In Fulfilment for the requirements for the degree of Doctor of Philosophy University of the Witwatersrand Johannesburg, South Africa Thesis Defended 23 September 2015 / The phylum nematoda has a variety of functional groups. The parasitic functional group comprise various nematodes some which are parasitic to insects and are known as entomopathogenic nematodes (EPNs). The two most studied genera of EPNs are Steinernema and Heterorhabditis. These EPNs are associated symbiotically with the two enterobacteria genera; Xenorhabdus and Photorhabdus, respectively. The explanation of EPNs has been recently expanded to include the genus Oscheius which have been found to be associated with Serratia species. The bacteria synthesize a range of insecticidal and antimicrobial metabolites which may be useful in various ways as agricultural pest control and medical disease control. An insight into the genome of the nematode-bacterium duo will provide us with information about the symbiosis between the two and parasitism against insect pests. Here in I discuss the isolation and identification of a South African EPN and its symbiotic bacterium. In addition I highlight the production of indole derivatives which are common metabolites produced by entomopathogenic bacteria. The thesis eventually describes and discusses the methods for whole genome sequencing of both the isolated nematode and its symbiotic bacterium, and the genomic content indicate similar genes with other known EPN genera and protein-coding genes involved in symbiosis and parasitism. / MT2016

Thesis advisor: Hugh P. Cam / Chromatin is the site of numerous structural features that contribute to the regulation of the genome. Although numerous posttranslational modifications to the histone proteins that make up chromatin have been identified, it remains unclear whether and to what extent these modifications might regulate transposons and other repetitive sequences. One such modification is methylation of histone H3 lysine 4 (H3K4me), which is catalyzed by Set1 and its associated complex Set1C/COMPASS. Although H3K4me is associated with actively transcribed regions in euchromatin, an emerging body of evidence suggests that Set1-mediated transcriptional control is often repressive. This thesis work describes expanded functions for Set1C/COMPASS as a regulatory module with roles throughout the genome. We identify novel locus-dependent repressive functions for Set1 at repetitive genomic regions. Interestingly, Set1 has multiple repressive modes that are dependent and independent of H3K4me. Additionally, we show that Set1 controls the nuclear organization of Tf2 retrotransposons by antagonizing H3K4 acetylation. We describe how the roles of Set1 in the nuclear organization and transcriptional repression of Tf2 cooperate to restrict Tf2 transposition. Finally, we identify an H3K4-dependent role in countering the reduced dosage of histone H3 genes to help maintain genome stability and silencing of Tf2s and pericentromeric heterochromatin. Our study considerably expands the regulatory repertoire of an important histone modifier and highlights the multifaceted function by a highly conserved chromatin-modifying complex with diverse roles in genome control. / Thesis (PhD) — Boston College, 2015. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Thesis advisor: Gabor T. Marth / Improvements in molecular and computational technologies have driven and will continue to drive advances in our understanding of genetic variation and its relationship to phenotypic diversity. Over the last three years, several new DNA sequencing technologies have been developed that greatly improve upon the cost and throughput of the capillary DNA sequencing technologies that were used to sequence the first human genome. The economy of these so‐called “next‐generation” technologies has enabled researchers to conduct genome‐wide studies in genetic variation that were previously intractable or too expensive. However, because the new technologies employ novel molecular techniques, the resulting sequence data is quite different from the capillary sequences to which the genomics field is accustomed. Moreover, the vast amounts of sequence data that these technologies produce present novel statistical and computational challenges in order to make even the simplest observations. The focus of my dissertation has been the development of novel computational and analytical methods that facilitate genome‐wide studies in genetic variation with traditional capillary sequencers and with new sequencing technologies. I present a novel method that produces more accurate error estimates for sequence data from one of these next‐generation sequencing technologies. I also present two studies that illustrate the utility of two such technologies for genome‐wide polymorphism discovery studies in Drosophila melanogaster and Caenorhabditis elegans. These studies accurately estimate the degree of genetic diversity in the fruitfly and nematode, respectively. I later describe how new sequencing approaches can be used to accelerate the mapping of causal genetic mutations in forward geetic screens. Lastly, I remark on where I believe these technologies will lead future studies in human genetic variation and describe their relevance to several of my future research interests. / Thesis (PhD) — Boston College, 2008. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Genetic analyses such as linkage and genome wide association studies (GWAS) have been extremely successful at identifying genomic regions that harbour genetic variants contributing to complex disorders. Over 90% of disease-associated variants from GWAS fall within non-coding regions (Maurano et al., 2012). However, pinpointing the causal variants has proven a major bottleneck to genetic research. To address this I have developed SuRFR, an R package for the ranked prioritisation of candidate causal variants by predicted function. SuRFR produces rank orderings of variants based upon functional genomic annotations, including DNase hypersensitivity signal, chromatin state, minor allele frequency, and conservation. The ranks for each annotation are combined into a final prioritisation rank using a weighting system that has been parametrised and tested through ten-fold cross-validation. SuRFR has been tested extensively upon a combination of synthetic and real datasets and has been shown to perform with high sensitivity and specificity. These analyses have provided insight into the extent to which different classes of functional annotation are most useful for the identification of known regulatory variants: the most important factor for identifying a true variant across all classes of regulatory variants is position relative to genes. I have also shown that SuRFR performs at least as well as its nearest competitors whilst benefiting from the advantages that come from being part of the R environment. I have applied SuRFR to several genomics projects, particularly the study of psychiatric illness, including genome sequencing of a large Scottish family with bipolar disorder. This has resulted in the prioritisation of such variants for future study.

Thesis (Ph.D.)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / DNA sequencing techniques have evolved to the point where one can sequence millions of bases per minute, while our capacity to use this information has been left behind. One particularly notorious example is in the area of gene regulatory networks. A molecular study of gene regulation proceeds one protein at a time, requiring bench scientists months of work purifying transcription factors and performing DNA footprinting studies. Massive scale options like ChIP-Seq and microarrays are a step up, but still require considerable resources in terms of manpower and materials. While computational biologists have developed methods to predict protein function from sequence, gene locations from sequence, and even metabolic networks from sequence, the space of regulatory network reconstruction from sequence remains virtually untouched. Part of the reason comes from the fact that the components of a regulatory interaction, such as transcription factors and binding sites, are difficult to detect. The other, more prominent reason, is that there exists no "recognition code" to determine which transcription factors will bind which sites. I've created a pipeline to reconstruct regulatory networks starting from an unannotated complete genomic sequence for a prokaryotic organism. The pipeline predicts necessary information, such as gene locations and transcription factor sequences, using custom tools and third party software. The core step is to determine the likelihood of interaction between a TF and a binding site using a black box style recognition code developed by applying machine learning methods to databases of prokaryotic regulatory interactions. I show how one can use this pipeline to reconstruct the virtually unknown regulatory network of Bacillus anthracis. / 2031-01-01

No description available.

With the rapid development of DNA synthesis technologies, synthetic biology has made tremendous progress in the past 15 years, in particular for synthetic genomics. Synthetic genomics is a nascent field of synthetic biology, which aims to design new biological systems/organisms to satisfy human needs. Conventional synthetic biology focuses on the redesign, construction and modeling of biological parts, pathways or genomes that do not exist in nature, while synthetic genomics encompasses technologies that allow the generation of chemically synthesized larger parts of genomes or whole genomes, with simultaneous redesign of an organism's genetic material. Synthetic genomics is painting a blueprint for a new era of biology and holds great potential for a multitude of applications, such as pharmaceuticals, biofuels and rapid generation of vaccines against emerging diseases. Chapter One gives an introduction of the current state of the art and challenges of synthetic genomics and the objectives of this study. Chapter Two demonstrates the design and construction strategy of two megabase-long synthetic yeast chromosomes, SynII and SynVII. Chapter Three describes the full characterization of SynII and SynVII. Chapter Four introduces the SCRaMbLE (Synthetic Chromosome Rearrangement and Modification by LoxPsym-mediated Evolution) system and its application in SynII and SynVII. Taken together, this work demonstrates the utility of synthetic yeast for understanding biological systems and its potential for industrial applications.

Thesis (Ph. D.)--University of Hong Kong, 2007. / Title proper from title frame. Also available in printed format.

Thesis (M.Sc.)--York University, 2003. Graduate Programme in Biology. / Typescript. Includes bibliographical references (leaves 122-134). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pMQ86279

Thesis (M.Sc.)--York University, 2004. Graduate Programme in Biology. / Typescript. Includes bibliographical references (leaves 46-56). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url%5Fver=Z39.88-2004&res%5Fdat=xri:pqdiss&rft%5Fval%5Ffmt=info:ofi/fmt:kev:mtx:dissertation&rft%5Fdat=xri:pqdiss:MQ99354