Doctor of Philosophy / Genetics Interdepartmental Program / Christopher Toomajian / Secondary metabolites (SMs), low molecular weight molecules that are not essential for normal organism growth and development, may confer a selective advantage in some environments. Fungal SMs are structurally and functionally diverse and include mycotoxins, plant regulators and pigments, and the genes that work together in SM biosynthetic pathways are physically clustered in the genome. Fusarium, a genus of filamentous fungi, is noted for SM production, especially mycotoxins, which may contribute to plant pathogenesis. Fusarium species exhibit differences in their SM profiles, and comparative genomics studies have found corresponding differences in the SM gene clusters in some Fusarium species. The investigation of differences in the genomes and SM gene clusters between closely related species, such as F. proliferatum and F. fujikuroi, may help explain their phenotypic divergence, including differences in SM profiles. In addition, the study of intra-species SM variation may indicate how SM loci affect a pathogen’s fitness traits. My research includes three main projects that address different aspects of Fusarium SM variability. To carry out my projects, I established a feasible Genotyping-by-Sequencing (GBS) protocol for Fusarium. One project explored the genetic bases underlying phenotypic divergence related to SM profiles and pathogenicity between F. proliferatum and F. fujikuroi using a quantitative genetics approach. Specifically, I 1) constructed the first high density genetic map based on progeny from an interspecific cross between these two species; and 2) detected a novel regulatory locus for gibberellic acid production and identified a region affecting onion virulence that includes the fumonisin gene cluster. The second project characterized the F. proliferatum parent genome from the previous cross and its SM gene clusters using a comparative genomics approach. Specifically, I 1) assembled the F. proliferatum genome into 12 chromosomes with a combined length of ~43 Mb; 2) annotated this assembly and characterized its 50 SM gene clusters; and 3) detected over 100 F. proliferatum specific genes that might play roles in this species’ host specificity and plant pathogenicity. The third project used a population genomics approach to explore how different F. graminearum chemotypes, or isolates classified based on the accumulation of alternate trichothecene toxin types, may differ for fitness traits and whether trichothecene genes are directly responsible for these differences. Specifically, I 1) genotyped over 300 F. graminearum strains from New York and the upper Midwest in the U.S. and from South America using our GBS protocol; 2) detected two major subpopulations that were correlated, though imperfectly, to the predicted 3-acetyl deoxynivalenol (3ADON) and 15-acetyl deoxynivalenol (15ADON) chemotypes in the U.S.; 3) identified a rapid linkage disequilibrium decay over a few tens of kb followed by a slower decay to background levels over a distance of 200 kb to 400 kb in selected subpopulations in the U.S.; and 4) found that neither chemotype has a clear fitness advantage in a small set of isolates from New York, but that isolates belonging to one genetic subpopulation may on average have a fitness advantage over isolates from the other subpopulation.

Tuberculosis is one of the leading causes of mortality globally. Although this disease has been around for many generations, treatment and management of the disease remains a daunting challenge. M. tb, is one of the most famous tuberculosis causing organisms, however there are many other mycobacterial strains and species that are also responsible for human mortality, globally. Not all mycobacterial species, however, are disease causing. It is only a few strains such as M. tb H37Rv, M. tb CDC1551, M. tb F11 and M. bovis which are responsible for causing disease. The rest are relatively harmless. What are the genetic differences between these virulent and avirulent strains that dictate a strain's behavior? The answers to these and many other questions lie hidden within the genomes of these organisms. Due to the great advances in DNA sequencing techniques, it is now now possible to more quickly and cheaply, sequence whole bacterial genomes in a single experimental run (High-throughput sequencing). Comparative genomics is therefore extremely relevant and important to be able to handle the dubious amounts of genomic data being poured into our public databases. Several comparative genomics environments already exist on the web today, however the goal of this project is to produce a web-based, comparative genomics environment which not only incorporates basic comparative genomics functions but also, novel tools such as the Seqword Genome Browser (SWGB) and the Mycobacterial Comparison Project (MCP). Using these tools, some interesting comparative genomics findings regarding certain strains of Mycobacteria are made. We reveal several genomic islands within M. avium and M. tb H37Rv. It is shown that certain genes which are usually found to be conserved among other bacteria, tend to be rather divergent among the mycobacteria. 'Mutational hotspots' containing many DNA replication genes are observed to have higher mutation rates relative to the rest of the genome which perhaps accounts for the slow-growth rate of these bacteria. By looking at the genetic profile of PE-PGRS genes in mycobacteria it was shown that M. tb H37Rv and M. tb F11 were actually closer for several genes than when compared to strain H37Ra. The finding was unexpected as H37Ra is known to be derived from H37Rv. These findings are extremely important in the area of TB research as it is of extreme importance to be able to trace areas of greater or lower selection within mycobacteria. Automated sequence comparison such as this is also important for tracking drug resistance markers and other features within mycobacteria so that more focused research can be carried out. The built system was tested and validated with mycobacteria, however, the system is flexible and designed with the intent of inclusion of any prokaryotic organism. It is hoped that systems such as these, and other advances in sequence comparison technology in the future, will provide the understanding needed to better control and cure diseases in the future. / Thesis (PhD)--University of Pretoria, 2010. / Biochemistry / unrestricted

Sox domain genes encode a family of developmentally important transcription factors conserved throughout the Metazoa. The subgroup B, which includes the mammalian Sox1, 2 and 3 proteins and their Drosophila counterparts Dichaete and SoxNeuro, are particularly important for the development of the nervous system where they appear to play conserved roles in neuronal specification and differentiation. Despite years of detailed study we still have a relatively poor idea of how Sox proteins function on a genome wide scale and the aim of my PhD work was to explore this aspect using the fly group B protein, Dichaete. A number of studies have shown that Dichaete performs a variety of critical functions during development and a few individual regulatory targets have been defined, however, at the start of my work no genome-wide data on Dichaete action were available. While such data emerged from large scale initiatives during my work, a systematic analysis of Dichaete action was lacking. Here I describe the first detailed genomic analysis of Dichaete activity, with a particular focus on three areas: finding the locations of Dichaete binding in the genome, a prediction of potential Dichaete cofactors and an analysis of Dichaete effects on gene expression. To address the issue of where Dichaete binds in the genome, I generated whole genome DamID data for embryos and followed this with a detailed comparative analysis, combining my data with three newly published ChIP-chip datasets. The combined studies identify thousands of binding regions, mostly in the vicinity of developmentally important genes. The binding profiles were found to be consistent with Dichaete acting on enhancer regions and also suggest a role in facilitating RNA Polymerase II pausing. The analysis also identified a Dichaete binding motif closely matching that found with in vitro studies. By combined ChIP and DamID datasets I generated a very high confidence core Dichaete binding dataset, which should be of considerable use in future studies. To identify potential Dichaete cofactors, I compiled the available embryonic transcription factor binding data from the Berkeley Drosophila Transcription Network and mod- ENCODE projects, and identified significant overlaps with the core Dichaete binding data. A number of the proteins highlighted in this analysis have known roles during neuroblast development, including Hunchback and Krüppel, transcription factors involved in temporal specification of neuroblast division, and Prospero, which plays a key role in neuroblast differentiation. The analysis suggests that Dichaete has a role during early neuroblast divisions, where it likely interacts with Hb and Kr to maintain neuroblast pluripotency. This is a role consistent with previous studies in Drosophila larval neuroblasts and is analogous to neural functions of Sox2 in mammals. My analysis suggests that Dichaete acts on the same target genes as Prospero but in an antagonistic role, with Dichaete preventing stem cell differentiation and Prospero promoting it. To examine the effects of Dichaete on gene expression, a number of microarray transcript profiling studies were performed, including a global study with Dichaete null mutants, and tissue specific studies in the CNS midline and neuroblasts via the use of dominant negative constructs. Whole transcriptome expression profiling data was combined with the binding data to establish a set of high confidence potential Dichaete targets, both for specific tissues and more globally during neurogenesis. Specific high confidence targets were found, including bancal during nervous system development. It was also concluded that Dichaete is likely to prevent cell cycle exit by repressing the apoptosis genes grim, hid and reaper, as well as the differentiation genes prospero and miranda. An extensive list of potential Dichaete direct targets was generated and can be used for validation and future research.

High-grade serous ovarian carcinoma (HGSOC) is characterised by genomic instability, ubiquitous TP53 loss, widespread disease at diagnosis and the frequent emergence of platinum resistance. This thesis explores the use of high-throughput genomics technologies to understand if resistance could be explained by the model of tumour evolution. We performed SNP array analysis of a cell line model system of platinum resistance consisting of matched cell lines from three cases of HGSOC established before and after clinical resistance developed, the OVOl clinical study consisting of six matched pairs of tumours before and after three cycles of chemotherapy, and the OV03/0V04 study consisting of 18 cases sampled at multiple timepoints and from multiple metastatic sites. The results showed evidence of metastatic site dependent divergence. Moreover, mutually exclusive loss of heterozygosity patterns between presentation and relapse genomes, including all the cases in the cell line system and one of two OV03 cases for which relapse material was available, suggest that the relapse arises from a minor subclone of the presentation disease, while in the remaining case, the subclone with an NFJ homozygous deletion was enriched in the relapsed disease. I then asked which mutational process drives evolution. Using next-generation sequencing (NGS), I compared the structural variants between and within cases in the model system and in 6 cases of the OV03 cohort. From the genomic signatures in the cell lines, I demonstrated that a case with homologous recombination (HR) deficiency acquired numerous translocations and small deletions (median size of 13.4kb) , whereas another showed a novel tandem duplicator phenotype (median size of tandem duplications was 350kb). Mutator phenotypes in both cases arose early in progression and persisted, but the tumour with HR deficiency showed evidence of re-stabilising its ,"genome and lost platinum sensitivity after a revertant BRCA2 mutation restored its HR function. A subset of tumours from the Cancer Genome Atlas (TCGA) dataset suggested that these two phenotypes were mutually exclusive. Amongst the six OV03 cases, preliminary analysis suggests that one case showed an amplifier phenotype and three cases showed evidence of parallel evolution. Taken together, early onset of mutator phenotypes and parallel evolution may provide a mechanism by which resistance evolves. Further work should aim to identify the processes involved in tumour evolution in 'purified' populations such as cancer stem cells.

Epithelial-mesenchymal plasticity (EMP) describes the interconversion of cells between epithelial and mesenchymal phenotypes. During the epithelial-mesenchymal transition (EMT), epithelial cells lose defining characteristics, such as stable cell-cell junctions, and gain the ability to migrate and invade through extracellular matrices. This plasticity contributes to tumour progression, promoting therapy resistance and immune cell evasion. Despite its importance, defining molecular features of this plasticity have largely remained elusive due to the limited scale of most studies. Here, I present my studies applying comparative single-cell genomics to map transcriptional changes associated with the EMT in diverse experimental conditions and EMP in tumours, I identify regulatory features associated with these dynamics, and explore opportunities to pharmacologically restrict them. This work provides critical steps towards building quantitative models of EMP, which will inform effective strategies to restrict these dynamics in cancer and improve patient prognosis.

Understanding the success of the human species is central to evolutionary anthropology. While we share many traits with our relatives the great apes, only humans migrated to all corners of the earth and domesticated other species, leading to the emergence of complex societies. Investigations into human genomes have shown that they are a rich source of information for insights into our past. However, for a complete understanding of human evolution it is necessary to look beyond our own genomes. This thesis is about using comparative genomics to place human evolution within a wider context by studying adaptation in our closest living relatives and in the species that we domesticated. In the first study, I investigate the genetic changes involved in the earliest stages of dog domestication. Using a global sample of dog and wolf genomes I identify regions that are highly diverged between these species. I find that selection in the initial stages of dog domestication likely involved genes involved in the fight-or-flight response, advancing our understanding of this process. In the second study, I look for commonalities in the genetic changes that occurred during animal domestication across species. I compare genome sequences from experimentally and historically domesticated species. I identify genes and variants that may underlie the phenotypic changes that occurred during domestication. I find evidence of biological pathways that appear to always be involved in the domestication process. In the third study, I characterise the signatures of natural selection in all major Hominidae lineages using population genomic data. I find that most signatures of positive selection are species specific, although some loci appear to be selected across several lineages. I determine that the efficacy of selection varies between species and is significantly correlated with long-term effective population size. These results contribute to a more complete understanding of human evolution. i This thesis is based on the following manuscripts: 1. Cagan A & Blass T. (2016) Identification of genomic variants putatively targeted by selection during dog domestication. BMC Evolutionary Biology,16:1. 2. Cagan A, Albert FW, Plyusnina I, Trut L, Renaud G, Romagné F, Wiebe V, Kozhemjakina R, Gulevich R, Trapezov O, Yudin N, Alekhina T, Aitnazarov R, Trapezova L, Herbeck Y, Schöneberg T, Pääbo S. Genes and pathways selected during animal domestication. Submitted to eLife. 3. Cagan A, Theunert C, Laayouni H, Santpere G, Pybus M, Casals F, Prüfer K, Navarro A, Marques-Bonet T, Bertranpetit J, Andrés AM. (2016). Natural Selection in the Great Apes. Molecular Biology and Evolution, 33:3268-3283.:Summary 1 Zusammenfassung 8 Chapter 1 Identification of genomic variants putatively targeted by selection during dog domestication 16 Chapter 2 Genes and pathways selected during animal domestication 38 Chapter 3 Natural Selection in the Great Apes 73 References 149 Acknowledgments 152 Curriculum Vitae 153 Declaration of Independence 156 Author Contribution Statements 157

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Stephen Jay Gould, a great scientist and evolutionary biologists, suggested that if we could replay the tape of life, we would not have observed similar course of events because evolution is stochastic and if affected by several events. Since then, the possibility that evolution is repeatable or predictable has been debated. Studies using large-scale evolution experiments, long-term data for individual populations, and controlled experiments in nature, have demonstrated phenotypic and genetic convergence in several taxa. These studies suggest that despite some randomness, predictable evolutionary patterns can emerge on a large temporal and spatial scale. However, a few cases also exist where evolution is unpredictable and stochastic. One way to understand evolutionary predictability better can be to have quantitative estimates of predictability at different heirarchical levels (mutations, genetic, phenotypic). This can help better understand if evolution is predictable and the extent to which it is predictable. My dissertation uses Lycaeides butterflies to identify and quantify evolutionary predictability in different contexts such as on a geographic scale, temporal scale and genomic scale. I accomplished this by sequencing and annotating the genomes of these butterflies across a vast geographic range and on a temporal scale and by comparing natural and experimental populations. My results show that different mechanisms can assist evolution of organisms to adapt to novel environmental challenges, and that the evolutionary changes can be somewhat predictable. Through this work I demonstrate three main findings: first, quantitative estimates of evolutionary predictability indicate that degree of predictability is variable and is highly context-dependent. Second, we can predict evolutionary patterns on a spatial as well as temporal scale, and can predict patterns in nature by controlled laboratory experiments. Additionally, genomic changes underlying repeatability vary across the genome. Lastly, the approach of quantifying predictability can help us better understand the mechanisms which drive evolution and how organisms will evolve in response to similar environmental pressures. These results suggest that evolution can be constrained and if we actually replay the tape of life, we could see a considerably similar outcome in biodiversity compared to what Gould predicted.

Diseases caused by Edwardsiella spp. are responsible for significant losses in wild and cultured fishes around the world. Historically, Edwardsiella tarda has been considered the most phenotypically and genotypically heterogeneous member of the genus. Investigations into intraspecific variability of E. tarda demonstrated isolates previously classified as E. tarda actually represent three genetically distinct yet phenotypically ambiguous groups, leading to the adoption of E. piscicida and E. anguillarum as discrete taxa. Current genomic investigations have demonstrated significant differences between these organisms. To this end, real-time quantitative PCR assays were developed to quickly and accurately detect the pathogens in pond water, fish tissue and broth culture. Additionally, whole genome sequencing was performed for representative isolates of each Edwardsiella spp. Furthermore, forty-seven Edwardsiella isolates, representing all five taxa, from different hosts and a wide temporal and geographic range were analyzed using commercial microbial identification kits, repetitive sequence-mediated polymerase chain reaction, fatty acid methyl ester analysis, antimicrobial resistance profiles, in addition to 16S, gyrB, sodB and plasmid sequencing. This analysis demonstrated key differences in gene sequences and plasmid profiles among these important bacterial pathogens and further supported contemporary taxonomic classifications. Additionally, a real-time multiplex PCR was developed to accurately discriminate between all Edwardsiella spp. affecting fish; namely E. ictaluri, E. piscicida, E. tarda and E. anguillarum. Moreover, recent publications suggest E. piscicida is more commonly associated with disease outbreaks in Mississippi catfish aquaculture than E. tarda or E. anguillarum. To this end, several different challenge models were evaluated. Comparative virulence was assessed, along with histopathological lesions and posterior kidney clearance rates in channel catfish (Ictalurus punctatus). Diagnostic case submissions suggest E. piscicida is more commonly associated with disease outbreaks in blue catfish (Ictalurus furcatus) x channel catfish hybrids compared to channel catfish. This led to investigations into the relative pathogenicity of E. piscicida in hybrid and channel catfish, which demonstrated a significantly lower median lethal dose (LD50) for E. piscicida in hybrid catfish; an important finding given the increased production of hybrid catfish in U.S. farm-raised catfish in the southeastern United States.

We studied root kinematics in relation to temperature and genome size variation in teosinte (Zea mays subspecies parviglumis) and corn (Zea mays subspecies mays). Corn had significantly faster radicle growth than teosinte when grown at a constant temperature. Both species exhibited variation in seed size and for each species larger seeds had faster root growth. Genome size was not significantly correlated with faster radicle growth rates across multiple land races of corn. To examine temperature dependent growth in corn and teosinte, a germinated seedling was grown at multiple temperatures. Growth rates at these temperatures were used to fit a temperature response model for each species. Parameters of this model (maximum growth temperature and optimum growth temperature) were not significantly different between the species.