Climate change has resulted in both increased mean water temperature and higher frequencies of extreme water temperatures in coastal areas. These new thermal regimes exert strong selective pressure on the thermal physiology of coastal aquatic species. Phenotypic plasticity (the ability of one genotype to display multiple phenotypes) and local adaptation (increased fitness to local environment due to natural selection) dictate both short-term (from hours to days to weeks) and long-term (from years to decades) resilience of a species. To better predict how a species will respond to the negative impacts of climate change, one first needs to know the current levels of variation in plasticity and local adaptation. Marginal populations are especially critical for the persistence of a species, as those populations can harbor unique genetic variation and the interaction between plasticity and local adaptation determines the boundaries of future distributional ranges. This dissertation focuses on the northern marginal population of spotted seatrout (Cynoscion nebulosus), an estuarine-dependent fish, and compares them with those from the core region of the distribution to elucidate the physiological, transcriptomic and genetic mechanisms of plasticity and adaptation. I discovered significant differences between fish from different areas at all three levels of biological organization: Chapter 1 shows different whole-organism metabolic physiology of fish sampled from distinct populations and the northern population is consistent with cold-adaptation, given the pressure of natural selection from more severe and frequent winter kills in the region. Chapter 2 presents functional genetic evidence that the cold-adapted northern spotted seatrout are more vulnerable to heat stress than the warm-adapted southern spotted seatrout, suggesting that differential gene expression is contributing to observed differences in thermal tolerance. A liver transcriptome is de novo assembled and serves as a valuable resource for future genetic studies of spotted seatrout. Chapter 3 discovers signatures of selection based on over 15,000 genome-wide single nucleotide polymorphism (SNP) markers. The pattern of genetic variation is consistent with thermal adaptation along the US east coast. Genes involved in metabolic pathways and transcriptional regulation are the main targets of natural selection. In summary, spotted seatrout are relatively resilient to the thermal effects of climate change due to a wide range of metabolic plasticity and adaptive potential in climate-related genetic variation. Range expansion at the leading edge, however, is largely constrained by the species’ cold tolerance limit. The northern and southern population will likely respond to climate change differently and this should be taken into consideration in future conservation management of this species.

Aquaculture has potential to support the food supply of increasing world population. Flavobacterial diseases pose a serious problem in wild and aquacultured fish stocks throughout the world. Flavobacterium columnare, F. branchiophilum, and F. psychrophilum are well-known Flavobacterium species that cause important fish losses. Recently, new Flavobacterium species, isolated from diseased fish, have been reported, but their virulence mechanisms are not clear. Thus, the goal of this study was to understand pathogenicity of Flavobacterium species. To this goal, 86 Flavobacterium genomes were analyzed by comparative genomics. Predicted virulence genes were identified for all genomes. For each species, unique and shared virulence genes were determined. For all genomes, unique and common predicted antibiotic resistance genes were identified as well. Secreted proteins are important virulence factors. Thus, all encoded secretion and related systems were determined. By using different genomics approaches, F. columnare genomovar I (highly virulent to cold-water fish species like trout) and genomovar II (extremely virulent to warm-water fish species such as catfish and tilapia) genomes were analyzed, and transposon mutants using Tn4351 in six F. columnare genomovar II strain 94-081 were generated. The hemolysin and glycine cleavage protein mutants had 15% and 10% mortalities, respectively while wild-type strain caused 100% mortality. Potential virulence genes, unique proteins, and other genomic features of F. columnare genomovars were determined. Mutants targeting unique genes in valine-leucine-isoleucine biosynthesis pathway were constructed. The virulence of Fcol(DELTA)leuD and Fcol(DELTA)ilvD mutants exhibited reduced virulence.

Abiotic stresses constitute a major category of stresses that negatively impact plant growth and development. It is important to understand how plants cope with environmental stresses and reprogram gene responses which in turn confers stress tolerance. Recent advances of genomic technologies have led to the generation of much genomic data for the model plant, Arabidopsis. To understand gene responses activated by specific external stress signals, these large-scale data sets need to be analyzed to generate new insight of gene functions in stress responses. This poses new computational challenges of mining gene associations and reconstructing regulatory interactions from large-scale data sets. In this dissertation, several computational tools were developed to address the challenges. In Chapter 2, ConSReg was developed to infer condition-specific regulatory interactions and prioritize transcription factors (TFs) that are likely to play condition specific regulatory roles. Comprehensive investigation was performed to optimize the performance of ConSReg and a systematic recovery of nitrogen response TFs was performed to evaluate ConSReg. In Chapter 3, CoReg was developed to infer co-regulation between genes, using only regulatory networks as input. CoReg was compared to other computational methods and the results showed that CoReg outperformed other methods. CoReg was further applied to identified modules in regulatory network generated from DAP-seq (DNA affinity purification sequencing). Using a large expression dataset generated under many abiotic stress treatments, many regulatory modules with common regulatory edges were found to be highly co-expressed, suggesting that target modules are structurally stable modules under abiotic stress conditions. In Chapter 4, exploratory analysis was performed to classify cell types for Arabidopsis root single cell RNA-seq data. This is a first step towards construction of a cell-type-specific regulatory network for Arabidopsis root cells, which is important for improving current understanding of stress response. / Doctor of Philosophy / Abiotic stresses constitute a major category of stresses that negatively impact plant growth and development. It is important to understand how plants cope with environmental stresses and reprogram gene responses which in turn confers stress tolerance to plants. Genomics technology has been used in past decade to generate gene expression data under different abiotic stresses for the model plant, Arabidopsis. Recent new genomic technologies, such as DAP-seq, have generated large scale regulatory maps that provide information regarding which gene has the potential to regulate other genes in the genome. However, this technology does not provide context specific interactions. It is unknown which transcription factor can regulate which gene under a specific abiotic stress condition. To address this challenge, several computational tools were developed to identify regulatory interactions and co-regulating genes for stress response. In addition, using single cell RNA-seq data generated from the model plant organism Arabidopsis, preliminary analysis was performed to build model that classifies Arabidopsis root cell types. This analysis is the first step towards the ultimate goal of constructing cell-typespecific regulatory network for Arabidopsis, which is important for improving current understanding of stress response in plants.

In modern genomics, all experiments begin data collection with sequencing and downstream alignment or assembly processing. As such, the development of reliable sequencing pipelines is hugely important as a foundation for any future analysis on that data. While much existing work has been done on enhancing the throughput and computational performance of such pipelines, there is still the question of accuracy. The rift in knowledge between speed and accuracy can be attributed to the more conceptually complex nature of what constitutes the measurement of accuracy. Unlike simply parsing logs of memory usage and CPU hours, accuracy requires experimental validation. Subsets of accuracy are also created when assessing alignment or variations around particular genomic features such as indels, Copy Number Variants (CNVs), or microsatellite repeats. Here is the development of accuracy measurements in read alignment and variation calls, allowing the optimization of sequencing pipelines at all stages. The underlying hypothesis, then, is that different sequencing platforms and analysis software can be distinguished from each other in accuracy by both sample and genomic variation of interest. As the term accuracy suggests, the measurements of alignment and variation recall require comparison against a truth set, for which read library simulations and high quality data from the Genome in a Bottle Consortium or Illumina Omni array have served us. In exploring the hypothesis, the measurements are built into a community resource to crowdsource the creation of a benchmarking repository for pipeline comparison. Results from pipelines promoted by this computational model are then wet lab validated with support for a hierarchy of pipeline performance. Particularly, the construction of an accurate pipeline for genotyping microsatellite repeats will be investigated, which is then used to create a database of human microsatellites. Progress in this area is vital for the growth of sequencing in both clinical and research settings. For genomics research to fully translate to the bedside, the boom of new technology must be controlled by rational metrics and industry standardization. This project will address both of these issues, as well as contribute to the understanding of human microsatellite variation. / Ph. D.

The 5' end of eukaryotic and viral mRNAs contain a "cap" structure with the sequence m7G(5')pppN(5'). The methylation of the 7-position on the guanine cap is very important to proper mRNA processing and initiation of translation. The enzyme responsible for this methylation, RNA guanine-7-methyltransferase, has been cloned and studied from a number of different species, including human, X. laevis, yeast, and C. elegans. The sequences for mouse guanine-7-methyltransferase cDNA and protein have been deduced based upon identity of mouse ESTs to the cDNA of the human enzyme. The deduced mouse cDNA encodes an ORF of 465 amino acids and is 76.4% identical to the human enzyme, or 86.5% within the C-terminal domain. Active site characterization of mouse and human guanine-7-methyltransferase indicates a cysteine residue is important to proper enzyme activity. Enzyme activity was completely eliminated when N-ethylmaleimide (NEM) was added to the assay mixture. When the product of the reaction, S-adenosyl-L-homocysteine (SAH), was added at a concentration of 40uM the mouse enzyme retained 60% activity while enzyme isolated from Human Osteosarcoma (HOS) cells retained 100% of the original activity. SAH demonstrated no protective effects on the cloned human enzyme. Factors that affect binding of RNA to the active site were also investigated. UV-cross-linking of RNA to the active site of the mouse enzyme was inhibited 35% by NEM. Cap analog, GpppG, at a concentration of 1mM, inhibited cross-linking, but the similar nucleotide GMP, at a concentration of 1mM, did not inhibit cross-linking. These analyses have given a clearer understanding of this very important enzyme. / Master of Science

CRISPR systems have been growing in their utility and their application throughout the biological field as researchers continue to grow in their understanding of the relatively novel genome editing technology. However, despite the potential of CRISPR as a genome editing tool, the complexity of applying this technology to a specific organism calls for custom modifications to the system to improve its success rate. In this project, a CRISPR-Cpf1 system that can be effectively employed in the cyanobacterium Nostoc punctiforme was designed, with a focus on the hormogonium development of this species. Multiple plasmids containing the CRISPR system and targeting different genes were constructed using a Gibson-based rapid assembly cloning method, and then were tested by introduction into Nostoc punctiforme via conjugation. Plasmids were constructed to mutate 7 different genes in N. punctiforme with 4 of the 7 successfully mutating their target genes. For one of the genes where the plasmid failed to produce mutants, the usage of a larger homology repair template (HRT) was found to enhance the efficiency of gene editing, allowing the gene to be knocked out. Thus, the length of the HRT appears to be a critical factor in designing successful constructs. The system developed in this project aims to make CRISPR a more viable tool in studying Nostoc cyanobacteria, and more specifically to aid in understanding the mechanisms behind hormogonium development in the studied species. This system may have a wider application for studying the Nostoc genus and related organisms, such as Anabaena.

Acute myocardial infarction (AMI) results in the activation of the innate immune system with monocytes playing critical roles in both the initial inflammation following myocardial ischaemia and subsequent recovery. Monocytes are a heterogeneous cell population and observations from experimental models demonstrate that immediately following myocardial injury, classical inflammatory monocytes, which are highly phagocytic, are recruited to ischaemic myocardium from the bone marrow and spleen and peak at 48 hours. This is followed by the recruitment of non-classical monocytes that are involved in repair and healing, peaking at day 5. The monocyte response in humans following AMI is currently poorly understood. Due to their central role in the pathogenesis of AMI, monocytes are attractive both as potential biomarkers to inform of extent of myocardial injury (and recovery) and also as therapeutic targets with the specific targeting of monocytes in experimental models resulting in reduced infarction size and improved LV remodelling. However, in spite of these promising results and our greater understanding of the pathogenesis of AMI, no immune-modulating therapeutic has been translated into routine clinical practice. We therefore hypothesized that characterisation of the monocyte response to AMI by flow cytometry and gene expression profiling in both experimental models and humans would give novel insights into underlying biological processes and function (both locally in the myocardium and systemically), identify novel therapeutic targets, enable their use as cellular biomarkers of disease, and test conservation between species validating the experimental model for future investigation. Classical inflammatory monocytes were found to significantly increase in the peripheral blood 48 hours following AMI in both mice and humans, with the magnitude of the monocyte response correlating with the extent of myocardial injury in both species. Gene expression profiling of peripheral circulating monocytes following AMI identified a number of candidate genes, biological pathways and upstream regulators that were conserved between species and that could represent novel therapeutic targets. Furthermore, in an experimental model of AMI, leukocytes appeared to have effects beyond the ischaemic myocardium, with leukocyte recruitment in remote myocardium and in kidneys associated with elevated inflammatory markers and endothelial activation.

Embryonic stem cells (ESCs) are a special type of cell marked by two key properties: The capacity to create an unlimited number of identical copies of themselves (self-renewal) and the ability to give rise to differentiated progeny that can contribute to all tissues of the adult body (pluripotency). Decades of past research have identified many of the genetic determinants of the state of these cells, such as the transcription factors Pou5f1, Sox2 and Nanog. Many other transcription factors and, more recently, epigenetic determinants like histone modifications, have been implicated in the establishment, maintenance and loss of pluripotent stem cell identity. The study of these regulators has been boosted by technological advances in the field of high-throughput sequencing (HTS) that have made it possible to investigate the binding and modification of many proteins on a genome-wide level, resulting in an explosion of the amount of genomic data available to researchers. The challenge is now to effectively use these data and to integrate the manifold measurements into coherent and intelligible models that will actually help to better understand the way in which gene expression in stem cells is regulated to maintain their precarious identity. In this thesis, I first explore the potential of HTS by describing two pilot studies using the technology to investigate global differences in the transcriptional profiles of different cell populations. In both cases, I was able to identify a number of promising candidates that mark and, possibly, explain the phenotypic and functional differences between the cells studied. The pilot studies highlighted a strong requirement for specialised software to deal with the analysis of HTS data. I have developed GeneProf, a powerful computational framework for the integrated analysis of functional genomics experiments. This software platform solves many recurring data analysis challenges and streamlines, simplifies and standardises data analysis work flows promoting transparent and reproducible methodologies. The software offers a graphical, user-friendly interface and integrates expert knowledge to guide researchers through the analysis process. All primary analysis results are supplemented with a range of informative plots and summaries that ease the interpretation of the results. Behind the scenes, computationally demanding tasks are handled remotely on a distributed network of high-performance computers, removing rate-limiting requirements on local hardware set-up. A flexible and modular software design lays the foundations for a scalable and extensible framework that will be expanded to address an even wider range of data analysis tasks in future. Using GeneProf, billions of data points from over a hundred published studies have been re-analysed. The results of these analyses are stored in an web-accessible database as part of the GeneProf system, building up an accessible resource for all life scientists. All results, together with details about the analysis procedures used, can be browsed and examined in detail and all final and intermediate results are available and can instantly be reused and compared with new findings. In an attempt to elucidate the regulatory mechanisms of ESCs, I use this knowledge base to identify high-confidence candidate genes relevant to stem cell characteristics by comparing the transcriptional profiles of ESCs with those of other cell types. Doing so, I describe 229 genes with highly ESC-specific transcription. I then integrate the expression data for these ES-specific genes with genome-wide transcription factor binding and histone modification data. After investigating the global characteristics of these "regulatory inputs", I employ machine learning methods to first cluster subgroups of genes with ESC-specific expression patterns and then to define a "regulatory code" that marks one of the subgroups based on their regulatory signatures. The tightly co-regulated core cluster of genes identified in this analysis contains many known members of the transcriptional circuitry of ESCs and a number of novel candidates that I deem worthy of further investigations thanks to their similarity to their better known counterparts. Integrating these candidates and the regulatory code that drives them into our models of the workings of ESCs might eventually help to refine the ways in which we derive, culture and manipulate these cells - with all its prospective benefits to research and medicine.

Genome sequencing of a large number Firmicute species has recently been completed, including some of the highly oxygen-sensitive butyrate-producing bacteria, belonging to the Lachnospiraceae and Ruminococcaceae families, which have been isolated at the Rowett Institute of Nutrition and Health. However, detailed knowledge of the biochemistry and physiology of these bacteria has been limited by a lack of detailed genomic annotation and pathway analysis, and lack of genetic manipulation techniques. Therefore, the aim of this work was the genomic analysis of the carbohydrate-utilisation and motility genes, and establishment of genetic manipulation techniques for a selected group of these bacteria, specifically the Roseburia/Eubacterium rectale group and Faecalibacterium prausnitzii. This involved the establishment of a Roseburia/E. rectale pan-genome consisting of genome sequences from eleven strains (three of which are first introduced in this work), representing five species. 1840 Carbohydrate-active enzymes (CAZymes), 932 of which were glycoside hydrolases (GHs), were identified in this pan-genome. The GH complement of each strain was used to predict dietary niches of these bacteria in the human colon. The members of the Roseburia/E. rectale group were predicted to have the core capacity to utilise starch, with specific members possessing specialised dietary niches. The motility loci of selected members of the Roseburia/E. rectale group were annotated, and the gene orders of these loci were highly conserved between different members of the group. The motility of these bacteria was shown to be affected by the carbon source utilised for growth. This was followed by the design of methods to allow the transfer of autonomously-replicating plasmids into Roseburia/E. rectale species. The modular plasmids pMTL83151 and pMTL82151 were transferred from an E. coli donor into Roseburia inulinivorans A2-194. pMTL83151 could also be transferred into Eubacterium rectale A1-86 and T1-815. This technique has enabled the heterologous expression of a β-(1,3-1,4)-glucanase enzyme in R. inulinivorans A2-194 and E .rectale T1-815.

published_or_final_version / abstract / Mathematics / Doctoral / Doctor of Philosophy