Mutations in the telomere length maintenance pathway can lead to a spectrum of diseases called telomere syndromes, however, the pathway is not fully understood and there may still be unknown components. We designed a forward genetic screen to identify new genes involved in telomere length maintenance. Of the top ranked genes, ZNF827, a zinc finger protein, is the most promising candidate gene. The possible discovery of a new component involved in telomere length maintenance increases our understanding of the pathway and opens new avenues of research. Recent advances in molecular biology techniques, such as the use of RNA-guided nuclease CRISPR associated protein 9 (Cas9), have made screens like this possible. Cas9 is a nuclease that uses a guide RNA(gRNA) to direct its endonuclease activity. The use of Cas9 has revolutionized the field of genome engineering, providing scientists with more efficient methods to knockout and modify genomes. We sought to optimize CRISPR-Cas9 genome editing to make it as widely accessible as possible. We compared plasmid, ribonucleoprotein (RNP), and RNA only lipid-mediated transfection of CRISPR-Cas9 into cell lines using a novel reporter system to measure genome editing efficiency. All methods were successful to some extent, however, RNP lipofection was the most efficient and has many advantages over other methods. We also found that short homology arms of 30-35bp on donor templates was able to mediate site specific editing. These methods should broaden the accessibility of CRISPR-Cas9 genome editing.

Maternal binge alcohol consumption has been linked to congenital birth defects in the fetus. Said defects include abnormalities in heart development, a category of disease referred to as Congenital Heart Disease. Given the prevalence of Congenital Heart Disease, with a study showing around 49.9% of women having at least participated in binge alcohol consumption at least once during the early stages of their pregnancy and Congenital Heart Disease being linked to various complications in adulthood, this is a topic relevant to the clinical setting. Alcohol consumption has been linked to decreases in DNA methylation, which generally increases transcriptional expression of nearby genes. This thesis will focus on how alcohol affects the genomic-wide epigenetics of the embryonic heart with the aim of identifying specific genes and sites within those genes that are affected by alcohol exposure in utero. We hypothesize that embryonic mouse hearts exposed to ethanol will show a differential methylation pattern characteristic of hypomethylation versus control hearts not exposed to ethanol. To test this hypothesis, we used oral gavage to administer ethanol to pregnant mice at embryonic age E9.5 (a time associated with heart chamber formation). Maternal mice were sacrificed at E11.5, embryonic hearts were removed, and DNA was extracted for further experimentation with whole genome bisulfite sequencing. Analysis of whole genome bisulfite sequencing data showed a slight trend towards hypomethylation but suggested no significant changes in the overall methylation pattern in embryonic mouse hearts at the genomic level, but we have independently identified several genes whose expression is depressed in the embryonic mouse following a single maternal binge ethanol dose at E9.5, and thus we are investigating potential alcohol-induced DNA methylation alterations in specific target genes of interest. Future investigations into gene and site-specific DNA methylation profiles as well as other epigenetic modifications should prove useful in our quest to learn how maternal alcohol consumption causes cardiac malformations leading to congenital heart disease.

The complete genomic sequence of Rhizobium leguminosarum ATCC 14479 has been determined. Its genome size is 7,935,223 base-pairs of DNA (bp). This multipartite genome contains 5 distinct replicons: a chromosome of 4,883,137 bp and four mega-plasmids of size 1,234,209 bp, 415,988 bp, 771,583 bp, and 630,306 bp. In silico (literally: on computer) analysis was done on the complete genome to detect genes relating to iron metabolism by bacteria. Seven iron-related operons and genes were found: nodulation genes, the Tol operon, the hmuPSTUV operon, iron response regulator genes, the cycHJKL operon, genes for bacterial cyclic glucans, and vicibactin genes.

Whole genome duplication, or polyploidy, is a common process in plants by which failures in meiosis or fertilization result in offspring with twice the number of chromosomes. This doubles the number of copies of every gene, an effect thought to generate new ‘raw material' upon which natural selection can act. Few studies exist examining the consequences of polyploidy for plant physiological traits. Doubling the number of gene copies may have unknown effects on leaf structure and function. In this study, I compare diploid, tetraploid, and hexaploid species within the genus Helianthus (wild sunflowers). Forty different accessions of wild sunflowers were grown under standardized greenhouse conditions and phenotyped for both leaf functional traits and leaf hyperspectral reflectance. Interestingly, I find that whole genome duplication can have effects on leaf functional traits relevant to both size and ecophysiology, and thus that polyploidy may lead to functional trait differentiation between polyploids and their diploid progenitors.

Metagenomics is a cultivation-independent approach for obtaining the genomic composition of microbial communities. Microbial communities are ubiquitous in nature. Microbes which are associated with the human body play important roles in human health and disease. These roles span from protecting us against infections from other bacteria, to being the causes of these diseases. A deeper understanding of these communities and how they function inside our bodies allows for advancements in treatments and preventions for these diseases. Recent developments in metagenomics have been driven by the emergence of Next-Generation Sequencing technologies and Third-Generation Sequencing technologies that have enabled cost-effective DNA sequencing and the generation of large volumes of genomic data. These technologies have allowed for the introduction of hybrid DNA assembly techniques to recover the genomes of the constituent microbes. While Next-Generation Sequencing technologies use paired-end sequencing reads from DNA fragments into short reads and have a relatively lower error rate, Third-Generation Sequencing technologies use much longer DNA fragments to generate longer reads, bringing contigs together for larger scaffolds with a higher error rate. Hybrid assemblers leverage both short and long read sequencing technologies and can be a critical step in the advancements of metagenomics, combining these technologies to allow for longer assemblies of DNA with lower error rates. We evaluate the strengths and weaknesses of the hybrid assembly framework using several state-of-the-art assemblers and simulated human microbiome datasets. Our work provides insights into metagenomic assembly and genome recovery, an important step towards a deeper understanding of the microbial communities that influence our well-being.

No description available.

The metritis complex (MC), characterizing post-partum uterine diseases in dairy cattle has negative implications on animal welfare, production efficiency, and the economic stability of the dairy industry. The studies in this thesis aimed to investigate the genetic architecture of the metritis complex and identify genomic regions and metabolites associated with the development of MC. Thereby enhancing our understanding of the biological pathways and molecular mechanisms involved in the pathophysiology of MC during the transition period in Jersey and Holstein dairy cattle. Chapter 2 sheds light on the previous work done on MC. The goals of this review were to (1) provide an updated epidemiological profile of uterine ailments, (2) integrate results from genomics, transcriptomics, metabolomics, and proteomics (OMICs) studies to reveal insights on the identified biological pathways modulated during the transitional period and the onset of metritis, and (3) discuss the commonly detected molecular mechanisms in OMICs studies. Chapter 3 utilized genomic profiles to identify genetic variants, genes, and biological pathways that modulate MC development. A genome-wide association study (GWAS) was performed using a single locus mixed linear model on 1,967 Holstein and Jersey cow genotypes (624,460 SNPs), and MC records from three dairy herds. Following this, in-silico functional and gene network analyses were performed to detect biological mechanisms and pathways linked to the development of endometritis, metritis, and pyometra, diseases defined under the metritis complex development. Potential genes were significantly (P ≤ 0.0001) associated with MC and located on chromosomes 12, 10, and 21. These genes are involved in potential metabolic pathways which are directly associated with the mode of transmission for well-known pathogens in the metritis complex. Chapter 4 followed the GWAS with a high-throughput liquid chromatography-mass spectrometry (LC-MS) metabolomic study. The goals of this study were to 1) to identify metabolites associated with the development of MC in multi-parous Jersey and Holstein cows, 2) to detect the molecular pathways linked to the identified metabolites for MC, and 3) and to identify potential metabolomic biomarkers for early detection of uterine disease development in dairy cattle following parturition. A case-control design was employed on transitioning dairy cattle (n=28), at three time points (week 1, 2, and 3 post-calving). The study identified 48 significant (at false discovery rate adjusted P≤0.05) metabolic deviations for MC during the second week post-partum using single point t-test model. Using repeated measurement, 50 metabolites were identified as significant across all three time points. The results from the studies done revealed mechanisms contributing to the development of uterine disease in Jersey and Holstein breeds. These results should be validated and may be used as genomic selection or management tool to decrease the incidence of metritis complex in dairy cattle.

<p dir="ltr">Spotted Turtle (Clemmys guttata) populations are declining dramatically across their range primarily due to habitat alteration, fragmentation, and reduction. Fragmented habitats have the potential to affect a population’s genetic diversity and size through the direct loss of individuals and the reduction of gene flow. Understanding genetic variation in Spotted Turtles can provide insight into population dynamics, the geographic distribution of genetic variants, and conservation needs. I examined the genetic variation in Spotted Turtle populations across the western portion of their geographic range including localities in Illinois, Indiana, Ohio, Michigan, and Ontario, Canada. Using blood samples collected during the 2022 and 2023 field seasons as well as previously collected tissues, I genotyped 611 individuals across 17 or more localities using 16 microsatellite loci. Five of 17 sites across the geographic extent of the sample suggested the presence of inbreeding (positive Fis values). Although the precision of estimates was low in most localities (10 of 17 with incalculable confidence intervals), the remaining localities in Ohio were estimated to have effective population sizes of < 20 individuals. Model-based and ordination-based clustering were conducted to assess population structure. Both types of clustering approaches identified four genetic clusters within the dataset. The two Illinois sites fell distinctly into their own cluster, whereas all other sites show a pattern of admixture. Despite these clustering results, incorporation of spatial information in principal component analysis (sPCA), shows that genetic composition gradually changes from west to east across the landscape, a pattern supported by isolation by distance using a Mantel test of the correlation between genetic and geographic distances. My results show that several Spotted Turtle populations have low levels of genetic variation and could benefit from augmentation. The observed pattern of isolation by distance 9 suggests that any translocations of turtles to support populations should be attempt to draw from viable populations that are in closer proximity.</p>

<p dir="ltr">In this dissertation, we investigated the genetic background of milk consumption, feeding behavior, disease resistance, and calf resilience in North American Holstein dairy calves using precision livestock farming (PLF) technologies and genetic modeling. Genomic and phenotypic information obtained from automatic milk feeding machines were obtained from 10,072 pre-weaned Holstein calves and used to derive and genetically evaluate novel traits such as daily milk consumption, calf resilience, and incidence of bovine respiratory disease (BRD). Heritability estimates for milk consumption and feeding behavior traits were found to be low but improved with specific statistical models, suggesting potential for genetic improvement if included in selection schemes. Random regression models captured greater amounts of genetic variability among calves for longitudinal milk feeding and behavior traits, with moderate negative (favorable) genetic correlations between milk consumption and BRD, indicating potential for genetic selection to enhance calf health outcomes and performance based on milk intake data. Various quantitative trait loci (QTL) for milk consumption, drinking duration traits, feeding behavior, and disease susceptibility were identified, linking key genes involved in metabolic processes, growth, and overall health. The same datasets were used to derive resilience indicators based on cumulative milk consumption. Genetic parameters for resilience traits, including amplitude, perturbation time, and recovery time, were estimated, highlighting substantial phenotypic and genetic variability. Significant genomic regions for six resilience traits were identified, with key genes such as <i>ABCB8</i>,<i> ABCF2</i>, and <i>AGAP3</i> linked to resilience traits, impacting mitochondrial function, cellular stress responses, and homeostasis. Pathway analyses revealed critical biological processes for stress response, including nucleotide binding and hormone activity. Genes such as <i>EPC1</i>, <i>ASB10</i>, and <i>ASIC3</i> were associated with recovery time, while <i>DPP6</i>, <i>GBX1</i>, and <i>GIMAP5</i> were linked to other resilience traits. These findings underscore the importance of genetic tools and breeding strategies in enhancing health, resilience, and productivity, offering potential new traits to genetically improve health and resilience in dairy cattle, and consequently, improve the sustainability of the dairy cattle industry.</p>

Tropical African pangolin species are threatened throughout their range due to habitat loss and illegal take. Limited knowledge on distribution has rendered conservation efforts challenging. Methods commonly used for other wildlife species need to be tested for each pangolin species as each has variable ecologies requiring specific detection and monitoring techniques. This thesis evaluates the efficacy of two non-invasive environmental methods for detecting tropical African pangolin species, and consists of two complementary studies; a proof of concept study using soil sourced eDNA from a white-bellied pangolin enclosure in the Columbus Zoo, Ohio, to detect the species, and a field study in the Campo Ma’an National Park, Cameroon, to evaluate the efficacy of targeted camera traps (terrestrial and arboreal), and environmental DNA (soil sourced eDNA and water sourced eDNA) to detect each tropical African pangolin species. Study results contribute to future ecological monitoring efforts for each species to inform conservation actions.