The genetic basis of the different cancer phenotypes has been a continuous and accelerating subject of investigation. Data accumulated thanks to recently introduced genome-wide scanning technologies have revealed that human diversity and diseases susceptibility is also greatly influenced by structural alterations in the human genome, such as DNA copy number variants (CNVs) and copy number alterations (CNAs), which influence gene expression in both healthy and pathological cells. Our research aims to investigate the influence of structural alterations on gene expression in cancer cells using SNP microarray data. Specifically, we focus on analyzing DNA copy number alternations (CNAs), which can significantly influence gene expression in cancer cells. Several cancer-predisposing mutations affect genes that are responsible for maintaining the integrity of the chromosomes during cell division, which can result in translocations, gains or losses of large parts of chromosome. To our knowledge, there have been no publications that link whole-genome copy number alterations in cancer to gene expression variations using the full range of possibilities offered by SNP arrays. The accurate use of SNP arrays in the analysis of cancer has been difficult due to tumour purity, tumour heterogeneity, aneuploidy/polyploidy and complex patterns of CNA and loss-of-heterozygosity (LOH). In our work, we use and further extend a recently developed novel tool for tumour genome profiling called OncoSNP (Yau, Mouradov et al. 2010), in order to resolve some of those problems and accurately estimate copy number alterations (CNA) and loss-of-heterozygosity (LOH) from SNP array data in cancer cell samples. The methods developed in this thesis tackle the problem of cancer genomic investigation by developing and validating an extension (DPS smoothing) of a new method (OncoSNP). This approach is used in the analysis of global expression versus CNA patterns in experimental systems and large clinical datasets. We analyse various cancer SNP and gene expression arrays of increasing complexity and heterogeneity, starting with a dataset of head and neck squamous cell carcinoma (HNSCC) cell lines, followed by leukaemia samples and finally a large breast cancer dataset. The central findings of our research are multifold. In the HNSCC dataset we find that the level of genetic instability is not indicative of the pathological state; i.e. there are premalignant lesions displaying extensive mutations. However some genetic features are typical of certain lesion type; e.g. we consistently observe copy loss in the short arm of chromosome 3 in carcinoma. The pattern of homozygous deletion in the dataset reveals common deletion of cancer related genes, especially CDK4 (pI6). Furthermore we notice a significant positive correlation between the copy number and the expression on a systematic level. In Leukaemia, we do not observe extended uniparental disomy as previously published (Akagi, Shih et al. 2009) and expected. However large alterations (whole arm amplification) are observed in individual patients: copy loss in chromosome 7 (2 patients), copy gain in chromosome 8 (3 patients) as well as common alterations around the centromeres and telomeres. In the breast cancer dataset significantly different level of mutations were observed in the different subtypes in the cohort. Furthermore 499 genes were identified with significant correlation between their gene expression (GE) and underlying genomic alterations (either copy number (CN) or loss-of-heterozygosity (LOH)). Performing hierarchical clustering on the cohort using the 499 correlated genes enabled us to recover the subtypes' separation previously based on gene expression alone.

<p>Quantifying the function of mammalian enhancers at the genome or population scale has been longstanding challenge in the field of gene regulation. Studies of individual enhancers have provided anecdotal evidence on which many foundational assumptions in the field are based. Genome-scale studies have revealed that the number of sites bound by a given transcription factor far outnumber the genes that the factor regulates. In this dissertation we describe a new method, chromatin immune-enriched reporter assays (ChIP-reporters), and use that approach to comprehensively test the enhancer activity of genomic loci bound by the glucocorticoid receptor (GR). Integrative genomics analyses of our ChIP-reporter data revealed an unexpected mechanism of glucocorticoid (GC)-induced gene regulation. In that mechanism, only the minority of GR bound sites acts as GC-inducible enhancers. Many non-GC-inducible GR binding sites interact with GC-induced sites via chromatin looping. These interactions can increase the activity of GC-induced enhancers. Finally, we describe a method that enables the detection and characterization of the functional effects of non-coding genetic variation on enhancer activity at the population scale. Taken together, these studies yield both mechanistic and genetic evidence that provides context that informs the understanding of the effects of multiple enhancer variants on gene expression.</p> / Dissertation

Recent developments in automation and novel experimental techniques have led to the accumulation of vast amounts of biological data and the emergence of numerous databases to store the wealth of information. Consequentially, bioinformatics have drawn considerable attention, accompanied by the development of a plethora of tools for the analysis of biological data. DNA microarrays constitute a prominent example of a high-throughput experimental technique that has required substantial contribution of bioinformatics tools. Following its popularity there is an on-going effort to integrate gene expression with other types of data in a common analytical approach. Pathway based microarray analysis seeks to facilitate microarray data in conjunction with biochemical pathway data and look for a coordinated change in the expression of genes constituting a pathway. However, it has been observed that genes in a pathway may show variable expression, with some appearing activated while others repressed. This thesis aims to add some contribution to pathway based microarray analysis and assist the interpretation of such observations, based on the fact that in all organisms a substantial number of genes take part in more than one biochemical pathway. It explores the hypothesis that the expression of such genes represents a net effect of their contribution to all their constituent pathways, applying statistical and data mining approaches. A heuristic search methodology is proposed to manipulate the pathway contribution of genes to follow underlying trends and interpret microarray results centred on pathway behaviour. The methodology is further refined to account for distinct genes encoding enzymes that catalyse the same reaction, and applied to modules, shorter chains of reactions forming sub-networks within pathways. Results based on various datasets are discussed, showing that the methodology is promising and may assist a biologist to decipher the biochemical state of an organism, in experiments where pathways exhibit variable expression.

One major challenge in synthetic biology is how to design genetic circuits with predictable behaviors in various biological contexts. There are two limitations to addressing this challenge in mammalian cells. First, models that can predict circuit behaviors accurately in bacteria cells cannot be directly translated to mammalian cells. Second, upon interconnection, the behavior of a module, the building block of a circuit, may be different from its behavior in a standalone setting. In this thesis, I present a bottom-up modeling framework that can be used to predict circuit behaviors in transiently transfected mammalian cells (TTMC). The first part of the framework is based on a novel bin-dependent ODE model that can describe the behavior of modules in TTMC accurately. The second part of the framework rests upon a method of modular composition that allows model-based design of circuits. The efficacies of the bin-dependent model and the method of modular composition are validated via experimental data. The effects of retroactivity, a loading effect that arises from modular composition, on circuit behaviors are also investigated.

There are an estimated 350 million people chronically infected with Hepatitis B Virus (HBV), of which approximately 600 000 die each year from HBV complications including cirrhosis and liver cancer. The X protein from HBV (HBx) has been implicated in the progression of chronic HBV to liver cancer and has been reported to manipulate several critical cellular pathways. These include the cell cycle, the tumour suppressor protein p53, protein degradation and signal transduction pathways. The role of these interactions in HBV replication and the viral lifecycle is currently unknown. The lack of animal models and infectable cell lines together with solubility and stability issues related to the HBx protein have made progress difficult. The reliance on approximate cellular and animal models has yielded many discordant studies that have confounded our interpretations of the role of HBx. There have been no novel approaches attempting to express HBx at a quantity and quality sufficient for high resolution X-ray and nuclear magnetic resonance structural determination. Additionally no bioinformatic analyses have been applied to HBx, and thus distinctive features of HBx that may be responsible for these challenges have not been reported. This thesis describes the detailed experimentation to express and purify HBx in a functional, soluble and stable form. The study focussed on Saccharomyces cerevisiae and Semliki Forest Virus (SFV) expression systems, together with the use of a solubility-enhancing Maltose Binding Protein protein tag (MBP). The S. cerevisiae-based pYES2 and YEp and mammalian expression vectors showed production of HBx protein. However HBx that had been expressed using S. cerevisiae and human cells could not be reliably detected in Western blots using antibodies raised against E. coliexpressed HBx. This result was despite the positive visualisation of HBx using the same antibodies and immunofluorescence microscopy. This validated previous reports describing the variable antigenicity of HBx. Furthermore these findings supported the decision to develop eukaryotic-based HBx expression vectors as results suggested structural differences between eukaryote and prokaryote expressed protein. HBx was subsequently detected and purified in a soluble and active form using an MBP tag as well as a SFV expression vector. All of these options provide an excellent point from which further work at optimising HBx expression and structural elucidation can occur. Bioinformatic analysis of HBx suggested the presence of protein disorder and protease sensitive sites within the negative regulatory domain of HBx. Literature descriptions of the molecular promiscuity that protein disorder allows, offers an explanation for the presence of the discordant findings on HBx interactions and functions. It is generally accepted that proteins containing disorder are tightly regulated and thus experimental systems employing overexpression methodologies may encourage cellular toxicity and non-specific interactions through the use of short linear motifs. Evolutionary analysis of HBx sequences revealed that the eight HBV genotypes (A-H) showed concordance regarding synonymous and non-synonymous substitutions at the overlapping and non-overlapping domains of hbx. Substitutions in hbx were most common at positions where a synonymous substitution occurred in the overlapping partner gene. The presence of sites under positive, neutral and negative selection were identified across the length of HBx. The different genotypes showed positive selection indicating selective pressures unique to each, thus offering a contributing explanation for the variable disease severity observed between the subtypes. Overall, this thesis has provided novel methods to express and purify HBx in S. cerevisiae and mammalian cells. These methods, together with an increased understanding of the nature of HBx sequences through bioinformatic analysis, pave the way to conduct both structural studies and biological assays to elucidate the genuine roles of HBx in the HBV lifecycle and its contribution to the progression to liver cancer.

[pt] A família de algoritmos BLAST é a mais utilizada pelos biólogos para a busca de similaridade entre biosseqüências, e por esta razão, melhoras nestes algoritmos, em suas estruturas de dados ou em seus métodos de acesso à memória secundária são muito importantes para o avanço das descobertas biológicas. Nesta dissertação, foi estudada detalhadamente uma versão do programa BLAST, analisando as suas estruturas de dados e os algoritmos que as manipulam. Além disso, foram realizadas medições de desempenho com o intuito de identificar os possíveis gargalos de processamento dentro das fases de execução do BLAST. A partir das informações obtidas, técnicas de compactação de dados foram utilizadas como uma estratégia para redução de acesso à memória secundária com o objetivo de melhorar o desempenho para a execução do BLAST. Finalmente, foi gerada uma versão modificada do BLAST no ambiente Windows, na qual foi alterado diretamente o código do programa. Os resultados obtidos foram comparados com os resultados obtidos na execução do algoritmo original. / [en] The BLAST is the sequence comparison strategy mostly used in computational biology. Therefore, research on data structures, secondary memory access methods and on the algorithm itself, could bring important optimizations and consequently contributions to the area. In this work, we study a NCBI BLAST version by analyzing its data structures and algorithms for data manipulating. In addition, we collect performance data for identifying processing bottleneck in all the BLAST execution phases. Based on this analysis, data compress techniques were applied as a strategy for reducing number of secondary memory access operations. Finally, a modified version of BLAST was implemented in the Microsoft Windows environment, where the program was directly altered. Finally, an analysis was made over using the results of execution of original BLAST against modified BLAST.

Listeria monocytogenes and Campylobacter spp. are bacteria that sometimes can cause severe illness in humans. Both can be found as contaminants in food that has been produced, stored or prepared improperly, which is why it is important to ensure that the handling of food is done correctly. The National Food Agency (Livsmedelsverket) is the Swedish authority responsible for food safety. One important task is to, in collaboration with other authorities, track and prevent food-related disease outbreaks. For this purpose bacterial samples are regularly collected from border control, at food production facilities and retail as well as from suspected food items and drinking water during outbreaks, and epidemiological analyses are employed to determine the type of bacteria present and whether they can be linked to a common source. One part of these epidemiological analyses involve bioinformatic analyses of the bacterial DNA. This includes determination of sequence type and serotype, as well as calculations of similarities between samples. Such analyses require data processing in several different steps which are usually performed by a bioinformatician using different computer programs. Currently the National Food Agency outsources most of these analyses to other authorities and companies, and the purpose of this project was to develop a pipeline that would allow for these analyses to be performed in-house. The result was a pipeline named BacIL - Bacterial Identification and Linkage which has been developed to automatically perform sequence typing, serotyping and SNP-analysis of Listeria monocytogenes as well as sequence typing and SNP-analysis of Campylobacter jejuni, C. coli and C. lari. The result of the SNP-analysisis is used to create clusters which can be used to identify related samples. The pipeline decreases the number of programs that have to be manually started from more than ten to two.

This research is concerned with analyzing a set of viral genomes to elucidate the underlying characteristics and determine the information-theoretic aspects of the genomic signatures. The goal of this study thereof, is tailored to address the following: (i) Reviewing various methods available to deduce the features and characteristics of genomic sequences of organisms in general, and particularly focusing on the genomes pertinent to viruses; (ii) applying the concepts of information-theoretics (entropy principles) to analyze genomic sequences; (iii) envisaging various aspects of biothermodynamic energetics so as to determine the framework and architecture that decide the stability and patterns of the subsequences in a genome; (iv) evaluating the genomic details using spectral-domain techniques; (v) studying fuzzy considerations to ascertain the overlapping details in genomic sequences; (vi) determining the common subsequences among various strains of a virus by logistically regressing the data obtained via entropic, energetics and spectral-domain exercises; (vii) differentiating informational profiles of coding and non-coding regions in a DNA sequence to locate aberrant (cryptic) attributes evolved as a result of mutational changes and (viii) finding the signatures of CDS of genomes of viral strains toward rationally conceiving plausible designs of vaccines. Commensurate with the topics indicated above, necessary simulations are proposed and computational exercises are performed (with MatLabTM R2009b and other software as needed). Extensive data gathered from open-literature are used thereof and, simulation results are verified. Lastly, results are discussed, inferences are made and open-questions are identified for future research. / by Sharmistha P. Chatterjee. / Thesis (Ph.D.)--Florida Atlantic University, 2013. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Ebola viruses cause sever disease in humans and non-human primates. The resulting disease, Ebola virus disease (EVD), can have hemorrhagic manifestations and has mortality rates ranging from 20-90%. There is a strong need for better understanding of the disease as well as improved diagnostics and prognostics. One approach to improving diagnostic and prognostics for severe viral diseases such as EVD is to define how the host response to infection develops and produces indicators of disease and outcome. To create a better means to understand if a patient is likely to survive or succumb to Ebola (EBOV) infection, I have sought to develop an understanding of the host response to EBOV infection in humans from the recent outbreak. I analyzed RNA-Seq samples from the 2013-2016 West Africa outbreak. I identified that the innate immune pathways are in general over activated in EVD and is stronger in patients who succumbed to disease. Furthermore, I developed a set of 10 genes that can perform as a prognostic indicator of disease independent of the viral load. This is the first demonstration that the circulating transcriptional immune response to EBOV infection can be used to predict infection outcome. To work towards a diagnostic platform of disease, I analyzed multiple studies of time-resolved datasets in animal models of disease. I analyzed RNA-Seq and NanoString data coupled with telemetry data in EBOV-challenged macaques. The earliest and strongest changes seen in the pre-symptomatic stage of disease is the up-regulation of many innate immune genes. I used this information to develop a NanoString codeset that can act as a pre-symptomatic indicator of disease that was tested in further animal studies as a diagnostic in pre-symptomatic stages of disease. Together, this work has identified a sets of genes that can work as a diagnostic for pre-symptomatic patients of EBOV and act as a prognostic indicators of disease. In future outbreaks, this type of information will be important to help track primary contacts of infected individuals and first responders, as well as better inform clinical management of patients. This lays the groundwork for similar analysis to be performed on other severe viral diseases such as Lassa Fever and Marburg Fever. / 2019-11-27T00:00:00Z

Elementos transponíveis são elementos genéticos capazes de transpor para diferentes locais em um genoma hospedeiro. Na sua descoberta, considerou-se que tais elementos não apresentavam funções celulares úteis, classificando-os como genes parasitas. Atualmente, além do carácter deletério, reconhece-se que eles contribuam para a evolução dos genomas e, em alguns casos, podem realizar algumas funções celulares. Utilizando recursos de bioinformática, realizamos estudos para verificar a influência de duas famílias de retrotransposons non-LTR (Perere-3 e SR2) no genoma do Schistosoma mansoni. Estudos preliminares indicam que após a divergência entre S. japonicum e S. mansoni, esses elementos tiveram uma grande expansão em seu número de cópias em S. mansoni, sem paralelo em S. japonicum. Análises das regiões intrônicas que contêm inserções de qualquer uma destas duas famílias de retrotransposon em S. mansoni, mostrou que houve aproximadamente 30% de aumento no tamanho dos íntrons e aumento do conteúdo GC, quando comparado com os íntrons ortólogos de S. japonicum. As inserções foram diferencialmente representadas ao longo das estruturas dos genes com a acumulação preferencial nos íntrons localizados nas regiões terminais dos genes. As inserções dos dois elementos de transposição tendem a orientar-se na direção oposta da transcrição dos genes. As inserções de trechos do elemento SR2 enriquecidos em motivos CpG foram observados com maior frequência do que o esperado, sugerindo que estas inserções podem contribuir nas funções de genes. Nas regiões intergênicas, foi possível prever sítios para ligação de fatores de transcrição ao longo das sequências de ambos os retrotransposons. Também foi observado que elementos SR2 tendem a se fixar em regiões que flanqueiam genes codificando proteínas transmembranares, as quais podem estar envolvidas na relação hospedeiro-parasita. Usando dados de transcrição de S. mansoni disponíveis publicamente, foram detectados 94 casos possíveis de exonização de inserções dos retrotransposons, produzindo mudanças do produto proteico. Estes resultados sugerem que os elementos Perere-3 e SR2 podem promover mudanças funcionais e estruturais relevantes nos genes de S. mansoni e pode ter contribuído significativamente para a diferenciação entre S. mansoni e S. japonicum. / Transposable elements are genetic elements capable of transpose to different locations at a host genome. At their discovery, it was considered that such elements had no useful cellular functions, leading to their classification as parasitic genes. Currently, in addition to the deleterious character, it is recognized that they contribute to the evolution of genomes and, in some cases, may perform some cellular functions. Using bioinformatics resources, we have conducted studies to verify the influence of two families of non-LTR retrotransposons (Perere-3 and SR2) in the Schistosoma mansoni genome. Preliminary studies indicate that after the divergence between S. japonicum and S. mansoni, these elements had a great expansion in their copy number in S. mansoni, without parallel expansion in S. japonicum. The analysis of the intron regions containing insertions from either of these two families of transposons in S. mansoni, showed that there was approximately 30% of increase in the intron size and GC content when compared to orthologous introns from S. japonicum. Insertions were differentially represented along the gene structures with preferential accumulation in introns located at the terminal regions of the genes. Insertions of both transpositon elements tended to orientate themselves in the opposite direction of gene transcription. The insertions of SR2 transposon regions enriched in CpG motifs were observed in higher frequency than expected, suggesting that these regions might contributing in the gene functions. In the intergenic regions, it was possible to predict transcription factors binding sites along the sequences of both retrotransposons and also observed that SR2 elements were preferentially fixed at regions flanking genes coding for transmembrane proteins, which may be involved in parasite-host relationship. Using publicly available transcript data from S. mansoni, we detected 94 possible cases of exonization of transposon insertion, producing changes of the protein product. These results suggest that Perere-3 and SR2 insertions may promote relevant functional and structural changes in the S. mansoni genes and may have significantly contributed to the differentiation between S. mansoni and S. japonicum.