Understanding the factors influencing species ranges and dispersal are becoming increasingly important as climate change alters species distributions worldwide. If species are to persist, life-history strategies must rapidly evolve to accommodate shifting environments. This dissertation assesses the factors modulating dispersal in corals. First, I examined if there were any systematic differences in settlement between Indo-Pacific and Caribbean coral larvae that might explain Caribbean recruitment failures. No differences were observed, however I detected significant divergences in settlement cue preferences among coral species across both the Caribbean (Diploria strigosa, and Montastraea franksi) and the Indo-Pacific (Acropora tenuis, A. millepora, and Favia lizardensis), even for coral larvae from the same reef. Secondly, I established the extent of coral dispersal between remote reefs. I evaluated the genetic diversity and divergence across Micronesia for two coral species and investigated if these islands served as a connectivity corridor between the Indo-West-Pacific (Coral Triangle) and the Central Pacific. I found isolation-by-distance patterns whose strength depended on species, suggesting these corals are not panmictic across their ranges and that island stepping-stones facilitate gene flow to remote Pacific reefs. Next, I investigated genetic structure of symbionts in these same corals, to see if horizontally transmitted symbionts are less dispersive than their coral hosts. Symbiont genetic divergence between islands was an order of magnitude larger than host divergence and both host species and environment modulated symbiont composition. These results suggest that symbiont populations are host-specific and associating with local symbionts might be a mechanism for broadly dispersing corals to adapt locally. Lastly, I estimated heritable variation in dispersal-related traits in coral larvae. I observed strong heritable variation in gene expression, as well as parental effects on two phenotypic traits, settlement and fluorescence. I observed that patterns of differential expression in three-day-old larvae predicted variation in settlement and fluorescence two days later. Correlations between proteoglycan expression and settlement suggest that the larval extracellular matrix plays a role in settlement. Down-regulation of ribosomal proteins and differential expression of oxidative stress genes correlated with increasing fluorescence, possibly indicating reduced growth and increased stress. Overall, this dissertation contributes to our knowledge of factors affecting coral dispersal and the potential for evolution of dispersal-related traits. / text

Transcriptional regulation is a complicated process controlled by numerous factors such as transcription factors (TFs), chromatin remodeling enzymes, nucleosomes, post-transcriptional machineries, and cis-acting DNA sequence. I explored the complex transcriptional regulation in eukaryotes through three distinct studies to comprehensively understand the functional genomics at various steps. Although a variety of high throughput approaches have been developed to understand this complex system on a genome wide scale with high resolution, a lack of accurate and comprehensive annotation transcription start sites (TSS) and polyadenylation sites (PAS) has hindered precise analyses even in Saccharomyces cerevisiae, one of the simplest eukaryotes. We developed Simultaneous Mapping Of RNA Ends by sequencing (SMORE-seq) and identified the strongest TSS and PAS of over 90% of yeast genes with single nucleotide resolution. Owing to the high accuracy of TSS identified by SMORE-seq, we detected possibly mis-annotated 150 genes that have a TSS downstream of the annotated start codon. Furthermore, SMORE-seq showed that 5’-capped non-coding RNAs were highly transcribed divergently from TATA-less promoters in wild-type cells under normal conditions. Mapping of DNA-protein interactions is essential to understanding the role of TFs in transcriptional regulation. ChIP-seq is the most widely used method for this purpose. However, careful attention has not been given to technical bias reflected in final target calling due to many experimental steps of ChIP-seq including fixation and shearing of chromatin, immunoprecipitation, sequencing library construction, and computational analysis. While analyzing large-scale ChIP-seq data, we observed that unrelated proteins appeared to bind to the gene bodies of highly transcribed genes across datasets. Control experiments including input, IgG ChIP in untagged cells, and the Golgi factor Mnn10 ChIP also showed the strong binding at the same loci, indicating that the signals were obviously derived from bias that is devoid of biological meaning. In addition, the appearance of nucleosomal periodicity in ChIP-seq data for proteins localizing to gene bodies is another bias that can be mistaken for false interactions with nucleosomes. We alleviated these biases by correcting data with proper negative controls, but the biases could not be completely removed. Therefore, caution is warranted in interpreting the results from ChIP-seq. Nucleosome positioning is another critical mechanism of transcriptional regulation. Global mapping of nucleosome occupancy in S. cerevisiae strains deleted for chromatin remodeling complexes has elucidated the role of these complexes on a genome wide scale. In this study, loss of chromodomain helicase DNA binding protein 1 (Chd1) resulted in severe disorganization of nucleosome positioning. Despite the difficulties of performing ChIP-seq for chromatin remodeling complexes due to their transient and dynamic localization on chromatin, we successfully mapped the genome-wide occupancy of Chd1 and quantitatively showed that Chd1 co-localizes with early transcription elongation factors, but not late transcription elongation factors. Interestingly, Chd1 occupancy was independent of the methylation levels at H3K36, indicating the necessity of a new working model describing Chd1 localization.

Antibodies are essential molecules that help to provide immunity against a vast population of environmental pathogens. This antibody conferred protection is dependent upon genetic diversification mechanisms that produce an impressive repertoire of lymphocytes expressing unique B-cell receptors. The advent of high throughput sequencing has enabled researchers to sequence populations of B-cell receptors at an unprecedented depth. Such investigations can be used to expand our understanding of mechanistic processes governing adaptive immunity, characterization of immunity related disorders, and the discovery of antibodies specific to antigens of interest. However, next generation sequencing of immunological repertoires is not without its challenges. For example, it is especially difficult to identify biologically relevant features within large datasets. Additionally, within the immunology community, there is a severe lack of standardized and easily accessible bioinformatics analysis pipelines. In this work, we present methods which address many of these concerns. First, we present robust statistical methods for the comparison of immunoglobulin repertoires. Specifically, we quantified the overlap between the antibody heavy chain variable domain (V H ) repertoire of antibody secreting plasma cells isolated from the bone marrow, lymph nodes, and spleen lymphoid tissues of immunized mice. Statistical analysis showed significantly more overlap between the bone marrow and spleen VH repertoires as compared to the lymph node repertoires. Moreover, we identified and synthesized antigen-specific antibodies from the repertoire of a mouse that showed a convergence of highly frequent VH sequences in all three tissues. Second, we introduce a novel algorithm for the rapid and accurate alignment of VH sequences to their respective germline genes. Our tests show that gene assignments reported from this algorithm were more than 99% identical to assignments determined using the well-validated IMGT software, and yet the algorithm is five times faster than an IgBlast based analysis. Finally, in an effort to introduce methods for the standardization, transparency, and replication of future repertoire studies, we have built a cloud-based pipeline of bioinformatics tools specific to immunoglobulin repertoire studies. These tools provide solutions for data curation and long-term storage of immunological sequencing data in a database, annotation of sequences with biologically relevant features, and analysis of repertoire experiments. / text

Mitochondrial diseases involving dysfunction of the respiratory chain are the most common inborn errors of metabolism. Mitochondria are found in all cell types besides red blood cells; consequently, patients can present with any symptom in any organ at any age. These diseases are genetically heterogeneous, and exhibit maternal, autosomal dominant, autosomal recessive and X-linked modes of inheritance. Historically, clinical genetic evaluation of mitochondrial disease has been limited to sequencing of the mitochondrial DNA (mtDNA) or several candidate genes. As human genome sequencing transformed from a research grade effort costing $250,000 to a clinical test orderable by doctors for under $10,000, it has become practical for researchers to sequence individual patients. This thesis describes our experiences in applying "MitoExome" sequencing of the mtDNA and exons of >1000 nuclear genes encoding mitochondrial proteins in ~200 patients with suspected mitochondrial disease. In 42 infants, we found that 55% harbored pathogenic mtDNA variants or compound heterozygous mutations in candidate genes. The pathogenicity of two nuclear genes not previously linked to disease, NDUFB3 and AGK, was supported by complementation studies and evidence from multiple patients, respectively. In an additional two unrelated children presenting with Leigh syndrome and combined OXPHOS deficiency, we identified compound heterozygous mutations in MTFMT. Patient fibroblasts exhibit severe defects in mitochondrial translation that can be rescued by exogenous expression of MTFMT. Furthermore, patient fibroblasts have dramatically reduced fMet-\(tRNA^{Met}\) levels and an abnormal formylation profile of mitochondrially translated \(COX_1\). These results demonstrate that MTFMT is critical for human mitochondrial translation. Lastly, to facilitate evaluation of copy number variants (CNVs), we developed a web-interface that integrates CNV calling with genetic and phenotypic information. Additional diagnoses are suggested and in a male with ataxia, neuropathy, azoospermia, and hearing loss we found a deletion compounded with a missense variant in D-bifunctional protein, \(HSD_{17}B_4\), a peroxisomal enzyme that catalyzes beta-oxidation of very long chain fatty acids. Retrospective review of metabolic testing from this patient revealed alterations of long- and very-long chain fatty acid metabolism consistent with a peroxisomal disorder. This work expands the molecular basis of mitochondrial disease and has implications for clinical genomics.

Characterization of the RNA transcriptome by next-generation sequencing can produce an unprecedented yield of information that provides novel biologic insights. I describe four approaches for sequencing different aspects of the transcriptome and provide computational tools to analyze the resulting data. Methods that query the dynamic range of gene expression, low expressing transcripts, micro RNA levels, and start-site usage of transcripts are described.

The pathophysiology of asthma is characterized by airway inflammation, remodeling and hyper-responsiveness. Phenotypic changes in airway smooth muscle cells (ASM) play a pivotal role in the pathogenesis of asthma. ASM cells promote inflammation and are key drivers of airway remodeling. While airway hyper responsiveness and inflammation can be managed by bronchodilators and anti-inflammatory drugs, ASM remodeling is poorly managed by existing therapies. Therefore, targeting ASM remodeling remains a challenge, and a deeper understanding of the molecular mechanism that regulates ASM phenotypes in asthma pathogenesis will facilitate the search for next-generation asthma therapy. MicroRNAs are small yet versatile gene tuners that regulate a variety of cellular processes, including cell proliferation and inflammation - two phenotypes that are often altered in asthmatic ASM. We thus hypothesized that microRNAs regulate ASM phenotypes in asthma and represent new targets for future therapy. In this thesis, we used a genomic approach that combined next-generation sequencing with functional cellular assays to characterize the role of microRNAs in regulating airway smooth muscle function and drug response to conventional therapies. In Chapter 2, we identified miR-10a as the most abundant microRNA expressed in the primary human airway smooth muscle (HASM) cells. Using an unbiased target identification approach, we identified several novel potential targets of miR-10a, including the catalytic subunit alpha of PI3 kinase (PIK3CA)--the central component of the PI3K pathway. We demonstrated that miR-10a directly suppresses PIK3CA expression by targeting its 3' Untranslated region (3'-UTR). Inhibition of PIK3CA by miR-10a reduced AKT phosphorylation and blunted the expression of cyclins and cyclin-dependent kinases that are required for HASM proliferation. In Chapter 3, we examined the effect of conventional asthma therapies on miRNA expression. While we did not find significant changes in miRNA levels, it remains to be determined whether microRNAs play a role in ASM tissue response to asthma therapy. Our study is the first to examine the role of microRNAs in ASM proliferation. Results from our study identified a novel microRNA-mediated regulatory mechanism of PI3K signaling and ASM proliferation. They suggest further that miR-10a is a potential therapeutic target to treat airway remodeling in asthma.

Recent advancements in molecular biology such as next generation sequencing and more sensitive and rapid molecular detection methods like qPCR, have historically been developed for clinical applications in human genetics and for health care diagnostic purposes. The high demand for faster and more accurate molecular assays in the health care field has driven rapid development of inexpensive molecular techniques that when applied to the science of environmental microbiology, provides an unprecedented level of understanding of the microbial world around us. The goal of this dissertation is to begin to apply more advanced molecular technologies to problems in applied environmental microbiology. Appendix A is a brief literature review of next generation sequencing technologies for applications in environmental microbiology. Appendix B focuses on the development of a more robust virus nucleic extraction kit for the detection of viral genomes from environmental samples found to contain high concentrations of qPCR inhibitors, such as humic acids or heavy metals. Appendix C summarizes one of the largest virus surveys done in the US, using state of the art qPCR technologies in both wastewater influent and effluent from two wastewater treatment plants in the Southwest. Data suggests that traditional virus indicators may not be a viable tool to evaluate fecally impacted source water or virus removal during water treatment. The third study summarized in Appendix D, provides one of the first insights into the microbial ecology of biofilms utilized as biological treatment media using Roche 454 amplicon sequencing of the 16S rRNA gene.

Metagenomics is the study of a collective microbial genetic content recovered directly from natural (e.g., soil, ocean, and freshwater) or host-associated (e.g., human gut, skin, and oral) environmental communities that contain microorganisms, i.e., microbiomes. The rapid technological developments in next generation sequencing (NGS) technologies, enabling to sequence tens or hundreds of millions of short DNA fragments (or reads) in a single run, facilitates the studies of multiple microorganisms lived in environmental communities. Metagenomics, a relatively new but fast growing field, allows us to understand the diversity of microbes, their functions, cooperation, and evolution in a particular ecosystem. Also, it assists us to identify significantly different metabolic potentials in different environments. Particularly, metagenomic analysis on the basis of functional features (e.g., pathways, subsystems, functional roles) enables to contribute the genomic contents of microbes to human health and leads us to understand how the microbes affect human health by analyzing a metagenomic data corresponding to two or multiple populations with different clinical phenotypes (e.g., diseased and healthy, or different treatments). Currently, metagenomic analysis has substantial impact not only on genetic and environmental areas, but also on clinical applications. In our study, we focus on the development of computational and statistical methods for functional metagnomic analysis of sequencing data that is obtained from various environmental microbial samples/communities.

The effects of a mutation in one gene can occasionally be suppressed by mutation in another gene. Genetic suppression indicates functional relationships and provides clues about the mechanism and order of action in genetic pathways. Here I explored the existing yeast deletion collection to identify suppressor relationships. The collection was released in 2000 and it is known that some strains in the collection have acquired mutations. Whole genome sequencing of 48 yeast deletion strains corresponding to 26 genome integrity genes was performed. High-throughput sequencing revealed a broad mutational spectrum including point mutations, indels, and copy number variations. I identified and experimentally validated two new suppressor mutations (sgs1 mutations in both top3Δ and rmi1Δ strains) corresponding to gene pairs with previously known suppressor relationships. Thus, high-throughput sequencing and analysis of yeast deletion strains can identify suppressor mutations. The resulting genome sequences also provide a baseline for future laboratory evolution experiments.

<p>Neurodevelopmental disorders develop over time and are characterized by a wide variety of mental, behavioral, and physical phenotypes. The categorization of neurodevelopmental disorders encompasses a broad range of conditions including intellectual disability, autism spectrum disorder, attention deficit hyperactivity disorder, cerebral palsy, schizophrenia, bipolar disorder, and epilepsy, among others. Diagnostic classifications of neurodevelopmental disorders are complicated by comorbidities among these neurodevelopmental disorders, unidentified causal genes, and growing evidence of shared genetic risk factors. </p><p>We sought to identify the genetic underpinnings of a variety of neurodevelopmental disorders, with a particular emphasis on the epilepsies, by employing next&ndash;generation sequencing to thoroughly interrogate genetic variation in the human genome/exome. First, we investigated four families presenting with a seemingly identical and previously undescribed neurodevelopmental disorder characterized by congenital microcephaly, intellectual disability, progressive cerebral atrophy, and intractable seizures. These families all exhibited an apparent autosomal recessive pattern of inheritance. Second, we investigated a heterogeneous cohort of &sim;60 undiagnosed patients, the majority of whom suffered from severe neurodevelopmental disorders with a suspected genetic etiology. Third, we investigated 264 patients with epileptic encephalopathies &mdash; severe childhood epilepsy disorders &mdash; looking specifically at infantile spasms and Lennox&ndash;Gastaut syndrome. Finally, we investigated &sim;40 large multiplex epilepsy families with complex phenotypic constellations and unclear modes of inheritance. The studied neurodevelopmental disorders exhibited a range of genetic complexity, from clear Mendelian disorders to common complex disorders, resulting in varying degrees of success in the identification of clearly causal genetic variants. </p><p>In the first project, we successfully identified the disease&ndash;causing gene. We show that recessive mutations in <italic>ASNS </italic> (encoding asparagine synthetase) are responsible for this previously undescribed neurodevelopmental disorder. We also characterized the causal mutations <italic>in vitro</italic> and studied Asns&ndash;deficient mice that mimicked aspects of the patient phenotype. This work describes ASNS deficiency as a novel neurodevelopmental disorder, identifies three distinct causal mutations in the ASNS gene, and indicates that asparagine synthesis is essential for the proper development and function of the brain.</p><p>In the second project, we exome sequenced 62 undiagnosed patients and their unaffected biological parents (trios). By analyzing all identified variants that were annotated as putatively functional and observed as a novel genotype in the probands (not observed in the unaffected parents or controls), we obtained a genetic diagnosis for 32% (20/62) of these patients. Additionally, we identify strong candidate variants in 31% (13/42) of the undiagnosed cases. We also present additional analysis methods for moving beyond traditional screens, e.g., considering only securely implicated genes, or subjecting qualifying variants from any gene to two unique analysis approaches. This work adds to the growing evidence for the utility of diagnostic exome sequencing, increases patient sizes for rare neurodevelopmental disorders (enabling more detailed analyses of the phenotypic spectrum), and proposes novel analysis approaches which will likely become beneficial as the number of sequenced undiagnosed patients grows. </p><p>In the third project, we again employ a trio&ndash;based exome sequencing design to investigate the role of <italic>de novo</italic> mutations in two classical forms of epileptic encephalopathy. We find a significant excess of <italic>de novo</italic> mutations in the &sim;4,000 genes that are the most intolerant to functional genetic variation in the human population (P = 2.9 x 10<super>&ndash;3</super>, likelihood analysis). We provide clear statistical evidence for two novel genes associated with epileptic encephalopathy &mdash; <italic>GABRB3</italic> and <italic>ALG13</italic>. Together with the 15 well&ndash;established epileptic encephalopathy genes, we statistically confirm the association of an additional ten putative epileptic encephalopathy genes. We show that only &sim;12% of epileptic encephalopathy patients in our cohort are explained by <italic>de novo</italic> mutations in one of these 24 genes, highlighting the extreme locus heterogeneity of the epileptic encephalopathies. </p><p>Finally, we investigated multiplex epilepsy families to uncover novel epilepsy susceptibility factors. Candidate variants emerging from sequencing within discovery families were further assessed by cosegregation testing, variant association testing in a case&ndash;control cohort, and gene&ndash;based resequencing in a cohort of additional multiplex epilepsy families. Despite employing multiple approaches, we did not identify any clear genetic associations with epilepsy. This work has, however, identified a set of candidates that may include real risk factors for epilepsy; the most promising of these is the <italic>MYCBP2</italic> gene. This work emphasizes the extremely high locus and allelic heterogeneity of the epilepsies and demonstrates that very large sample sizes are needed to uncover novel genetic risk factors. </p><p>Collectively, this body of work has securely implicated three novel neurodevelopmental disease genes that inform the underlying pathology of these disorders. Furthermore, in the final three studies, this work has highlighted additional candidate variants and genes that may ultimately be validated as disease&ndash;causing as sample sizes increase.</p> / Dissertation