Genetics and Genomics Commons^™

Transcriptomic Profiling Of Engineered Human Gene Integration In The Mouse Genome Following In Vitro Gene Editing, Ethan Potts, Made Harumi Padmaswari, Christopher Nelson

Biomedical Engineering Undergraduate Honors Theses

Gene replacement is a promising method of therapy for genetic diseases. However, safety and efficacy are areas that need more research. This experiment aims to use RNA sequencing and bioinformatic techniques to provide answers to these questions and provide direction to future studies to develop a gene replacement therapeutic. C2C12 mouse myoblast cells were transfected with a vector containing a CRISPR-Cas9 system and the Human Factor IX (hF9) gene in order to hijack target genes and integrate the hF9 gene. The two target genes, myoglobin (Mb) and creatine kinase (Ckm), were chosen for their high rate of expression and low …

Exploring Genomic Convergence For Adaptations To Freezing Environments In Polar Fish, Ethan Talley

Biological Sciences Undergraduate Honors Theses

Convergent evolution provides valuable insights into how natural selection shapes species traits. Genomic analysis of lineages that display convergent traits has the potential to identify candidate genes for environmental adaptations across the scope of entire genomes. One remarkable example of convergent evolution is the independent development of antifreeze proteins (AFPs) in phylogenetically distant polar fish lineages. While AFPs themselves are relatively well studied, the full genomic context of adaptation to freezing conditions in these fish lineages remains largely unexplored. Leveraging the whole genome sequences previously assembled in our lab, along with other high-quality genomes available in GenBank, I examined the …

Mismatch Repair Deficient Neoantigen And Associated Circulating T-Cell Receptor Repertoires In Lynch Syndrome, Ana Bolivar

Dissertations and Theses (Open Access)

Lynch Syndrome (LS) is the most common inherited colorectal cancer (CRC) syndrome. It constitutes the perfect model to understand DNA mismatch repair deficient (MMRd) carcinogenesis, which underlies 15% of early-stage CRC. LS patients develop MMRd tumors with high loads of shared neoantigens (neoAgs), which are recognized by the immune system. Previous research has concentrated on discovering neoAgs and their potential as targets for vaccines in LS patients. However, these studies have primarily identified shared neoAgs from cancers, lacking detailed information on targetable neoAgs present in precancerous lesions. Understanding this landscape of pre-cancer derived neoAgs is crucial for intercepting cancer development …

Uncovering Capillary Endothelial Cells Response During Lung Injury-Repair, Celine Shuet Lin Kong

Dissertations and Theses (Open Access)

Once thought to be a homogenous population, capillary endothelial cells (ECs) have embodied organotypic specialization and heterogenous properties, both during homeostasis and tissue injury. In the lung, capillary ECs consist of two distinct populations, CAP1 and CAP2s; how each population responds to diverse tissue injury is incompletely understood. In this thesis, I report the induction and function of a truncated isoform of Ntrk2, Ntrk2^-tk (lacking the tyrosine kinase domain) in multiple injury models. Using a combinatorial approach of single-cell multiome, mouse genetics and viral infection models, I found that Ntrk2^-tk is broadly induced in CAP1s after the initial …

Epigenetic Modification As A Therapeutic Target In Brafv600e-Mutated Metastatic Colorectal Cancer, Hey Min Lee

Dissertations and Theses (Open Access)

Patients with BRAF^V600E-mutated metastatic colorectal cancer (mCRC) experience a worse prognosis and demonstrate only a 5% response rate to BRAF inhibitor treatment. In this study, adaptive resistance, and a potential combination of standard therapies in BRAF^V600E CRC were unveiled. Intriguingly, a robust association of BRAF^V600E mutation and DNA hypermethylation suggests this is a unique subgroup harboring aberrant epigenetic phenotype. Firstly, DNA methyltransferase (DNMT) inhibitor treatment induced profound DNA hypomethylation in vivo, but minimal change in gene expression due to adaptive elevation of the repressive histone methylation, H3K27me3, leading to compensatory suppression of key tumor suppressor genes, …

The In4mer Crispr/Cas12a Multiplex Knockout Platform And Its Applications, Nazanin Esmaeili Anvar

Dissertations and Theses (Open Access)

Discovering synthetic lethal interactions between genes holds the key to uncovering cancer vulnerabilities, enabling the development of more effective drugs for patients. However, identifying these vulnerabilities in the complex genome of human, which comprises thousands of genes, poses a significant challenge. One alternative approach to investigate these interactions involves exploring enriched sources of synthetic lethal interactions, such as paralog pairs. In recent years, a couple of studies have conducted dual-gene knockout experiments on paralog pairs using different approaches to identify synthetic lethal interactions. In this study, we conducted a meta-analysis of CRISPR genetic interaction screens. We identified a candidate set …

Single Cell Pharmacodynamic Modeling Of Cancer Cell Lines, Arnab Mutsuddy

All Dissertations

Cancer is one of the leading causes of disease related death worldwide. Since the discovery of the genomic origins of cancer, targeted therapy has been developed towards specific mutations implicated for oncogenic transformation. However, current standard-of-care for mapping cancer patients to efficacious drug combination is often inadequate. The pathophysiology of tumor progression relies on the dysregulation of biomolecular pathways of which the topology and the dynamics challenge prognosis. Moreover, the overall genomic instability involved in disease states and the resulting inter-patient as well as intra-tumoral heterogeneity challenge rationalization of therapy and clinical decision-making. It highlights the need for the use …

Evolution In Complex Systems: A Computational Prespective, Andisheh Dadashi

Computer Science ETDs

As we are entering the era of multi-omic datasets, it is increasingly evident that the complexities of natural systems exceed the capabilities of current computational methodologies. My dissertation research aims to reduce this gap by using computational frameworks to investigate the evolution of complex systems. I apply a model of metabolic networks to predict human embryonic metabolism during peri-implantation (Chapter I), offering insights into the foundations of early human development. This dissertation further examines the basis of the phenotypic evolution of polygenic traits when subjected to directional (Chapter II) and temporally varying environmental shifts (Chapter III), revealing the roles of …

In Silico Analysis Of C-Type Lectins As Co-Infection Receptors Of Dengue And Chikungunya Viruses In Aedes Aegypti, Munawir Sazali, R. C. Hidayat Soesilohadi, Nastiti Wijayanti, Tri Wibawa, Arif Nur Muhammad Ansori

Makara Journal of Science

Aedes aegypti is a primer vector of dengue virus (DENV) and chikungunya virus (CHIKV). The susceptibility of mosquitoes to DENV and CHIKV depends on their recognition receptor of pathogens. C-type lectins (CTLs) are an important mediator of virus infection in A. aegypti. This study aims to identify potential receptors and determine the binding affinity between ligand–receptor interaction, CTLs and virus envelopes (DENV-1, 2, 3, and 4 and CHIKV) interaction based on in silico analysis. Sample sequences were obtained from GenBank (NCBI), and 10 CTLs were acquired from VectorBase. Homology modeling based on a minimum standard of 20% was processed …

A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes

Graduate Industrial Research Symposium

The genetic perturbations caused by spaceflight on biological systems tend to have a system-wide effect which is often difficult to deconvolute it into individual signals with specific points of origin. Single cell multi-omic data can provide a profile of the perturbational effects, but does not necessarily indicate the initial point of interference within the network. The objective of this project is to take advantage of large scale and genome-wide perturbational datasets by using them to train a tuned machine learning model that is capable of predicting the effects of unseen perturbations in new data. Perturb-Seq datasets are large libraries of …

Avian Symbionts Of Sulawesi: Identifying And Correlating Malaria Parasites And The Microbiome In Communities Of Endemic Avian Hosts, Rachael Joakim

Dissertations, Theses, and Capstone Projects

Since the evolution of complex organisms, there have been communities of symbionts inhabiting them. Thanks to the development of parallel sequencing techniques, DNA of entire microbial communities can be sequenced from a single sample. Some microbes can be parasitic in nature, such as Haemosporida, an order of eukaryotes causing malaria. While most symbionts form a more commensal host relationship in wild systems, host-symbiont dynamics can vary in pathogenicity based on biotic and abiotic factors. In vertebrates, microbial communities in the gut play a major role in host function, including immune responses to Haemosporida. Though this relationship is most commonly explored …

Parental Environnement Influences Offspring Gene Expression In The Olympia Oyster, Ostrea Lurida., Mark S. Yeats

LSU Master's Theses

The Olympia Oyster is the only native oyster species on the Pacific coast of North America. Seasonality in water temperatures across this threatened species’ broad and fragmented range has been linked to its development, reproductive timing, reproductive activity, growth, and survival rates. Recent evidence suggests parental environments can have carry-over effects on larval growth and respiration rates in response to temperature. In this study, we utilized transcriptomic methods to identify the underlying mechanisms of this cross-generation plasticity. Sequence libraries of adult ctenidia tissue and pooled larval replicates were extracted and spawned from hatchery raised oysters of the same parentage immediately …

Recent Progress And Perspectives On Development Of Gene Editing Tools, Zixian Liu, Chengping Li, Gogo Jun-Jie Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The gene editing field has witnessed remarkable advancements in recent years, leading to the establishment and refinement of multidimensional gene editing platforms. These innovations have enabled precise targeted gene knockout, repair, and insertion. These tools have stimulated significant progress in fundamental research, therapeutics, agriculture, environment protection, and industrial applications. In this review, we provide a comprehensive overview of the milestones in gene editing tool development and offer perspectives on potential future directions for this rapidly evolving field.

Research On Innovative Development Path And Policy Guarantee Of China’S Synthetic Biology Industry, Hongjun Geng, Chang Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Synthetic biology is hailed as the third revolution in life sciences after the discovery of the DNA double helix structure and genomic technology, and is the core driving force for the leapfrog development of next-generation biomanufacturing and the future bioeconomy, opening up an opportunity window for the reshaping of the global manufacturing map. How to strategically position the synthesis biology industry and seize the strategic high ground in the industry is a core topic of interest for global science and technology powers and manufacturing powers. Based on the identification of problems in the development of China’s synthesis biology industry, this …

Understanding The Origin Of Parthenogenesis Via Crossing And Crispr Gene Editing In Daphnia Pulex, Thinh Pham

Biology Dissertations - Archive

Daphnia has been used as a key model system for studying ecological changes, evolution, and genomics for the past few decades due to its rapid turnover time in reproduction. The organism possesses two fascinating modes of reproduction: obligate parthenogenesis and cyclical parthenogenesis. This dissertation delves into the intricate reproductive strategies of Daphnia pulex, focusing on hybrid F1s from different reproductive modes. The first aim is to investigate 31 hybrid F1s generated from obligate parthenogenesis (OP) and cyclical parthenogenesis (CP) parental lines. Transcriptomic analysis reveals misexpression patterns and regulatory divergences, highlighting meiosis-related genes like CDC6 as potential parthenogenesis regulators. The …

Coral Scar Investigation: An Application Of Machine Learning And Computational Biology Methods To Understand Coral Holobiont Response To Various Tissue Loss Diseases, Emily W. Van Buren

Biology Dissertations - Archive

Coral disease is one of the biggest challenges facing coral reefs that actively changes biodiversity resulting in coral decline. With the rising threat of diseases, corals require biomarkers that reflect the immune systems and differences between common coral tissue loss diseases to best assist in coral restoration efforts. To obtain these biomarkers, my dissertation leverages two previously published datasets from two tissue loss disease exposure studies to investigate genes that are relevant for coral immune pathways, disease susceptibility, and classification between the diseases. In Chapter 2, I use comparative computational biology tools and protein assays to identify the melanin cascade …

Corals In Crisis: A Transcriptomic Investigation Of Stony Coral Tissue Loss Disease, Kelsey M. Beavers

Biology Dissertations - Archive

Coral reefs face existential threats due to climate change and human activities. The combined effects of ocean warming, overfishing, pollution, and habitat destruction have fundamentally altered the functionality of coral reefs and are driving a drastic increase in the prevalence and severity of coral disease outbreaks. Stony coral tissue loss disease (SCTLD) has emerged one of the most devastating disturbances to Caribbean reef ecosystems on record. Despite notable progress, the cellular mechanisms driving SCTLD pathogenesis remain poorly understood. To address this issue, my dissertation investigates the gene expression, histopathology, immune protein activity, and symbiont community dynamics involved in SCTLD progression …

Creation Of A Digital Storage System For Genome Sequencing Metadata, Jacquelin W. Olexa

Undergraduate Theses, Professional Papers, and Capstone Artifacts

As the field of computational genomics continues to expand in both potential and application, it is now more imperative than ever to ensure that massive genetic sequencing datasets are properly stored in an accessible manner. This project sought to establish a practical, user-friendly, secure system for a genomics research lab (the Good Lab; thegoodlab.org) at the University of Montana. A MySQL database and connected web application was ruled the best configuration to maximize utility and accessibility for the lab’s researchers. Building the logical framework for the database, creating the server, and sourcing data occurred over several months. The dataset ranged …

Identifying New Cancer Genes Based On The Integration Of Annotated Gene Sets Via Hypergraph Neural Networks, Chao Deng, Hong-Dong Li, Li-Shen Zhang, Yiwei Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation

Identifying cancer genes remains a significant challenge in cancer genomics research. Annotated gene sets encode functional associations among multiple genes, and cancer genes have been shown to cluster in hallmark signaling pathways and biological processes. The knowledge of annotated gene sets is critical for discovering cancer genes but remains to be fully exploited.

Results

Here, we present the DIsease-Specific Hypergraph neural network (DISHyper), a hypergraph-based computational method that integrates the knowledge from multiple types of annotated gene sets to predict cancer genes. First, our benchmark results demonstrate that DISHyper outperforms the existing state-of-the-art methods and highlight the advantages of …

Sccad: Cluster Decomposition-Based Anomaly Detection For Rare Cell Identification In Single-Cell Expression Data, Yunpei Xu, Shaokai Wang, Qilong Feng, Jiazhi Xia, Yaohang Li, Hong-Dong Li, Jianxin Wang

Computer Science Faculty Publications

Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for characterizing cellular landscapes within complex tissues. Large-scale single-cell transcriptomics holds great potential for identifying rare cell types critical to the pathogenesis of diseases and biological processes. Existing methods for identifying rare cell types often rely on one-time clustering using partial or global gene expression. However, these rare cell types may be overlooked during the clustering phase, posing challenges for their accurate identification. In this paper, we propose a Cluster decomposition-based Anomaly Detection method (scCAD), which iteratively decomposes clusters based on the most differential signals in each cluster to effectively separate …

Genomic Studies Of The Equine Bloodworm, Strongylus Vulgaris, Nichol Ripley

Theses and Dissertations--Veterinary Science

Strongylus vulgaris is the most pathogenic nematode parasite of grazing horses worldwide. This gastrointestinal parasitic nematode is in the family Strongylidae under the subfamily Strongylinae, or Strongylins. While the epidemiology, complete life cycle, and high pathogenicity of the fourth and fifth larval stages of S. vulgaris are well established, we understand very little about its biology. This parasite is renowned for its unique life cycle and capacity to cause arterial damage, leading to significant health and economic impacts for the equine industry. It also is the most intensively documented Strongylin; however, S. vulgaris has yet to gain drug resistance as …

Exploring 3d Genome Interaction And Epigenetic Regulation Via Swi/Snf Complex And Deep Learning Models, Ruoyun Wang

Dartmouth College Ph.D Dissertations

The three-dimensional organization of the genome is fundamental in regulating gene expression and maintaining cellular function. This organization's complexities, influenced by epigenetic marks and chromatin remodeling complexes, are crucial for understanding genomic regulation. Among these, the SWI/SNF complexes are key, facilitating chromatin accessibility and regulating gene activity across cell types. The first part of my dissertation focuses on SWI/SNF complexes, exploring their role in chromatin remodeling and their impact on 3D genome architecture. Utilizing next-generation sequencing (NGS) techniques, this section investigates the interplay between these complexes and chromatin structure. During my research on the SWI/SNF complex, I was intrigued by …

Contemporary Vs. Traditional Dna-Based Mutation Testing To Detect Hereditary Breast And Ovarian Cancer Syndrome (Hboc) In Women: A Meta Narrative Review, Hannah Olivia Cantu, Jacob Hipp, Nyela Y. Lopez, Duc Duy Nguyen

Research Methods Poster Session 2024

No abstract provided.

The Evolution Of The Metazoan Circadian Molecular Mechanism And The Conservation Of Canonical Circadian Elements, Olivia Waldridge

Theses and Dissertations--Biology

The temporal organization of biological activities through circadian rhythms is pivotal for the survival of organisms. Significant progress has been made in understanding the molecular foundations of animal circadian clocks through the characterization of key components such as Clock, Bmal1/Cycle(Cyc), Period (Per), Timeless, and Cryptochrome (Cry) in several model organisms. To determine the universality of this conservation, we investigated the sequences of these genes and their paralogs across 46 animal species that encompass multiple phyla in the metazoan kingdom to resolve the relative timing of duplication and loss events that have diversified core clock components in the metazoan kingdom. Using …

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 …

Developing Cellular Systems To Elucidate Rna Structural Dynamics Of Cag Expansion Transcripts In Spinocerebellar Ataxias, Victoria Demeo

Electronic Theses & Dissertations (2024 - present)

Spinocerebellar ataxias (SCAs) are a diverse group of over 40 genetically heterogeneous neurodegenerative disorders, many of which are caused by a trinucleotide CAG repeat expansion in the coding region of specific genes. These expansions lead to the production of polyglutamine (polyQ) tracts that interfere with normal protein function, triggering cellular dysfunction and contributing to disease pathogenesis. The most well-known of these SCAs, such as SCA1, SCA2, and SCA3, exhibit progressive neurodegeneration, yet the precise mechanisms through which these mutations cause disease remain poorly understood.

A significant challenge in studying CAG repeat expansion disorders lies in the complexity of the disease …

Ai And Ml-Based Risk Assessment Of Chemicals: Predicting Carcinogenic Risk From Chemical-Induced Genomic Instability, Ajay Vikram Singh, Preeti Bhardwaj, Peter Laux, Prachi Pradeep, Madleen Busse, Andreas Luch, Akihiko Hirose, Christopher J. Osgood, Michael W. Stacey

Biological Sciences Faculty Publications

Chemical risk assessment plays a pivotal role in safeguarding public health and environmental safety by evaluating the potential hazards and risks associated with chemical exposures. In recent years, the convergence of artificial intelligence (AI), machine learning (ML), and omics technologies has revolutionized the field of chemical risk assessment, offering new insights into toxicity mechanisms, predictive modeling, and risk management strategies. This perspective review explores the synergistic potential of AI/ML and omics in deciphering clastogen-induced genomic instability for carcinogenic risk prediction. We provide an overview of key findings, challenges, and opportunities in integrating AI/ML and omics technologies for chemical risk assessment, …

A Case Of Incipient Budding Speciation In The California Floristic Province, Infraspecific Divergence In Abronia Villosa, Eli J. Allen

Cal Poly Humboldt theses and projects

Physical barriers to gene flow are the traditional evidence for species divergence. Conversely, there has been increasing acknowledgment of speciation in the face of gene flow as an evolutionary process. Budding speciation involves peripheral populations adapting to local ecological conditions, thereby budding off from a widespread progenitor species. Budding speciation is distinguished by ecological divergence and is generally evidenced by asymmetrical range size and nested phylogenetic relationships of sister species. The narrow endemic Abronia villosa var. aurita is adapted to montane sandy washes adjacent to its widespread sister variety, the desert dwelling var. villosa. Here, I tested the hypothesis …

Machine Learning And Rna Bioinformatics, Jason Rafe Miller

Graduate Theses, Dissertations, and Problem Reports (ETD)

The applied science of bioinformatics encompasses computational analysis of molecular biology data. Advances in genomics and DNA sequencing technology have enabled computational analysis of ribonucleic acids (RNAs), which play diverse and critical roles in most cells. To assist the study of human RNA, we trained machine learning models on RNA nucleotide sequences, devoid of domain knowledge. We built models that distinguish long non-coding lncRNA from protein-coding mRNA, and models that predict the cytoplasmic vs. nuclear preferences of lncRNAs. In a review of published lncRNA subcellular localization classifiers, we show that the commonly used validation protocol generates optimistic performance measures, and …

Model-Based Deep Autoencoders For Clustering Single-Cell Rna Sequencing Data With Side Information, Xiang Lin

Dissertations

Clustering analysis has been conducted extensively in single-cell RNA sequencing (scRNA-seq) studies. scRNA-seq can profile tens of thousands of genes' activities within a single cell. Thousands or tens of thousands of cells can be captured simultaneously in a typical scRNA-seq experiment. Biologists would like to cluster these cells for exploring and elucidating cell types or subtypes. Numerous methods have been designed for clustering scRNA-seq data. Yet, single-cell technologies develop so fast in the past few years that those existing methods do not catch up with these rapid changes and fail to fully fulfil their potential. For instance, besides profiling transcription …