtrées, une analyse manuelle et une analyse avec PhenoVar ont été faites. L’analyse manuelle consiste à regarder manuellement chaque variation pour voir son impact et identifier le diagnostic, sans regarder le phénotype du patient. Puis, Exomiser, un autre logiciel utilisant le phénotype, a été utilisé pour comparer les performances de PhenoVar. En comparaison avec l’analyse manuelle, PhenoVar nous a permis de diminuer de six fois le temps d’analyse et de diminuer de moitié le nombre de diagnostics potentiels. Avec ces deux méthodes, nous avons pu trouver le diagnostic moléculaire de 18 patients, soit un rendement diagnostic de 35%. Il est à noter qu’un diagnostic a été manqué par PhenoVar. Cependant, ce diagnostic a été récupéré en enlevant un filtre au niveau du phénotype. De plus, parmi les diagnostics effectués, 16 (89%) se retrouvent dans les dix premiers rangs de PhenoVar, tandis que seulement 10 (56%) se retrouvent dans les dix premiers rangs d’Exomiser. En conclusion, PhenoVar est supérieur à Exomiser pour trouver un diagnostic dans les dix premiers rangs. De plus, il se compare à l’analyse manuelle tout en diminuant le temps d’analyse et le nombre de variants. / Abstract: Although the heterogeneity of genetic disorders limits our capacity to identify the causal gene with conventional approaches, exome sequencing has increased the diagnostic yield. However, the large number of variants identified by this method poses a significant challenge in their clinical interpretation. Thus, we developed PhenoVar: a software that integrates phenotypic and genotypic data and produces a short list of potential diagnoses. The objective of this study is to validate this phenotype-based approach on a clinical level and show that it can be efficient to diagnose patients with rare genetic disorders. Exome sequencing was performed on a cohort of 51 patients. These presented with dysmorphic features with or without neurodevelopmental disorders of undetermined etiology, following conventional analysis. Following exome sequencing, a bioinformatics pipeline allowed us to filter variations, keeping only rare coding variations harboring high quality. Then, we analysed these filtered variations with both manual analysis and PhenoVar. In the manual analysis each variant was manually examined to determine its impact and to identify the diagnosis without taking the patient’s phenotype into consideration. Then, Exomiser, another phenotype-based tool, was used to compare PhenoVar’s performances. In comparison to the manual analysis, PhenoVar has allowed us to reduce the analysis time by six-fold and to reduce by half the number of potential diagnoses. With both methods, we found the molecular diagnosis in 18 patients; a rate of 35%. Moreover, among these diagnoses, 16 (89%) are found in the top 10 ranks of PhenoVar, compared to only 10 (56%) for Exomiser. In conclusion, PhenoVar proved to Exomiser in prioritizing the correct diagnosis in the top 10 ranks. Finally, diagnostic yield of PhenoVar is comparable to the manual analysis while reducing the analysis time and the number of variants.

Lower motor neuron diseases and peripheral neuropathies are two groups of diseases that include multiple rare disorders where many causes are unknown and definitive treatments are unavailable. Understanding the molecular etiology of these genetic diseases provides an opportunity for rapid diagnosis, preconception genetic counseling and, in a subset, direction for the development of future treatment options. The recent introduction of whole exome sequencing (WES) marks a new era in Mendelian genetic disease research as the majority of the coding region of the genome can be sequenced in a timely and cost-effective manner. In this study, WES was used to investigate the molecular etiology of a cohort of 37 patients presenting with lower motor neuron disease or peripheral neuropathy. A molecular diagnosis was determined for seven patients informing the diagnostic utility of WES. Novel phenotypes were found for three genes originally associated with a different disorder. Finally, the foundation has been laid, through the use of functional studies and large scale data-sharing, to identify novel disease-causing genes for lower motor neuron disease and peripheral neuropathy.

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/ Doctorat en Sciences biomédicales et pharmaceutiques (Médecine) / info:eu-repo/semantics/nonPublished