Mutation is the source of heritable variation of genotype and phenotype, on which selection may act. Mutation rates describe a fundamental parameter of living things, which influence the rate at which evolution may occur, from viral pathogens to human crops and even to aging cells and the emergence of cancer. An understanding of the variables which impact mutation rates and their estimation is necessary to place mutation rate estimates in their proper contexts. To better understand mutation rate estimates, this research investigates the impact of temperature upon transcription rate error estimates; the impact of growing cells in liquid culture vs. on agar plates; the impact of many in vitro variables upon the estimation of deoxyribonucleic acid (DNA) mutation rates from a single sample; and the mutational hazard induced by expressing clustered regularly interspaced short palindromic repeat (CRISPR) proteins in yeast. This research finds that many of the variables tested did not significantly alter the estimation of mutation rates, strengthening the claims of previous mutation rate estimates across the tree of life by diverse experimental approaches. However, it is clear that sonication is a mutagen of DNA, part of an effort which has reduced the sequencing error rate of circle-seq by over 1,000-fold. This research also demonstrates that growth in liquid culture modestly skews the mutation spectrum of MMR- Escherichia coli, though it does not significantly impact the overall mutation rate. Finally, this research demonstrates a modest mutational hazard of expressing Cas9 and similar CRISPR proteins in yeast cells at an un-targeted genomic locus, though it is possible the indel rate has been increased by an order of magnitude.

Phenotypic evolution is of great significance within biology, as it is the culmination of the influence of key evolutionary factors on the expression of genotypes. Deeper studies of the fundamental components, such as fitness effects of mutations and genetic variance within a population, allow one to predict the evolutionary trajectory of phenotypic evolution. In this regard, how much the change in mutational variance and the ongoing natural selection influence the rate of phenotypic evolution has yet to be fully understood. Therefore, this study measured mutational variances and the increasing rate of genetic variance during the experimental evolution of Escherichia coli populations, focusing on two growth-related traits, the populational maximum growth rate and carrying capacity. Mutational variances were measured by mutation-accumulation experiments, which allowed for the analysis of the effects of spontaneous mutations on growth-related traits in the absence of selection. This analysis revealed that some evolved populations developed a higher mutational variance for growth-related traits. Further investigation showed that most evolved populations have also developed a greater mutational effect, which could explain the increase in mutational variance. Finally, the genetic variances for most evolved populations are lower than expected in the absence of selection, and the involvement of either stabilizing or directional selection is evident. Future experiments with a larger sample size of experimentally evolved populations, as well as more intermediate timepoints during experimental evolution, may provide further insight regarding the complexities of the evolutionary outcomes of these traits.

Embryonic and juvenile development consist of a series of complex and rapid changes driven by a suite of crucially timed developmental cues within the cell. The developmental process begins at the moment of zygote activation, “jump-started” by maternal factors such as mRNA and proteins until transcription can be zygotically-driven. Regulation of transcription initiation plays a crucial role in this process, as minute changes in the timing, density, and characteristics of gene expression can have drastic effects on the zygote’s development. Specific promoter elements can be linked to different patterns of transcription, driving both ubiquitous and sharply regulated gene expression, thus forming the basis for the time-sensitive developmental processes. In order to better understand the genes expressed during different stages of development and the impact of promoter elements on transcription patterns and transcript concentrations within the cell, I created a Gene Expression and Promoter Atlas in two species within the cryptic species complex, Daphnia pulex. I surveyed five embryonic and two juvenile developmental stages in both a North American and mitochondrially European Daphnia pulex utilizing developmental landmarks to visually stages embryos. A total of 17,993 genes were identified in the European species and 15,295 were identified in the North American species, with 11,551 orthologs identified between the two. I utilized the transcription start site (TSS) profiling method STRIPE-seq to identify promoter motifs and RNA-seq to survey mRNA concentration at each stage, generating a wealth of genetic data. The methodology for library construction and the dataset generated therein provide an informative basis for further comparative developmental studies and the elucidation of full gene functionality in an emerging model organism.

I studied the evolution and cell biology of Paramecium tetraurelia—a model ciliate with over 40,000 distinct protein-coding genes resulting from as many as three ancient whole-genome duplication events. I was interested in the functional diversification of these gene duplicates at the level of protein localization, but the commonly used tools to study this were tedious. I instead applied a protein-correlation profiling approach to this system by way of generating a dozen sub-cellular fractions with different protein constituents due to the density of their resident organelle and then assayed these fractions using quantitative mass spectrometry. Each protein’s unique abundance profile provided evidence for its subcellular localization, and I used both supervised and unsupervised classification algorithms to cluster proteins together based on the similarity of these profiles to several hundred “marker proteins” which I manually curated. After expanding the protein inventory for numerous organelles by as many as a thousand proteins, I determined many features not previously understood or appreciated such as mosaic biochemical pathways, evidence for differential sorting mechanisms, and the abnormal evolutionary patterns of the mitochondrial proteome of ciliates. I developed a simple bioinformatic tool to probe spatial proteomics datasets more easily for proteins of interest. I demonstrate its applicability using a handful of well-characterized proteins in the budding yeast Saccharomyces cerevisiae as well as interesting proteins in less well-studied model systems like P. tetraurelia and the apicomplexan Toxoplasma gondii to both recapitulate known interactions and discover new ones. Finally, I look for large-scale evidence of gene duplicates relocalizing to new cellular compartments in P. tetraurelia and S. cerevisiae using this new dataset and a previously generated one, respectively. I find thousands of pairs of duplicates which are differentially identified and display evidence for subcellular divergence, and this seems to be largely decoupled from large changes in protein sequence but are instead associated with indels in their N-terminal peptide. These findings support the use of high-throughput proteomic techniques to determine evidence of functional divergence of gene duplicates. Taken together, this works provides a deep characterization of one of the largest unicellular proteomes in nature.

Different populations of evolved E.coli and their ancestors were grown in a variety of single amino acid environments to determine their ability to use that amino acid as a carbon source. Some evolved lines were able to grow in amino acids that their ancestors weren't able to. The source of this change in amino acid growth was investigated by testing uptake, searching for candidate mutations, and comparing growth rates of populations with and without certain mutations.

Mutation rate is the rate of appearance for mutations to occur in a living organism. Studying and quantifying mutation rates and their evolution is important because mutations are the ultimate source of genetic variation and one of the reasons why evolution occurs. Much of the current research has investigated the mutational rate increase. The evolution of reduced mutation rate, which can be favored by natural selection because the accumulation of too many mutations can be deleterious and result in death, is less studied. Therefore, this study will be focused on antimutators, which are mutations that result in a lowering of the mutation rate. Using Escherichia coli K-12 str. MG1655 as a model system, the effects and reasons for how MMR- background E. coli evolves lower mutation rates were studied. Here we show that the candidate antimutator in dnaE lowers the mutation rate in an experimentally evolved population of E. coli with MMR- background by using a mutation rate assay to demonstrate the difference between populations with and without the antimutator candidate. The results also suggest the importance of an antimutator for populational survival.

Regulation of transcription initiation is a critical factor in the emergence of diverse biological phenotypes, including the development of multiple cell types from a single genotype, the ability of organisms to respond to environmental cues, and the rise of heritable diseases. Transcription initiation is regulated in large part by promoter regions of DNA. The identification and characterization of cis-regulatory regions, and understanding how these sequences differ across species, is a question of interest in evolution. To address this topic, I used the model organism Daphnia pulex, a well-characterized microcrustacean with an annotated genome sequence and selected a distribution of well-defined populations geographically located throughout the Midwestern US, Oregon, and Canada. Using isolated total RNA from adult, female Daphnia originating from the selected populations as well as a related taxon, Daphnia pulicaria (200,000 years diverged from D. pulex), I identified an average of over 14,000 (n=14,471) promoter regions using a novel transcription start site (TSS) profiling method, STRIPE-seq. Through the identification of sequence architecture, promoter class, conservation, and transcription start region (TSR) width, of cis-regulatory regions across the aforementioned Daphnia populations, I constructed a system for the study of promoter evolution, enabling a robust interpretation of promoter evolution in the context of the population-genetic environment. The methodology presented, coupled with the generated dataset, provides a foundation for the study of the evolution of promoters across both species and populations.

Many factors are at play within the genome of an organism, contributing to much of the diversity and variation across the tree of life. While the genome is generally encoded by four nucleotides, A, C, T, and G, this code can be expanded. One particular mechanism that we examine in this thesis is modification of bases—more specifically, methylation of Adenine (m6A) within the GATC motif of Escherichia coli. These methylated adenines are especially important in a process called methyl-directed mismatch repair (MMR), a pathway responsible for repairing errors in the DNA sequence produced by replication. In this pathway, methylated adenines identify the parent strand and direct the repair proteins to correct the erroneous base in the daughter strand. While the primary role of methylated adenines at GATC sites is to direct the MMR pathway, this methylation has also been found to affect other processes, such as gene expression, the activity of transposable elements, and the timing of DNA replication. However, in the absence of MMR, the ability of these other processes to maintain adenine methylation and its targets is unknown.
To determine if the disruption of the MMR pathway results in the reduced conservation of methylated adenines as well as an increased tolerance for mutations that result in the loss or gain of new GATC sites, we surveyed individual clones isolated from experimentally evolving wild-type and MMR-deficient (mutL- ;conferring an 150x increase in mutation rate) populations of E. coli with whole-genome sequencing. Initial analysis revealed a lack of mutations affecting methylation sites (GATC tetranucleotides) in wild-type clones. However, the inherent low mutation rates conferred by the wild-type background render this result inconclusive, due to a lack of statistical power, and reveal a need for a more direct measure of changes in methylation status. Thus as a first step to comparative methylomics, we benchmarked four different methylation-calling pipelines on three biological replicates of the wildtype progenitor strain for our evolved populations.
While it is understood that these methylated sites play a role in the MMR pathway, it is not fully understood the full extent of their effect on the genome. Thus the goal of this thesis was to better understand the forces which maintain the genome, specifically concerning m6A within the GATC motif.

Phenotypic evolution is an essential topic within the general field of evolution. Theoretically, the outcome of phenotypic evolution may be influenced by factors such as genetic background and the interaction of natural selection and genetic drift. To gain empirical evidence for testing the effects of those factors, we used eight long-term evolved Escherichia coli populations as a model system. These populations differ in terms of genetic background (different mutation rates) as well as bottleneck size (small- and large-magnitude). Specifically, we used a plate reader to measure three growth-related traits: maximum growth rate (umax), carrying capacity (Kc), and lag time (Lt) for 40 clones within each population. For each trait we quantified the change in mean per generation, the change in variance per generation, and the correlation coefficient between pairs of traits. Interestingly, we found that the small and large bottleneck populations of one background displayed clear, distinguishing trends that were not present within the populations of the other background. This leads to the conclusion that the influence of selection and drift on a population’s phenotypic outcomes is itself influenced by the genetic background of that population. Additionally, we found a strong positive correlation between umax and Kc within each of the high-mutation populations that was not consistent with our neutral expectation. However, the other two pairs did not exhibit a similar pattern. Our results provide a novel understanding in the relationship between the evolution of E. coli growth-related phenotypes and the population-genetic environment.