Genetics and Genomics Commons^™

Whole-Exome Sequencing And Hipsc Cardiomyocyte Models Identify Myrip, Trappc11, And Slc27a6 Of Potential Importance To Left Ventricular Hypertrophy In An African Ancestry Population, Marguerite R. Irvin, Praful Aggarwal, Steven A. Claas, Lisa De Las Fuentes, Anh N. Do, C. Charles Gu, Andrea Matter, Benjamin S. Olson, Amit Patki, Karen Schwander, Joshua D. Smith, Vinodh Srinivasasainagendra, Hemant K. Tiwari, Amy J. Turner, Deborah A. Nickerson, Dabeeru C. Rao, Ulrich Broeckel, Donna K. Arnett

Epidemiology and Environmental Health Faculty Publications

Background: Indices of left ventricular (LV) structure and geometry represent useful intermediate phenotypes related to LV hypertrophy (LVH), a predictor of cardiovascular (CV) disease (CVD) outcomes.

Methods and Results: We conducted an exome-wide association study of LV mass (LVM) adjusted to height^2.7, LV internal diastolic dimension (LVIDD), and relative wall thickness (RWT) among 1,364 participants of African ancestry (AAs) in the Hypertension Genetic Epidemiology Network (HyperGEN). Both single-variant and gene-based sequence kernel association tests were performed to examine whether common and rare coding variants contribute to variation in echocardiographic traits in AAs. We then used a data-driven …

Deep Learning For Multi-Tissue Cancer Classification Of Gene Expressions, Tarek Khorshed

Theses and Dissertations

We contribute in saving the lives of cancer patients through early detection and diagnosis, since one of the major challenges in cancer treatment is that patients are diagnosed at very late stages when appropriate medical interventions become less effective and full curative treatment is no longer achievable. Cancer classification using gene expressions is extremely challenging given the complexity and high dimensionality of the data. Current classification methods typically rely on samples collected from a single tissue type and perform a prerequisite of gene feature selection to avoid processing the full set of genes. These methods fall short in taking advantage …

Forensic Genealogy: A Tool In Dna Analysis, Samantha Olsen

Undergraduate Honors College Theses 2016-

DNA is the basic unit of which differentiates one individual to the next. Short Tandem Repeats and Single Nucleotide Polymorphisms are two locations of DNA that have been the most successful in DNA analysis. Unique DNA profiles can be created so that interpretations can be made about the individual who contributed to the DNA sample. Systems like STRmix are currently being employed to give unbiased assumptions about the DNA profiles. There are several different statistical approaches in assigning probabilities to DNA evidence, likelihood ratio and random match probability are two common approaches. After assumptions are made, comparisons can be made …

Principal Components Analysis Corrects Collider Bias In Polygenic Risk Score Effect Size Estimation, Nathaniel S. Thomas, Peter B. Barr, Fazil Aliev, Sally I. Kuo, Danielle M. Dick, Jessica E. Salvatore

Graduate Research Posters

BACKGROUND: Genome-wide polygenic scoring has emerged as a way to predict psychiatric and behavioral outcomes and identify environments that promote the expression of genetic risks. An increasing number of studies demonstrate that the effects of polygenic risk scores (PRS) may be biased by the inclusion of heritable environments as covariates when the environment is influenced by unmeasured confounding variables, an example of collider bias. Inclusion of the principal components of observed confounders as covariates may correct for the effect of unmeasured confounders.

METHODS: A simulation study was conducted to test principal components analysis (PCA) as a correction for collider bias. …

Transcriptional Repressor Protein Based Macrolide Biosensor Development With Improved Sensitivity, Jayani A. Christopher

Graduate Research Posters

Macrolide antibiotics are in high demand for clinical applications. Macrolides are biosynthesized via giant assembly line polyketide synthases (PKS) which are arranged in a modular fashion. Combinatorial biosynthetic methods have been used to produce diversified macrolides by reprograming these modules and modifying tailoring enzymes required for post synthetic modifications. However it is challenging due to the size and complexity of PKSs. To overcome this challenge, new enzymes for macrolide diversification could be obtained by directed evolution where a large number of enzyme variants need to be screened. Therefore it is important to develop high throughput screening methods to identify the …

Computational Study Of Target Gene Interactions - Enhancers And Micrornas, Amlan Talukder

Electronic Theses and Dissertations, 2020-2023

Gene expression is an essential mechanism for physical and mental development of human. Aberrant regulation of gene expression creates abnormality in human body than can lead to complicated diseases. Gene expression can be regulated at any stage from the chromatin unfolding stage to post-translation stage of protein. In this study, we focused on two important factors of gene expression regulation that participate in the gene expression process at the transcription and the post-transcriptional stages; enhancer-promoter interactions and miRNA-mRNA interactions. The enhancer-promoter interactions are difficult to detect due to the large distance between the enhancer and promoter region and cell-specific activity …

An Evaluation Of The Bighorn Sheep Population In Badlands National Park, Austin J. Wieseler

Electronic Theses and Dissertations

Within the last century, bighorn sheep (Ovis canadensis) in the badlands ecosystem of western South Dakota have been subjected to complete extirpation, reintroduction, disease die-offs, genetic bottlenecking, and population augmentation. Subsequently, the population in Badlands National Park (BNP) appears to have recovered, but it was unknown to what degree past events had influenced the population. From 2017-2019, we conducted research on 5 subherds within 2 management units in BNP to 1) survey for the presence of respiratory pathogens and estimate the prevalence of other potentially infectious diseases; 2) assess adult and lamb survival and cause-specific mortality; 3) estimate population size …

Comparison Of Software Packages For Detecting Differentially Expressed Genes From Single-Sample Rna-Seq Data, Rong Zhou

Electronic Theses and Dissertations

RNA-sequencing (RNA-seq) has rapidly become the tool in many genome-wide transcriptomic studies. It provides a way to understand the RNA environment of cells in different physiological or pathological states to determine how cells respond to these changes. RNA-seq provides quantitative information about the abundance of different RNA species present in a given sample. If the difference or change observed in the read counts or expression level between two experimental conditions is statistically significant, the gene is declared as differentially expressed. A large number of methods for detecting differentially expressed genes (DEGs) with RNA-seq have been developed, such as the methods …

Analysis Of Subtelomeric Rextal Assemblies Using Quast, Tunazzina Islam, Desh Ranjan, Mohammad Zubair, Eleanor Young, Ming Xiao, Harold Riethman

Computer Science Faculty Publications

Genomic regions of high segmental duplication content and/or structural variation have led to gaps and misassemblies in the human reference sequence, and are refractory to assembly from whole-genome short-read datasets. Human subtelomere regions are highly enriched in both segmental duplication content and structural variations, and as a consequence are both impossible to assemble accurately and highly variable from individual to individual. Recently, we developed a pipeline for improved region-specific assembly called Regional Extension of Assemblies Using Linked-Reads (REXTAL). In this study, we evaluate REXTAL and genome-wide assembly (Supernova) approaches on 10X Genomics linked-reads data sets partitioned and barcoded using the …

Construction And Analysis Of Genetic Regulatory Networks With Rna-Seq Data From Arabidopsis Thaliana, Tessa Kriz

Dissertations, Master's Theses and Master's Reports

Reconstruction of gene regulatory networks (GRNs) is a fundamental aspect of genetic engineering and provides a deeper understanding of the biological processes of an organism. Two methods were implemented to reconstruct the gene regulatory networks of Arabidopsis thaliana under two treatments: methyl jasmonate (MeJa) and salicylic acid (SA). The Joint Reconstruction of multiple Gene Regulatory Networks (JRmGRN) method was utilized to construct a joint network for identifying hub genes common to both conditions in addition to networks specific to each condition. The Differential Network Analysis with False Discover Rate Control method constructed a network of connections unique to only one …

Statistical Methods In Genetic Studies, Cheng Gao

Dissertations, Master's Theses and Master's Reports

This dissertation includes three Chapters. A brief description of each chapter is organized as follows.

In Chapter 1, we proposed a new method, called MF-TOWmuT, for genome-wide association studies with multiple genetic variants and multiple phenotypes using family samples. MF-TOWmuT uses kinship matrix to account for sample relatedness. It is worth mentioning that in simulations, we considered hidden polygenic effects and varied the proportion of variance contributed by it to generate phenotypes. Simulation studies show that MF-TOWmuT can preserve the type I error rates and is more powerful than several existing methods in different simulation scenarios, MFTOWmuT is also quite …

Mite Diet Sequences Obtained By High Throughput Sequencing Of Gut Contents Of Freshly Collected Water Mites, Adrian Amelio Vasquez, Obadeh Mohiddin, Zeyu Li, Brittany L. Bonnici, Katherine Gurdziel, Jeffrey L. Ram

Physiology Faculty Research Publications

Cytochrome oxidase subunit I (COI) barcode sequences in this file were obtained from gut DNA extracted from 54 freshly collected water mites, comprising 21 Lebertia quinquemaculosa , 30 Lebertia davidcooki , 1 Limnesia , and 2 Arrenurus specimens. Methods and other details about these sequences are described in a paper by the same authors in a submitted publication (2021: URL to be given here when published). Data on collection locations, primers (mLep and LCOI), amino acid translations, etc. are included in corresponding sequences uploaded to GenBank. The right column below contains additional notes on naming the taxa of the sequences …

Joint Modeling Of Rnaseq And Radiomics Data For Glioma Molecular Characterization And Prediction, Zeina A. Shboul, Norou Diawara, Arastoo Vossough, James Y. Chen, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

RNA sequencing (RNAseq) is a recent technology that profiles gene expression by measuring the relative frequency of the RNAseq reads. RNAseq read counts data is increasingly used in oncologic care and while radiology features (radiomics) have also been gaining utility in radiology practice such as disease diagnosis, monitoring, and treatment planning. However, contemporary literature lacks appropriate RNA-radiomics (henceforth, radiogenomics) joint modeling where RNAseq distribution is adaptive and also preserves the nature of RNAseq read counts data for glioma grading and prediction. The Negative Binomial (NB) distribution may be useful to model RNAseq read counts data that addresses potential shortcomings. …

Exploring The Genetic Variability Of Zebra Mussels Dreisenna Polymoprha, Maxwell Carr

Journal of Earth and Life Science

Zebra Mussels Dreisenna polymorpha are one of the most well-known invasive species here in the United States. This species can take over watersheds very quickly, causing damage to both the ecosystem and man-made structures. The basic physical behavior of this species has been well documented, but the invasive North American Zebra Mussel is much more aggressive and therefore causes more damage in the Great Lakes region compared to its native waters. Genetic variation may be playing a very large role in how and why D. polymorpha is causing such large problems for stakeholders in the United States. This review cites …

An Enumeration Of Nested Networks, Nathan Cornelius

Williams Honors College, Honors Research Projects

Nested networks have several applications in phylogenetics and electrical circuit theory. In many cases, there may exist more than one distinct network which correctly models a given data set. This proposes a combinatorial problem to determine all possible network solutions. In this paper, we partially solve this problem by developing exponential generating functions which enumerate all 1-nested and 2-nested unicyclic networks. We also describe our procedure to directly count all 1-nested and 2-nested networks and provide all 1-nested networks with 7, 8, and 9 terminal nodes.

Ensemble Protein Inference Evaluation, Kyle Lee Lucke

Graduate Student Theses, Dissertations, & Professional Papers

The Protein inference problem is becoming an increasingly important tool that aids in the characterization of complex proteomes and analysis of complex protein samples. In bottom-up shotgun proteomics experiments the metrics for evaluation (like AUC and calibration error) are based on an often imperfect target-decoy database. These metrics make the inherent assumption that all of the proteins in the target set are present in the sample being analyzed. In general, this is not the case, they are typically a mix of present and absent proteins. To objectively evaluate inference methods, protein standard datasets are used. These datasets are special in …

Fmri Feature Extraction Model For Adhd Classification Using Convolutional Neural Network, Senuri De Silva, Sanuwani Udara Dayarathna, Gangani Ariyarathne, Dulani Meedeniya, Sampath Jayarathna

Computer Science Faculty Publications

Biomedical intelligence provides a predictive mechanism for the automatic diagnosis of diseases and disorders. With the advancements of computational biology, neuroimaging techniques have been used extensively in clinical data analysis. Attention deficit hyperactivity disorder (ADHD) is a psychiatric disorder, with the symptomology of inattention, impulsivity, and hyperactivity, in which early diagnosis is crucial to prevent unwelcome outcomes. This study addresses ADHD identification using functional magnetic resonance imaging (fMRI) data for the resting state brain by evaluating multiple feature extraction methods. The features of seed-based correlation (SBC), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) are comparatively applied to …

A Hybrid Gene Selection Strategy Based On Fisher And Ant Colony Optimization Algorithm For Breast Cancer Classification, Mohammed Hamim, Ismail El Moudden, Mohan D. Pant, Hicham Moutachaouik, Mustapha Hain

EVMS School of Health Professions Faculty Publications

Breast cancer poses the greatest threat to human life and especially to women's life. Despite the progress made in data mining technology in recent years, the ability to predict and diagnose such fatal diseases based on gene expression data still reveals a limited prediction performance, which may not be surprising since most of the genes in expression data are believed to be irrelevant or redundant. The dimensionality reduction process may be considered as a crucial step to analyze gene expression data, as it can reduce the high dimensionality of the breast cancer datasets, which may result into a better prediction …

Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das

Electronic Theses and Dissertations

Recently, gene set analysis has become the first choice for gaining insights into the underlying complex biology of diseases through high-throughput genomic studies, such as Microarrays, bulk RNA-Sequencing, single cell RNA-Sequencing, etc. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results. Further, the statistical structure and steps common to these approaches have not yet been comprehensively discussed, which limits their utility. Hence, a comprehensive overview of the available gene set analysis approaches used for different high-throughput genomic studies is provided. The analysis of gene sets is usually carried out based on …

Gene Set Testing By Distance Correlation, Sho-Hsien Su

Graduate Theses and Dissertations

Pathways are the functional building blocks of complex diseases such as cancers. Pathway-level studies may provide insights on some important biological processes. Gene set test is an important tool to study the differential expression of a gene set between two groups, e.g., cancer vs normal. The differential expression of a gene set could be due to the difference in mean, variability, or both. However, most existing gene set tests only target the mean difference but overlook other types of differential expression. In this thesis, we propose to use the recently developed distance correlation for gene set testing. To assess the …

Bayesian Variable Selection Methods For Genome-Wide Association Studies With Categorical Phenotypes, Benazir Rowe

UNLV Theses, Dissertations, Professional Papers, and Capstones

Genome-wide association studies (GWAS) attempt to find the associations between genetic markers and studied traits (phenotypes). The problem of GWAS is complex and various methods have been developed to approach it. One of such methods is Bayesian variable selection (BVS). We describe the BVS methods in detail and demonstrate the ability of BVS method Posterior Inference via Model Averaging and Subset Selection (piMASS) to improve the power of detecting phenotype-associated genetic loci, potentially leading to new discoveries from existing data without increasing the sample size.

We present several ways to improve and extend the applicability of piMASS for GWAS. The …

Neogene And Quaternary Events Shaped Diversification And Speciation In Bhutanese Rheophilic Fishes Of The Family Nemacheilidae (Cypriniformes) And Sisoridae (Siluriformes), Karma Wangchuk

Graduate Theses and Dissertations

Biogeography of the Himalayan region [to include the Qinghai-Tibetan Plateau (QTP)] evolved over a ~30M year span, catalyzed by the collision of the Indian and Eurasian plates. The resulting uplift produced major ecological and climatic effects, that in turn drove the diversification of biodiversity. As a result, the QTP is designated as a global biodiversity hotspot particularly vulnerable to cumulative climatic effects, including shrinking distributions, declining numbers, and local extinctions. Understanding how the biodiversity within the Himalaya/ QTP was established and maintained is a necessary first step in prioritizing conservation efforts.

Fishes in global montane regions, such as the Himalaya, …

The Effect Of Fcgammariia Polymorphisms On Dengue Outbreak Severity, Leah Darwin, Richard V. Clarke

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Genetic Polymorphism Of Bitter Taste Perception In Tempe, Arizona And Its Association With Nutritional Status, Daniel Woodley, Benjamin Cabrera

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Defining Relictual Biodiversity: Conservation Units In Speckled Dace (Leuciscidae: Rhinichthys Osculus) Of The Greater Death Valley Ecosystem, Steven M. Mussmann, Marlis R. Douglas, David D. Oakey, Michael E. Douglas

Biological Sciences Faculty Publications and Presentations

The tips in the tree of life serve as foci for conservation and management, yet clear delimitations are masked by inherent variance at the species–population interface. Analyses using thousands of nuclear loci can potentially sort inconsistencies, yet standard categories applied to this parsing are themselves potentially conflicting and/or subjective [e.g., DPS (distinct population segments); DUs (Diagnosable Units-Canada); MUs (management units); SSP (subspecies); ESUs (Evolutionarily Significant Units); and UIEUs (uniquely identified evolutionary units)]. One potential solution for consistent categorization is to create a comparative framework by accumulating statistical results from independent studies and evaluating congruence among data sets. Our study illustrates …

Machine Learning Applications For Drug Repurposing, Hansaim Lim

Dissertations, Theses, and Capstone Projects

The cost of bringing a drug to market is astounding and the failure rate is intimidating. Drug discovery has been of limited success under the conventional reductionist model of one-drug-one-gene-one-disease paradigm, where a single disease-associated gene is identified and a molecular binder to the specific target is subsequently designed. Under the simplistic paradigm of drug discovery, a drug molecule is assumed to interact only with the intended on-target. However, small molecular drugs often interact with multiple targets, and those off-target interactions are not considered under the conventional paradigm. As a result, drug-induced side effects and adverse reactions are often neglected …

Statistical Methods For Resolving Intratumor Heterogeneity With Single-Cell Dna Sequencing, Alexander Davis

Dissertations and Theses (Open Access)

Tumor cells have heterogeneous genotypes, which drives progression and treatment resistance. Such genetic intratumor heterogeneity plays a role in the process of clonal evolution that underlies tumor progression and treatment resistance. Single-cell DNA sequencing is a promising experimental method for studying intratumor heterogeneity, but brings unique statistical challenges in interpreting the resulting data. Researchers lack methods to determine whether sufficiently many cells have been sampled from a tumor. In addition, there are no proven computational methods for determining the ploidy of a cell, a necessary step in the determination of copy number. In this work, software for calculating probabilities from …

An Investigation Into Multi-View Error Correcting Output Code Classifiers Applied To Organ Tissue Classification, Daniel Alvarez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Large amounts of data is being generated constantly each day, so much data that it is difficult to find patterns in order to predict outcomes and make decisions for both humans and machines alike. It would be useful if this data could be simplified using machine learning techniques. For example, biological cell identity is dependent on many factors tied to genetic processes. Such factors include proteins, gene transcription, and gene methylation. Each of these factors are highly complex mechanism with immense amounts of data. Simplifying these can then be helpful in finding patterns in them. Error-Correcting Output Codes (ECOC) does …

An Investigation Of Gene Regulatory Network State Space Variability, Sara Faye Liesman

Theses and Dissertations

Genes are segments of DNA that provide a blueprint for cells and organisms to effectively control processes and regulations within individuals. There have been many attempts to quantify these processes, as a greater understanding of how genes operate could have large impacts on both personalized and precision medicine. Gene interactions are of particular interest, however, current biological methods can not easily reveal the details of these interactions. Therefore, we infer networks of interactions from gene expression data which we call a gene regulatory network, or GRN. Due to the robust behavior of genes and the inherent variability within interactions, models …

Statistical Inference Of Adaptation At Multiple Genomic Scales Using Supervised Classification And A Hidden Markov Model, Lauren A. Sugden

Biology and Medicine Through Mathematics Conference

No abstract provided.