The integrity of the genome is critical to organisms and it is affected by many factors. Radiation, for example, poses a serious threat to genome stability of human beings. While physical monitors for radiation hazard are present, the biological consequences of long term exposure to radiation are not well understood. With the opportunity as part of the International Caenorhabditis elegans Experiment-1 flight project, several approaches using C. elegans were taken to measure mutational changes that occurred during the spaceflight. Among these methods, the eT1 balancer system was demonstrated to be well-suited as an integrating biological dosimeter for spaceflight. The dog-1 gene in C. elegans is required to prevent mutations at poly-G/poly-C tracts, and previous work has described that in the absence of DOG-1, small deletions initiate within these tracts, most likely as a consequence of improperly repaired replication blocks. The eT1 balancer system was adapted to investigate the broad mutational spectrum of dog-1 mutants. Using this system, I was able to determine a forward mutation rate of approximately 1 x 10-3, 10 fold higher than spontaneous. Both small deletions as reported previously and unreported large chromosome rearrangements were observed, and most of mutations analyzed are associated with G/C tracts. Thus, I propose that following dog-1-induced replication blocks, repair leads to a wide range of mutational events and chromosomal instabilities, similar to those seen in human cancers. The existence of the G/C tracts in C. elegans creates a fortuitous but perplexing problem. They are hotspots for genome instability and need enzymatic protection. In the genome of C. elegans, approximately 400 G/C tracts exist and are distributed along every chromosome in a non-random pattern. G/C tracts are also over-represented in another Caenorhabditis species, C. briggsae. However, the positions and distribution differ from those in C. elegans. Furthermore, in C. elegans, analysis of SAGE data showed that the position of the G/C tracts correlated with the level of gene expression. Although being a threat to genome stability, the genomic distribution of G/C tracts in C. elegans and their effect on regional transcription levels suggest a role for G/C tracts in chromatin structure.

The highly developed and specialized anatomical and physiological characteristics observed for eukaryotes in general and mammals in particular are underwritten by an elaborate and intricate process of genome regulation. This precise control of the location, timing and amplitude of gene expression is achieved by a variety of genetic and epigenetic tools and mechanisms. While several of these regulatory mechanisms have been extensively studied, our understanding of the complex and diverse associations between various epigenetic marks and genetic elements with genome regulatory systems has remained incomplete. However, the recent profound improvements in sequencing technologies have significantly improved the depth and breadth to which their functions and relationships can be understood. The objective of this thesis has been to apply bioinformatics, computational and statistical tools to analyze and interpret various recent high throughput datasets from a combination of Next generation sequencing and Chromatin immune precipitation (ChIP-seq) experiments. These datasets have been analyzed to further our understanding of the dynamics of gene regulation in humans, particularly as it relates to repetitive DNA, cis-regulation and DNA methylation. The thesis thus resides at the intersection of three major areas; transposable elements, cis-regulatory elements and epigenetics. It explores how those three aspects of regulation relate with gene expression and the functional implications of those interactions. From this analysis, the thesis provides new insights into; 1) the relationship between the transposable element environment of human genes and their expression, 2) the role of mammalian-wide interspersed repeats (MIRs) in the function of human enhancers and enhancement of tissue-specic functions, 3) the existence and function of composite cis-regulatory elements and 4) the dynamics and relationship between human gene-body DNA methylation and gene expression.

No description available.

Natural compounds have been largely excluded from characterization via high-throughput profiling strategies due to their limited abundance. Herein, I describe the modification of high-throughput yeast chemical genomic (CG) interaction profiling to permit identifying the modes of action of natural compounds. The previous assay proceeded by evaluating the genome-wide yeast deletion collection for drug-hypersensitivity in a volume of 0.7mL. Compound consumption was minimized with the adapted approach by reducing the assay volume 70% through simplifying the complexity of the yeast deletion pool screened. By recreating each yeast mutant in a drug-hypersensitive background, I created a novel resource that increases compound efficiency and further diminishes compound use. Evaluating a series of characterized compounds analyzed previously by the traditional CG approach validated the adaptations incorporated did not negatively affect the quality of data yielded. Ultimately, this modified strategy will be used to screen thousands of natural compounds contained within the RIKEN NPDepo library.

In the quest to understand cell behavior and cure genetic diseases such as cancer, the fundamental approach being taken is undergoing a gradual change. It is becoming more acceptable to view these diseases as an engineering problem, and systems engineering approaches are being deployed to tackle genetic diseases. In this light, we believe that logic synthesis techniques can play a very important role. Several techniques from the field of logic synthesis can be adapted to assist in the arguably huge effort of modeling cell behavior, inferring biological networks, and controlling genetic diseases. Genes interact with other genes in a Gene Regulatory Network (GRN) and can be modeled as a Boolean Network (BN) or equivalently as a Finite State Machine (FSM). As the expression of genes deter- mine cell behavior, important problems include (i) inferring the GRN from observed gene expression data from biological measurements, and (ii) using the inferred GRN to explain how genetic diseases occur and determine the ”best” therapy towards treatment of disease. We report results on the application of logic synthesis techniques that we have developed to address both these problems. In the first technique, we present Boolean Satisfiability (SAT) based approaches to infer the predictor (logical support) of each gene that regulates melanoma, using gene expression data from patients who are suffering from the disease. From the output of such a tool, biologists can construct targeted experiments to understand the logic functions that regulate a particular target gene. Our second technique builds upon the first, in which we use a logic synthesis technique; implemented using SAT, to determine gene regulating functions for predictors and gene expression data. This technique determines a BN (or family of BNs) to describe the GRN and is validated on a synthetic network and the p53 network. The first two techniques assume binary valued gene expression data. In the third technique, we utilize continuous (analog) expression data, and present an algorithm to infer and rank predictors using modified Zhegalkin polynomials. We demonstrate our method to rank predictors for genes in the mutated mammalian and melanoma networks. The final technique assumes that the GRN is known, and uses weighted partial Max-SAT (WPMS) towards cancer therapy. In this technique, the GRN is assumed to be known. Cancer is modeled using a stuck-at fault model, and ATPG techniques are used to characterize genes leading to cancer and select drugs to treat cancer. To steer the GRN state towards a desirable healthy state, the optimal selection of drugs is formulated using WPMS. Our techniques can be used to find a set of drugs with the least side-effects, and is demonstrated in the context of growth factor pathways for colon cancer.

<p>In this thesis, we have firstly cloned and expressed the domains that harbours the putative catalytic GC domain in these receptor molecules and demonstrate that these molecules can convert GTP to cGMP in vitro. Secondly, we show that exogenous application of both Phytosulfokine and Brassinosteroid increase changes of intracellular cGMP levels in Arabidopsis mesophyll protoplast demonstrating that these molecules have GC activity in vivo and therefore provide a link as second messenger between the hormones and down-stream responses. In order to elucidate a relationship between the kinase and GC domains of the PSK receptor, we have used the AtPSKR1 receptor as a model and show that it has Serine/Threonine kinase activity using the Ser/Thr peptide 1 as a substrate. In addition, we show that the receptor`s ability to phosphorylate a substrate is affected by the product (cGMP) of its co-domain (GC) and that the receptor autophosphorylates on serine residues and this step was also observed to be affected by cGMP. When Arabidopsis plants are treated with a cell permeable analogue of cGMP, we note that this can affect changes in the phosphoproteome in Arabidopsis and conclude therefore that the cGMP plays a role in kinase-dependent downstream signalling. The obtained results suggest that the receptor molecules investigated here belong to a novel class of GCs that contains both a cytosolic kinase and GC domains, and thus have a domain organisation that is not dissimilar to that of atrial natriuretic peptide receptors NPR1 and NPR2. The findings also strongly suggest that cGMP has a role as a second messenger in both Brassinosteroid and Phytosulfokine signalling. We speculate that other proteins with similar domain organisations may also have dual catalytic activities and that a significant number of GCs, both in plants and animals, remain to be discovered and characterised.</p>

Medulloblastoma is the most common malignant pediatric brain tumour. Although survival rates have improved in recent years, long-term survivors exhibit a significantly diminished quality of life complicated by neurological, endocrine, intellectual, and social sequelae as a result of conventional therapies. In order to improve the current outlook for patients with medulloblastoma, rational, targeted therapies that are more efficient and less toxic are required. Despite insight gained from the study of hereditary tumour syndromes and candidate gene approaches, the molecular basis of medulloblastoma remains poorly defined, with more than half of all cases remaining unaccounted for at the genetic level. The intent of my PhD research program was to use high-resolution genomics in an attempt to gain an improved understanding of the medulloblastoma genome and potentially uncover novel genes and pathways driving its pathogenesis. By applying a combination of single nucleotide polymorphism (SNP) arrays, exon arrays, and microRNA arrays to a large cohort of primary medulloblastoma samples, we have identified novel oncogenes and tumour suppressors, implicated deregulation of the histone code as an important event in the pathogenesis of medulloblastoma, and refined the definition of medulloblastoma subgroups. This thesis demonstrates the extent of heterogeneity that exists in the medulloblastoma genome, showing that relatively few genomic aberrations are common when studying medulloblastoma as a single disease. In spite of this heterogeneity, we have identified novel candidate genes and processes that may serve as potential targets for future therapies. Importantly, we have established an improved method of classifying medulloblastomas into distinct molecular variants, showing that certain genomic changes are enriched and occasionally restricted to a specific subgroup. Finally, in addition to genomic differences, we have confirmed that medulloblastoma subgroups differ in their demographics and clinical behavior, and propose that medulloblastoma subgroup affiliation should become an integral component of patient stratification in the future.

Medulloblastoma is the most common malignant pediatric brain tumour. Although survival rates have improved in recent years, long-term survivors exhibit a significantly diminished quality of life complicated by neurological, endocrine, intellectual, and social sequelae as a result of conventional therapies. In order to improve the current outlook for patients with medulloblastoma, rational, targeted therapies that are more efficient and less toxic are required. Despite insight gained from the study of hereditary tumour syndromes and candidate gene approaches, the molecular basis of medulloblastoma remains poorly defined, with more than half of all cases remaining unaccounted for at the genetic level. The intent of my PhD research program was to use high-resolution genomics in an attempt to gain an improved understanding of the medulloblastoma genome and potentially uncover novel genes and pathways driving its pathogenesis. By applying a combination of single nucleotide polymorphism (SNP) arrays, exon arrays, and microRNA arrays to a large cohort of primary medulloblastoma samples, we have identified novel oncogenes and tumour suppressors, implicated deregulation of the histone code as an important event in the pathogenesis of medulloblastoma, and refined the definition of medulloblastoma subgroups. This thesis demonstrates the extent of heterogeneity that exists in the medulloblastoma genome, showing that relatively few genomic aberrations are common when studying medulloblastoma as a single disease. In spite of this heterogeneity, we have identified novel candidate genes and processes that may serve as potential targets for future therapies. Importantly, we have established an improved method of classifying medulloblastomas into distinct molecular variants, showing that certain genomic changes are enriched and occasionally restricted to a specific subgroup. Finally, in addition to genomic differences, we have confirmed that medulloblastoma subgroups differ in their demographics and clinical behavior, and propose that medulloblastoma subgroup affiliation should become an integral component of patient stratification in the future.

The long-term success of transplantation is limited by the need for immunosuppression; thus, tolerance induction is an important therapeutic goal. A 16-day treatment with rapamycin in mice led to indefinite graft survival of fully mismatched cardiac allografts, whereas untreated hearts were rejected after 8-10 days. Specific tolerance was confirmed through subsequent skin grafts and in vitro lymphocyte assays that showed recipient mice remained immunocompetent towards 3rd party antigens but were impaired in responding to donor antigens. Mechanisms that account for this tolerant state were then investigated. Splenic CD8+CD44+ memory T-cells were reduced in tolerant mice but had increased frequencies of the CD62LLO population. CD4+CD25+Foxp3+ regulatory T-cells were increased in tolerant mice. Through multiplex PCR, 4 regulatory T-cell related genes were found up-regulated and 2 proinflammatory genes were down-regulated in accepted hearts. This expression pattern may serve as a putative biomarker of tolerance in patients undergoing transplantation.

The long-term success of transplantation is limited by the need for immunosuppression; thus, tolerance induction is an important therapeutic goal. A 16-day treatment with rapamycin in mice led to indefinite graft survival of fully mismatched cardiac allografts, whereas untreated hearts were rejected after 8-10 days. Specific tolerance was confirmed through subsequent skin grafts and in vitro lymphocyte assays that showed recipient mice remained immunocompetent towards 3rd party antigens but were impaired in responding to donor antigens. Mechanisms that account for this tolerant state were then investigated. Splenic CD8+CD44+ memory T-cells were reduced in tolerant mice but had increased frequencies of the CD62LLO population. CD4+CD25+Foxp3+ regulatory T-cells were increased in tolerant mice. Through multiplex PCR, 4 regulatory T-cell related genes were found up-regulated and 2 proinflammatory genes were down-regulated in accepted hearts. This expression pattern may serve as a putative biomarker of tolerance in patients undergoing transplantation.