<p>This project is an investigation of whether analysing subsets of time series gene expression data can give additional information about putatively co-regulated genes, compared to only using the whole time series. The original gene expression data set was partitioned into subsets and similarity was computed for both the whole timed series and subsets. Pearson correlation was used as similarity measure between gene expression profiles. The results indicate that analysing co-expression in subsets of gene expression data derives true-positive connections, with respect to co-regulation, that are not detected by only using the whole time series data. Unfortunately, with the actual data set, chosen similarity measure and partitioning of the data, randomly generated connections have the same amount of true-positives as the ones derived by the applied analysis. However, it is worth to continue further analysis of the subsets of gene expression data, which is based on the multi-factorial nature of gene regulation. E.g. other similarity measures, data sets and ways of partitioning the data set should be tried.</p>

<p>Recent methods to infer genetic networks are based on identifying gene interactions by similarities in expression profiles. These methods are founded on the assumption that interacting genes share higher similarities in their expression profiles than non-interacting genes. In this dissertation this assumption is validated when using mutual information as a similarity measure. Three algorithms that calculate mutual information between expression data are developed: 1) a basic approach implemented with the histogram technique; 2) an extension of the basic approach that takes into consideration time delay between expression profiles; 3) an extension of the basic approach that takes into consideration that genes are regulated in a complex manner by multiple genes. In our experiments we compare the mutual information distributions for profiles of interacting and non-interacting genes. The results show that interacting genes do not share higher mutual information in their expression profiles than non-interacting genes, thus contradicting the basic assumption that similarity measures need to fulfil. This indicates that mutual information is not appropriate as similarity measure, which contradicts earlier proposals.</p>

Covalent histone modifications such as methylation, acetylation as well as differential incorporation of histone variants are shown to coincide with different chromatin compartments and mark active or repressed genes. Msc1 is one of the seven JmjC Domain Proteins (JDPs) in Fission Yeast. JDPs are known to function in chromatin and some act as histone demethylases. We found that Msc1 is a member of Swr1 Complex which is known to exchange histone H2A variant H2A.z in nucleosomes. We purified H2A.z as a member of Swr1 Complex and its interaction with Swr1 Complex depends on Swr1. We’ve shown that histone H4 Lysine 20 trimethylation (H4 K20 Me3) is lost in h2A.z and msc1 deletion strains and these strains are sensitive to UV. Deletion strain of h2A.z is sensitive to Camptothecin. Histones H3 and H4 are obtained in Msc1 and H2A.z purifications and we’ve shown that histone H4 from these purifications has low level of Lysine 16 acetylation (H4 K16 Ac). Deletion strains of h2A.z, swr1 and msc1 are shown to be sensitive to TSA, a histone deacetylase (HDAC) inhibitor suggesting that H2A.z cooperates with HDACs. TSA treatment of wild type cells cause an increase in H4 K16 Ac and a decrease in H4 K20 Me3. Gene expression profiles of h2A.z, swr1 and msc1 are significantly similar and upregulated genes in deletion strains localize at chromosome ends (a region of 160 kb for each end). The number of stress or meiotic inducible genes is increased in deletion strains suggesting that H2A.z has a role in regulation of inducible genes. We suggest that H2A.z, in cooperation with HDACs, functions in regulation of chromatin accessibility of inducible promoters.

The diplomonads are a diverse group of eukaryotic flagellates found in microaerophilic and anaerobic environments. The most studied diplomonad is the intestinal parasite Giardia intestinalis, which infects a variety of mammals and cause diarrheal disease. Less is known about Spironucleus salmonicida, a parasite of salmonid fish, known to cause systemic infections with high mortality. We created a transfection system for S. salmonicida to study cellular functions and virulence in detail (Paper I). The system was applied to explore the mitochondrion-related organelle (MRO) in S. salmonicida. We showed that S. salmonicida possesses a hydrogenosome (Paper II) with a higher metabolic capacity than the corresponding MRO of Giardia, the mitosome. Evolutionary analysis of key hydrogenosomal proteins showed ancient origin, indicating their presence in the ancestral diplomonad and subsequent loss in Giardia. Annexins are of evolutionary interest since these proteins are found across all kingdoms. Annexin-like proteins are intriguingly expanded into multigene families in Giardia and Spironucleus. The annexins of S. salmonicida were characterized (Paper III) with distinct localizations to various cellular structures, including a putative adhesion structure anterior in the cell. The disease-causing Giardia trophozoites differentiate into infectious cysts, a process essential for transmission and virulence of the parasite. Cysts are often spread via contaminated water and exposed to environmental stressors, such as UV irradiation. We studied the survival and transcriptional response to this stress factor (Paper IV) and results showed the importance of active DNA replication machinery for parasite survival after DNA damage. In addition, we studied transcriptional changes along the trajectory of encystation (Paper V), which revealed a coordinated cascade of gene regulation. This was observed for the entire transcriptome as well as putative regulators. Large transcriptional changes appeared late in the process with the majority of differentially regulated genes encoding hypothetical proteins. We studied the localizations of several of these to gain information of their possible function. To conclude, the diplomonads are complex eukaryotic microbes with cellular processes adjusted to match their life styles. The work in this thesis has provided insight of their adaptations, differences and similarities, but also new interesting leads for future studies of diplomonad biology and virulence.

The evolution of antibiotic resistance is shaped by interactions between genes, the chemical environment, and an antibiotic's mechanism of action. This thesis explores these interactions with experiments, theory, and analysis, seeking a mechanistic understanding of how different interactions between genes and drugs can enhance or constrain the evolution of antibiotic resistance. Chapter 1 investigates the effects of the chemical decay of an antibiotic. Tetracycline resistant and sensitive bacteria were grown competitively in the presence of tetracycline and its decay products. Antibiotic decay did not only remove selection for resistance, but long-lived decay products favored tetracycline sensitivity by inducing costly drug efflux pumps in the resistant strain. Selection against resistance by antibiotic-related compounds may contribute to the coexistence of drug-sensitive and resistant bacteria in nature. Chapter 2 investigates how genetic interactions can favor particular combinations of resistance-conferring mutations. All possible combinations of a set of trimethoprim resistance-conferring mutations in the drug's target gene were constructed and phenotyped. Incompatibilities between mutations arose in a high-order, not pairwise, manner. One mutation was found to induce this ruggedness and create a multi-peaked adaptive landscape. Chapters 1 and 2 observed that non-optimal expression of a drug resistance gene or a drug's target could compromise antibiotic resistance. Chapter 3 broadly characterizes non-optimal gene expression under antibiotic treatment, using a functional genetic screen to identify over one hundred pathways to antibiotic resistance through positive and negative changes in gene expression. Genes with the potential to confer antibiotic resistance were found to often go unused during antibiotic stress. The optimization of gene expression for drug-free growth was found to cause non-optimal expression under drug treatment, creating a situation where regulatory mutations can confer resistance by correcting errors in gene expression. Chapter 4 investigates whether it is beneficial to up-regulate the genes encoding antibiotic targets when they are inhibited. Drug target genes were quantitatively over-expressed, and drug resistance was found to not always increase, but alternatively to remain unchanged or even decrease. These diverse effects were explained by simple models that consider toxicity arising from gene over-expression, and mechanisms of drug action in which drugs induce harmful enzymatic reactions.

RNA interference (RNAi) potently and specifically induces gene knockdown, and its potential for reverse genetics in Caenorhabditis elegans is enormous. However, even in these nematodes, RNAi can be induced more effectively via enhanced RNAi (Eri) mutant backgrounds. With advances in small RNA sequencing, evidence has suggested that the eri pathway plays an endogenous gene regulatory role, which competes with experimentally introduced RNAi triggers for limiting resources. However, the nature, cellular location, and physiological consequences of this small RNA pathways competition remain unclear. To answer these questions, I first fully characterized the genetic phenotypes of all known Eri mutants. I discovered that different components of the eri pathway have subtle differences upon mutation, which affects more than exogenous RNAi. I then attempted to screen for novel enhanced RNAi mutants, guided by hypothetical mechanisms or tissues of expression not associated with known mutants. After these attempts, I fully characterized the genetic mechanisms that account for enhanced RNAi. Surprisingly, I discovered that the nuclear Argonaute nrde-3 and the peri-nuclear P-granule component pgl-1 are necessary and sufficient for an Eri response. Finally, I examined the impact of the competition among microRNA, endogenous siRNA, and exogenous RNAi pathways. I discovered that C. elegans develops slower upon perturbations to its normal flux of small RNA pathways. Insights from these phenotypes and genetic mechanisms shed light on the importance of small RNA biology and offer a novel suite of tools for sensitizing RNAi in broader contexts, especially given the deep evolutionary conservation of most eri-associated genes.

Engineered DNA-binding proteins enable targeted manipulation of the genome. Zinc fingers are the most well characterized DNA-binding domain and for many years research has focused on understanding and manipulating the sequence-specificities of these proteins. Recently, major advances in the ability to engineer zinc finger proteins, as well as the discovery of a new class of DNA-binding domains - transcription activator-like effectors (TALEs), have made it possible to rapidly and reliably engineer proteins targeted to any sequence of interest. With this capability, focus has shifted to exploring the applications of this powerful technology. In this dissertation I explore three important applications of engineered DNA-binding proteins.

The Gram-negative bacterium Francisella tularensis is the causative agent of tularemia and a model intracellular pathogen. It is also considered a potential bioweapon, as F. tularensis is highly infectious and has the potential to cause fatal disease in humans. Many factors required for F. tularensis virulence have been identified, yet we know relatively little regarding how these factors are regulated at the level of transcription. In order to further understand the regulation of virulence factors in F. tularensis, we have systematically determined the genomic regions associated with all of the transcription factors implicated in virulence using chromatin immunoprecipitation coupled with high-throughput DNA sequencing (ChIP-Seq).

The human genome contains tens of thousands of gene loci which code for an even greater number of protein and RNA products. The highly complex temporal and spatial expression of these genes makes possible all the biological processes of life. Altered gene expression by mutation or deregulation is fundamental for the development of many human diseases. The ultimate aim of this thesis was to identify gene expression changes relevant to cancer. The advent of genome-wide expression profiling techniques, such as microarrays, has provided powerful new tools to identify such changes and researchers are now faced with an explosion of gene expression data. Processing, comparing and integrating these data present major challenges. I approached these challenges by developing and assessing novel methods for cross-platform analysis of expression data, scalable subspace clustering, and curation of experimental gene regulation data from the published literature. I found that combining results from different expression platforms increases reliability of coexpression predictions. However, I also observed that global correlation between platforms was generally low, and few gene pairs reached reasonable thresholds for high-confidence coexpression. Therefore, I developed a novel subspace clustering algorithm, able to identify coexpressed genes in experimental subsets of very large gene expression datasets. Biological assessment against several metrics indicates that this algorithm performs well. I also developed a novel meta-analysis method to identify consistently reported genes from differential expression studies when raw data are unavailable. This method was applied to thyroid cancer, producing a ranked list of significantly over-represented genes. Tissue microarray analysis of some of these candidates and others identified a number of promising biomarkers for diagnostic and prognostic classification of thyroid cancer. Finally, I present ORegAnno (www.oreganno.org), a resource for the community-driven curation of experimentally verified regulatory sequences. This resource has proven a great success with ~30,000 sequences entered from over 900 publications by ~50 contributing users. These data, methods and resources contribute to our overall understanding of gene regulation, gene expression, and the changes that occur in cancer. Such an understanding should help identify new cancer mechanisms, potential treatment targets, and have significant diagnostic and prognostic implications.

Adenylyl cyclase (Adcy) is an important early effector of adrenocorticotrophin (ACTH) on the adrenal cortex; however, this enzyme consists of ten isozymes in mammalian cells and the factors governing the expression of different Adcy isozymes have not been well defined. The aim of this study is to investigate the regulation of mouse Adcy4, one of ten isozymes, in Y1 adrenocortical tumor cells and in mutant subclones derived from the Y1 cells. Adcy4 is expressed at a high level in brain but at lower levels in many other tissues including the Y1 cells. Moreover, this isozyme is specifically deficient in Y1 mutants with impaired steroidogenic factor 1 (SF1) activity. These observations support a hypothesis that Adcy4 expression is influenced by both ubiquitously expressed and tissue-specific transcription factors. My sequencing results indicate that mouse Adcy4 is highly homologous to the human and rat counterparts; its gene is located less than 1 kb downstream of Ripk3 and contains 26 exons. Primer extension and in silico analyses suggest that Adcy4 contains a TATA-less promoter and initiates transcription from multiple sites. Luciferase reporter gene assays indicate that Adcy4 promoter activity is mainly stimulated by the proximal GC-rich region but is inhibited by the first intron. This 124 bp GC-rich region is well conserved among several mammalian species and exhibits strong promoter activity in Y1 cells, which is functionally compromised in the Adcy4-deficient mutant. Within this region, three Sp1/Sp3- and one SF1-binding sites have been identified which bind the corresponding proteins Sp1 and Sp3 or SF1 in electrophoretic mobility shift assays (EMSAs). Site-directed mutagenesis reveals that the 5’-most Sp1/Sp3 site enhances Adcy4 promoter activity, whereas the middle Sp1/Sp3 and SF1 sites each repress this activity. In Y1 mutant cells, mutating the SF1 site restores Adcy4 promoter activity and knocking down SF1 with shRNA increases Adcy4 expression. All these data demonstrate that Adcy4 expression is under the control of the ubiquitous factors Sp1 and Sp3 and the tissue-specific factor SF1 and establish that SF1 is a repressor for Adcy4 promoter activity. This study is the first to demonstrate a repressor function for SF1 in certain promoter contexts.