DNA sequence information is constantly threatened by damage. In the clinic, intentional DNA damage is often used to treat cancer. Cisplatin, a first-line chemotherapy used to treat millions of patients, functions specifically by generating physical links within DNA strands, blocking DNA replication, and killing dividing cells. To maintain genome integrity, organisms have evolved the capacity to repair, respond, or otherwise resist change to the DNA sequence through a network of genetically encoded DNA damage tolerance pathways. In chapter 1, I present advances in experimental design and current progress for a systems genetics approach, using Saccharomyces cerevisiae, to reveal relationships between cisplatin tolerance pathways. Additionally, recent efforts to sequence thousands of cancer genomes have revealed recurrent genetic changes that cause overexpression of specific cisplatin tolerance genes. In chapter 2, I present a submitted manuscript that models overexpression of an essential cisplatin tolerance gene. This study uses a systems genetics approach to reveal the genetic pathways that are essential for tolerating this perturbation, which ultimately led to mechanistic insights for this gene. Convenient genome engineering in Saccharomyces has made this organism an ideal model to develop systems genetics concepts and approaches. In chapter 3, I present a published manuscript that demonstrates a new approach to disrupting genes by making site-specific nonsense mutations. Importantly, this approach does not require cytotoxic double-strand DNA breaks and is applicable to many model organisms for disrupting almost any gene, which may advance systems genetics into new model organisms. Systems genetics provides a framework for determining how DNA damage tolerance pathways act together to maintain cellular fitness and genome integrity. Such insights may one day help clinicians predict which cancers will respond to treatment, potentially sparing patients from unnecessary chemotherapy.

Cells die when they are starved of thymidine, one of the four DNA nucleotides. Since the discovery of this killing phenomenon, termed thymineless death (TLD), researchers have been trying to understand why. The goal of the work presented here is to use systems level approaches to shed light on this process. Because DNA synthesis is the only cellular process that requires thymidine, it is logical that the focus has been mainly on DNA stability and damage. My work expands the focus to new frontiers: acetate metabolism, the cytoplasm and the inner membrane. I generated thymidine auxotrophs in two genetic backgrounds by inactivating the thymidylate synthase enzyme, thyA. These mutants need supplementation with exogenous thymidine in order to survive. I used these strains in three experimental approaches to explore the mechanisms of TLD. Fitness profiling of a transposon insertion library in a thyA- strain, long-term laboratory evolution during thymidine-limitation, and RNA sequencing of TLD-sensitive and TLD-resistant strains identified genes in previously known processes as well as genes in novel processes. These approaches allowed me to gather rich data sets that identified many contributing genes. 52 genes showed consistent effects across approaches. My work confirms that ROS is a key contributor to killing during thymidine starvation and reveals that putrescine biosynthesis enzymes, an acetate overflow kinase, and the proton-transporting ATP synthase are novel players in TLD. I suggest that these three novel players contribute through their shared role in modulating cytoplasmic pH and propose a model in which DNA damage, ROS accumulation, and cytoplasmic acidification converge on the killing process during thymidine starvation. My findings expand the sites of critical action during TLD from the DNA to the cell’s inner and outer membranes and the cytoplasm. Theories on active vs. passive and specific vs. general bacterial death pathways will be discussed at the end.

Copies of author's previously published articles inserted. / Includes bibliographies. / iii, 277, [81] leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / The aim of this research is to investigate the phylogeny of isolates of the intestinal protozoan parasite Giardia intestinalis using molecular systematic techniques. Most of the isolates used in this study are propagated by the infection of suckling mice. Isolates are characterised allozymically and their genetic relationships are inferred using clustering methods. Seven lineages of isolates are identified, five comprising animal-derived G. intestinalis, and two comprising human-and animal-derived G. intestinalis. / Thesis (Ph.D.)--University of Adelaide, Dept. of Microbiology and Immunology, 1997?

Tissues are heterogeneous communities of cells that work together to achieve a higher-order function. Large-scale single cell RNA-sequencing (scRNA-seq) offers an unprecedented opportunity to systematically map the transcriptional programs underlying this diversity. However, extracting biological signal from noisy, high-dimensional scRNA-seq data requires carefully designed, statistically robust methodology that makes appropriate assumptions both for the data and for the biological question of interest. This thesis explores computational approaches to finding biological signal in scRNA-seq datasets. Chapter 2 focuses on preprocessing and cell-centric approaches to downstream analysis that have become a mainstay of analytical pipelines for scRNA-seq, and includes dissections of lineage diversity in high grade glioma and in the largest neural stem cell niche in the adult mouse brain. Notably, the former study suggests that heterogeneity in high grade glioma arises from at least two distinct biological processes: aberrant neural development and mesenchymal transformation. Chapter 3 presents a flexible approach for de novo discovery of gene expression programs without an a priori structure across cells, revealing subtle properties of a spatially sampled high grade glioma that would not have been apparent with previous approaches. Chapter 4 leverages our prior work and a unique tissue resource to build a unified reference map of human T cell functional states across tissues and ages. We discover and validate a novel pan-T cell activation marker and a previously undescribed kinetic intermediate in CD4+ T cell activation. Finally, ongoing work defines key programs of gene expression in tissue-associated T cells in infants and adults and predicts their candidate regulators.

Meiotic recombination is a fundamental genetic process in all sexually reproducing eukaryotes, ultimately responsible for the generation of new combinations of alleles upon which natural selection can act. It begins with the formation of programmed double stranded breaks along the genome, and ends with their repair as non-crossover or crossover recombination events. The localization of such events along the genome has important evolutionary consequences for genome structure, base composition, patterns of genetic diversity, linkage disequilibrium and introgression, along the genome, as well as in the evolution of post-zygotic hybrid sterility and speciation. Understanding how meiotic recombination events are localized is thus crucial to the proper interpretation of observed genetic variation, and to the field of population genetics as a whole. However, little is known about how most species localize recombination events. While some species localize meiotic recombination events fairly evenly along the genome (e.g., Caenorhabditis elegans or Drosophila), most species studied to date, including all yeasts, plants and vertebrates, localize the vast majority of meiotic recombination events to narrow intervals of the genome known as recombination hotspots. Within such species, there appear to be at least two general mechanisms underlying the localization of hotspots. First, in many species, including baker’s yeast, canids, birds, and plants, the vast majority of hotspots are found in close proximity with promoter-like features of the genome, such as transcriptional start sites and CpG-islands. Recombination landscapes in these species tend to be highly conserved between closely related species. Second, in mice, primates and cattle, the vast majority of hotspots are found away from promoter-like features of the genome, and at sites bound by the PRDM9 protein, which has a rapidly evolving DNA-binding specificity. Concordantly, the recombination landscapes in these species tends to be rapidly evolving. The aim of Chapter 2 of this dissertation is to characterize the distribution of mechanisms across vertebrates indirectly, by leveraging what is known about their genetic and molecular underpinnings. In particular, I consider what is known about the molecular mechanisms and evolutionary consequences of using PRDM9 to localize recombination events, and attempt to infer which vertebrate species are or are not likely to be using PRDM9 in an analogous manner. I find that PRDM9 has been lost repeatedly within vertebrates, and, moreover, that many species carry partial PRDM9 orthologs lacking one or more feature believed to be important for its role in recombination. In Chapter 3, I demonstrate that swordtail fish, which have such a partial PRDM9 ortholog, do not use PRDM9 to localize recombination events. Instead, they use promoter-like features of the genome, similar to species lacking PRDM9 altogether. This work suggests that only species carrying complete PRDM9 orthologs are likely to use them to localize recombination events, and that upon the partial or complete loss of PRDM9, species typically default to the use of promoter-like features. Beyond more immediately practical insight, understanding the phylogenetic distribution of mechanisms by which meiotic recombination events are localized along the genome will shed light on why different species employ different mechanisms. The repeated losses of PRDM9-directed recombination across vertebrates suggests that selective pressures are not always strong enough to justify the evolutionary maintenance of PRDM9. Notably, theory suggests that PRDM9’s DNA-binding specificity has to be continually evolving in order for it to localize recombination events to hotspots. This is a consequence of gene conversion acting to remove PRDM9 binding sites from the population over time. Models have been proposed in which selection favors younger PRDM9 alleles because their binding sites have experienced less erosion due to gene conversion. Nonetheless, it has remained unclear how the loss of PRDM9 binding sites might cause a reduction in fitness, principally because it has remained unclear what the evolutionary benefit of having hotspots is more generally. Recently, however, a number of studies investigating the role of PRDM9 in mediating hybrid sterility in certain crosses of musculus subspecies have implicated the erosion of its binding sites in this process. In particular, the lineage specific erosion of PRDM9 binding sites causes, in the F1 generation, the PRDM9 alleles from each parental lineage to bind primarily to the non-parental genetic background, where its binding sites have not yet been eroded. These studies suggest that there is a benefit to the symmetric binding of PRDM9 across homologous chromosomes, and that fitness is reduced as a consequence of asymmetry in PRDM9 binding. In Chapter 4 of this dissertation I develop a population genetics based model of the co-evolution of PRDM9 and its binding sites taking into consideration these recent findings. In particular, I model competition between PRDM9 binding sites and define fitness as a function of PRDM9 binding symmetry. This model demonstrates that PRDM9 binding symmetry will decrease over time in randomly mating populations, and that selection for symmetric binding is sufficient to drive the rapid turnover of PRDM9 alleles. Importantly, the requirement for symmetry in this model shapes the recombination landscape by favoring highly skewed binding distributions. This model thus provides theoretical support for the hypothesis that a requirement for symmetry might underlie the evolutionary advantage of recombination hotspots.

Despite decades of effort, the mechanistic underpinnings of many cancers remain unsolved It has increasingly become appreciated that cancers can be more readily classified by their transcriptional identities rather than by genomics alone. A fuller understanding of the mechanistic connections between the aberrant genomics leading to the transcriptional dysregulation of tumors is key to both improving our knowledge of cancer biology as well as developing more precise and effective therapeutics. This thesis explores the development and application of a network based multi-omic master regulator framework designed to elucidate these pathways. In Chapter 2 we apply this analysis across 20 tumor types from the Cancer Genome Atlas and in doing so identify 407 key master regulators responsible for canalizing a high percentage of the driver genetics present across these samples. Further evaluation of these key regulators revealed a highly modular structure, indicating that the regulators work in coordinated groups to implement a variety of key cancer hallmarks. Genetic and pharmacological validation assays confirmed the predicted interactions and biological phenotypes. Chapter 3 focuses on the application of this analytical framework specifically on gastroesophageal tumors. Using a more fine-grained approach we find 15 distinct subtypes across a cohort of these heterogenous tumors. These subtypes align well with previously identified features of these cancers but also reveal novel genomic associations and key master regulators that can serve as potential avenues for therapeutic treatment.

Diffuse Midline Glioma (DMG) are universally fatal, primarily pediatric malignancies affecting the midline structures (i.e., pons, thalamus, and spinal cord) of the central nervous system. Despite decades of clinical trials, no drugs have emerged as effective against this disease, and treatment remains limited to palliative radiation therapy. Primary treatment challenges include: A) Well-stablished, yet non-actionable, genetic alterations; B) significant intratumoral heterogeneity, and C) blood-brain barrier (BBB) drug permeability. Here, we address the former two challenges by leveraging network-based methodologies to dissect the heterogeneity of DMG tumors and to discover Master Regulators (MR) proteins representing pharmacologically accessible, mechanistic determinants of molecularly distinct DMG cell states. We reverse engineered the first DMG gene regulatory network from 122 publicly available DMG RNA-seq profiles with ARACNe and inferred sample-specific MR protein activity with VIPER based on the differential expression of their targets. Nine of the top 25 most active MRs (i.e., FOXM1, CENPF, TOP2A, ASF1B, E2F2, TIMELESS, MYBL2, CENPK, TRIP13) comprise a well-characterized MR block (MRB2), frequently activated across aggressive tumors, and found to be enriched in DMG patient MR signatures (Fisher’s Exact Test p = 3.96x10-16). A pooled CRISPR/Cas9-mediated knockout (KO) screen across three DMG patient cell lines targeting 1,433 genes identified a set of 73 essential genes that were enriched in the MR signature of 80% of patient samples (GSEA p = 0.000034). FOXM1 emerged as a highly essential MR, significantly activated across virtually all patients. We then generated drug-induced differential protein activity from RNA-seq profiles following perturbation with 372 oncology drugs in two DMG cell lines that together recapitulate DMG patient MR and used this to identify drugs that invert patient MR activity profiles using the NYS/CA Department of Health approved OncoTreat algorithm OncoTreat predicted sensitivity to HDAC, MEK, CDK, PI3K, and tyrosine kinase inhibitors in subsets of patients, overlapping with published DMG drug screens. Importantly, 80% of OncoTreat-predicted drugs (p < 10-5) from three DMG patient tumor biopsies showed in vitro sensitivity in cultured tumor cells from the respective patients, with overall 68% accuracy among 223 drugs evaluated by both OncoTreat and in vitro drug screen (Fisher’s Exact Test p = 0.0449). Given known resistance in DMG to single-agent therapy, we further interrogated single-cell DMG regulatory networks generated by ARACNe with gene expression signatures from 3,039 tumor cells previously published across six patients using VIPER to infer single-cell regulatory protein activity. Unsupervised clustering of cells by protein activity defined 7 patient-independent cell states with distinct MR profiles reflecting known glial lineage markers (OPC-like-S1, OPC-like-S2, OC-like-S1, OC-like-S2, Cycling, AC-like, and AC/OPC-like). We identified drugs that invert the MR activity profiles of the individual cell states by using OncoTarget (inhibitors of individual MRs) or OncoTreat using the drug-induced differential protein activity we previously generated. Predicted drugs were distinct across the previously defined cell states with bulk RNA-seq recapitulating predictions seen in the more prevalent OPC-like stated, but failing to recapitulate the MRs and drug predictions for the smaller AC-like stated. We selected five drugs targeting the OPC/cycling-like cells (Trametinib, Dinaciclib, Avapritinib, Mocetinostat, and Etoposide), and four drugs targeting the AC-like cells (Ruxolitinib, Venetoclax, Napabucasin, Larotrectinib) for further validation as these states comprised most tumor cells across patients. We then generated single-cell RNA-seq for 95,687 cells after 5 days of treatment with either vehicle control (n = 4) or candidate drug (n = 2-3/drug) in subcutaneous SU-DIPG-XVII patient cell line-derived mouse models. We show this model recapitulates DMG cell states seen in patients, and confirm reduction in tumor growth and significant depletion of either OPC/cycling-like cells or AC-like cells in line with our drug predictions for 8/9 candidate drugs (Chi-square p<0.01). We further treated a syngeneic (DIPG4423) orthotopic DMG model with each drug and demonstrate significant differences in survival with Avapritinib, Dinaciclib, and Trametinib. Notably, the combination of drugs targeting OPC/cycling-like and AC-like cells (i.e. Trametinib+Ruxolitinib, Dinaciclib+Ruxolitinib, Avapritinib+Venetoclax, etc.) showed significantly lower tumor volumes after 2 weeks of treatment as compared to vehicles or each drug alone, and significant survival differences for some of the combinations. This work provides a precision medicine platform to nominate much-needed novel drug combinations addressing DMG tumor heterogeneity for further study to improve outcomes in this devastating disease.

Bridging the gap between genetic variants and functional relevance is a principal goal of human genetics. Despite centuries of research, interpreting the biological mechanisms that link variants to phenotypes is a continuous challenge. This goal applies to rare and common variants, although the specific challenges vary depending on the variant’s frequency and effect on gene dosage or protein structure. Deciphering these variants’ modes of action is crucial for a more holistic understanding of genome regulation. This dissertation advances interpretation of rare and common variants across the annotation spectrum, by utilizing functional data derived from population scale RNA-sequencing studies. Thus, three main research questions are addressed: (1) How do rare variants affect gene expression, and can these subtle changes be robustly detected? (2) How do common variants that influence pre-mRNA splicing influence protein structure and human traits? (3) Can joint effects between common splice-regulatory and rare loss-of-function variants be detected through the lens of purifying selection? All three chapters build on knowledge acquired through large-scale transcriptomics and open access data. Chapter 1 evaluates the utility of allele specific expression to prioritize variants with functional effects. Chapter 2 involves quantifying splicing using the common Percent Spliced In (PSI) metric, and performing quantitative trait locus (QTL) mapping. Chapter 3 builds on the known phenomenon of modified penetrance, where common regulatory variants reduce the pathogenicity of rare coding variants. Ultimately, these three studies will contribute to our knowledge of genome regulation, which will be crucial in a future of personalized medicine.

Vita. / Digitized by Kansas Correctional Industries

This thesis describes the development of an systems biology method to study transcriptional programs that are activated during early and late phases of cell-fusion mediated reprogramming, as well as an implementation of systems-level analysis using reverse-engineered regulatory networks to study CNS disorders like Alcohol Addiction, and neurodegenerative disorders like Alzheimer's Disease (AD), and Parkinson's Disease (PD). The results will show an unprecedented view into the mechanisms underlying complex processes and diseases, and will demonstrate the predictive power of these methodologies that extended far beyond their original contexts.