Life Sciences Commons^™

Early Onset Alzheimer’S Disease Markers In Mouse Hippocampus Unveiled By Single-Cell Transcriptomic Analysis Following Cranial Radiotherapy, Tuba Aksoy

Dissertations & Theses (Open Access)

Cranial radiation therapy plays an integral role in the treatment of brain tumors but can lead to progressive cognitive deficits in survivors by mechanisms that are poorly understood. To develop preventive or mitigative strategies, it is crucial to better understand the underlying pathogenesis of radiation-induced cognitive impairments. The study investigated single-cell transcriptomics and DNA methylation changes as potential drivers of persistent cellular dysfunction after radiation exposure, specifically concentrating on the CA1-3 regions of the hippocampus and the prefrontal cortex due to their role in cognitive functions. Thirteen-week-old mice underwent whole-brain radiation at clinically relevant doses. Following whole-brain radiation, an assessment …

Elucidating Immune-Related Gene Transcriptional Programs Via Factorization Of Large-Scale Rna-Profiles, Shan He, Matthew M Gubin, Hind Rafei, Rafet Basar, Merve Dede, Xianli Jiang, Qingnan Liang, Yukun Tan, Kunhee Kim, Maura L Gillison, Katayoun Rezvani, Weiyi Peng, Cara Haymaker, Sharia Hernandez, Luisa M Solis, Vakul Mohanty, Ken Chen

Student and Faculty Publications

Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy (ACT), have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA sequencing (RNA-seq) datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated …

Systematic Comparison Of Propensity Score Matching And Structural Causal Modeling For Clinical Applications, With A Case Study Of Albumin Treatment For Acute Kidney Injury (Aki) Patients: Propensity Score Matching Vs. Structural Causal Models, Layaal Khellah

Student Research Symposium

Introduction:

Propensity Score Matching (PSM) and Structural Causal Models (SCMs) are key approaches in causal inference for treatment evaluation and clinical decisions, both rooted in the potential outcome framework but differing in their foundations—PSM follows Rubin's Causal Model, while SCMs adhere to the Structural Theory of Causation.

Methods:

Our study compares PSM and SCMs in clinical contexts, focusing on albumin as an AKI treatment. We examine each method's steps, highlighting differences. Using data from AKI patients with cirrhosis, we assess albumin’s treatment efficacy with both PSM and SCMs, offering insights into their performance in estimating causal effects..

Results:

PSM and …

An Investigation Of Information Structures In Dna, Joel Mohrmann

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The information-containing nature of the DNA molecule has been long known and observed. One technique for quantifying the relationships existing within the information contained in DNA sequences is an entity from information theory known as the average mutual information (AMI) profile. This investigation sought to use principally the AMI profile along with a few other metrics to explore the structure of the information contained in DNA sequences.

Treating DNA sequences as an information source, several computational methods were employed to model their information structure. Maximum likelihood and maximum a posteriori estimators were used to predict missing bases in DNA sequences. …

Archaeal Diversity In The Anna's Hummingbird Microbiome, Lauren E. Chance

Honors Scholar Theses

The microbial communities that are present in and on vertebrates are collectively called the microbiome. The composition of a microbiome is dependent upon the host, the environment, and evolution. There has been extensive research on the bacterial composition of host-associated microbiomes, however, there has been much less work on the archaeal composition of host-associated microbiomes. Archaea have previously been assumed to primarily exist in extreme environments, but this may not be true and has been influenced by their generally low abundance and methodological difficulties in detection. It is possible they are consistent members of diverse host-associated microbiomes.

Archaea-specific PCR primers …

The Genomics Of Champ1: Insights Into Their Cell-Type Specificity And Developmental Trajectories, Zoe Marie Van Caugherty

MUSC Theses and Dissertations

Chromosome alignment maintaining phosphoprotein 1(CHAMP1) is a gene that encodes a zinc finger protein that is involved in in the maintenance of kinetochore-microtubule attachment and regulating chromosome segregation in mitosis. (Itoh et al., 2011) CHAMP1 mutations have been shown to be major risk factors for neurodevelopmental disorders (NDDs) and autism spectrum disorder (ASD).(Asakura et al., 2021; Isidor et al., 2016; Levy et al., 2022) Although there is information on the link between CHAMP1 mutations and NDD, the role of CHAMP1 in regulating processes of human cortical development, namely, neurogenesis, proliferation, and electrophysiological properties of newly born neurons, is unknown. This …

Mmappr2: An Improved Bioinformatics Approach To Find Novel Genes, Aiden Cardall, Jonathon T. Hill, Kyle Johnsen, Connor Ward, Maliha Tasnim, Jared Taylor

Library/Life Sciences Undergraduate Poster Competition 2024

Introduction

• New genes are commonly found by randomly inducing mutations in model organisms.

• Mapping the mutations to the genome to find novel genes is difficult, time-consuming, and expensive.

• We created a bioinformatics program, MMAPPR, to automate this process.

• Here, we introduce a new algorithm, MMAPPR2, which requires little to no bioinformatics knowledge to use.

• MMAPPR2 makes several improvements that allow it to identify genes more rapidly and precisely.

• MMAPPR2 will aid the rapid identification of genes in a wide range of species and developmental systems.

Determining The Role Of Noncoding Insertion And Deletion Mutations In Lung Cancer, Zachary Everton, Matthew H. Bailey

Library/Life Sciences Undergraduate Poster Competition 2024

Background

● Cancer is a disease in which cells grow and divide at an uncontrolled rate and cause damage to surrounding tissue and is caused by mutations in the cells’ DNA.

● Though some cancer-causing mutations are inherited from parents, most cancer-causing mutations emerge over the course of a person’s life and are localized to the tumor. These localized mutations are also known as somatic mutations.

● The human genome is over 6.27 billion base pairs long and cannot be read from end to end; instead it is read in small pieces that are aligned to best-matching sequences in the …

Lake Bonneville's Legacy: Genetic Drift And Diversity Loss In Snake Range Bonneville Cutthroat Trout, Tanner Van Orden, Dennis Shiozawa, Peter Searle, Ana Kokkonen, Jonathan Reynolds, R. Paul Evans

Library/Life Sciences Undergraduate Poster Competition 2024

• Many Bonneville Basin streams have been isolated for 18,000-plus years (Behnke 1976).
• Bonneville cutthroat trout in small streams may have been experiencing genetic drift since the desiccation of Lake Bonneville.
• Small streams in the west desert of Utah and Nevada are at a high risk of genetic drift and diversity loss due to their small size

Protein-Protein Interactions In Cell Cycle Proteins: An In Silico Investigation Of Two Important Players, Andriele Eichner

Dissertations, Theses, and Capstone Projects

The examination of the cell cycle carries significant implications for the biology, health, and overall existence of all living things. These implications span from the development and growth of these organisms to the aging process and cancer, as well as the potential of stem cell therapies to repair diseases and injuries. Numerous proteins of the cell cycle are essential for cellular division and proliferation and are widely conserved over the course of evolution. In this work, we aimed to investigate the molecular processes of protein-protein interactions in cell cycle proteins, centering on two key players: Cdc6 in budding yeast and …

Using Single Cell Genomics To Explore The Impact Of Marine Viruses On Microbial Respiration., Paxton Tomko

MCB Articles

Viral metabolic reprograming of marine prokaryotes, through the use of virally encoded auxiliary metabolic genes (AMGs), plays a critical role in marine ecosystem function by influencing biochemical cycles and genetic diversity in these environments. Despite the fundamental role viruses play in global environmental ecosystems, they remain an understudied aspect of microbial ecology and evolution, in part due to the methods available for studying virus host interactions in natural systems. Thus far, metagenomic analyses have been used to study the interactions of virus host pairs, but these types of analyses have their limitations in accurately linking viruses to hosts, or culture-based …

From Code To Crops: Harnessing Bioinformatics And Artificial Intelligence (Ai) In Agricultural Omics, Lakshay Anand

Theses and Dissertations--Plant and Soil Sciences

Global agricultural faces numerous challenges, such as climate change, resource limitations, novel pests and diseases, increasing costs, and the ever-increasing human population. To tackle these challenges, we need innovative strategies that combine new technologies and data analytics approaches to enhance agricultural output, promote sustainable methods, and optimize resource allocation. The key to this innovation lies in understanding the complex molecular web within plants that governs their growth, defense, and adaptability mechanisms. By mastering this molecular network, we can cultivate crops that are more resilient, sustainable, and suitable for different climatic terrains. Moreover, studying the symbiotic relationship between plants and microorganisms …

Genomic Characterization Of Adolescent And Young Adult Cancers: Investigation Of Ewing Sarcoma Susceptibility And Chornobyl Thyroid Tumors, Olivia Lee

Dissertations & Theses (Open Access)

Adolescent and young adult (AYA) cancers, diagnosed between the ages of 15 and 39, can exhibit distinctive genetic and molecular characteristics. Reported epidemiologic findings and treatment outcomes based on pediatric and adult cancer studies are often not suitable for application to the AYA population, underscoring the need for more thorough genomic research. Advances in sequencing technologies have enabled comprehensive analyses of complex genomic characteristics of AYA cancers, crucial for understanding the underlying biology of these malignancies. Here, I have utilized advanced sequencing techniques and integrated analytic approaches to describe important genomic features in two different AYA cancer types: Ewing Sarcoma …

Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone

Complex Biosystems PhD Program: Dissertations

The task of gene prediction has been largely stagnant in algorithmic improvements compared to when algorithms were first developed for predicting genes thirty years ago. Rather than iteratively improving the underlying algorithms in gene prediction tools by utilizing better performing models, most current approaches update existing tools through incorporating increasing amounts of extrinsic data to improve gene prediction performance. The traditional method of predicting genes is done using Hidden Markov Models (HMMs). These HMMs are constrained by having strict assumptions made about the independence of genes that do not always hold true. To address this, a Convolutional Neural Network (CNN) …

Repurposing Normal Chromosomal Microarray Data To Harbor Genetic Insights Into Congenital Heart Disease, Nephi Walton, Hoang Nguyen, Sara Procknow, Darren Johnson, Alexander Anzelmi, Patrick Jay

Department of Medicine Faculty Papers

About 15% of congenital heart disease (CHD) patients have a known pathogenic copy number variant. The majority of their chromosomal microarray (CMA) tests are deemed normal. Diagnostic interpretation typically ignores microdeletions smaller than 100 kb. We hypothesized that unreported microdeletions are enriched for CHD genes. We analyzed "normal" CMAs of 1762 patients who were evaluated at a pediatric referral center, of which 319 (18%) had CHD. Using CMAs from monozygotic twins or replicates from the same individual, we established a size threshold based on probe count for the reproducible detection of small microdeletions. Genes in the microdeletions were sequentially filtered …

Generative Ai-Assisted Pathway Analysis And Interpretation Of Rna-Seq Experiment Data, Junguk Hur

AI Assignment Library

No abstract provided.

Predicting Marine Teleost Responses To Ocean Warming And Pollution, Akila Harishchandra

Electronic Theses and Dissertations

Ocean warming and pollution are two detrimental anthropogenic factors causing rapid marine ecosystem degradation recorded in the past decades. These factors alter the marine environment intolerable for many marine species, forcing them to either adapt or shift their contemporary habitat ranges to reduce the extinction risk embedded with environmental degradation. Estimating marine species’ habitat range shifts, and their potential for developing adaptive mechanisms are critical for ecosystem conservation and management, human health risk assessment, and climate change vulnerability assessments. Given that, for the first chapter of this thesis, we focused on developing a species distribution model (SDM) integrating marine species …

Evolution Of Overlapping Reading Frames In Virus Genomes, Laura Muñoz Baena

Electronic Thesis and Dissertation Repository

Viruses are formidable pathogens that represent the majority of biological entities in our planet, and their genomes are a source of interesting enigmas. One feature in which virus genomes are usually rich, is the presence of overlapping reading frames (OvRFs) — portions of the genome where the same nucleotide sequence encodes more than one protein. OvRFs are hypothesized to be used by viruses to encode proteins more compactly and to regulate transcription. In addition, OvRFs might be a source of gene novelty, facilitating the creation of new open reading frames (ORF) within the transcriptional context of existing ones.

To characterize …

Sequestered Sequences: A Bioinformatic Approach To The Forgotten Genome, Dylan Barth

UNLV Theses, Dissertations, Professional Papers, and Capstones

As high throughput sequencing generates ever increasing amounts of genetic and epigenetic data new lines of inquiry open up in the field of genomic research. In this thesis, we discuss three ways in which we can utilize public databases of next generation genomic data in order to study areas of the genome previously ignored by traditional approaches. These include the study of linker regions between domains of proteins, indirect enhancers that do not strongly contact promoters of genes they regulate, and transposon-derived enhancer elements. The work uncovers many exceptions to known biological principles, and adds nuance to our understanding of …

Exploration Of The Immune Landscape Of Ebv-Associated Gastric Cancers, Mikhail Salnikov

Electronic Thesis and Dissertation Repository

Epstein–Barr virus (EBV) is a gammaherpesvirus associated with 9% of all gastric cancers (GCs). EBV-associated GCs (EBVaGCs) are pathologically and clinically distinct entities from EBV-negative GCs (EBVnGCs), with EBVaGCs exhibiting differential molecular pathology and patient prognosis. The purpose of this thesis is to investigate the tumor microenvironment (TME) of EBVaGCs, which has not been explored in-depth. We hypothesize that EBVaGCs and EBVnGCs are also distinct in terms of the molecular immune landscape. We employed over 400 stomach adenocarcinoma (STAD) samples from The Cancer Genome Atlas (TCGA), as well as a single cell dataset, for the construction of a web suite …

Utilizing Natural Language Processing For Automated Clinical Text Review: Identification Of Care Preference Documentation In Patients’ Discharge Summaries, Saksham Arora

Computer Science Senior Theses

Improving patient-centered care necessitates accurate documentation of care preferences, a crucial aspect often underrepresented in administrative data. Most studies apply care documentation to specific patient populations, rather than more appropriately broad population of `seriously ill' patients. This paper addresses this gap by leveraging transformer-based machine learning models, exhibiting an improvement over traditional keyword-based search methods in identifying care preference documentation.

In order to capture a broad spectrum of seriously ill patients, we matched decedent patients to non-decedent counterparts by utilizing a propensity score matching, accounting for important variables like age, gender, primary diagnoses and commodities. We trained and fine-tuned Bio_ClinicalBERT …

Understanding Host-Microbe Interactions In Maize Kernel And Sweetpotato Leaf Metagenomic Profiles., Alison K. Adams

Doctoral Dissertations

Functional and quantitative metagenomic profiling remains challenging and limits our understanding of host-microbe interactions. This body of work aims to mediate these challenges by using a novel quantitative reduced representation sequencing strategy (OmeSeq-qRRS), development of a fully automated software for quantitative metagenomic/microbiome profiling (Qmatey: quantitative metagenomic alignment and taxonomic identification using exact-matching) and implementing these tools for understanding plant-microbe-pathogen interactions in maize and sweetpotato. The next generation sequencing-based OmeSeq-qRRS leverages the strengths of shotgun whole genome sequencing and costs lower that the more affordable amplicon sequencing method. The novel FASTQ data compression/indexing and enhanced-multithreading of the MegaBLAST in Qmatey allows …

Computational Analysis Of Microbial Sequence Data Using Statistics And Machine Learning, Zhixiu Lu

Doctoral Dissertations

Since the discovery of the double helix of DNA in 1953, modern molecular biology has opened the door to a better understanding of how genes control chemical processes within cells, including protein synthesis. Although we are still far from claiming a complete understanding, recent advances in sequencing technologies, increased computational capacity, and more sophisticated computational methods have allowed the development of various new applications that provide further insight into DNA sequence data and how the information they encode impacts living organisms and their environment. Sequencing data can now be used to start identifying the relationships between microorganisms, where they live, …

Deephtlv: A Deep Learning Framework For Detecting Human T-Lymphotrophic Virus 1 Integration Sites, Johnathan Jia, Johnathan Jia

Dissertations & Theses (Open Access)

In the 1980s, researchers found the first human oncogenic retrovirus called human T-lymphotrophic virus type 1 (HTLV-1). Since then, HTLV-1 has been identified as the causative agent behind several diseases such as adult T-cell leukemia/lymphoma (ATL) and a HTLV-1 associated myelopathy or tropical spastic paraparesis (HAM/TSP). As part of its normal replication cycle, the genome is converted into DNA and integrated into the genome. With several hundreds to thousands of unique viral integration sites (VISs) distributed with indeterminate preference throughout the genome, detection of HTLV-1 VISs is a challenging task. Experimental studies typically use molecular biology …

Investigating The Role Of Spatial Compartmentalization And Genomic Translocations In Metastatic Cancer: A Multi-Omic Analysis, Joshua Harris Garretson

Chancellor’s Honors Program Projects

No abstract provided.

A Review Of How Bioinformatics And Genome Sequencing Are Affecting Precision Medicine, Taylor S. Hickey

Honors Theses

Advancement in genomic sequencing and bioinformatics methods have been affecting biomedical research through precision medicine, especially in the area of cancer. Vaccine therapies can be developed using neoantigens that target specific mutations in tumors. The goals of this research are to identify mutations that lead to cancer and then define subpopulations in which patients can easily be identified. The future goal is to have targeted vaccines that are specific to each subpopulation ready to be used in treatment of their cancer. Limitations to reaching these goals have been due to tumor heterogeneity, cancer location, and difficulty in creating neoantigens for …

The Genomics Of Autism-Related Genes Il1rapl1 And Il1rapl2: Insights Into Their Cortical Distribution, Cell-Type Specificity, And Developmental Trajectories, Jacob Weaver

MUSC Theses and Dissertations

Neuropsychiatric disorders have a significant impact on modern society. These disorders affect a large percentage of the population: schizophrenia has a world-wide prevalence of 1% and autism spectrum disorders (ASD) affects 1 in 59 school-aged children in the US. There is substantial evidence that most neuropsychiatric disorders have a genetic component. Thus, with the advent of high throughput sequencing much effort has gone into identifying genetic variants associated with these disorders. The emerging picture from these studies is a complex one where hundreds of genes with small effects interact with a varied landscape of common variants to result in disease. …

Structural Analysis Of Predicted Proteins Using Alphafold, Brydon P. Wall

Undergraduate Research Posters

The function of around 67% of predicted proteins from genes in Mycobacteriophage CheetoDust can not be confidently predicted using traditional techniques and can only be functionally labeled “hypothetical proteins”. However, a new approach using AlphaFold, an artificial intelligence tool to generate a structural prediction from a sequence, can take advantage of structurally conserved regions that were previously obfuscated to gain new insights and visualize data in new ways.

Since amino acid sequences are more conserved than its corresponding DNA sequence, amino acid sequences are used when predicting the function of the corresponding translated protein. Until recently, predicting structure from an …

Taxonomic Classification Of Viral And Bacterial Dna Following 2021 Avian Mass Mortality Event, Tessa Baillargeon

Honors Theses and Capstones

From May through July 2021, an unusual mortality event occurred along the eastern coast and Midwest of the United States. Thousands of birds, mostly from the order Passeriformes, were part of the die-off including blue jays (Cyanocitta cristata), common grackles (Quiscalus quiscula), European starlings (Sturnus vulgaris), American robins (Turdus migratorius). Clinical signs included crusted eyes, swollen conjunctiva, otitis, seizures, and ataxia.

The New Hampshire Veterinary Diagnostic Laboratory (NHVDL) received over 100 affected birds from various collaborators throughout the United States including Washington DC, NJ, CT, MD, and OH. Given the timing and geologic …

The Hepatic Immunological Pattern Shaped By Dominant-Subdominant Cellular Interactions Creates A Collective Function Beyond The Function Of Each Cellular Constituent To Orchestrate Progression Of Hepatocellular Carcinoma, Nicholas J. Koelsch

Theses and Dissertations

Abundance of data on the role of inflammatory immune responses in the progression or inhibition of hepatocellular carcinoma (HCC) has failed to offer a curative immunotherapy for HCC. This is largely because of taking reductionist approaches and missing the collective function of the hepatic immune system by focusing on specific immune cell types. To this end, we propose that focusing on the dominant-subdominant patterns of the immune cells would allow understanding of the mechanism by which a collective immune function emerges. To identify the collective immune function through a systems immunology perspective, we performed high-throughput analysis of snRNAseq data collected …