Cancer development is driven by somatic genome alterations, ranging from single point mutations to larger structural variants (SV) affecting kilobases to megabases of one or more chromosomes. Studies of somatic rearrangement have previously been limited by a paucity of whole genome sequencing data, and a lack of methods for comprehensive structural classification and downstream analysis. The ICGC project on the Pan-Cancer Analysis of Whole Genomes provides an unprecedented opportunity to analyse somatic SVs at base-pair resolution in more than 2500 samples from 30 common cancer types. In this thesis, I build on a recently developed SV classification pipeline to present a census of rearrangement across the pan-cancer cohort, including chromoplexy, replicative two-jumps, and templated insertions connecting as many as eight distant loci. By identifying the precise structure of individual breakpoint junctions and separating out complex clusters, the classification scheme empowers detailed exploration of all simple SV properties and signatures. After illustrating the various SV classes and their frequency across cancer types and samples, Chapter 2 focuses on structural properties including event size and breakpoint homology. Then, in Chapter 3, I consider the SV distribution across the genome, and show patterns of association with various genome properties. Upon examination of rearrangement hotspot loci, I describe tissue-specific fragile site deletion patterns, and a variety of SV profiles around known cancer genes, including recurrent templated insertion cycles affecting TERT and RB1. Turning to co-occurring alteration patterns, Chapter 4 introduces the Hierarchical Dirichlet Process as a non-parametric Bayesian model of mutational signatures. After developing methods for consensus signature extraction, I detour to the domain of single nucleotide variants to test the HDP method on real and simulated data, and to illustrate its utility for simultaneous signature discovery and matching. Finally, I return to the PCAWG SV dataset, and extract SV signatures delineated by structural class, size, and replication timing. In Chapter 5, I move on to the complex SV clusters (largely set aside throughout Chapters 2—4) , and develop an improved breakpoint clustering method to subdivide the complex rearrangement landscape. I propose a raft of summary metrics for groups of five or more breakpoint junctions, and explore their utility for preliminary classification of chromothripsis and other complex phenomena. This comprehensive study of somatic genome rearrangement provides detailed insight into SV patterns and properties across event classes, genome regions, samples, and cancer types. To extrapolate from the progress made in this thesis, Chapter 6 suggests future strategies for addressing unanswered questions about complex SV mechanisms, annotation of functional consequences, and selection analysis to discover novel drivers of the cancer phenotype.

Massively parallel high throughput sequencers are transforming the scientific research by reducing the cost and time necessary to sequence entire genomes. The goal of this project is to produce preliminary genome assemblies of calliphorid flies using Life Technologies’ Ion Torrent sequencing and Illumina’s MiSeq sequencing. I located, assembled, and annotated a novel mitochondrial genome for one such fly, the little studied Chrysomya pacifica that is central to one hypothesis about blow fly evolution. With sequencing data from Chrysomya megacephala, its forensically relevant sister species, much insight can be gained by alignments, sequence and protein analysis, and many more tools within the CLC Genomics Workbench software program. I present these analyses here of these recently diverged species.

<p>Humans have altered natural landscape since the agricultural revolution, but it has been most destructive since human globalization and rampant industrialization in the last two centuries. These activities deteriorate and fragments natural habitat of many wild species that creates small isolated populations that lose genetic diversity over time. Loss of genetic diversity reduces the adaptive capacity of a population to respond to future environmental change and increases their extinction risks. Implementing strategies for wildlife conservation is a challenge primarily because of our lack of understanding of the biology of many wild species, the risks they are currently facing, and their evolutionary histories. With the advent of genomic and computational techniques, it is now possible to address these concerns. In my research, I used genomics to study the evolutionary history of the Montezuma Quail (<i>Cyrtonyx montezumae</i>) and created monitoring tools that can be readily applied by wildlife managers for its conservation. Montezuma Quail is a small gamebird found mostly in Mexico with peripheral populations existing in Arizona, New Mexico, and Texas. Montezuma Quail are going through species wide decline in the United States and are listed as vulnerable in the state of Texas due to their small population sizes and geographic isolation from rest of the range. My results show that Texas quail are genetically distinct and significantly less diverse than Arizona quail. Analysis of whole genome sequences from multiple individuals show that due to small population sizes and isolation, Texas quail are significantly more inbred and genetic drift is the major contributor for loss of genetic diversity we see today. Inbreeding is negatively impacting Texas quail as they carry more deleterious alleles within their genome that reduce fitness of the individuals. Demographic models predict that both Arizona and Texas populations were formed via founding bottlenecks around 20,000 years ago. Texas populations have maintained small population sizes since its split from the ancestral populations and are less efficient in purging new deleterious mutations that arise post-bottleneck. The inferences from my research not only carries direct implications for Montezuma Quail conservationists, but also illustrate the power of evolutionary genomics in implementing targeted management strategies for any species that face existential threats in today’s waning world. </p>

Endocytosis is an essential cellular process consisting of the internalization of extracellular cargo and its transport towards different intracellular destinations. Multiple endocytic routes are tailored for the internalization and trafficking of different types of cargo and multiple endocytic organelles provide specialized biochemical environments where different molecular events take place. Membrane receptors and cargo molecules are internalized by both Clathrin-dependent and –independent endocytosis into early endosomes. From here two main endocytic routes are followed: 1) the recycling route, mainly followed by membrane receptor and other molecules like Transferrin, brings the cargo back to the plasma membrane and 2) the degradative route, followed by molecules like Epidermal Growth Factor (EGF) and Lipoprotein particles (LDL), leads the cargo to degradation into late endosomes/lysosomes. In addition to the basic function of intracellular cargo transport, the endocytic system fulfils many other cellular and developmental functions such as transmission of proliferative and survival signals and defence against pathogens. In order for cells to properly perform their various and numerous functions in organs and tissues, the activity of the endocytic system needs to be coordinated between cells and, within individual cells, integrated with other cellular functions. Even though molecules orchestrating the endocytic sorting and transport of different types of cargo have long been investigated, our understanding of the molecular machinery underlying endocytosis and its coordination into the cellular systems remains fragmentary. The work presented in this thesis aimed at understanding how this high-order regulation and integration is achieved. This requires not only a comprehensive analysis of molecular constituents of the endocytic system but also an understanding of the general design principles underlying its function. To this end, in collaboration with several members of the Zerial group and with the HT-Technology Development Studio (TDS) at MPI-CBG, I developed a new strategy to accurately profile the activity of human genes with respect to Transferrin (Tfn) and Epidermal Growth Factor (EGF) endocytosis by combining genome-wide RNAi with several siRNA/esiRNA per gene, automated high-resolution confocal microscopy, quantitative multi-parametric image analysis and high-performance computing. This provided a rich and complex genomic dataset that was subsequently subjected to analysis with a combination of tools such as a multi-parametric correlation of oligo profiles, phenotypic clustering and pathways analysis, and a Bayesian network reconstruction of key endocytic features. Altogether, the genomic endeavour and the subsequent analyses provided a number of important results: first, they revealed a much higher extent of off-target effects from RNAi and provided novel tools to infer the specific effects of genes loss of function; second, they identified a large number of novel molecules exerting a regulatory role on the endocytic system, including uncharacterized genes and genes implicated in human diseases; third, they uncovered the regulatory activity of signalling pathways such as Wnt, Integrin, TGF-β, and Notch, and found new genes regulating the sorting of cargo to a specialized subset of early endosomes that function as intracellular signalling platforms; and fourth, a systems analysis by Bayesian networks revealed that the cell specifically regulates the number, size, concentration of cargo and intracellular position of endosomes, thus uncovering novel properties of the endocytic system. In conclusion, the work presented here not only provided a dataset extremely rich of information whose potential has just begun to be uncovered but also shows how genomic datasets can be used to reveal design principles governing the functioning of biological processes.

<p>  </p> <p>Aging is characterized by changes in transcriptional outputs that correlate with physiological changes observed as we age, including decreased function, and increased cell death. Importantly, many of these changes are conserved across tissues and organisms . Because one of the molecular hallmarks of aging is epigenetic dysregulation, we are interested in understanding how age-associated changes in chromatin contribute to the aging transcriptome. To accomplish this, we use the <em>Drosophila </em>visual system as a model for aging, with a particular focus on photoreceptor neurons. </p> <p>To perform cell-type specific genomic studies in <em>Drosophila, </em>we previously developed a nuclei immuno-enrichment method that was compatible with RNA-seq. However, due to low nuclei yields, this protocol was not amenable to chromatin-based studies, such as ChIP-seq and ATAC-seq. In Chapter 1, we developed an improved approach to isolate Drosophila melanogaster nuclei tagged with a GFPKASH protein that increased yields without compromising efficiency. We further demonstrate that this protocol is compatible with several chromatin profiling techniques, such as Assay of Transposable-Accessible Chromatin (ATAC)-seq, Chromatin Immunoprecipitation (ChIP-seq), and CUT&Tag. </p> <p>Chromatin accessibility is enriched for transcription factors. Thus, in Chapter 2, we profiled accessible chromatin in aging photoreceptors and integrated this data with RNA-seq to identify transcription factors that showed differential activity in aging Drosophila photoreceptors. Surprisingly, we found that 57 transcription factors had differential binding activity during aging, including two circadian regulators, Clock and Cycle, that showed sustained increased activity during aging. When we disrupted the Clock:Cycle complex by expressing a dominant negative version of Clock (ClkDN) in adult photoreceptors, we observed changes in expression of 15–20% of genes including key components of the phototransduction machinery and many eye-specific transcription factors. Using ATAC-seq, we showed that expression of ClkDN in photoreceptors leads to changes in activity of 37 transcription factors and causes a progressive decrease in global levels of chromatin accessibility in photoreceptors. Supporting a key role for Clock-dependent transcription in the eye, expression of ClkDN in photoreceptors also induced light-dependent retinal degeneration and increased oxidative stress, independent of light exposure. Together, our data suggests that the circadian regulators Clock and Cycle act as neuroprotective factors in the aging eye by directing gene regulatory networks that maintain expression of the phototransduction machinery and counteract oxidative stress.</p> <p>Previous work in the Weake lab found that long, highly expressed genes were more susceptible to be downregulated with age. DNA:RNA hybrids are co-transcriptional structures that form when the nascent RNA hybridizes with the template strand, resulting in a displaced non-template ssDNA. Importantly, accumulation of R-loops is associated with transcriptional inhibition and genomic instability, both hallmarks of aging. In Chapter 3, I characterized R-loop in maintaining proper transcriptional outputs and regulating visual function during aging. Bulk assays to measure R-loop levels revealed a significant increase in nuclear R-loops with age. Further, genome-wide mapping of R-loops revealed that transcribed genes accumulated R-loops over gene bodies during aging, which correlated with decreased expression of long and highly expressed genes. Importantly, while photoreceptor-specific down-regulation of Top3β, a DNA/RNA topoisomerase associated with R-loop resolution, lead to decreased visual function, over-expression of Top3β or nuclear-localized RNase H1, which resolves R-loops, enhanced positive light response during aging. </p> <p>Together, these studies underscore the importance of understanding how age-related changes in genomic processes, such as circadian transcription and maintenance of R-loops, contribute to physiological changes observed during aging. </p>

<p>Specialized metabolites are chemical tools produced by organisms to aid in their interaction with the surrounding environment. These diverse compounds can often function as metabolic weapons (<em>e.g.</em> antibiotics), structural components (<em>e.g.</em> lignins), or even attractants (<em>e.g.</em> flavonoids). Because of their frequent utilization in niche environments, specialized metabolite production is often lineage- or even species-specific. Therefore, knowledge between specialized metabolic systems is often nontransferable, which poses a major obstacle in the characterization of these bioactive and commercially relevant compounds. Beyond resolving the chemical composition of a specialized metabolite, the identification of responsible pathway genes and the evolutionary processes responsible for their formation is an arduous task. These gaps in knowledge are further widened by the lack of genomic resources available for specialized metabolite producing species. In this work, we present the genome assemblies of two organisms, each with unique specialized metabolic pathways: the Chinese medicinal plant <em>Lithospermum erythrorhizon </em>and the toxic golden alga <em>Prymnesium parvum. </em>Leveraging the predicted proteome of <em>L. erythrorhizon</em>, we investigated the evolutionary history of specialized metabolic genes responsible for the production of shikonin, a 1,4-naphthoquinone specialized metabolite. We identified a retrotransposition-mediated duplication event responsible for the creation of the core shikonin biosynthesis gene, <em>PGT</em>. In addition, we performed a global coexpression network analysis to identify regulatory and enzymatic gene candidates involved in the shikonin biosynthesis pathway. We also built phylogenetic trees of known and candidate shikonin genes to reveal patterns of lineage-specific gene duplication and retroduplication. Like plants, unicellular algae are known for their production of diverse, often toxic, specialized metabolites. However, these species are often enigmatic. For example, previous studies have documented large phenotypic variation in both toxin chemotypes and levels among different strains of <em>P. parvum</em>. To investigate the genetic basis of this variation, we generated near chromosome level assemblies of two <em>P. parvum </em>strains and performed a broad genome survey of thirteen additional strains. As a result, we identified a commonly studied reference strain, UTEX 2797, as a hybrid with two distinct subgenomes. We also provide evidence of significant variation in haploid genome size across the species. Collectively, these studies supply genetic resources for the future study of these organisms, as well as provide insight into the evolution of their specialized metabolic pathways.</p>

Mobile genetic elements represent a large portion of the genome in many species. Posing a danger to the integrity of genetic information, silencing and structural machinery has evolved to suppress the mobility of foreign and transposable elements within the genome. Condensin proteins – which regulate chromosome structure to promote chromosome segregation – have been demonstrated to function in repetitive gene regulation and transposon silencing in several species. In model system Caenorhabditis elegans, microarray analysis studies have implicated Condensin II subunit HCP-6 in the silencing of multiple loci, including DNA transposon MIRAGE. To address the hypothesis that HCP-6 has a direct function in transcriptional gene silencing of the MIRAGE transposon, we queried MIRAGE expression and chromatin profiles in wild-type and hcp-6 mutant animals. Our evidence confirms that HCP-6 does indeed function during silencing of MIRAGE. However, we found no significant indication that HCP-6 binds to MIRAGE, nor that HCP-6 mediates MIRAGE enrichment of H3K9me3, the repressive heterochromatin mark observed at regions undergoing transcriptional silencing. We suggest that the silencing of MIRAGE, a newly evolved transposon and the only tested mobile element considerably derepressed upon loss of HCP-6, is managed by HCP-6 indirectly.

Interactions between 3´ untranslated regions (UTRs) and RNA-binding proteins (RBPs) play critical roles in post-transcriptional gene regulation. Metazoan genomes encode hundreds of RBPs and thousands of 3’ UTRs have been experimentally identified, yet the spectrum of interactions between 3´UTRs and RBPs remains largely unknown. Several methods are available to map these interactions, including protein-centered methods such as RBP immunoprecipitation (RIP) and cross-link immunoprecipitation (CLIP), yeast three-hybrid assays and RNAcompete. However, there is a paucity of RNA-centered approaches for assaying an RNA element of interest against multiple RBPs in a parallel, scalable manner. Here, I present a strategy for delineating protein-RNA interaction networks using a gene centered approach. This approach includes annotating RBPs and identifying physical interactions between an RNA of interest and these RBPs using the Protein-RNA Interaction Mapping Assay (PRIMA). Few RBPs have been experimentally determined in most eukaryotic organisms. Therefore I show that existing RBP annotations can be supplemented using computational predictions of RNA binding domains (RBD) from protein sequences. A single RNA of interest can be tested using PRIMA against a library of RBPs constructed from these annotations. PRIMA utilizes the green fluorescent protein (GFP) in yeast as a reporter. PRIMA is based on reconstitution of the interaction between the 5´ and 3´ ends of an mRNA, which increases mRNA stability and enhances translation. PRIMA recapitulates known and uncovers new interactions involving RBPs from human, Caenorhabditis elegans and bacteriophage with short RNA fragments and full-length 3´UTRs. The development of RBP prey libraries will enable the testing of 3´UTRs against the hundreds of RBPs, which is essential to gain broad insights into post-transcriptional gene regulation at a systems level.

Widely effective treatment for alcohol use disorder is not yet available, because the exact biological mechanisms that underlie this disorder are not completely understood. One way to gain a better understanding of these mechanisms is to examine the genetic frameworks that contribute to the risk for developing this disorder. This dissertation examines genetic association data in combination with gene expression networks in the brain to identify functional groups of genes associated with alcohol consumption and dependence. The first study took advantage of the behavioral complexity of human samples, and experimental capabilities provided by mouse models, by co-analyzing gene expression networks in the mesolimbocortical system of acute alcohol-treated mice and human genetic alcohol dependence association data. This study successfully identified ethanol-responsive gene expression networks with overrepresentation of genes suggestively associated with alcohol dependence in an independent human sample, indicating that gene expression networks in mouse models are informative for identifying mechanistic networks relevant to the risk for developing dependence. The second study aimed to identify quantitative trait loci for voluntary alcohol drinking behaviors under an intermittent ethanol access paradigm, in the genetically complex Diversity Outbred mice. After determining high heritability for alcohol consumption and dependence amongst the progenitor strains, we identified several specific genetic loci associated with these traits. One locus replicated results from a human association study of alcohol consumption, and provided insight to the potentially contributing genes. Finally, we identified alcohol consumption-correlated gene expression networks in the prefrontal cortex of these mice. We also mapped quantitative trait loci for network expression levels, some of which overlapped with the behavioral loci, indicating that the functions represented by these modules mediate the relationship between the genotypes in that region and drinking behaviors. Overall, our studies revealed neuroplastic and ubiquitin-related genes pathways involved in alcohol consumption in mice and humans, and that likely contribute to the risk for developing dependence.

Our understanding of microbial evolution is largely dependent on available genomic data of diverse organisms. Yet, genome-sequencing efforts have mostly ignored the diverse uncultivable majority in favor of cultivable and sociologically relevant organisms. In this thesis, I have applied and developed cultivation independent methods to explore microbial diversity and obtain genomic data in an unbiased manner. The obtained genomes were then used to study the evolution of mitochondria, Rickettsiales and Haloarchaea. Metagenomic binning of oceanic samples recovered draft genomes for thirteen novel Alphaproteobacteria-related lineages. Phylogenomics analyses utilizing the improved taxon sample suggested that mitochondria are not related to Rickettsiales but rather evolved from a proteobacterial lineage closely related to all sampled alphaproteobacteria. Single-cell genomics and metagenomics of lake and oceanic samples, respectively, identified previously unobserved Rickettsiales-related lineages. They branched early relative to characterized Rickettsiales and encoded flagellar genes, a feature once thought absent in this order. Flagella are most likely an ancestral feature, and were independently lost during Rickettsiales diversification. In addition, preliminary analyses suggest that ATP/ADP translocase, the marker for energy parasitism, was acquired after the acquisition of type IV secretion systems during the emergence of the Rickettsiales. Further exploration of the oceanic samples yielded the first draft genomes of Marine Group IV archaea, the closest known relatives of the Haloarchaea. The halophilic and generally aerobic Haloarchaea are thought to have evolved from an anaerobic methanogenic ancestor. The MG-IV genomes allowed us to study this enigmatic evolutionary transition. Preliminary ancestral reconstruction analyses suggest a gradual loss of methanogenesis and adaptation to an aerobic lifestyle, respectively. The thesis further presents a new amplicon sequencing method that captures near full-length 16S and 23S rRNA genes of environmental prokaryotes. The method exploits PacBio's long read technology and the frequent proximity of these genes in prokaryotic genomes. Compared to traditional partial 16S amplicon sequencing, our method classifies environmental lineages that are distantly related to reference taxa more confidently. In conclusion, this thesis provides new insights into the origins of mitochondria, Rickettsiales and Haloarchaea and illustrates the power of cultivation independent methods with respect to the study of microbial evolution.