Browsing by Subject "Genetics"

Basement membrane (BM) is a sheet-like extracellular matrix that underlies most tissues and acts as a barrier to invading cells. Many cell types, including immune cells, cells migrating during development and morphogenesis, and metastatic cancer cells utilize F-actin-based structures called invadopodia to breach BM as they leave one tissue to enter another. Despite extensive study and interest in understanding invasion for its clinical importance, the molecular mechanisms regulating invadopodia and BM breach in vivo remain unclear. During uterine-vulval attachment in C. elegans, the specialized uterine anchor cell (AC) uses invadopodia to mediate breach of the underlying BM in order to contact the underlying vulval epithelium. The AC offers several advantages as a model, including experimental, visual, and genetic tractability, the presence of endogenous extracellular environment, and availability of the tissue targeted for invasion. In Chapter 2, I describe development of a novel technique for spatiotemporal-specific knockdown of proteins that will facilitate investigation of proteins, particularly those that are essential or required in other tissues, in the regulation of invadopodia and AC invasion. Using a sensitized genome-wide RNAi screen, classical genetics, and timelapse imaging of invadopodia at the AC-BM interface, Chapter 3 presents two in vivo invadopodia regulators that function by distinct mechanisms. This is the first in vivo evidence that the RhoGTPase CDC-42 regulates invadopodia formation through WSP-1. RabGTPase GDI-1 is a novel regulator of the unique membrane compartment required for invadopodia formation. CDC-42 and GDI-1 both function downstream of an unknown cue secreted by the cells targeted by the AC for invasion, illustrating that extracellular cues can play key roles in mediating cell invasion. The characterization of CDC-42 and GDI-1 as in vivo regulators of invadopodia is an important first step to understanding the mechanisms of this critical cellular process and we expect the AC will be an excellent model for future identification of novel regulators of BM breach.

Centromeres, or sites of chromosomal spindle attachment during mitosis and meiosis, are non-randomly distributed in complex genomes and are largely associated with expansive, near-identical satellite DNA arrays. While the sequence basis of centromere identity remains a subject of considerable debate, one approach is to examine the genomic organization of satellite DNA arrays and their potential function. Current genome assembly and sequence annotation strategies, however, are dependent on robust sequence variation, and, as a result, these regions of near sequence identity remain absent from current genome reference sequences and thus are detached from explorations of centromere biology. This dissertation is designed as a foundational study for centromere genomics, providing the initial steps to characterize those sequences at endogenous centromeres, while further classifying `functional' sequences that directly interact with, or are capable of recruiting proteins involved in, centromere function. These studies build on and take advantage of the limited sequence variation in centromeric satellite DNA, providing the necessary genomic scope to promote biologically meaningful characterization of endogenous centromere sequences in both human and non-human genomes. As a result, this thesis demonstrates possible genomic standards for future studies in the emerging field of satellite biology, which is now positioned to address functional centromere sequence variation across evolutionary time.

One of the most important questions in evolutionary biology is how new genes and new functions arise and evolve. Among the theories addressing this question, gene duplication is one of the most popular. Previous study has shown that two threonine deaminase (TD) gene copies exist in Solanum lycopersicum, and these two copies have very different functions and low sequence similarities. The primary objective of this study was to widen our understanding of this gene duplication and the subsequent evolutionary processes affecting the duplicate copies by first collecting additional TD sequences from related species, building a gene tree, and inferring the point of gene duplication. The evolutionary processes acting on this gene were then analyzed using the program PAML. Results indicate that 1) The TD duplication probably occurred in before the split of the Solanoideae from the Nicotianoidea; and 2) there is strong evidence for positive selection on one of the TD copies after gene duplication, while for the other TD copy, only weak evidence for positive selection was found; and 3) adaptive improvement of the copy with new function probably spanned a period of at least 25 million years.

Nearly all animals live in environments with fluctuations in nutrient availability. The ability to sense and respond to these changes is essential for survival. Nutrition impacts physiology immediately, but can also have long-lasting effects across generations. The nematode Caenorhabditis elegans is particularly well-adapted to thrive in conditions of variable food availability. Here we find that starvation responses in C. elegans are largely independent of the larval stage at which worms experience starvation. Starvation in worms results in shrinkage, delayed growth upon recovery, and ultimately death. In order to adapt to starvation, metabolism is dramatically altered. At a gross level, this can be seen in a reduction of mitochondrial genomes and a more fragmented network of mitochondria.

Insulin-like signaling is a key cell signaling pathway controlling nutrient responses. We interrogate the role of insulin-like signaling in regulation of the acute starvation response. We show that daf-16/FoxO restructures carbohydrate metabolism by driving carbon flux through the glyoxylate shunt and gluconeogenesis and into synthesis of trehalose, a disaccharide of glucose. Trehalose is a well-known stress protectant, capable of preserving membrane organization and protein structure during abiotic stress. Metabolomic, genetic, and pharmacological analyses confirm increased trehalose synthesis and further show that trehalose not only supports survival as a stress protectant, but also serves as a glycolytic input. Further, we provide evidence that metabolic cycling between trehalose and glucose is necessary for this dual function of trehalose. This work demonstrates that daf-16/FoxO promotes starvation resistance by shifting carbon metabolism to drive trehalose synthesis, which in turn supports survival by providing an energy source and acting as a stress protectant.

In addition to acute changes in response to the nutrient environment, effects can persist intergenerationally. Maternal effects of environmental conditions produce intergenerational phenotypic plasticity. Adaptive value of these effects depends on appropriate anticipation of environmental conditions in the next generation, and mismatch between conditions may contribute to disease. However, regulation of intergenerational plasticity is poorly understood. Dietary restriction (DR) delays aging but maternal effects have not been investigated. We demonstrate maternal effects of DR in the roundworm C. elegans. Worms cultured in DR produce fewer but larger progeny. Nutrient availability is assessed in late larvae and young adults, rather than affecting a set point in young larvae, and maternal age independently affects progeny size. Reduced signaling through the insulin-like receptor daf-2/InsR in the maternal soma causes constitutively large progeny, and its effector daf-16/FoxO is required for this effect. nhr-49/Hnf4, pha-4/FoxA, and skn-1/Nrf also regulate progeny-size plasticity. Genetic analysis suggests that insulin-like signaling controls progeny size in part through regulation of nhr-49/Hnf4, and that pha-4/FoxA and skn-1/Nrf function in parallel to insulin-like signaling and nhr-49/Hnf4. Furthermore, progeny of DR worms are buffered from adverse consequences of early-larval starvation, growing faster and producing more off- spring than progeny of worms fed ad libitum. These results suggest a fitness advantage when mothers and their progeny experience nutrient stress, compared to an environmental mismatch where only progeny are stressed. This work reveals maternal provisioning as an organismal response to DR, demonstrates potentially adaptive intergenerational phenotypic plasticity, and identifies conserved pathways mediating these effects.

Increased attention has recently been placed on understanding the natural variation of the malaria parasite Plasmodium vivax across the globe, as in 2020 alone, P. vivax caused an estimated 4.5 million malaria cases and lead to over 600,000 deaths around the world. P. vivax infections in central Africa have been of particular interest, as humans in Sub-Saharan Africa frequently possess a P. vivax resistance allele known as the Duffy-negative phenotype that is believed to prevent infection in these individuals. However, new reports of asymptomatic and symptomatic infections in Duffy-negative individuals in Africa raise the possibility that P. vivax is evolving to evade host resistance.Whole genome sequencing has become more common as a means of understanding the population diversity of P. vivax. However, there is still a scarcity of information about P. vivax in central Africa. In this dissertation, I analyze whole genome sequencing data from a new P. vivax sample collected from the Democratic Republic of the Congo in central Africa. By studying P. vivax from central Africa, we can begin to understand the evolutionary history of the pathogen in this part of the world as it relates to the global context of this pathogen. I also investigate the relationship of P. vivax in the DRC with a potential animal reservoir of a closely related species, P. vivax-like, in non-human primates in this region. Due to the scarcity of P. vivax samples in central Africa, I also investigated methods with which to best make use of whole genome sequencing data, particularly in generating phylogenetic trees. While many studies of P. vivax genetic diversity employ whole genome variation data in order to study evolutionary relationships of P. vivax populations, in this dissertation I make use of the P. vivax apicoplast, a non-photosynthetic plastid organelle genome. The apicoplast genome is five times longer than the mitochondrial genome and does not undergo recombination, making it a valuable locus for studying P. vivax evolutionary history using phylogenetic trees.

Admixture occurs when previously isolated populations come together to form a new population with genetic ancestry from those sources. Admixture is ubiquitous across the tree of life, including humans, and is often associated with migration and exposure to new environments and selective pressures. Admixed populations provide a unique opportunity to study adaptation on short timescales by introducing beneficial alleles at high frequency. However, admixed populations are often excluded from genomic studies due to lack of applicable methodology. Instead of relying on classical methods confounded by the process of admixture itself, we can detect changes in patterns of genetics ancestry that are informative about selection in admixed populations and at the short timescales often relevant for post-admixture selection. However, we lack theoretical expectations and methods to detect and characterize ancestry-based genomic signals indicative of post-admixture selection and adaptation. Common ancestry outlier approaches discard information about the surrounding genomic context and are prone to false positives due to drift and demography. Here, I present three studies which leverage patterns of genetic ancestry to investigate the evolutionary history of admixed populations. First, I develop a suite of ancestry-based summary statistics and computational methods to detect post-admixture adaptation, and demonstrate their application in a case study of human adaptation to malaria. In particular, these summary statistics incorporate patterns of ancestry beyond the site under selection, such as the length of contiguous ancestry tracts surrounding the locus, and are informative about the strength and timing of selection in admixed populations. I observe one of the strongest signals of recent selection in humans at the malaria protective Duffy-null allele, and show that this mode of strong single-locus selection over 20 generations has impacted genome-wide patterns of ancestry. Next, I move beyond summary statistics to develop a deep learning strategy for localizing regions of the genome under selection. This method takes images of chromosomes painted by ancestry as input to avoid the loss of information and bias that can occur when relying on user-defined summary statistics. I demonstrate this approach on simulated admixture scenarios and find that the method successfully localizes variants under selection 95% percent of the time, outperforms the common ancestry outlier approach, and is robust to demographic misspecification. Lastly, I present the first Illyrian genome sequences available from the Iron Age in a study of the ancestry and genetic relationships of five neonates buried in Korčula, Croatia. I find genetic support for classifying these individuals as Illyrian, and show that patterns of ancestry and genetic variation are consistent with their geographic location between Italy and the mainland Balkans. In the combined work presented here, I advance our ability to study the evolutionary history of admixed populations, which has implications for our understanding of phenotypic variation, disease risk, and conservation genetics across many study systems. Further, these methods tailored to the mosaic ancestry of admixed populations is a step towards expanding the diversity of populations, especially humans, who benefit from discoveries and advancement in genomic research.

Although it has been known for many years that B-cyclin/CDK complexes regulate the assembly of the mitotic spindle and entry into mitosis, the full complement of relevant CDK targets has not been identified. It has previously been shown in a variety of model systems that B-type cyclin/CDK complexes, kinesin-5 motors, and the SCFCdc4 ubiquitin ligase are required for the separation of spindle poles and assembly of a bipolar spindle. It has been suggested that in the budding yeast, Saccharomyces cerevisiae, B-type cyclin/CDK (Clb/Cdc28) complexes promote spindle pole separation by inhibiting the degradation of the kinesins-5 Kip1 and Cin8 by the anaphase-promoting complex (APCCdh1). I have determined, however, that the Kip1 and Cin8 proteins are actually present at wild-type levels in yeast in the absence of Clb/Cdc28 kinase activity. Here, I show that Kip1 and Cin8 are in vitro targets of Clb2/Cdc28, and that the mutation of conserved CDK phosphorylation sites on Kip1 inhibits spindle pole separation without affecting the protein's in vivo localization or abundance. Mass spectrometry analysis confirms that two CDK sites in the tail domain of Kip1 are phosphorylated in vivo. In addition, I have determined that Sic1, a Clb/Cdc28-specific inhibitor, is the SCFCdc4 target that inhibits spindle pole separation in cells lacking functional Cdc4. Based on these findings, I propose that Clb/Cdc28 drives spindle pole separation by direct phosphorylation of kinesin-5 motors.

In addition to the positive regulation of kinesin-5 function in spindle assembly, I have also found evidence that suggests CDK phosphorylation of kinesin-5 motors at different sites negatively regulates kinesin-5 activity to prevent premature spindle pole separation. I have also begun to characterize a novel putative role for the kinesins-5 in mitochondrial genome inheritance in S. cerevisiae that may also be regulated by CDK phosphorylation.

In the course of my dissertation research, I encountered problems with several established molecular biology tools used by yeast researchers that I have tried to address. I have constructed a set of 42 plasmid shuttle vectors based on the widely used pRS series for use in S. cerevisiae that can be propagated in the bacterium Escherichia coli. This set of pRSII plasmids includes new shuttle vectors that can be used with histidine and adenine auxotrophic laboratory yeast strains carrying mutations in the genes HIS2 and ADE1, respectively. My new pRSII plasmids also include updated versions of commonly used pRS plasmids from which common restriction sites that occur within their yeast-selectable biosynthetic marker genes have been removed in order to increase the availability of unique restriction sites within their polylinker regions. Hence, my pRSII plasmids are a complete set of integrating, centromere and 2 episomal plasmids with the biosynthetic marker genes ADE2, HIS3, TRP1, LEU2, URA3, HIS2 and ADE1 and a standardized selection of at least 16 unique restriction sites in their polylinkers. Additionally, I have expanded the range of drug selection options that can be used for PCR-mediated homologous replacement using pRS plasmid templates by replacing the G418-resistance kanMX4 cassette of pRS400 with MX4 cassettes encoding resistance to phleomycin, hygromycin B, nourseothricin and bialaphos. Finally, in the process of generating the new plasmids, I have determined several errors in existing publicly available sequences for several commonly used yeast plasmids. Using updated plasmid sequences, I constructed pRS plasmid backbones with a unique restriction site for inserting new markers in order to facilitate future expansion of the pRS/pRSII series.

Basement membranes are a dense, sheet-like form of extracellular matrix that underlie epithelia and endothelia, and surround muscle, fat and Schwann cells. Basement membranes separate tissues and protect them from mechanical stresses. Although traditionally thought of as a static support structure, a growing body of evidence suggests that dynamic basement membrane deposition and modification instruct cell behavior and morphogenetic processes. In this thesis, I discuss how changes to basement membrane affect anchor cell (AC) invasion during C. elegans uterine vulval attachment. During AC invasion, the uterine AC breaches two juxtaposed basement membranes to contact the underlying vulval epithelium. Using live-cell imaging, genetics, molecular biology and electron microscopy I identify three modifications to the BM that affect AC invasion. In Chapter 2, I describe a system for linking juxtaposed basement membranes to stably align or connect adjacent tissues. This adhesion system promotes rapid AC invasion and also regulates a more long-term connection between the uterine tissue and the hypodermal seam cell in the adult worm. Chapter 3 elucidates how the BM component SPARC promotes cell invasion. As SPARC overexpression is correlated with cancer metastasis, this aims to understand how SPARC overexpression promote invasion in a pathological situation. In Chapter 4, I discuss preliminary data showing that the AC actively secretes laminin into the basement membrane targeted for invasion. I outline how future studies could elucidate the mechanism by which AC-derived laminin might promote cell invasion. Finally, Chapter 5 discusses conclusions and future directions for these studies.

The main contribution of this thesis is to examine the utility of kernel regression ap- proaches and variance component models for solving complex problems in statistical genetics and molecular biology. Many of these types of statistical methods have been developed specifically to be applied to solve similar biological problems. For example, kernel regression models have a long history in statistics, applied mathematics, and machine learning. More recently, variance component models have been extensively utilized as tools to broaden understanding of the genetic basis of phenotypic varia- tion. However, because of large combinatorial search spaces and other confounding factors, many of these current methods face enormous computational challenges and often suffer from low statistical power --- particularly when phenotypic variation is driven by complicated underlying genetic architectures (e.g. the presence of epistatic effects involving higher order genetic interactions). This thesis highlights two novel methods which provide innovative solutions to better address the important statis- tical and computational hurdles faced within complex biological data sets. The first is a Bayesian non-parametric statistical framework that allows for efficient variable selection in nonlinear regression which we refer to as "Bayesian approximate kernel regression", or BAKR. The second is a novel algorithm for identifying genetic vari- ants that are involved in epistasis without the need to identify the exact partners with which the variants interact. We refer to this method as the "MArginal ePIstasis Test", or MAPIT. Here, we develop the theory of these two approaches, and demonstrate their power, interpretability, and computational efficiency for analyz- ing complex phenotypes. We also illustrate their ability to facilitate novel biological discoveries in several real data sets, each of them representing a particular class of analyses: genome-wide association studies (GWASs), molecular trait quantitative trait loci (QTL) mapping studies, and cancer biology association studies. Lastly, we will also explore the potential of these approaches in radiogenomics, a brand new subfield of genetics and genomics that focuses on the study of correlations between imaging or network features and genetic variation.

Microbial population growth measurements are widespread in the study of microorganisms, providing insight into areas including genetics, physiology, and engineering. The most common models of microbial population growth data are parametric, and are derived from specific assumptions about the underlying growth process. While useful in cases where these assumptions are valid, these models are inadequate in many cases typically found in microbial growth studies, including presence of significant population death and the presence of multiple growth phases (e.g. diauxie). Here, we explore the use of the Bayesian non-parametric model Gaussian processes on microbial population growth. We first develop a general hypothesis-test using Gaussian process regression and false-discovery rate corrected Bayes factor scores. We then explore a fully Bayesian model with Gaussian process priors that can capture the latent growth processes of many population measurements under a single model. Finally, we develop hierarchical Bayesian model with GP priors in order to capture random effects in microbial population growth data.

Recombination is the process in which genetic material is exchanged between one's homologous chromosome pairs during egg or sperm development (meiosis). Recombination is necessary for proper segregation of chromosomes during meiosis, and also plays a role in purging deleterious mutations, accelerating adaptation, and influencing the distribution of genomic features over evolutionary time. While recombination is clearly an important process, recombination rate is known to vary within and between individuals, populations, and species. Furthermore, what causes this variation remains relatively unknown. Using empirical and sequenced based estimates of recombination rate for the closely related species Drosophila pseudoobscura and Drosophila miranda, I seek to understand where recombination happens across the genome, to what extent recombination changes between species, and what genomic features are responsible for these changes. These data will deepen our understanding of mechanisms determining the recombination landscape, and shed light on generalized patterns and exceptions of recombination rate variation across the tree of life.

Recombination occurs during meiosis to produce new allelic combinations in natural populations, and thus strongly affects evolutionary processes. The model system Drosophila has been crucial for understanding the mechanics underlying recombination and assessing the association between recombination rate and several evolutionary parameters. Drosophila was the first system in which genetic maps were developed using recombination frequencies between genes. Further, Drosophila has been used to determine genetic and environmental conditions that cause variation in recombination rate. Finally, Drosophila has been instrumental in elucidating associations between local recombination rate and nucleotide diversity, divergence and codon bias, as well as helping determine the causes of these associations.

Here I present a fine-scale map of recombination rates across two major chromosomes in Drosophila persimilis using 181 SNP markers spanning two of five major chromosome arms. Using this map, I report significant fine-scale heterogeneity of local recombination rates. However, I also observed "recombinational neighborhoods", where adjacent intervals had similar recombination rates after excluding regions near the centromere and telomere. I further found significant positive associations of fine-scale recombination rate with repetitive element abundance and a 13-bp sequence motif known to associate with human recombination rates. I noted strong crossover interference extending 5-7 Mb from the initial crossover event. Further, I observed that fine-scale recombination rates in D. persimilis are strongly correlated with those obtained from a comparable study of its sister species, D. pseudoobscura. I documented a significant relationship between recombination rates and intron nucleotide sequence diversity within species, but no relationship between recombination rate and intron divergence between species. These results are consistent with selection models (hitchhiking and background selection) rather than mutagenic recombination models for explaining the relationship of recombination with nucleotide diversity within species. Finally, I found significant correlations between recombination rate and GC content, supporting both GC-biased gene conversion (BGC) models and selection-driven codon bias models.

Next, I looked at the role of chromosomal inversions in species maintenance by examining the impact of inversions distinguishing species to disrupt recombination rates within inverted regions, at inversion boundaries and throughout the remainder of the genome. By screening nearly 10,000 offspring from females heterozygous for 3 major inversions, I observed recombination rates within an inverted region in hybrids between Drosophila pseudoobscura and D. persimilis to be ~10-4 (similar to rates of exchange for inversion heterozygotes within species). However, despite the apparent potential for exchange, I do not find empirical evidence of ongoing gene exchange within the largest of 3 major inversions in DNA sequence analyses of strains isolated from natural populations. Finally, I observe a strong 'interchromosomal effect' with up to 9-fold higher (>800% different) recombination rates along collinear segments of chromosome 2 in hybrids, revealing a significantly negative association between interchromosomal effect and recombination rate in homokaryotypes, and I show that interspecies nucleotide divergence is lower in regions with larger changes in recombination rates in hybrids, potentially resulting from greater interspecies exchange. This last result suggests an effect of chromosomal inversions on interspecies gene exchange not considered previously.

Finally, I experimentally tested for a novel male-mediated effect on female recombination rates by crossing males that differed by either induced treatment variation or standing genetic variation to genetically identical females. After assaying recombination frequency in the offspring of these genetic crosses, I fitted these data to a statistical model where I showed no effect of male temperature treatment or male genetic background on offspring recombination rate. However, I did observe a difference of recombination rates of offspring laid 5-8 days post-mating between males treated with Juvenile Hormone relative to control males. Environmental variation in male ability to affect recombination rate in their mates suggests the potential for sexual conflict on optimal proportion of recombinant offspring, perhaps leading to changes in population-level recombination rates with varying levels of sexual selection.

Overall, my map of fine-scale recombination rates allowed me to confirm findings of broader-scale studies and identify multiple novel features that merit further investigation. Furthermore, I have identified several similarities and differences between inversions segregating within vs. between species in their effects on recombination and divergence, and I have identified possible effects of inversions on interspecies gene exchange that had not been considered previously. Finally, I have provided some evidence that males may impact female recombination rates, although future work should attempt to explore the range of male differences that impact this trait and the mechanism through which males impact the outcome of female meiosis.

The Arabidopsis root apical meristem (RAM) is a complex tissue capable of generating all the cell types that ultimately make up the root. The work presented in this thesis takes advantage of the versatility of high-throughput sequencing to address two independent questions about the root meristem. Although a lot of information is known regarding the cell fate decisions that occur at the RAM, cortex specification and differentiation remain poorly understood. In the first part of this thesis, I used an ethylmethanesulfonate (EMS) mutagenized marker line to perform a forward genetics screen. The goal of this screen was to identify novel genes involved in the specification and differentiation of the cortex tissue. Mapping analysis from the results obtained in this screen revealed a new allele of BRASSINOSTEROID4 with abnormal marker expression in the cortex tissue. Although this allele proved to be non-cortex specific, this project highlights new technology that allows mapping of EMS-generated mutations without the need to map-cross or back-cross. In the second part of this thesis, using fluorescence activated cell sorting (FACS) coupled with high throughput sequencing, my collaborators and I generated single-base resolution whole genome DNA methylomes, mRNA transcriptomes, and smallRNA transcriptomes for six different populations of cell types in the Arabidopsis root meristem. We were able to discover that the columella is hypermethylated in the CHH context within transposable elements. This hypermethylation is accompanied by upregulation of the RNA-dependent DNA methylation pathway (RdDM), including higher levels of 24-nt silencing RNAs (siRNAs). In summary, our studies demonstrate the versatility of high-throughput sequencing as a method for identifying single mutations or to perform complex comparative genomic analyses.

My thesis work has focused on characterizing mechanisms by which human fungal pathogens regulate their adaptive cellular responses in order to survive and cause disease in the human host. Unlike most microbial fungi found in the environment, Cryptococcus neoformans has become a successful human pathogen due to two intrinsic abilities: 1) to survive and grow at human body temperature and 2) to employ virulence factors to combat host immune defenses. Over the past two decades, the fungal pathogenesis field has made enormous progress in identifying and characterizing C. neoformans proteins responsible for these adaptive cellular responses with a particular focus on enzymes, like those involved in cell cycle progression or those responsible for synthesizing components of the fungal cell surface. Although we know a substantial amount about the functions of these enzymes and their implications on fungal pathogenesis, the mechanisms by which these enzymes are regulated are less clear. I have attempted to address this gap in knowledge by focusing my thesis work on the identification and characterization of C. neoformans non-enzymatic proteins that regulate enzymes important for adaptive cellular responses. I have identified and characterized the C. neoformans arrestin proteins as regulators of enzyme ubiquitination, and likely enzyme function, in response to specific extracellular stressors (Chapters 2 & 3). I have also characterized a Cryptococcus-specific protein, Mar1, as an important modulator of host-fungal interactions due to its regulation of cell surface remodeling through maintenance of mitochondrial metabolic activity and homeostasis in response to cellular stress (Chapters 4 & 5). Furthermore, I also performed a comprehensive comparative analysis of different RNA enrichment methods for RNA sequencing applications and long non-coding RNA identification in C. neoformans, which can help researchers select appropriate tools for studying adaptive cellular responses from the RNA level (Chapter 6). These studies collectively have demonstrated that non-enzymatic proteins are important “cellular coordinators” in human fungal pathogens; they regulate the activity of many different enzymes in response to distinct extracellular signals, and as a result are required for both fungal growth and virulence factor employment in response to host-relevant stressors.

Cerebral cavernous malformations (CCMs) are multicavernous vascular lesions affecting the central nervous system. Affected individuals have a lifetime risk of recurrent headaches, focal neurological deficits, seizures, and intracerebral hemorrhage leading to stroke. Patients tend to fall into two classes: familial cases with a known family history and multiple lesions, and; sporadic cases with no family history and single lesions. This epidemiological pattern suggests a two-hit mutational mechanism for CCM. While somatic mutations have been identified in lesions from familial patients, it is unknown if sporadic cases follow the same genetic mechanism. Using a next-generation sequencing strategy, I have identified somatic mutations from sporadic CCM lesions in the three known CCM genes, including one lesion bearing two independent mutations in CCM1. These data support a two-hit mutation mechanism in CCM for sporadic patients.

The mechanism of CCM pathogenesis (how mutations in one of the three CCM genes causes lesions to form and develop) is currently unknown. We developed mouse models that recapitulate the human disease. We have further shown that inhibition of Rho Kinase decreases the number of late-stage, multicavernous lesions. This is the first potential therapeutic strategy to specifically treat CCM, and suggests that the RhoA pathway is a central player in CCM pathogenesis.

An organism's ability to detect and interpret chemical signals from the surrounding environment is vital to its survival. In mammals, the vomeronasal organ provides an integral part of this requirement as it allows for the detection of inter-individual chemical signals. Located within the vomeronasal epithelium is a group of highly specialized receptors called vomeronasal type-1 receptors (V1Rs). These receptors bind pheromones and kairomones, which are chemical cues from conspecifics and heterospecifics, respectively. Recently, V1Rs have been recognized as highly variable across mammalian taxa. One extraordinary example is the mouse lemur, in which ~83% of the estimated 259 genes are expected to be intact. This relatively young and cryptically diverse prosimian group has a controversial history of species delimitation and it is possible that patterns in the rapidly evolving and highly diverse V1R gene family may provide insight into species boundaries. This study generated broad and deep coverage of the two most diverse V1R subfamilies across multiple Microcebus species. By utilizing Pacific Bioscience's single molecule real time sequencing technology, this study produced sequences at a fraction of the time and cost of the traditional method of Sanger-sequenced clones. The results advance our understanding of the high diversity-at least 5.6% and 9.9% sequence divergence intra- and inter-individually for V1RIX and V1Rstrep, respectively-and rapid evolution of V1Rs in mouse lemurs. Comparing these results with draft genome mined sequences demonstrates the limited utility of low coverage genomes for identifying variation in this gene family. The patterns uncovered here provide no clear evidence for the role of these two characterized subfamilies in maintaining or generating species boundaries, but may instead point to an alternative mechanism of species recognition that is more complex and intricate than previously envisioned.

The advent of next-generation sequencing, now nearing a decade in age, has enabled, among other capabilities, measurement of genome-wide sequence features at unprecedented scale and resolution.

In this dissertation, I describe work to understand the genetic underpinnings of non-Hodgkin’s lymphoma through exploration of the epigenetics of its cell of origin, initial characterization and interpretation of driver mutations, and finally, a larger-scale, population-level study that incorporates mutation interpretation with clinical outcome.

In the first research chapter, I describe genomic characteristics of lymphomas through the lens of their cells of origin. Just as many other cancers, such as breast cancer or lung cancer, are categorized based on their cell of origin, lymphoma subtypes can be examined through the context of their normal B Cells of origin, Naïve, Germinal Center, and post-Germinal Center. By applying integrative analysis of the epigenetics of normal B Cells of origin through chromatin-immunoprecipitation sequencing, we find that differences in normal B Cell subtypes are reflected in the mutational landscapes of the cancers that arise from them, namely Mantle Cell, Burkitt, and Diffuse Large B-Cell Lymphoma.

In the next research chapter, I describe our first endeavor into understanding the genetic heterogeneity of Diffuse Large B Cell Lymphoma, the most common form of non-Hodgkin’s lymphoma, which affects 100,000 patients in the world. Through whole-genome sequencing of 1 case as well as whole-exome sequencing of 94 cases, we characterize the most recurrent genetic features of DLBCL and lay the groundwork for a larger study.

In the last research chapter, I describe work to characterize and interpret the whole exomes of 1001 cases of DLBCL in the largest single-cancer study to date. This highly-powered study enabled sub-gene, gene-level, and gene-network level understanding of driver mutations within DLBCL. Moreover, matched genomic and clinical data enabled the connection of these driver mutations to clinical features such as treatment response or overall survival. As sequencing costs continue to drop, whole-exome sequencing will become a routine clinical assay, and another diagnostic dimension in addition to existing methods such as histology. However, to unlock the full utility of sequencing data, we must be able to interpret it. This study undertakes a first step in developing the understanding necessary to uncover the genomic signals of DLBCL hidden within its exomes. However, beyond the scope of this one disease, the experimental and analytical methods can be readily applied to other cancer sequencing studies.

Thus, this dissertation leverages next-generation sequencing analysis to understand the genetic underpinnings of lymphoma, both by examining its normal cells of origin as well as through a large-scale study to sensitively identify recurrently mutated genes and their relationship to clinical outcome.

The cell division cycle is the process in which the entirety of a cell's contents is duplicated completely and then equally segregated into two identical daughter cells. The order of the steps in the cell cycle must be followed with fidelity to guarantee two viable cells. Understanding the regulatory mechanisms that control cell-cycle events remains to be a fundamental question in cell biology. In this dissertation, I explore the mechanisms that coordinate and regulate cell-cycle progression in the budding yeast, Saccharomyces cerevisiae.

Cell-cycle events have been shown to be triggered by oscillations in the activity of cyclin dependent kinases (CDKs) when bound to cyclins. However, several studies have shown that some cell-cycle events, such as periodic transcription, can continue in the absence of CDK activity. How are periodic transcription and other cell-cycle events coupled to each other during a wild-type cell cycle? Currently, two models of cell-cycle regulation have been proposed. One model hypothesizes that oscillations in CDK activity controls the timing of cell-cycle events, including periodic transcription. The second model proposes that a transcription factor (TF) network oscillator controls the timing of cell-cycle events, via proper timing of gene expression, including cyclins. By measuring global gene expression dynamics in cells with persistent CDK activity, I show that periodic transcription continues. This result fits with the second model of cell-cycle regulation. Further, I show that during a wild-type cell cycle, checkpoints are responsible for arresting the bulk of periodic transcription. This finding adds a new layer of regulation to the second model, providing a mechanism that coordinates cell-cycle events with a TF network oscillator. Taken together, these data provide further insight into the regulation of the cell cycle.