A Single-Cell Atlas Of Bovine Skeletal Muscle Reveals Mechanisms Regulating Intramuscular Adipogenesis And Fibrogenesis, Leshan Wang, Peidong Gao, Chaoyang Li, Qianglin Liu, Zeyang Yao, Yuxia Li, Xujia Zhang, Jiangwen Sun, Constantine Simintiras, Matthew Welborn, Kenneth Mcmillin, Stephanie Oprescu, Shihuan Kuang, Xing Fu

Computer Science Faculty Publications

Background

Intramuscular fat (IMF) and intramuscular connective tissue (IMC) are often seen in human myopathies and are central to beef quality. The mechanisms regulating their accumulation remain poorly understood. Here, we explored the possibility of using beef cattle as a novel model for mechanistic studies of intramuscular adipogenesis and fibrogenesis.

Methods

Skeletal muscle single-cell RNAseq was performed on three cattle breeds, including Wagyu (high IMF), Brahman (abundant IMC but scarce IMF), and Wagyu/Brahman cross. Sophisticated bioinformatics analyses, including clustering analysis, gene set enrichment analyses, gene regulatory network construction, RNA velocity, pseudotime analysis, and cell-cell communication analysis, were performed to elucidate …

An Approach To Developing Benchmark Datasets For Protein Secondary Structure Segmentation From Cryo-Em Density Maps, Thu Nguyen, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5--10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study …

Characterization Of Cell Type-Specific Molecular Heterogeneity In Cancer Using Multi-Omic Approaches, Min Kyung Lee

Dartmouth College Ph.D Dissertations

Tumors are composed of heterogeneous cell types each with its own unique molecular profiles. Recent advances in single cell genomics technologies have begun to increase our understanding of the molecular heterogeneity that exists in tumors with particular focus on gene expression and chromatin accessibility profiles. However, due to limitations in methods for certain sample types and high cost for single cell genomics, bulk tumor molecular profiling has been and remains widely used. In addition, other facets of single cell epigenomic profiling, particularly methylation and hydroxymethylation, remains underexplored. Thus, investigations to understand the cell type specific epigenetic heterogeneity and the cooperation …

A Standardized Pipeline For Isolation And Assembly Of Genomes From Symbiotic Bacteria In Whole Louse Genomic Sequence Data., Mohammad Mikail I. Bala

Theses and Dissertations

Many insects are known to harbour intracellular and heritable bacteria (endosymbionts), which provide their hosts with adaptive traits. Whole insect gDNA shotgun sequencing projects often sequence the genome of endosymbiont, in addition to the insect’s genome. There are approximately 600 whole genome shotgun libraries from insects available on the public repository (NCBI), which can be mined to obtain endosymbiont genomes. The assembly and annotation of endosymbiont genomes can contribute towards the exploration of their role as obligate symbiotic partners. However, de novo assembly of an endosymbiont genome, continues to be challenging, when the host and/or enteric bacterial gDNA is present …

Cellbrf: A Feature Selection Method For Single-Cell Clustering Using Cell Balance And Random Forest, Yunpei Xu, Hong-Dong Li, Cui-Xiang Lin, Ruiqing Zheng, Yaohang Li, Jinhui Xu, Jianxin Wang

Computer Science Faculty Publications

Motivation

Single-cell RNA sequencing (scRNA-seq) offers a powerful tool to dissect the complexity of biological tissues through cell sub-population identification in combination with clustering approaches. Feature selection is a critical step for improving the accuracy and interpretability of single-cell clustering. Existing feature selection methods underutilize the discriminatory potential of genes across distinct cell types. We hypothesize that incorporating such information could further boost the performance of single cell clustering. Results

We develop CellBRF, a feature selection method that considers genes’ relevance to cell types for single-cell clustering. The key idea is to identify genes that are most important for discriminating …

Methylation Patterns Across Tissue Type And Time In Peromyscus Leucopus: A Targeted Museum Study, Loryn Smith

Master's Theses or Doctor of Nursing Practice

Museum specimens are a vital data source for many types of studies. One relatively new use includes studying methylation patterns. Methylation patterns are a form of epigenetics or how gene expression changes without alteration of the genetic code. These patterns have been examined in many mammals. However, the focus has previously been on overall epigenetic patterns. Few studies have investigated whether methylation patterns differ across tissue types, time, or preservation method. In this study, I compared methylation patterns in muscle, liver, toe pads, and nasal bones from Peromyscus leucopus (white-footed mouse) museum specimens collected in 2022, 2018, 2014, and 2008 …

Cell Signaling And Stress Response In The Yeast Saccharomyces Cerevisiae: A Study Of Snf1, Scott E. Arbet Ii

Graduate Theses, Dissertations, and Problem Reports (ETD)

Saccharomyces cerevisiae are yeast that are unicellular eukaryotic organisms that are well studied as a model organism for understanding fundamental cellular processes. The ability of yeast to sense nutrient availability is crucial for their survival, growth, and reproduction. Yeast cells use various mechanisms to sense and respond to nutrient availability, including transporter-mediated uptake, receptor-mediated signaling, and sensing of metabolites. The subcellular localization of nutrient-sensing components is crucial for yeast function in nutrient sensing and signaling. Protein complexes, such as the AMP-activated protein kinase (AMPK) pathway, in nutrient sensing and response, as well as the downstream effects of these pathways …

Dfhic: A Dilated Full Convolution Model To Enhance The Resolution Of Hi-C Data, Bin Wang, Kun Liu, Yaohang Li, Jianxin Wang

Computer Science Faculty Publications

Motivation: Hi-C technology has been the most widely used chromosome conformation capture(3C) experiment that measures the frequency of all paired interactions in the entire genome, which is a powerful tool for studying the 3D structure of the genome. The fineness of the constructed genome structure depends on the resolution of Hi-C data. However, due to the fact that high-resolution Hi-C data require deep sequencing and thus high experimental cost, most available Hi-C data are in low-resolution. Hence, it is essential to enhance the quality of Hi-C data by developing the effective computational methods.

Results: In this work, we propose …

Intergenic Transcription In In Vivo Developed Bovine Oocytes And Pre-Implantation Embryos, Saurav Ranjitkar, Mohammad Shiri, Jiangwen Sun, Xiuchun Tian

Computer Science Faculty Publications

Background

Intergenic transcription, either failure to terminate at the transcription end site (TES), or transcription initiation at other intergenic regions, is present in cultured cells and enhanced in the presence of stressors such as viral infection. Transcription termination failure has not been characterized in natural biological samples such as pre-implantation embryos which express more than 10,000 genes and undergo drastic changes in DNA methylation.

Results

Using Automatic Readthrough Transcription Detection (ARTDeco) and data of in vivo developed bovine oocytes and embryos, we found abundant intergenic transcripts that we termed as read-outs (transcribed from 5 to 15 kb after TES) and …

Adjusting For Gene-Specific Covariates To Improve Rna-Seq Analysis, Hyeongseon Jeon, Kyu-Sang Lim, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

Summary

This paper suggests a novel positive false discovery rate (pFDR) controlling method for testing gene-specific hypotheses using a gene-specific covariate variable, such as gene length. We suppose the null probability depends on the covariate variable. In this context, we propose a rejection rule that accounts for heterogeneity among tests by employing two distinct types of null probabilities. We establish a pFDR estimator for a given rejection rule by following Storey's q-value framework. A condition on a type 1 error posterior probability is provided that equivalently characterizes our rejection rule. We also present a suitable procedure for selecting a tuning …

Prediction Of Kinase-Substrate Associations Using The Functional Landscape Of Kinases And Phosphorylation Sites, Serhan Yilmaz, Filipa Blasco Tavares Pereira Lopes, Mark R. Chance, Mehmet Koyutürk

Faculty Scholarship

Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships …

Accucalc: A Python Package For Accuracy Calculation In Gwas, Jana Biová, Nicholas Dietz, Yen On Chan, Trupti Joshi, Kristin Bilyeu, Mária Škrabišová

Biomedical Sciences

The genome-wide association study (GWAS) is a popular genomic approach that identifies genomic regions associated with a phenotype and, thus, aims to discover causative mutations (CM) in the genes underlying the phenotype. However, GWAS discoveries are limited by many factors and typically identify associated genomic regions without the further ability to compare the viability of candidate genes and actual CMs. Therefore, the current methodology is limited to CM identification. In our recent work, we presented a novel approach to an empowered “GWAS to Genes” strategy that we named Synthetic phenotype to causative mutation (SP2CM). We established this strategy to identify …

Caribbean Reef-Building Coral-Symbiodiniaceae Network: Identifying Symbioses Critical For System Stability In A Changing Climate, Shaman Patel

All HCAS Student Capstones, Theses, and Dissertations

Increasing global ocean temperatures and frequency of marine heatwaves pose dire consequences for coral reefs. High temperatures often lead to disruptions in coral symbiosis resulting in coral bleaching, increasing the mortality of corals. However, corals can potentially avoid bleaching peril by associating with thermally tolerant symbionts. Here we provide a tool for understanding symbiosis network stability of Caribbean reef-building corals. We created a network of Caribbean hermatypic corals and their associated Symbiodiniaceae phylotypes. A bleaching model was applied to this network to test for resilience and robustness (R50) to thermal stress. It was also layered with trait data for coral …

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

School of Computing: 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 …

Large Genomes Assembly Using Mapreduce Framework, Yuehua Zhang

All Dissertations

Knowing the genome sequence of an organism is the essential step toward understanding its genomic and genetic characteristics. Currently, whole genome shotgun (WGS) sequencing is the most widely used genome sequencing technique to determine the entire DNA sequence of an organism. Recent advances in next-generation sequencing (NGS) techniques have enabled biologists to generate large DNA sequences in a high-throughput and low-cost way. However, the assembly of NGS reads faces significant challenges due to short reads and an enormously high volume of data. Despite recent progress in genome assembly, current NGS assemblers cannot generate high-quality results or efficiently handle large genomes …

Data-Driven Biomarker Panel Discovery In Ovarian Cancer Using Heterogenous Data Fusion On Exosomal And Non-Exosomal Microrna Expression Data, Paritra Mandal

All Dissertations

Ovarian cancer (OC) is an aggressive gynecological cancer and is currently the 5th leading cause of deaths due to cancer in women. High mortality rates are attributable to the vague pathogenesis and asymptomatic nature of the early stages. The development of a liquid biopsy for routine OC screening could help identify the disease at an earlier stage, making treatments more likely to be effective thereby increasing survival rates. Exosomes, small (~100nm) extracellular vesicles present in body fluids, have been shown to contain cancer-progression, onset, and related factors, making them good candidates for use in liquid biopsies. However, to date, only …

Defining The Role Of Core Histones In Cellular Quiescence, Eric M. Small

Biomedical Sciences ETDs

Quiescence is a distinct cell cycle phase, termed G0, in which growth, transcriptional and translational activity, and replication are halted. Importantly, quiescent cells are viable and can return to the cell cycle. Quiescence is a feature of all organisms and a key hallmark of stem cells; however, the regulation of quiescence is still poorly understood.

Prior studies have implicated chromatin in the regulation of quiescence. In aim 1 I conducted a comprehensive screen of H3 and H4 histone mutants to identify chromatin features that may affect quiescence. I identified several histone residues implicated in transcriptional regulation that altered quiescence and …

Spatiotemporal Transcriptome Diversity And Responses To Salinity Tolerance In The Extremophyte Schrenkiella Parvula, Chathura Wijesinghege

LSU Doctoral Dissertations

Schrenkiella parvula is an extremophyte model related to the most widely studied plant model, Arabidopsis thaliana and Brassica crops in the mustard family (Brassicaceae). It can thrive in highly saline environments where the soil is enriched in Na⁺, K⁺, Li⁺, borates, and chlorides. Understanding how this extremophyte can survive high salinity with genomic adaptations can provide insight into developing stress resilient crops in the future. Gene expression of S. parvula in response to salt has been investigated using shoot and root tissue from mature vegetative-phase plants. However, prior studies have not examined the transcript …

Model-Free Identification Of Relevant Variables From Response Data, Alan Veliz-Cuba, David Murrugarra

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.