<p>Fungi display diverse growth forms. Some grow as unicellular yeasts, some grow as multicellular hyphae, while others switch between these two growth forms, i.e., the dimorphic fungi. Dimorphism is found in many pathogenic fungi, and it is thought to be a strategy to maximize their fitness during different stages of life cycles. The corn smut fungus <i>Ustilago maydis</i> serves as a renowned model organism for studying fungal dimorphism and its role in pathogenesis. However, knowledge only from the model species may not be expanded to other species unless multispecies studies have been demonstrated. In this dissertation, I performed comparative analyses to examine if knowledge from <i>U. maydis</i> is translational to other dimorphic fungi. First, a physiological study was conducted to find what can serve as a common signal for dimorphic transition of several Ustilaginomycotina species. I found that the lipid serves as a potential common cue for yeast-to-hyphal transition in most dimorphic species, while alternate types of energy-source carbohydrate do not affect fungal dimorphism. In addition, pectin and high temperature can also trigger filamentous growth in some Ustilaginomycotina species. Second, I performed comparative transcriptomics to determine if a mechanism for yeast-to-hyphal dimorphic transition is conserved across multiple dimorphic species. Three species of Ustilaginomycotina (<i>U. maydis</i>, <i>Tilletiopsis washingtonensis </i>and <i>Meira miltonrushii</i>) plus one species from Ascomycota (<i>Ophiostoma novo-ulmi</i>) were included in the analyses. I found that the similarity of transcriptomic alteration is not dependent on phylogenetic relatedness. Genes in amino acid transport and metabolism, energy production and conversion and cytoskeleton are commonly altered during the dimorphic transition of all studied species. Moreover, I discovered several core genes which can play a conserved role in transducing signals for the dimorphic transition. Finally, I performed comparative analyses of 190 fungal genomes to determine genomic properties that are associated with types of fungal growth form. I found that small genome size is a characteristic for yeast-like fungi. Few indicator genes, such as genes encoding proteins in the NADPH oxidase complex and cytoskeletons, which are predominantly lost in yeast-like fungi in both Ascomycota and Basidiomycota. However, many other genes are associated with types of growth form in a lineage-specific manner. Findings from this dissertation will serve as fundamentals for future research in fungal cell biology, especially in fungal dimorphism. Additionally, results from this study suggest cautions when extrapolating results from model species onto non-model species.</p>

Amphibians face an unknown future in a time of rapid environmental change due to global climate perturbations. Since amphibians are perceived to be indicators of ecosystem health, understanding the causes of their declines can improve our perception of threats to other species. Molecular techniques have allowed us to explore how environmental change affects genetic variation and to predict evolutionary adaptive potential of amphibian populations. The identification of populations with the greatest potential to respond to changing environmental variables may be an important conservation strategy to aid in future management efforts. I utilized targeted exon capture sequencing to identify adaptive variation in California tiger salamanders (CTS; Ambystoma californiense), a species threatened by land use change and hybridization with barred tiger salamanders (A. mavortium). I identified 17 and 26 outlier loci for balancing selection in historic and recent samples of CTS respectively. The outlier loci corresponded to genes of various functions, though none of the outliers associated significantly with the change in several tested environmental variables. Despite the lack of environmental correlations detected, it must also be considered that the outlier loci could be involved in epistatic interactions where many genes with small effects influence a single phenotype with fitness benefits. Additional hypotheses to explain the observed changes in allele frequencies and outliers may be the effects of UV-B radiation, pesticide use, or indirect effects of climate change.

High-throughput genomic data contain gazillion of information that are influenced by the complex biological processes in the cell. As such, appropriate mathematical modeling frameworks are required to understand the data and the data generating processes. This dissertation focuses on the formulation of mathematical models and the description of appropriate computational algorithms to obtain insights from genomic data. Specifically, characterization of intra-tumor heterogeneity is studied. Based on the total number of allele copies at the genomic locations in the tumor subclones, the problem is viewed from two perspectives: the presence or absence of copy-neutrality assumption. With the presence of copy-neutrality, it is assumed that the genome contains mutational variability and the three possible genotypes may be present at each genomic location. As such, the genotypes of all the genomic locations in the tumor subclones are modeled by a ternary matrix. In the second case, in addition to mutational variability, it is assumed that the genomic locations may be affected by structural variabilities such as copy number variation (CNV). Thus, the genotypes are modeled with a pair of (Q + 1)-ary matrices. Using the categorical Indian buffet process (cIBP), state-space modeling framework is employed in describing the two processes and the sequential Monte Carlo (SMC) methods for dynamic models are applied to perform inference on important model parameters. Moreover, the problem of estimating gene regulatory network (GRN) from measurement with missing values is presented. Specifically, gene expression time series data may contain missing values for entire expression values of a single point or some set of consecutive time points. However, complete data is often needed to make inference on the underlying GRN. Using the missing measurement, a dynamic stochastic model is used to describe the evolution of gene expression and point-based Gaussian approximation (PBGA) filters with one-step or two-step missing measurements are applied for the inference. Finally, the problem of deconvolving gene expression data from complex heterogeneous biological samples is examined, where the observed data are a mixture of different cell types. A statistical description of the problem is used and the SMC method for static models is applied to estimate the cell-type specific expressions and the cell type proportions in the heterogeneous samples.

Coregonines, including cisco (Coregonus artedi), kiyi (Coregonus kiyi), and bloater (Coregonus hoyi), are a focus for prey fish conservation and restoration efforts throughout the Laurentian Great Lakes. However, fundamental questions about coregonine ecology and genetics remain. For example, we know little about how the early life stages of coregonines respond to environmental change at either the genotypic or phenotypic level. We also have limited knowledge about how to identify different species at the larval stage and the genetic relationships among species, which makes the different species difficult to study at the larval stage. To increase the probability for success in restoration efforts, current and future research need to integrate traditional and novel approaches to better understand what leads to current and future coregonine successes. We used DNA and RNA omics tools, genomics and transcriptomics to boost our comprehension of current coregonine populations and to help understand how C. artedi may respond to environmental change. During the winter of 2017, we conducted a pilot experiment to evaluate how C. artedi eggs may respond to increased light exposure resulting from current and expected reductions in annual ice and snow cover due to global warming. We used transcriptomics to assess differences in gene expression between a continuous light and continuous dark treatment. Our results indicate that light is an environmental factor that could lead to earlier hatch dates, smaller yolk sacs, changes in mortality and differential gene expression in metabolic related and other functionally important genes. In 2018, we sampled larval coregonines in the Apostle Islands of Lake Superior each week from hatch in May until late July. We used genomic sequencing to genetically identify 197 larvae to species: C. artedi, C. hoyi, and C. kiyi. The larval demographic characteristics of each species was assessed and revealed that length ranges, growth rates, yolk sac condition, and effective population size varied among species. Larvae of all three species were found throughout the entirety of the Apostle Islands and the genetic diversity within each species appears high. The results from our pilot experiment and field observations help advance our understanding of the important early life stages of coregonines and how changes in light exposure or growth rates could affect their success or failure in a changing climate.

Domesticated species are vital to global food security and have also been foundational to the formulation and advancement of evolutionary theory. My dissertation employs emerging molecular genomic tools to provide an evolutionary context for crop improvement. I begin by providing a contemporary perspective on two components of domestication biology that have long been used to improve crop production: wild relatives of crop species and grafted rootstocks. First, I propose a method to systematically introgress crop wild relative diversity into crop breeding programs. Then, I explore rootstocks, the lesser-known half of the perennial crop equation, documenting prevalence and diversity, cataloging rootstock traits under selection, and discussing recent advances in rootstock biology. Both crop wild relatives and rootstocks remain largely underutilized resources and hold great promise for agricultural innovation. While humans have domesticated thousands of plant species, research has largely focused on annual crops, to the exclusion of perennials. To improve our understanding of how tree species respond to domestication, I examine the evolution and domestication of one of the world’s most important perennial tropical fruit crops, the mango, Mangifera indica, and its wild and semi-domesticated relatives. I generated a dataset suitable for studying Mangifera across evolutionary time using double digest restriction site associated DNA sequencing (ddRADseq). I present a multilocus phylogeny that informs the classification of Mangifera and reveals, for the first time, the evolutionary relationships of wild, semi-domesticated, and domesticated species in the genus. Narrowing my focus to the intraspecific level, I examine how the introduction of M. indica into regions of the world impacted its genetic diversity. My results show M. indica maintained high levels of genetic diversity during its introduction into the Americas. However, the novel diversity I detect in Southeast Asian mango cultivars suggests that M. indica has a more complex domestication history than previously assumed. I also find evidence that M. indica hybridized with multiple congeners following its introduction into Southeast Asia, forming two hybrid lineages that may be maintained by clonal polyembryonic reproduction. Collectively, my research provides a comprehensive framework for understanding the evolution and domestication of a tropical tree crop of global economic importance.

reinhardtii, a unicellular green alga, is a model organism to study the circadian clock. Cryptochromes are the blue light photoreceptors that entrain the clock in some organisms. The CPH1 protein of C. reinhardtii resembles the cryptochromes of the plant model Arabidopsis, but whether CPH1 entrains the circadian clock in C. reinhardtii is not yet known. Recent reports have suggested the existence of one more cryptochrome in C. reinhardtii, which resembles the cryptochromes of animals. However, the amino acid sequence of this protein shows even higher sequence similarity with the 6-4 DNA photolyase of Arabidopsis. DNA photolyases are involved in the repair of UV light-induced DNA damage using the energy of blue light. In order to determine, if the “animal cryptochrome” gene of C. reinhardtii actually encodes a 6-4 DNA photolyase rather than a photoreceptor, an experimental design was developed to test whether the protein product is able to rescue an E. coli mutant defective in its DNA photolyase gene. The design is as follows: In a first step, the coding region of the “animal cryptochrome” cDNA is cloned. In a second step, the cDNA is inserted in-frame into an E. coli expression vector. In a third step, the construct is transformed into an E. coli photolyase mutant, its expression induced, and the strain tested for better survival after UV light exposure. To accomplish the first step, the cloning of “animal cryptochrome” cDNA, total RNA was successfully extracted from C. reinhardtii 4 hrs into the light phase of a 12 h light/12 h dark cycle and reverse transcribed into cDNA using oligo(dT) primers. After initially unsuccessful attempts at amplifying animal cryptochrome from cDNA or genomic template with a variety of primers and conditions, a short fragment with the expected size of 186 bp was amplifiable with both templates. However, even this fragment was not reliably obtained in every PCR assay. Because of this difficulty, real-time PCR was finally performed in the presence of DMSO (Dimethylsulfoxide) and Betaine. These two adjuvants were reported to improve amplifications particularly for GC-rich templates. C. reinhardtii DNA is especially GC-rich with an average of 64% Gs and Cs. The improved conditions allowed the reliable amplification of the 186 bp fragment from genomic template. It also enabled the amplification of a larger fragment of 528 bp from the same template. The results suggest that a combination of 5% DMSO and 1M Betaine is optimal for the amplification of C. reinhardtii DNA and thus can serve as the basis for successful amplification of the entire 1788 bp coding region of the animal cryptochrome cDNA.

High-throughput genome processing, sophisticated protein sequence analysis, programming, and information management were used to achieve two major advances in the comparative genomics of microbial signal transduction. First, an integrated and flexible bioinformatics platform and the Microbial Signal Transduction database (MiST) were developed, which facilitated the genome-wide analysis of bacterial signal transduction. This platform was used successfully for the high-throughput identification and classification of signal transduction proteins in more than 300 archaeal and bacterial organisms. Second, analysis of information encoded in prokaryotic genomes revealed that the majority of signal transduction systems consist of one-component systems a single protein containing both input and output domains but lacking phosphotransfer domains typical of two-component systems. The prevalence of one-component systems is a paradigm-shifting discovery because two-component systems are currently viewed as the primary mode of signal transduction in prokaryotes. One-component systems are more widely distributed among bacteria and archaea and display a greater diversity of domains than two-component systems. Additionally, in-depth bioinformatic analyses were performed that further characterized the function of two, input, signaling domains. In summary, this systematic, high-throughput delineation of microbial signal transduction is another step forward in our understanding of the genomic basis of life.

Bacteria evolve during the colonization of human hosts, yet little is known about the selective pressures and evolutionary forces that shape this evolution. Illumination of these processes may inspire new therapeutic directions for combating bacterial infections and promoting healthy bacteria-host interactions. The advent of high-throughput sequencing has enabled the identification of mutations that occur within the human host, and various tools from computational and evolutionary biology can aid in creating biological understanding from these mutations. Chapter 1 describes recent progress in understanding within-patient bacterial adaption, focusing on insights made from genomic studies.

The sea lamprey (Petromyzon marinus) undergoes programmed genome rearrangements (PGRs) during embryogenesis that results in the deletion of ~0.5 Gb of germline DNA from the somatic lineage. The underlying mechanism of these rearrangements remains largely unknown. miRNAs (microRNAs) and piRNAs (PIWI interacting RNAs) are two classes of small noncoding RNAs that play important roles in early vertebrate development, including differentiation of cell lineages, modulation of signaling pathways, and clearing of maternal transcripts. Here, I utilized next generation sequencing to determine the temporal expression of miRNAs, piRNAs, and other small noncoding RNAs during the first five days of lamprey embryogenesis, a time series that spans the 24-32 cell stage to the formation of the neural crest. I obtained expression patterns for thousands of miRNA and piRNA species. These studies identified several thousand small RNAs that are expressed immediately before, during, and immediately after PGR. Significant sequence variation was observed at the 3’ end of miRNAs, representing template-independent covalent modifications. Patterns observed in lamprey are consistent with expectations that the addition of adenosine and uracil residues plays a role in regulation of miRNA stability during the maternal-zygotic transition. We also identified a conserved motif present in sequences without any known annotation that is expressed exclusively during PGR. This motif is similar to binding motifs of known DNA binding and nuclear export factors, and our data could represent a novel class of small noncoding RNAs operating in lamprey.

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