Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Desde a década de 1990, os esforços internacionais para a obtenção de genomas completos levaram à determinação do genoma de inúmeros organismos. Isto, aliado ao grande avanço da computação, tem permitido o uso de abordagens inovadoras no estudo da estrutura, organização e evolução dos genomas e na predição e classificação funcional de genes. Entre os métodos mais comumente empregados nestas análises está a busca por similaridades entre sequências biológicas. Análises comparativas entre genomas completamente sequenciados indicam que cada grupo taxonômico estudado até o momento contém de 10 a 20% de genes sem homólogos reconhecíveis em outras espécies. Acredita-se que estes genes taxonomicamente restritos (TRGs) tenham um papel importante na adaptação a nichos ecológicos particulares, podendo estar envolvidos em importantes processos evolutivos. Entretanto, seu reconhecimento não é simples, sendo necessário distingui-los de ORFs não-funcionais espúrias e/ou artefatos derivados dos processos de anotação gênica. Além disso, genes espécie- ou gêneroespecíficos podem representar uma oportunidade para o desenvolvimento de métodos de identificação e/ou tipagem, tarefa relativamente complicada no caso dos procariotos, onde o método padrão-ouro na atualidade envolve a análise de um grupo de vários genes (MultiLocus Sequence Typing MLST). Neste trabalho utilizamos dados produzidos através de análises comparativas de genomas e de sequências para identificar e caracterizar genes espécie- e gênero-específicos, os quais possam auxiliar no desenvolvimento de novos métodos para identificação e/ou tipagem, além de poderem lançar luz em importantes processos evolutivos (tais como a perda e ou origem de genes em linhagens particulares, bem como a expansão de famílias de genes em linhagens específicas) nos organismos estudados. / Since the 1990s, international efforts to obtain complete genomes led to the determination of the genome of many organisms. This, coupled with great advances in computing, has allowed the use of innovative approaches in the study of structure, organization and evolution of genomes and the prediction and functional classification of genes. Among the methods most commonly employed in such analysis is the search for similarities between biological sequences. Comparative analysis of whole genome sequences indicate that each taxonomic group studied so far contain 10 to 20% of genes with no recognizable homologues in other species. It is believed that these taxonomically restricted genes (TRGs) have an important role in adaptation to particular ecological niches and may be involved in important evolutionary processes. However, the recognition of such genes is not simple, being necessary to distinguish them from spurious ORFs nonfunctional and / or artifacts from the processes of gene annotation. Furthermore, species- or genus-specific genes may be an opportunity for the development of methods for identification and / or typing, a relatively complicated task in the case of prokaryotes, where the gold standard at present involves the analysis of a group of several genes (Multilocus Sequence Typing - MLST). This study used data generated through comparative analysis of genome sequences to identify and characterize species- and genusspecific genes, which may help in the development of new methods for identification and / or typing, and can possibly shed light on important evolutionary processes (such as loss and / or origin of genes in particular lineages, as well as expansion of gene families in specific strains) involving the studied organisms.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Desde a década de 1990, os esforços internacionais para a obtenção de genomas completos levaram à determinação do genoma de inúmeros organismos. Isto, aliado ao grande avanço da computação, tem permitido o uso de abordagens inovadoras no estudo da estrutura, organização e evolução dos genomas e na predição e classificação funcional de genes. Entre os métodos mais comumente empregados nestas análises está a busca por similaridades entre sequências biológicas. Análises comparativas entre genomas completamente sequenciados indicam que cada grupo taxonômico estudado até o momento contém de 10 a 20% de genes sem homólogos reconhecíveis em outras espécies. Acredita-se que estes genes taxonomicamente restritos (TRGs) tenham um papel importante na adaptação a nichos ecológicos particulares, podendo estar envolvidos em importantes processos evolutivos. Entretanto, seu reconhecimento não é simples, sendo necessário distingui-los de ORFs não-funcionais espúrias e/ou artefatos derivados dos processos de anotação gênica. Além disso, genes espécie- ou gêneroespecíficos podem representar uma oportunidade para o desenvolvimento de métodos de identificação e/ou tipagem, tarefa relativamente complicada no caso dos procariotos, onde o método padrão-ouro na atualidade envolve a análise de um grupo de vários genes (MultiLocus Sequence Typing MLST). Neste trabalho utilizamos dados produzidos através de análises comparativas de genomas e de sequências para identificar e caracterizar genes espécie- e gênero-específicos, os quais possam auxiliar no desenvolvimento de novos métodos para identificação e/ou tipagem, além de poderem lançar luz em importantes processos evolutivos (tais como a perda e ou origem de genes em linhagens particulares, bem como a expansão de famílias de genes em linhagens específicas) nos organismos estudados. / Since the 1990s, international efforts to obtain complete genomes led to the determination of the genome of many organisms. This, coupled with great advances in computing, has allowed the use of innovative approaches in the study of structure, organization and evolution of genomes and the prediction and functional classification of genes. Among the methods most commonly employed in such analysis is the search for similarities between biological sequences. Comparative analysis of whole genome sequences indicate that each taxonomic group studied so far contain 10 to 20% of genes with no recognizable homologues in other species. It is believed that these taxonomically restricted genes (TRGs) have an important role in adaptation to particular ecological niches and may be involved in important evolutionary processes. However, the recognition of such genes is not simple, being necessary to distinguish them from spurious ORFs nonfunctional and / or artifacts from the processes of gene annotation. Furthermore, species- or genus-specific genes may be an opportunity for the development of methods for identification and / or typing, a relatively complicated task in the case of prokaryotes, where the gold standard at present involves the analysis of a group of several genes (Multilocus Sequence Typing - MLST). This study used data generated through comparative analysis of genome sequences to identify and characterize species- and genusspecific genes, which may help in the development of new methods for identification and / or typing, and can possibly shed light on important evolutionary processes (such as loss and / or origin of genes in particular lineages, as well as expansion of gene families in specific strains) involving the studied organisms.

Orientador: Laymert Garcia dos Santos / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Filosofia e Ciencias Humanas / Made available in DSpace on 2018-08-05T01:28:26Z (GMT). No. of bitstreams: 1 Leite_Marcelo_D.pdf: 18137235 bytes, checksum: d2ccf296709649c706ae95e568a4a4e8 (MD5) Previous issue date: 2005 / Resumo: A tese central deste trabalho é que a aceitação pública despertada pelo Projeto Genoma Humano só se explica pelo uso político e retórico de um determinismo genético crescentemente irreconciliável com os resultados empíricos da pesquisa genômica atual. A complexidade verificada no genoma humano e em suas interações com o meio desautoriza a manutenção de uma noção simples e unidirecional de causalidade, contrariamente ao pressuposto na idéia de gene como único portador de informação, esteio da doutrina do determinismo genético. Um complexo de metáforas informacionais e/ou lingüísticas continuo vivo nos textos publicados por biólogos moleculares na literatura científica, notadamente nos artigos veiculados nos periódicos de alto impacto Nature e Science de 15 e 16 fevereiro de 2001, respectivamente. Tais metáforas inspiram um tipo de discurso ambíguo que modula nuances variadas de retórica determinista, conforme se dirija aos próprios pares ou ao público leigo" O campo da genômica ainda está longe de rejeitar a conjunção problemática das noções de gene pré-formacionista e de gene como recurso desenvo/vimenta/ na base da metáfora do gene como informação. Essa fusão inspirada pela terminologia cibernética propicia uma versão asséptica de gene, distanciada da natureza, puramente sintática, móvel e virtual o bastante para circular desimpedida nos circuitos de produção de valor como recurso genético passível de garimpagem e de patenteamento. Críticos dã tecnociência devem desafiar o campo da genômica a reformular drasticamente as metáforas que dão suporte a seu programa hegemônico de pesquisa / Abstract: The central thesis of this work is that the public support generated for the Human Genome Project and the hype surrounding it can be explained only by the political and rhetorical uses of genetic determinism, a notion which increasingly cannot be reconciled with the empirical results of on-going genomic research. The complexity that has been uncovered in the human genome and in its interactions with the environment implies that a simple and unidirectional notion of causality cannot be maintained, contrary to a presupposition of the idea of the gene as the sole carrier of iliformation, an idea that contributes to sustain the doctrine of genetic determinism. A complex of informational and/or linguistic metaphors lives on in the texts published by molecular biologists in the scientific press, most notably in the issues published February 15thand 16thof 2001 ofthe high impact journals Nature and Science, respectively. These metaphors generate an ambiguous type of discourse that modulates various nuances of deterministic rhetoric, depending on whether it addresses peers or the lay publico The field of genomics is still a long way ITom rejecting the questionable conflation of the notions of gene as preformation and gene as developmental resource which underpins the metaphor of gene as information. This conflation inspired by cybernetics terminology enables an aseptic version of the gene, separated ITom nature, portable and virtual enough to flow unimpeded through the channels ofvalue production as genetic resource suitable for mining and patenting. Critics of technoscience should challenge the field of genomics to drastically reshape the metaphors which have supported its hegemonic research agenda / Doutorado / Doutor em Ciências Sociais

Indiana University-Purdue University Indianapolis (IUPUI) / Juvenile Myelomonocytic Leukemia (JMML) is rare, fatal myeloproliferative disease (MPD) affecting young children, and is characterized by expansion of monocyte lineage cells and hypersensitivity to Granulocyte Macrophage-Colony Stimulating Factor (GM-CSF) stimulation. JMML is frequently associated with gain-of-function mutations in the PTPN11 gene, which encodes the protein tyrosine phosphatase, Shp2. Activating Shp2 mutations are known to promote hyperactivation of the Ras-Erk signaling pathway, but Akt is also observed to have enhanced phosphorylation, suggesting a potential role for Phosphatidylinositol-3-Kinase (PI3K)-Akt signaling in mutant Shp2-induced GM-CSF hypersensitivity and leukemogenesis. Having demonstrated that Class IA PI3K is hyperactivated in the presence of mutant Shp2 and contributes to GM-CSF hypersensitivity, I hypothesized the hematopoietic-specific Class IA PI3K catalytic subunit p110δ is a crucial mediator of mutant Shp2-induced PI3K hyperactivation and GM-CSF hypersensitivity in vitro and MPD development in vivo. I crossed gain-of-function mutant Shp2 D61Y inducible knockin mice, which develop fatal MPD, with mice expressing kinase-dead mutant p110δ D910A to evaluate p110δ’s role in mutant Shp2-induced GM-CSF hypersensitivity in vitro and MPD development in vivo. As a comparison, I also crossed Shp2 D61Y inducible knockin mice with mice bearing inducible knockout of the ubiquitously expressed Class IA PI3K catalytic subunit, p110α. I found that genetic interruption of p110δ, but not p110α, significantly reduced GM-CSF-stimulated hyperactivation of both the Ras-Erk and PI3K-Akt signaling pathways, and as a consequence, resulted in reduced GM-CSF-stimulated hyper-proliferation in vitro. Furthermore, I found that mice bearing genetic disruption of p110δ, but not p110α, in the presence of gain-of-function mutant Shp2 D61Y, had on average, smaller spleen sizes, suggesting that loss of p110δ activity reduced MPD severity in vivo. I also investigated the effects of three PI3K inhibitors with high specificity for p110δ, IC87114, GDC-0941, and GS-9820 (formerly known as CAL-120), on mutant Shp2-induced GM-CSF hypersensitivity. These inhibitors with high specificity for p110δ significantly reduced GM-CSF-stimulated hyperactivation of PI3K-Akt and Ras-Erk signaling and reduced GM-CSF-stimulated hyperproliferation in cells expressing gain-of-function Shp2 mutants. Collectively, these findings show that p110δ-dependent PI3K hyperactivation contributes to mutant Shp2-induced GM-CSF hypersensitivity and MPD development, and that p110δ represents a potential novel therapeutic target for JMML.

Indiana University-Purdue University Indianapolis (IUPUI) / Alzheimer's disease (AD) is the most common form of dementia defined by loss in memory and cognitive abilities severe enough to interfere significantly with daily life activities. Amnestic mild cognitive impairment (MCI) is a clinical condition in which an individual has memory deficits not normal for the individual's age, but not severe enough to interfere significantly with daily functioning. Every year, approximately 10-15% of individuals with MCI will progress to dementia. Currently, there is no treatment to slow or halt AD progression, but research studies are being conducted to identify causes that can lead to its earlier diagnosis and treatment. Genetic variation plays a key role in the development of AD, but not all genetic factors associated with the disease have been identified. Copy number variants (CNVs), a form of genetic variation, are DNA regions that have added genetic material (duplications) or loss of genetic material (deletions). The regions may overlap one or more genes possibly affecting their function. CNVs have been shown to play a role in certain diseases. At the start of this work, only one published study had examined CNVs in late-onset AD and none had examined MCI. In order to determine the possible involvement of CNVs in AD and MCI susceptibility, genome-wide CNV analyses were performed in participants from three cohorts: the ADNI cohort, the NIA-LOAD/NCRAD Family Study cohort, and a unique cohort of clinically characterized and neuropathologically verified individuals. Only participants with DNA samples extracted from blood/brain tissue were included in the analyses. CNV calls were generated using genome-wide array data available on these samples. After detailed quality review, case (AD and/or MCI)/control association analyses including candidate gene and genome-wide approaches were performed. Although no excess CNV burden was observed in cases compared to controls in the three cohorts, gene-based association analyses identified a number of genes including the AD candidate genes CHRFAM7A, RELN and DOPEY2. Thus, the present work highlights the possible role of CNVs in AD and MCI susceptibility warranting further investigation. Future work will include replication of the findings in independent samples and confirmation by molecular validation experiments.

Ljudski genom sadrži milijune regulatornih elemenata - enhancera - koji kvantitativno reguliraju ekspresiju gena. Unatoč ogromnom napretku u razumijevanju načina na koji enhanceri reguliraju ekspresiju gena, području još uvijek nedostaje pristup koji je sustavan, integrativan i dostupan za otkrivanje i dokumentiranje cis-regulatornih odnosa u cijelom genomu. Razvili smo novu računalnu metodu - reg2gene - koja modelira i integrira aktivnost enhancera~ekspresije gena. reg2gene sastoji se od tri glavna koraka: 1) kvantifikacija podataka, 2) modeliranje podataka i procjena značaja, i 3) integracija podataka prikupljenih u reg2gene R paketu. Kao rezultat toga, identificirali smo dva skupa enhancer-gen interakcija (EGA): fleksibilni skup od ~ 230K EGA (flexibleC) i strogi skup od ~ 60K EGA (stringentC). Utvrdili smo velike razlike u prethodno objavljenim računalnim modelima enhancer-gen interakcija; uglavnom u lokaciji, broju i svojstvima definiranih enhancera i EGA. Izveli smo detaljno mjerenje performansi sedam skupova računalno modeliranih EGA-a, ali smo pokazali da se niti jedan od trenutno dostupnih skupova referentnih podataka ne može koristiti kao referentni skup podataka "zlatnI standard". Definirali smo dodatni referentni skup pozitivnih i negativnih EGA -a pomoću kojih smo pokazali da stringentC ima najveću pozitivnu prediktivnu vrijednost (PPV). Pokazali smo potencijal EGA-a za identifikaciju genskih meta nekodirajucih SNP-ova. Proveli smo funkcionalnu analizu kako bismo otkrili nove genske mete, pleiotropiju enhancera i mehanizme aktivnosti enhancera. Ovaj rad poboljšava naše razumijevanje regulacije ekspresije gena posredovane enhancerima. / Das menschliche Genom enthält Millionen von regulatorischen Elementen - Enhancern -, die die Genexpression quantitativ regulieren. Trotz des enormen Fortschritts beim Verständnis, wie Enhancer die Genexpression steuern, fehlt es in diesem Bereich immer noch an einem systematischen, integrativen und zugänglichen Ansatz zur Entdeckung und Dokumentation von cis-regulatorischen Beziehungen im gesamten Genom. Wir haben eine neuartige Methode - reg2gene - entwickelt, die Genexpression~Enhancer-Aktivität modelliert und integriert. reg2gene besteht aus drei Hauptschritten: 1) Datenquantifizierung, 2) Datenmodellierung und Signifikanzbewertung und 3) Datenintegration, die in dem R-Paket reg2gene zusammengefasst sind. Als Ergebnis haben wir zwei Sätze von Enhancer-Gen-Assoziationen (EGAs) identifiziert: den flexiblen Satz von ~230K EGAs (flexibleC) und den stringenten Satz von ~60K EGAs (stringentC). Wir haben große Unterschiede zwischen den bisher veröffentlichten Berechnungsmodellen für Enhancer-Gene-Assoziationen festgestellt, vor allem in Bezug auf die Lage, die Anzahl und die Eigenschaften der definierten Enhancer-Regionen und EGAs. Wir führten ein detailliertes Benchmarking von sieben Sets von rechnerisch modellierten EGAs durch, zeigten jedoch, dass keiner der derzeit verfügbaren Benchmark-Datensätze als "goldener Standard" verwendet werden kann. Wir definierten einen zusätzlichen Benchmark-Datensatz mit positiven und negativen EGAs, mit dem wir zeigten, dass das stringentC-Modell den höchsten positiven Vorhersagewert (PPV) hatte. Wir haben das Potenzial von EGAs zur Identifizierung von Genzielen von nicht-kodierenden SNP-Gene-Assoziationen nachgewiesen. Schließlich führten wir eine funktionelle Analyse durch, um neue Genziele, Enhancer-Pleiotropie und Mechanismen der Enhancer-Aktivität zu ermitteln. Insgesamt bringt diese Arbeit unser Verständnis der durch Enhancer vermittelten Regulierung der Genexpression in Gesundheit und Krankheit voran. / Human genome contains millions of regulatory elements - enhancers - that quantitatively regulate gene expression. Multiple experimental and computational approaches were developed to associate enhancers with their gene targets. Despite the tremendous progress in understanding how enhancers tune gene expression, the field still lacks an approach that is systematic, integrative and accessible for discovering and documenting cis-regulatory relationships across the genome. We developed a novel computational approach - reg2gene- that models and integrates gene expression ~ enhancer activity. reg2gene consists of three main steps: 1) data quantification, 2) data modelling and significance assessment, and 3) data integration gathered in the reg2gene R package. As a result we identified two sets of enhancer-gene associations (EGAs): the flexible set of ~230K EGAs (flexibleC), and the stringent set of ~60K EGAs (stringentC). We identified major differences across previously published computational models of enhancer-gene associations; mostly in the location, number and properties of defined enhancer regions and EGAs. We performed detailed benchmarking of seven sets of computationally modelled EGAs, but showed that none of the currently available benchmark datasets could be used as a “golden-standard” benchmark dataset. To account for that observation, we defined an additional benchmark set of positive and negative EGAs with which we showed that the stringentC model had the highest positive predictive value (PPV) across all analyzed computational models. We reviewed the influence of EGA sets on the functional analysis of risk SNPs and demonstrated the potential of EGAs to identify gene targets of non-coding SNP-gene associations. Lastly, we performed a functional analysis to detect novel gene targets, enhancer pleiotropy, and mechanisms of enhancer activity. Altogether, this work advances our understanding of enhancer-mediated gene expression regulation in health and disease.