Digital Commons Network^™

Deciphering The Genetic Architecture Of Key Female Floral Traits For Hybrid Wheat Seed Production, Juan Jimenez

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Wheat (Triticum aestivum L.) is a staple cereal that provides 20% of the calories and proteins in human intake (Ray et al., 2013). Global population is projected to increase to 9.7 billion by 2050. Food production must increase by 70% to feed this future population. Wheat production is in crisis due to political and environmental challenges and is projected to decline by 0.8% in 2022 (FAO, 2022). To ensure food security yield genetic gain must increase by around 1.4% annually. Taking advantage of heterosis, hybrid wheat has the potential to boost grain yield. However, hybrid wheat seed production systems …

Sequence-Based Bioinformatics Approaches To Predict Virus-Host Relationships In Archaea And Eukaryotes, Yingshan Li

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

Viral metagenomics is independent of lab culturing and capable of investigating viromes of virtually any given environmental niches. While numerous sequences of viral genomes have been assembled from metagenomic studies over the past years, the natural hosts for the majority of these viral contigs have not been determined. Different computational approaches have been developed to predict hosts of bacteria phages. Nevertheless, little progress has been made in the virus-host prediction, especially for viruses that infect eukaryotes and archaea. In this study, by analyzing all documented viruses with known eukaryotic and archaeal hosts, we assessed the predictive power of four computational …

Radiation Exposure Determination In A Secure, Cloud-Based Online Environment, Ben C. Shirley, Eliseos J. Mucaki, Peter Rogan

Biochemistry Publications

Rapid sample processing and interpretation of estimated exposures will be critical for triaging exposed individuals after a major radiation incident. The dicentric chromosome (DC) assay assesses absorbed radiation using metaphase cells from blood. The Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI) identifies DCs and determines radiation doses. This study aimed to broaden accessibility and speed of this system, while protecting data and software integrity. ADCI Online is a secure web-streaming platform accessible worldwide from local servers. Cloud-based systems containing data and software are separated until they are linked for radiation exposure estimation. Dose estimates are identical to ADCI …

Tree To Tree: Phylogenetics Of Diverse Anura Using Portable Lab Equipment: Primer Optimization, Bioinformatic Pipeline, And Phylogenetic Analyses Reveal Potential New Species And Ability To Identify Evolutionary Relationships In A Hyper Diverse Anura Clade Using Nanopore Sequencing, Elinor Sterner

Independent Study Project (ISP) Collection

The Corredor Llanganates-Sangay is an extremely significant region for conservation, coined a “gift to the earth” by the World Wildlife Fund. Understanding amphibians species and populations is key due to their roles as hyper sensitive bioindicators. In recent years, portable sequencing equipment (Mini PCR thermocyclers, Oxford Nanopore Technology’s MinION sequencer, etc) make genetic data collection in remote areas possible, greatly increasing potential for conservation genetics and genomics. This study uses portable equipment to sequence two mitochondrial loci in 104 Anuran samples collected in four sites in the Corridor and presents phylogenies of each gene as well as a concatenated phylogeny. …

Patient-Specific Genome-Scale Metabolic Models For Individualized Predictions Of Liver Disease, Alexandra Manchel, Jan B. Hoek, Ramon Bataller, Radhakrishnan Mahadevan, Rajanikanth Vadigepalli

Department of Pathology, Anatomy, and Cell Biology Faculty Papers

The prevalence of liver disease is steadily increasing, coupled with the limited availability of therapeutic treatments. Recent literature points to metabolic reprogramming as a key feature of liver failure. Hence, we sought to uncover the metabolic pathways and mechanisms associated with liver disease and acute liver failure. We generated patient-specific genome scale metabolic models by integrating RNA-seq data from patient liver samples with a generalized human metabolic model. Flux balance analysis simulations showed a distinct separation of non-alcohol associated and alcohol-associated disease states. Our analysis suggests that the alcohol associated liver has an increased flux through nucleotide and glycerophospholipid metabolic …

Statistical Genetic Discoveries Using Restricted Maximum Likelihood Method, Erika Wu

2022 REYES Proceedings

In statistical genetics, genetic association and genomic prediction become more successful with a highly heritable trait. Identifying highly heritable components of a complex disease can thus advance scientific understanding of the disease and potentially lead to effective prevention and treatments. Using Matlab and existing large-scale genome datasets, we evaluate a restricted maximum likelihood approach to identify highly heritable components of a complex disease as a function of multiple clinical variables.

Insights To Protein Pathogenicity From The Lens Of Protein Evolution, Janelle Nunez-Castilla

FIU Electronic Theses and Dissertations

As protein sequences evolve, differences in selective constraints may lead to outcomes ranging from sequence conservation to structural and functional divergence. Evolutionary protein family analysis can illuminate which protein regions are likely to diverge or remain conserved in sequence, structure, and function. Moreover, nonsynonymous mutations in pathogens may result in the emergence of protein regions that affect the behavior of pathogenic proteins within a host and host response. I aimed to gain insight on pathogenic proteins from cancer and viruses using an evolutionary perspective. First, I examined p53, a conformationally flexible, multifunctional protein mutated in ~50% of human cancers. Multifunctional …

In Silico Characterization Of Protein-Protein Interactions Mediated By Short Linear Motifs, Heidy Elkhaligy

FIU Electronic Theses and Dissertations

Short linear motifs (SLiMs), often found in intrinsically disordered regions (IDPs), can initiate protein-protein interactions in eukaryotes. Although pathogens tend to have less disorder than eukaryotes, their proteins alter host cellular function through molecular mimicry of SLiMs. The first objective was to study sequence-based structure properties of viral SLiMs in the ELM database and the conservation of selected viral motifs involved in the virus life cycle. The second objective was to compare the structural features for SliMs in pathogens and eukaryotes in the ELM database. Our analysis showed that many viral SliMs are not found in IDPs, particularly glycosylation motifs. …

Alterations Of The Gut Mycobiome In Patients With Ms - A Bioinformatic Approach, Saumya Shah

Honors Scholar Theses

The mycobiome is the fungal component of the gut microbiome and is implicated in several autoimmune diseases. However, its role in multiple sclerosis (MS) has not been studied. We performed descriptive and formal statistical tests using the R language to characterize the gut mycobiome in people with MS (pwMS) and healthy controls. We found that the microbiome composition of multiple sclerosis patients is different from healthy people. The mycobiome had significantly higher alpha diversity and inter-subject variation in pwMS than controls. Additionally, Saccharomyces and Aspergillus were over-represented in pwMS. Different mycobiome profiles, defined as mycotypes, were associated with different bacterial …

Comparative Analyses Of De Novo Transcriptome Assembly Pipelines For Diploid Wheat, Natasha Pavlovikj

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

Gene expression and transcriptome analysis are currently one of the main focuses of research for a great number of scientists. However, the assembly of raw sequence data to obtain a draft transcriptome of an organism is a complex multi-stage process usually composed of pre-processing, assembling, and post-processing. Each of these stages includes multiple steps such as data cleaning, error correction and assembly validation. Different combinations of steps, as well as different computational methods for the same step, generate transcriptome assemblies with different accuracy. Thus, using a combination that generates more accurate assemblies is crucial for any novel biological discoveries. Implementing …

Genomic Analysis Of Metabolic Differences Found In Clostridium Perfringens That Cause Necrotic Enteritis In Poultry, Connor Aylor

School of Veterinary and Biomedical Sciences: Dissertations, Theses, and Student Research

Clostridium perfringens is a common member of gut microbiota in healthy animals, but can also be an important pathogen in human and veterinary medicine. It produces several protein toxins that contribute to both histotoxic and enteric diseases in animals. Necrotic enteritis in poultry has been associated with the NetB toxin of C. perfringens; however, this toxin alone is insufficient to cause disease in infected chickens. While considerable research has focused on the presence of toxins and virulence factors, little has been done to assess the function of metabolic factors on the ability of the bacteria to cause disease. In …

Using Machine Learning To Recognize Chronic Rhinosinusitis, Irene Liu '23

Student Publications & Research

Chronic Rhinosinusitis (CRS) is a nasal disease characterized by the inflammation of the mucosa and paranasal sinuses with a duration of at least 12 consecutive weeks. So, to diagnose CRS, one needs to keep a record of their symptoms for ~12 weeks before they are recommended to get a tomography which will allow physicians to classify them as a patient with CRS or without. This is a timely and costly process; thus, machine learning should be used to speed the process up. Since patients with CRS have more obstructed noses, the sound produced should be different than an individual without …

A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun

FIU Electronic Theses and Dissertations

Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.

However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.

Traditional approaches for biomarker discovery calculate the fold change for each …

The Low Abundance Of Cpg In The Sars-Cov-2 Genome Is Not An Evolutionarily Signature Of Zap, Ali Afrasiabi, Hamid Alinejad-Rokny, Azad Khosh, Mostafa Rahnama, Nigel Lovell, Zhenming Xu, Diako Ebrahimi

Plant Pathology Faculty Publications

The zinc finger antiviral protein (ZAP) is known to restrict viral replication by binding to the CpG rich regions of viral RNA, and subsequently inducing viral RNA degradation. This enzyme has recently been shown to be capable of restricting SARS-CoV-2. These data have led to the hypothesis that the low abundance of CpG in the SARS-CoV-2 genome is due to an evolutionary pressure exerted by the host ZAP. To investigate this hypothesis, we performed a detailed analysis of many coronavirus sequences and ZAP RNA binding preference data. Our analyses showed neither evidence for an evolutionary pressure acting specifically on CpG …

Cbp60-Db: An Alphafold-Predicted Plant Kingdom-Wide Database Of The Calmodulin-Binding Protein 60 (Cbp60) Protein Family With A Novel Structural Clustering Algorithm, Keaun Amani, Vanessa Shivnauth, Christian Castroverde

Biology Faculty Publications

Molecular genetic analyses in the model species Arabidopsis thaliana have demonstrated the major roles of different CAM-BINDING PROTEIN 60 (CBP60) proteins in growth, stress signaling, and immune responses. Prominently, CBP60g and SARD1 are paralogous CBP60 transcription factors that regulate numerous components of the immune system, such as cell surface and intracellular immune receptors, MAP kinases, WRKY transcription factors, and biosynthetic enzymes for immunity-activating metabolites salicylic acid (SA) and N-hydroxypipecolic acid (NHP). However, their function, regulation and diversification in most species remain unclear. Here we have created CBP60-DB, a structural and bioinformatic database that comprehensively characterized 1052 CBP60 gene homologs …

Completing Single-Cell Dna Methylome Profiles Via Transfer Learning Together With Kl-Divergence, Sanjeeva Dodlapati, Zongliang Jiang, Jiangwen Sun

Computer Science Faculty Publications

The high level of sparsity in methylome profiles obtained using whole-genome bisulfite sequencing in the case of low biological material amount limits its value in the study of systems in which large samples are difficult to assemble, such as mammalian preimplantation embryonic development. The recently developed computational methods for addressing the sparsity by imputing missing have their limits when the required minimum data coverage or profiles of the same tissue in other modalities are not available. In this study, we explored the use of transfer learning together with Kullback-Leibler (KL) divergence to train predictive models for completing methylome profiles with …