DNA methylation is an epigenetic mechanism that usually occurs at CpG sites in the genome. Both sequencing and array-based techniques are available to detect methylation patterns. Whole-genome bisulfite sequencing is the most comprehensive but cost-prohibitive approach, and microarrays represent an affordable alternative approach. Array-based methods are generally cheaper but assess a specific number of genomic loci, such as Illumina methylation arrays. Differentially methylated regions (DMRs) are genomic regions with specific methylation patterns across multiple CpG sites that associate with a phenotype. Methylation at nearby sites tends to be correlated, therefore it may be more powerful to study sets of sites to detect methylation differences as well as reduce the multiple testing burden, compared to utilizing individual sites. Several statistical approaches exist for identifying DMRs, and a few prior publications compared the performance of several commonly used DMR methods. However, as far as we know, no comprehensive comparisons have been made based on genome-wide simulation studies. This dissertation provides some comprehensive suggestions for DMR analysis based on genome-wide evaluations of existing DMR tools and presents the development of a novel approach to increase the power to identify DMRs with clinical value in genomic research. The second chapter presents genome-wide null simulations to compare five commonly used array-based DMR methods (Bumphunter, comb-p, DMRcate, mCSEA and coMethDMR) and identifies coMethDMR as the only approach that consistently yields appropriate Type I error control. We suggest that a genome-wide evaluation of false positive (FP) rates is critical for DMR methods. The third chapter develops a novel Principal Component Analysis based DMR method (denoted as DMRPC), which demonstrates its ability to identify DMRs using genome-wide methylation arrays with well-controlled FP rates at the level of 0.05. Compared to coMethDMR, DMRPC is a robust and powerful novel DMR tool that can examine more genomic regions and extract signals from low-correlation regions. The fourth chapter applies the new DMR approach DMRPC in two “real-world” datasets and identifies novel DMRs that are associated with several inflammatory markers.

No description available.

DNA methylation is an epigenetic mechanism critical for tissue development, cell specification and cellular function. Mammalian brains consist of millions to billions of neurons and glial cells that can be subdivided into many distinct types of cells. We hypothesize that brain methylomes are heterogeneously methylated across different types of cells and the transcription factors play key roles in brain methylome programming. To dissect brain methylome heterogeneity, in Chapter 2, we first focused on the identification of cell-subset specific methylated (CSM) loci which demonstrate bipolar DNA methylation pattern, i.e., hypermethylated in one cell subset but hypomethylated in others. With the genome-scale hairpin bisulfite sequencing approach, we demonstrated that the majority of CSM loci predicted likely resulted from the methylation differences among brain cells rather than from asymmetric DNA methylation between DNA double strands. Importantly, we found that putative CSM loci increased dramatically during early stages of brain development and were enriched for GWAS variants associated with neurological disorder-related diseases/traits. It suggests the important role of putative CSM loci during brain development, implying that dramatic changes in functions and complexities of the brain may be companied by a rapid change in epigenetic heterogeneity. To explore epigenetic regulatory mechanisms during brain development, as described in Chapter 3, we adopted unbiased data-driven approaches to re-analyze methylomes for human and mouse frontal cortices at different developmental stages. We predicted Egr1, a transcriptional factor with important roles in neuron maturation, synaptic plasticity, long-term memory formation and learning, plays an essential role in brain epigenetic programming. We performed EGR1 ChIP-seq and validated that thousands of EGR1 binding sites are with cell-type specific methylation patterns established during postnatal frontal cortex development. More specifically, the CpG dinucleotides within these EGR1 binding sites become hypomethylated in mature neurons but remain heavily methylated in glia. We further demonstrated that EGR1 recruits a DNA demethylase TET1 to remove the methylation marks at EGR1 binding sites and activate downstream genes. Also, we found that the frontal cortices from the knockout mice lacking Egr1 or Tet1 share strikingly similar profiles in both gene expression and DNA methylation. Collectively, the study in this dissertation reveals EGR1 programs the brain methylome together with TET1 during postnatal development. This study also provides new insights into how life experience and neuronal activity may shape the brain methylome. / Ph. D. / DNA methylation is a widespread epigenetic mark on DNA, serving as a “switch” to turn on or off gene expression. It plays essential roles in cellular functions, tissue development. Mammalian brains contain millions to billions of neurons and glial cells, which can be further divided into many different types of cells. We hypothesize that brain cells have different methylation profiles across the genome, and transcriptional factors play important roles in programming methylation in the mammalian brain genome. To study the diversity of methylation profiles across the genomes of different brain cells, in Chapter 2, we first focused on the identification of cell-subset specific methylated (CSM) genomic regions which show bipolar DNA methylation pattern, i.e., hypermethylated in one type of cell but hypomethylated in others. By applying a technique called the genome-scale hairpin bisulfite sequencing to mouse frontal cortices, we demonstrated that the majority of CSM genomic regions predicted likely resulted from the methylation differences among brain cells, rather than from methylation differences between DNA double strands. Surprisingly, we found that these predicted CSM genomic regions increased dramatically during early stages of brain development and were enriched for GWAS variants associated with neurological disorder-related diseases/traits. It suggests the importance of predicted CSM genomic regions, implying that dramatic changes in brain function and structure may be companied by a rapid change in DNA methylation diversity during brain development. To explore underlying epigenetic mechanisms during brain development, as described in Chapter 3, we re-analyzed methylomes for human and mouse frontal cortices at different developmental stages, and predicted Egr1, a transcriptional factor with important roles in neuron maturation, synaptic plasticity, long-term memory formation and learning, plays an essential role in brain methylome programming. We found thousands of EGR1 binding sites showed cell-type specific methylation patterns, and were established during postnatal frontal cortex development. More specifically, the methylation level of these EGR1 binding sites was low in mature neurons but pretty high in glial cells. We further demonstrated that EGR1 recruits a DNA demethylase TET1 to remove the methylation marks at EGR1 binding sites and activate downstream genes. Also, we found that the frontal cortices from the Egr1 knockout or Tet1 knockout mice show strikingly similar profiles in both gene expression and DNA methylation. Collectively, the study in this dissertation reveals EGR1 works together with TET1 to program the brain methylome during postnatal development. This study also provides new insights into how life experience and neuronal activity may shape the brain methylome.

A Febre de Chikungunya é uma doença sistêmica causada por arbovírus e estima-se que afete cerca de 1 milhão de pessoas anualmente. Os principais sintomas associados com esta doença são febre e poliartralgia, podendo esta última assumir um caráter crônico em cerca de metade dos casos. Devido aos inúmeros surtos que ocorreram nos últimos 50 anos, diversos estudos tiveram como objetivo determinar os mecanismos de replicação do vírus e da resposta imune. Mesmo assim, pouco se sabe sobre quais moléculas possibilitam o processo de infecção. Já foi demonstrada a importância de interferons, principalmente de tipo I, citocinas e quimiocinas na diminuição da replicação viral. Além disso, há uma preferência do vírus por tipos celulares específicos como células endoteliais e epiteliais. Porém, estudos mostram informações contraditórias referentes ao papel de células mononucleares do sangue periférico (PBMC), principalmente com relação a monócitos e células B e T. Diante deste contexto, o tratamento utilizado atualmente é direcionado apenas ao alívio de sintomas uma vez que não existem drogas ou vacinas licenciadas específicas para esta doença. Logo, o objetivo deste trabalho é estudar as modificações transcricionais que ocorrem em amostras humanas durante o processo de infecção pelo vírus de Chikungunya de modo a esclarecer os mecanismos utilizados pelo sistema imune em resposta a infecção. Além disso, este estudo tem como finalidade apontar possíveis diferenças transcricionais entre amostras crônicas e não-crônicas. / The Chikungunya Fever is a systemic disease transmitted by arboviruses and is estimated to affect 1 million people annually. The main symptoms associated with this disease are fever and polyarthralgia, which can develop to chronic features in about half of the cases. Due to outbreaks that occurred in the last 50 years, many studies had the goal of determining the mechanisms of virus replication and immune response. Nevertheless, it is still poorly understood which molecules enable the ocurrence of the infection process. It has already been shown the importance of interferons, mainly type I, cytokines and chemokines in restricting the viral replication. In addition, the Chikungunya virus shows a preference for specific cell types such as endothelial and epithelial cells. However, studies display contradictory information regarding the role of peripheral blood mononuclear cells (PBMC), mainly in relation to monocytes and B and T cells. Given this context, the treatment currently used is directed only to alleviate the symptoms since there are no specific licensed drugs or vaccines for this disease. Therefore, the objective of this work was to study the transcriptional modifications that occur in humans during the process of Chikungunya virus infection in order to clarify the mechanisms used by the immune system. In addition, it aims to point out possible transcriptional differences between sample from the Chronic and Non-Chronic acute phase of the infection.

Microarray technology permit us to study the expression levels of thousands of genes simultaneously. The technique has a wide range of applications including identification of genes that change their expression in cells due to disease or drug stimuli. The dissertation is addressing statistical methods for the selection of differentially expressed genes in two experimental conditions. We propose two different methods for the selection of differentially expressed genes. The first method is a classical approach, where we consider a common distribution for the summary measure of equally expressed genes. To estimate this common distribution, the Johnson system of distribution is used. The advantage of using Johnson system is that, there is no need of a parametric assumption for gene expression data. In contrast to other classical methods, in the proposed method, there is a sharing of information across the genes by the assumption of a common distribution for the summary measure of equally expressed genes. The second method is the gene selection using a mixture model approach and Baye's theorem. This approach also uses the Johnson System of distribution for the estimation of distribution of summary measure. Johnson system of distribution has the flexibility of covering a wide variety of distributional shapes. This system provides a unique distribution corresponding to each pair of mathematically possible values of skewness and kurtosis. The significant flexibility of Johnson system is very useful in characterizing the complicated data set like microarray data. In this dissertation we propose a novel algorithm for the estimation of the four parameters of the Johnson system.

Submitted by MARIA LETICIA GUINDALINI MELLONI null (letmell@yahoo.com.br) on 2016-01-14T15:02:04Z No. of bitstreams: 1 Tese_Maria_Letícia_Guindalini_Melloni.pdf: 683985 bytes, checksum: 53424c1e6da45d38a2d516aeb0a405fd (MD5) / Rejected by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br), reason: Solicitamos que realize uma nova submissão seguindo as orientações abaixo: A versão do trabalho submetida ao Repositório Institucional UNESP deve conter o texto completo. 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No. of bitstreams: 1 melloni_mlg_dr_jabo_par.pdf: 733459 bytes, checksum: d8b36f206c9b78d184a6e2627f86b26d (MD5) Previous issue date: 2015-12-15 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Com o intuito de aumentar o conhecimento da rede gênica envolvida no controle do florescimento em cana-de-açúcar, diferentes cultivares de cana-de-açúcar foram submetidos a tratamentos fotoperiódicos de indução e não indução do florescimento em câmara de fotoperíodo. Aos 5, 10 e 20 dias de indução, a folha +1 e a bainha foliar foram coletadas para a identificação de fragmentos diferencialmente expressos (FDEs) por meio da técnica de cDNA-AFLP entre e dentro dos tratamentos fotoperiódicos. Um total de 162 fragmentos foram selecionados e reamplificados. Destes, 63 FDEs tiveram sucesso na reação de reamplificação e foram clonados e sequenciados. As sequências foram confrontadas com seis bancos de sequências: 1. Transcritos do projeto SUCEST ;2. Proteínas do genoma de sorgo; 3. BAC de cana-de-açúcar; 4. Proteínas do genoma de arroz, 5. Proteínas presentes no Phytozome e 6. NCBI. A busca por similaridade se deu pelo uso da ferramenta BLASTn (e-value 1e-5) nos casos do banco SUCEST e dos BACs de cana-de-açúcar e BLASTx (e-value 1e-5) para os demais bancos. Dentre os 63 FDEs, 23 corresponderam a sequências de genes enquanto os outros 40 representam sequências que não estão depositadas nestes bancos (no hits). A maioria das 23 sequencias apresenta similaridade com genes que codificam proteínas hipotéticas ou preditas em diversos organismos. Com base na análise do domínio da proteína realizada pelo Pfam, seis sequências podem estar associadas ao metabolismo da indução do florescimento. Dentre estas as sequencias LM-19, LM-40 e LM-53 se destacaram. A LM-19 possui similaridade com o gene que codifica uma proteína com o domínio DNAJ sendo que proteína com este domínio é considerada mediador da integração dos sinais do florescimento em Arabidopsis thaliana. LM-40 possui similaridade com o gene que codifica proteína de domínio (F-BOX); estudos indicam forte relação deste domínio aos processos de indução ao florescimento. LM-53 tem um domínio de proteína predita semelhante ao domínio da proteína codificada pelo gene CONSTANS que regula a expressão de FLOWERING LOCUS T (FT), que codifica o florígeno em Arabidopsis thaliana e em algumas outras espécies. De maneira geral, a técnica do cDNA-AFLP foi eficiente, na identificação de FDEs ao longo dos tratamentos fotoperiódicos de indução e não indução do florescimento. Os resultados obtidos sugerem que as sequencias LM-19, LM-40 e LM-53 estão vinculadas aos metabolismos de indução do florescimento. É provável que a maioria dos FDEs obtidos possam estar envolvidos nos metabolismos da indução do florescimento, porém ainda não foram identificados na literatura. / In order to increase the knowledge of the gene network involved in sugarcane flowering induction, sugarcane cultivars were submitted to different photoperiod treatments of flowering induction and non-induction in a photoperiod facility. At 5, 10 and 20 days of induction, the +1 leaf and the leaf sheath were collected for the identification of different transcript-derived fragments (TDFs) within and between the photoperiod treatments to apply the cDNA-AFLP technique. A total of 162 TDFs were selected and re-amplified. Of these, 63 TDFs were successful in re-amplification and were cloned and sequenced. The sequences were confronted against 6 sequence databanks (SUCEST transcripts; Sorghum genome proteins; Sugarcane BACs; proteins from rice genome; Phytozome and NCBI). Similarity search was done by using the BLASTn (e-value 1e-5) tool for the SUCEST databank and sugarcane BACs while BLASTx (e-value 1e-5) was use for the other banks. Among the 63 TDFs, 23 corresponded to gene sequences while the remaining 40 represent sequences that are not deposited in these banks (no hits). The majority of the 23 sequences showed similarity with genes coding for hypothetical or predicted proteins of different organisms. Based on the protein domain analysis conducted by Pfam, six sequences may be associated with flowering induction metabolism. Among these: LM-19, LM-40 and LM-53 sequences stood out. LM-19 has similarity to the gene encoding a protein with DnaJ domain. Proteins having this domain are considered as an integrating floral signals mediator in Arabidopsis thaliana. LM-40 has similarity to the gene encoding a protein with (F-BOX) domain. This domain has a strong relationship in flowering induction processes. LM-53 has one of the predicted protein domain similar to the domain of the protein encoded by the CONSTANS gene which governs the expression of FLOWERING LOCUS T (FT), this later one encodes the florigen. Generally the cDNA-AFLP technique was effective in identifying TDFs across the flowering inductive and non-inductive photoperiodic treatments. The results suggest that LM-19, LM-40 and LM-53 sequences are linked to flowering induction metabolisms. Probably, most of the TDF here obtained may be involved in the flowering induction metabolism, although not yet been identified in the literature. / FAPESP: 2013/24020-0

Made available in DSpace on 2015-03-26T13:32:18Z (GMT). No. of bitstreams: 1 texto completo.pdf: 619084 bytes, checksum: 33699c369d9fd3f595c40375c27f4c43 (MD5) Previous issue date: 2013-01-16 / One of the current objectives of molecular biology is to measure and assess the gene expression profiles in different types of biological tissues, to understand the mechanisms of molecular transformation under certain conditions. Next-generation sequencing (NGS) technologies promote DNA sequencing in platforms capable of generating information about millions of base pairs in a single step. However these technologies still have high cost, making it difficult to obtain large number of repetitions of sample data. Therefore, it becomes necessary the discovery and the improvement of efficient statistical methodologies for optimizing analysis of data generated in genome sequencing platforms. The overall objective of this work was to evaluate the effect of the number of repetitions in the identification of differentially expressed genes, in RNA-Seq experiments, contributing to the clarification of the statistic that researchers will assist in data analysis in RNA-Seq experiments. Specifically, we evaluate empirically the effect of the number of repetitions in the statistical analysis of gene expression in RNA-Seq experiments. To carry out the analyses we used a dataset defined in Li et al. (2008), which compared treated and non-treated cancer cells. That work had four biological replications for the control group (non-treated) and three replications for biological treatment group (cells that have received the treatment). The data was analyzed using the package DESeq from the statistical environment R. A total of 2566 genes were considered differentially expressed (DE) when we evaluate the original and complete dataset. When we analyzed three replications of the control and treatment, we found, on average, 2153 genes DE. From the moment in which only two reps for both treatments were used, were identified, on average, 1241 genes DE. The major change in the number of genes DE was observed when replications were not used. In this case we identified around 44 differentially expressed genes. According to the results generated in the analysis, it was possible to verify that the number of repetitions is an essential factor in order to obtain a significant number of differentially expressed genes. / Um dos objetivos atuais da biologia molecular é medir e avaliar os perfis de expressão gênica em diferentes tipos de tecidos biológicos, para entender os mecanismos de transformação molecular sob determinadas condições. Tecnologias de sequenciamento de Nova Geração (NGS) promovem o sequenciamento de DNA em plataformas capazes de gerar informações sobre milhões de pares de bases em uma única etapa. Porém essas tecnologias ainda apresentam custo elevado, dificultando a obtenção de elevado número de repetições de dados amostrais. Assim, torna-se necessária a descoberta e o aprimoramento de metodologias estatísticas eficientes para a otimização das análises de dados gerados em plataformas de sequenciamento de genomas. O objetivo geral desse trabalho consistiu em avaliar o efeito do número de repetições na identificação de genes diferencialmente expressos, em experimentos de RNA-Seq, contribuindo para o esclarecimento de pesquisadores que venham a auxiliar nas análises de dados em experimentos de RNA-Seq. De forma específica, avaliamos empiricamente o efeito do número de repetições na análise estatística da expressão gênica em experimentos de RNA-Seq. Para a realização das análises foi utilizado um conjunto de dados definido em Li et al. (2008), o qual comparou células cancerígenas tratadas e não tratadas. Naquele estudo havia quatro repetições biológicas para o grupo controle (células não tratadas) e três repetições biológicas para grupo de tratamento (células que receberam o tratamento). Os dados foram analisados utilizando o pacote DESeq do Programa computacional R. Um total de 2566 genes foram considerados diferencialmente expressos (DE) quando avaliamos o conjunto de dados original completo. Quando analisamos três repetições do controle e do tratamento, nós encontramos, em média, 2153 genes DE. A partir do momento em que apenas duas repetições para ambos os tratamentos foram utilizadas, foram identificadas, em média, 1241 genes DE. A grande alteração no número de genes DE foi observada quando repetições não foram utilizadas. Nesse caso identificamos em torno de 44 genes diferencialmente expressos. De acordo com os resultados gerados nas análises, foi possível verificar que o número de repetições é um fator essencial para se obter um número significativo de genes diferencialmente expressos.

No description available.

The in vitro cell culture models of human pluripotent stem cells (hPSC)-derived cardiomyocytes (CMs) have gained a predominant value in the field of drug discovery and is considered an attractive tool for cardiovascular disease modellings. However, despite several reports of different protocols for the hPSC-differentiation into CMs, the development of an efficient, controlled and reproducible 3D differentiation remains challenging. The main aim of this research study was to understand the changes in the gene expression as an impact of spatial orientation ofhPSC-derived CMs in 2D(two-dimensional) and 3D(three-dimensional) culture conditions and to identify the topologically important Hub and Hub-Bottleneck proteins using centrality measures to gain new knowledge for standardizing the pre-clinical models for the regeneration of CMs. The above-mentioned aim was achieved through an extensive bioinformatic analysis on the list of differentially expressed genes (DEGs) identified from RNA-sequencing (RNA-Seq). Functional annotation analysis of the DEGs from both 2D and 3D was performed using Cytoscape plug-in ClueGO. Followed by the topological analysis of the protein-protein interaction network (PPIN) using two centrality parameters; Degree and Betweeness in Cytoscape plug-in CenTiScaPe. The results obtained revealed that compared to 2D, DEGs in 3D are primarily associated with cell signalling suggesting the interaction between cells as an impact of the 3D microenvironment and topological analysis revealed 32 and 39 proteins as Hub and Hub-Bottleneck proteins, respectively in 3D indicating the possibility of utilizing those identified genes and their corresponding proteins as cardiac disease biomarkers in future by further research.

The thesis is focused on the medium dynamics simulation in the environmental scanning electron microscope. Specifically, it researches (examines) the conical aperture location effect in the differential pumped chamber and the width of the pumping channel in this chamber. The theoretical part deals with the environmental scanning microscope generally and other tools used in this thesis, e.g. ANSYS Fluen software, fluid turbulence, medium free path of molecules and electrons scattering. In the practical part, the work is focused on data processing from the ANSYS Fluent program and on their evaluation.