Genetics and Genomics Commons^™

Identifying Rna Splicing Changes During Alcohol Withdrawal Using An Optimized Rna-Seq Analysis Pipeline, Yasaswi Veera, Luana Martins De Carvalho, Amy Lasek

UROP Posters

Alcohol use disorder (AUD) causes long-lasting changes in brain gene expression and RNA splicing, particularly in the ventral hippocampus. This study analyzes RNA-Seq data from rats exposed to chronic alcohol and withdrawal to identify transcript-level and splicing alterations. An optimized RNA-Seq pipeline using STAR, FeatureCounts, edgeR, and WGCNA improved efficiency by 25-40% while maintaining consistency across 25 datasets. Results reveal changes in neural signaling and stress-response pathways associated with withdrawal. This work provides both biological insight into AUD and a reproducible computational framework for transcriptomic analysis.

Genetics Of Mycangial Development And Host Colonization Within The Ambrosia Symbiosis, Mckeon James Laws

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ambrosia beetles, a polyphyletic group of weevils, utilize pouch-like structures at various locations on the body to transport for their sole food source, their fungal partner. Ambrosia fungi are known to originate from multiple unrelated fungal lineages with no consensus of traits required to become a fungal cultivar. While the biology and ecology of both partners is in many cases well understood, the genetic underpinnings of this fascinating mutualism remain a mystery. The aim of this dissertation is to add to the understanding of the ambrosia symbiosis by providing insights into its molecular and genetic underpinnings through RNA sequencing data, …

Generating Predictive Gene Expression Signatures For Alzheimer's Disease Using Postmortem Brain Tissue, Ashley Duche

Pharmaceutical Sciences (PhD) Dissertations

Background: Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by the accumulation of amyloid-beta (Aβ) plaques and tau protein aggregates. These pathological features develop in specific brain regions, but why some areas are more vulnerable to early AD-related changes remains unclear. To address this, predictive gene expression signatures were developed to explore the molecular mechanisms underlying regional susceptibility to AD pathology.

Methods: This was performed using postmortem brain (PMB) tissue from participants in the Religious Orders Study and Memory and Aging Project (ROSMAP), Mayo Clinic, and Mount Sinai Brain Bank (MSBB) to generate gene expression signatures from six brain …

A Persistent Homology Framework For Scrna-Seq: Assessing Clustering Robustness And Quantifying Preprocessing And Integration Effects On Topological Features., Jonah Daneshmand

Electronic Theses and Dissertations

As single-cell RNA sequencing (scRNA-seq) data expands, robust methods for integrating diverse datasets are critical. This dissertation applies Persistent Homology (PH), a technique from Topological Data Analysis (TDA), to a collection of scRNA-seq datasets spanning eight tissue types to quantify how data integration affects topological features and biological interpretability. We assessed global topological structure using Betti curves, Euler characteristics, and persistence landscapes across raw, normalized, and integrated data representations. Our analysis revealed a performance inversion: while conventional methods excelled on unintegrated data, high-granularity topological methods, particularly those sensitive to global data structure, became superior after integration. This suggests a synergy …

The Genetic And Environmental Determinants Of Stress Resilience Across Model Systems, Carson Len Stacy

Graduate Theses and Dissertations

Survival in fluctuating environments demands that organisms effectively anticipate and respond to future challenges. This capacity is shaped by both genetic background and environmental context. In this dissertation, I apply a population aware lens to explore how genetic diversity and environmental conditions intersect to shape stress survival. Integrating functional genomics and transcriptomics in Saccharomyces cerevisiae (brewer’s yeast) and a vertebrate (common canary) system, I dissect gene-by-environment (GE) interactions that underpin resilience. First, I move beyond a single reference genome by using a pan-genomic CRISPR knockout screen to assess osmotic stress survival across diverse S. cerevisiae isolates. This analysis reveals a …

Orthogonal Comparison Of Nuclear And Mitochondrial Clonal Architectures In Hematologic Malignancies, Nehali Shah

Dissertations and Theses (Open Access)

Acute myeloid leukemia (AML) is a hematologic malignancy characterized by accumulation of mutations that disrupt hematopoietic differentiation and promote clonal expansion. Understanding how these mutations arise and evolve is essential for improving diagnosis, prognosis, and treatment stratification. Current methods are limited by either restricted genomic coverage (targeted panels) or low throughput and high cost (in single-cell whole genome sequencing, scWGS). An emerging alternative is the use of mitochondrial DNA (mtDNA) mutations as clonal markers.

This study aims to determine whether mitochondrial-derived clonal architectures correlate with nuclear-derived clonal architectures in AML, thereby evaluating mtDNA as a scalable orthogonal tool for lineage …

Population Structure Analysis Of Four Basal Higher-Attines Using Bioinformatic Approaches, Gabriel Mcdanield

Biology Theses

Metapopulations within the family Formicidae are unique among other animals due to the large colonies they build, and the mating strategies required to fertilize a specialized reproductive caste that will often produce young for the life of the colony. One group of ants, the fungus-gardeners (tribe Attini). The population structure of North American non-leafcutting, fungus-gardening ants has been understudied, especially in the southwest of the United States. Additionally, not much is known about their dispersal biology, so the dynamics of dispersal of these species and how they affect population structure is likewise not well known. To shed light on the …

Leveraging Dna Methylation Profiling And Microrna Sequencing To Characterize The Epigenomic Landscape Of Major Depressive Disorder Disease Trajectory, Jan Dahrendorff

USF Tampa Graduate Theses and Dissertations

Major depressive disorder (MDD) is a common and debilitating mental disorder associated with a significant disease burden and economic cost. Despite ample evidence documenting the efficacy of a diverse array of established MDD therapies, a large proportion of patients are inadequately responsive to initial treatment attempts, with first-line treatments leading to remission in only ~30% of the patients. Importantly, about a third of patients even fail to achieve symptom improvement after two or more antidepressant trials, resulting in what is commonly defined as treatment-resistant depression (TRD). The ability to identify which treatments are most likely to elicit a positive response …

Bioinformatic Analysis Of Pogz Variants In Relation To White Sutton Syndrome, Hannah Rollins

Theses

White-Sutton syndrome (WHSUS) is a rare neurodevelopmental disorder caused by mutations in the Pogo Transposable Element with ZNF Domain (POGZ) gene, which encodes pogo-transposable element with ZNF domain, a chromatin regulator essential for proper mitotic progression and DNA repair. This study uses a bioinformatic framework to evaluate the structural and functional impact of missense mutations in the conserved amino acid region (positions 500–800) of the POGZ protein. Protein modeling, variant effect prediction, conservation analysis, and molecular dynamics simulations were employed to gain an understanding of the effects of POGZ missense mutations on protein structure and movement with specific emphasis on …

Sequence And Phylogenetic Analysis Of Citrus Maxima (Burm.) Merr. From Tomini Bay, Sulawesi Island, Based On The Maturase K Gene, Brenda Febrina Zusriadi, Novri Youla Kandowangko, Febriyanti Febriyanti

Makara Journal of Science

This study was conducted in the coastal area of Tomini Bay, Sulawesi Island, and it focused on Citrus maxima, a plant known for its unique fruit flesh colors, which range from yellow to pink, and its varying leaf stalk wings. The study aimed to analyze the variations in maturase K (matK) sequences, molecular characteristics, and phylogenetic relationships of two C. maxima samples from Tomini Bay compared to other C. maxima and Citrus species using data available in GenBank. The study utilized DNA barcoding with matK molecular markers, followed by phylogenetic tree construction using the maximum likelihood method …

Gene Expression Of Anthocyanin Pigments In The California Native Plant Leptosiphon Parviflorus: Interactions Between Flower Color Morphology And Abiotic Stressors, Weston Gonor

Master's Theses

For plants to survive in harsh conditions imposed by abiotic stressors, they must develop mechanisms of adaptation. One of the common types of adaptation seen in plants is the production of anthocyanin pigments, which have been shown to protect plants from UV radiation, metabolic stress, and drought. In this study, we used the flower color polymorphic species Leptosiphon parviflorus to investigate the role of anthocyanin pigments in protecting plants from abiotic stress. To accomplish this, RNA samples were taken from flower, leaf and root tissue of different flower color morphs of Leptosiphon parviflorus (Polemoniaceae) grown in high magnesium and water …

Ibi-Dt: A Novel Approach Combining Individualized Bayesian Inference And Decision Tree For Identifying Cancer Drivers And Their Interactions, Md Asad Rahman, Gregory F. Cooper, Jinying Zhao, Xinghua Lu, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Cancer is mainly caused by a relatively small portion of somatic genome alterations (SGAs), called cancer drivers. Despite success in identifying a good number of cancer drivers, many more remain to be discovered to explain various cancers. Moreover, limited tools are available to identify potential interactions among cancer drivers for a better understanding of oncogenesis. To tackle these challenges, we have developed a novel approach called individualized Bayesian inference using a decision tree (IBI-DT). IBI-DT recognizes the genetic heterogeneity among cancer patients, where different individuals or patient subgroups of distinct genomic makeup may have different drivers. IBI-DT works by constructing …

Performance Analysis Of Computational Methods For Predicting Protein Function In Rare Diseases, Aichetou Mohamed Sidiya, Hanin Alzaher, Razan Almahdi, Tayeb Brahimi

Effat Undergraduate Research Journal

Protein function prediction is crucial for understanding the underlying mechanisms of rare diseases. With the increasing availability of computational methods including machine learning-based approaches, network-based methods, and sequence-based methods, predicting protein functions has become more accessible. However, it is not clear which of these methods performs better or how they compare to each other in terms of accuracy, efficiency, and scalability. In this study, we evaluate several computational methods for predicting protein functions in rare diseases using key performance indicators (KPIs). We analyze the strengths and weaknesses of each method and provide recommendations for researchers and clinicians interested in using …

Quantile Index Predictors Using R Package Hyper.Gam, Tingting Zhan, Misung Yi, Inna Chervoneva

Department of Pharmacology, Physiology, and Cancer Biology Faculty Papers

MOTIVATION: Evaluation of single-cell protein expression from immunohistochemistry images is used increasingly in biomedical research. Many proteins are used solely for phenotyping cells in the tumor microenvironment. Other proteins with meaningfully quantitative expression levels provide so-called functional protein biomarkers. There is still a limited number of methods and software tools available for utilizing the entire distributions of single-cell expression levels.

RESULTS: We present the R package hyper.gam, providing a supervised learning framework for deriving biomarkers based on single-cell distribution quantiles. The single-cell data are first converted into sample quantile functions, which are then used as predictors in scalar-on-function regression models …

Genes That Matter: Survival Modeling In Tcga-Brca With Treatment Interactions., David Pratt

Electronic Theses and Dissertations

High-dimensional genomic data offer both promise and challenges for identifying clinically relevant biomarkers. This study developed a parallelized survival modeling pipeline to identify genes associated with overall survival in breast cancer, with a focus on gene-by-treatment interactions and patient heterogeneity. RNA-Seq data from female patients in the TCGA-BRCA cohort were analyzed. Univariate Cox proportional hazards models were used to screen genes, adjusting for age, race/ethnicity, treatment status, and cancer stage. A LASSO-penalized Cox regression was fit across 2000 random seeds to assess feature stability. Genes were filtered by expression level, statistical significance, and hazard ratios (effect sizes) in either direction, …

Predicting Genetic Interactions Using Functional Interaction Networks, Iulia Veronica Gheorghe

Dissertations and Theses (Open Access)

Mapping genetic interactions is central to understanding cellular systems and identifying therapeutic vulnerabilities, particularly in the context of cancer. Among these interactions, synthetic lethality, where simultaneous loss of two genes is lethal but loss of either alone is tolerated, offers a powerful framework for selectively targeting tumor-specific dependencies. In model organisms like S. cerevisiae, comprehensive double-knockout screens have revealed detailed genetic interaction maps, enabling systems-level insights into pathway structure, gene function, and cellular organization. Replicating this achievement in human cells, however, is complicated by the scale and complexity of the human genome. Recent advances in genome-wide CRISPR knockout screening have …

An Integrative Genomics Approach For The Discovery Of Potential Clinically Actionable Diagnostic And Prognostic Biomarkers In Colorectal Cancer, Mark Fertel, Duaa Mohammad Alawad, Chindo Hicks

School of Graduate Studies Faculty Publications

Background: Despite remarkable progress in clinical management of patients and intensified screening, colorectal cancer remains the second most common cause of cancer-related death in the United States. The recent surge of next generation sequencing has enabled genomic analysis of colorectal cancer genomes. However, to date, there is little information about leveraging gene expression data and integrating it with somatic mutation information to discover potential biomarkers and therapeutic targets. Here, we integrated gene expression data with somatic mutation information to discover potential diagnostic and prognostic biomarkers and molecular drivers of colorectal cancer. Methods: We used publicly available gene expression and somatic …

Cazyme Gene Cluster Diversity In Human Gut Microbiome, Yi Xing

Department of Food Science and Technology: Dissertations, Theses, and Student Research

In gut microbiome research, carbohydrate-active enzyme gene clusters (CGCs) have emerged as key functional units for understanding microbial glycan degradation. Unlike taxonomic or broad pathway annotations, CGCs offer gene-cluster-level resolution and capture substrate-specific microbial functions. However, their diversity and distribution in relation to host metabolic phenotypes, such as obesity, remain poorly characterized. This study tests the hypothesis that the composition and abundance of fiber-targeting CGCs vary between obese and healthy human gut microbiomes, reflecting distinct microbial carbohydrate utilization strategies. To examine this, we constructed a high-quality reference CGC dataset comprising 94,019 clusters from the Unified Human Gastrointestinal Genome and profiled …

Topodino: Self-Supervised Topological Representation Learning For Neuronal Morphologies, Yasser Binbisher

Master's Theses

Neuronal cell types are categorized by transcriptomic identity, yet their morphological heterogeneity defies this classification. In response, researchers have adopted unsupervised graph representation learning as a tool to reveal morphological variation within single-class transcriptomic types. However, the complex geometry of neuronal morphology—especially long axons and dense dendrites—challenges graph neural networks, which struggle with message propagation across extended structures. To mitigate this, current approaches enforce sub-sampling on neuronal graphs and omit axons entirely, sacrificing critical biological features for computational efficiency. To overcome this trade-off, this thesis introduces TopoDINO, a self-supervised, topology-aware representation learning model designed to preserve the full hierarchical organization …

Analytical Approaches For Identification Of Essential Genomes Of Plasmodium Knowlesi And Babesia Divergens, Sida Ye

Graduate Doctoral Dissertations

Apicomplexa constitute a large phylum of single-celled, obligate intracellular protozoan parasites. Notably, Plasmodium spp. and Babesia spp. are apicomplexan parasites that infect red blood cells. Plasmodium species are the causative agent of malaria and are transmitted by Anopheles mosquitoes, affecting large human populations, whereas Babesia spp., transmitted through the bite of Ixodes ticks cause babesiosis.

In this dissertation, we investigate the essential genome of these parasites using high-throughput transposon mutagenesis. Identifying the essential genome is key to finding new drug targets and understanding resistance mechanisms, a crucial pursuit given the rising resistance to frontline antimalarial drugs and the challenges …

Comparative Methylation Analyses Across Juglans Species To Investigate Epigenetic Contributions To Fungal Resistance, Keertana Chagari

Honors Scholar Theses

Juglans cinerea (butternut) is a critically threatened North American tree species experiencing severe declines due to the fungal pathogen Ophiognomonia clavigignentijuglandacearum. In contrast, its Asian relative, Juglans ailantifolia (Japanese walnut), shows natural resistance. To investigate the genomic and epigenetic factors underlying this difference, we constructed and analyzed high-quality, chromosome-level genome assemblies for both species from long-read sequencing data (J. ailantifolia: 527Mb; J. cinerea: 586Mb), focusing on transposable element (TE) content, DNA methylation patterns, and regulation of pathogen resistance genes (PRGs).

Repeat analysis revealed that J. cinerea has a slightly higher overall transposable element (TE) content, with …

Network Analysis Of Antimicrobial Resistance In Staphylococcus Aureus: Characterization Of Hub Genes And Their Functional Implications, Md Imran Hasan, Davida Smyth, Jeong Yang, Ashley Teufel

Masters Theses (Archived)

Antimicrobial resistance is a major cause of morbidity and mortality in patients with S. aureus infections. In this study, we analyzed genes, molecular mechanisms, and pathways driving drug resistance in S. aureus using network analysis. Using whole-genome sequencing (WGS) data and systems biology approaches, we identified 229 AMR-associated genes and constructed a protein-protein interaction network among these genes. Through network topology and functional enrichment analyses, we not only confirmed their association with resistance, but also highlighted the central roles of these genes in resistance pathways, such as efflux, target replacement, and target protection, which are directly linked to multiple drug …

Generation Of A Transgenic Vector For The Purpose Of Transforming Charcoal Rot Resistance Into Soybeans (Glycine Max), John M. Bear Jr

Electronic Theses & Dissertations

Charcoal rot, caused by Macrophomina phaseolina, is among the most devastating fungal pathogens affecting G. max, particularly in drought-susceptible regions such as the midwestern United States. Traditional agricultural practices have included crop rotation and irrigation, which have proved ineffective or economically unfeasible. Charcoal rot infects over 500 other species of plants and can overwinter as dormant sclerotia which can germinate once soybeans are re-planted and infect young plants. As a result, transgenic solutions have offered a promising alternative for the development of disease-resistant soybeans. This thesis documents the construction of a transgenic vector to express BOZO, a …

Investigating The Effects Of Transcription Factor Binding And Genetic Variants In The Striatum Of Post-Mortem Cohorts With Opioid Use Disorder, Rajashree Chakraborty

Theses & Dissertations

The opioid crisis has emerged as one of the most pressing public health challenges of our time, with Opioid Use Disorder (OUD) affecting millions of lives across the globe. Studying OUD is not merely an academic pursuit but a critical necessity in addressing this multifaceted epidemic. The urgency of this research is underscored by the staggering prevalence of OUD, with an estimated 3.7% of U.S. adults requiring treatment in 2022 alone. Despite the availability of effective medications for OUD, a significant treatment gap persists, with only a quarter of those in need receiving these life-saving interventions. The far-reaching consequences of …

Uncovering The Evolutionary Origins Of Neo-Sex Chromosomes In The Insect Family Membracidae, Mary Kumah

2025 Spring Honors Capstone Projects - Archive

This research explores the evolution of the neo-XX/XY sex chromosome system of Amblyophallus exaltatus, a treehopper insect in the family Membracidae. Neo-XX/XY sex chromosome systems can evolve from an XX/X0 sex chromosome system via fusion events between the X chromosome and an autosome. Although cytological work has indicated the presence of a neo-XX/XY system within A.exaltatus, the chromosomal identity of the fused autosome and the molecular drivers behind this chromosomal fusion remain poorly understood. By performing a coverage analysis with whole genome sequence data, the parts of the A.exaltatus genome that fused with the X chromosome will be better …

Integration Of Multi-Omics Datasets Evaluating Structural And Functional Features Of The Gut Microbiome In People With Hiv (Pwh)., Aakarsha Vijayakumar Rao

Electronic Theses and Dissertations

Gut dysbiosis characterized by reduced abundance of beneficial butyrate-producing bacteria has been independently linked to HIV-1 infection and heavy alcohol drinking. Further, gut dysbiosis results in loss of gut barrier integrity, microbial translocation and host-specific systemic inflammation. Therefore, to evaluate the functional consequences of structural changes in the gut microbiome, integrated data analysis is imperative. In this dissertation, we perform integrated analyses using data from multi-omics platforms to examine the structural and functional features of the gut microbiome of PWH. Gut microbiome composition was evaluated by sequencing V4 region of 16S rDNA, concentrations of metabolites and host-specific immune markers were …

Intraspecific Genetic Variation In Green Salamanders (Aneides Aeneus) At Bays Mountain Park, Brianna Drake

Electronic Theses and Dissertations

Accurate taxonomy is crucial for conserving vulnerable cryptic species like the green salamander (Aneides aeneus) in the Southern Appalachian Mountains. Prior studies identified three distinct lineages within the A. aeneus complex: Northern Appalachians, Southern Appalachians, and Blue-Ridge Escarpment. One previously collected sample indicated green salamanders in northeast Tennessee fit within the Northern lineage. The present study uses molecular data of A. aeneus at Bays Mountain Park (BMP) in Kingsport, Tennessee, to determine where the BMP population fits within these lineages. It was hypothesized that individuals from BMP belong in the northern lineage. Tail tips were collected from thirty-four …

The Role And Expression Of Pros-1 In The C. Elegans Gonad, Brandon W. Thomas, Mary B. Kroetz, Roberta Challener

Undergraduate Theses

The nematode, formally known as Caenorhabditis elegans, has served as an excellent model organism in understanding fundamental biological processes, including those governed by conserved genes like pros-1. pros-1 is partially responsible for the formation of tubular structures within the organism. Glial cells and excretory canals are both examples of tubular structures governed by pros-1. pros-1 orchestrates the embryonic development of these cell types by modulating cell proliferation and differentiation, thus ensuring proper morphogenesis and organogenesis. Its regulatory influence likely extends beyond embryogenesis, potentially affecting reproductive processes as well. Furthermore, the evolutionary conservation of pros-1 underscores its significance …

Life After Death: Investigating The Resistance And Recovery Of Fungal Communities To Foundation Tree Mortality, Jessie F. Marlenee

Biology ETDs

Tree mortality can have cascading effects on the composition and resilience of interacting fungal communities. Yet, little is known about the impact tree mortality, distinct from abiotic drivers (i.e., drought), has on these communities. This dissertation focuses on the resilience of fungal communities to experimental tree mortality in a piñon-juniper woodland. In chapter one, I found that piñon mortality reduced piñon fine root biomass and piñon mycorrhizal fungal diversity, whereas juniper mycorrhizal fungi were unaffected by juniper mortality. In chapter two, I revealed that piñon mortality altered the composition and spatial structure of mycorrhizal and saprotrophic fungi in the soil, …

Leveraging Attention Mechanism To Unlock Gene And Protein Attributes, Ala Jararweh

Computer Science ETDs

Advancing personalized medicine depends on effectively integrating and interpreting the vast, heterogeneous landscape of biological data, from genomic sequences and transcriptomics to the insights embedded in scientific literature. Current machine learning models often focus on single data modalities, limiting their capacity to capture the multifaceted nature of biological systems. We address this gap by developing three attention-based machine-learning models integrating diverse data modalities. Firstly, DeepVul is a multi-task model that leverages cancer transcriptome data to predict genes critical for cancer survival and their corresponding drugs. Subsequently, LitGene refines gene representations by integrating textual information from the scientific literature. Finally, Protein2Text …