Modeling Repeated Evolution Of Polygenic Traits, Marshall N. Hoskins

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Understanding the genetic composition of adaptive evolution is a longstanding and primary goal of evolutionary genetics. Despite many advances in our knowledge of trait adaptation, it remains unclear how demographic changes and repeated selection might alter the expected genetic architecture of adaptation. We used forward-in-time genetic simulations to test and observe the effects of opposing, repeated selection regimes on a polygenic trait in populations with and without changes in demography to better understand the genetic alleles that underlie polygenic adaptation. To further illuminate how natural populations might evolve, we investigated the impact of mutation effect size, the role of dominant/recessive …

Chromosome Evolution Model Reveals Hidden Variation In Karyotype-Driven Speciation In Ferns, Thomas Buchloh

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Because karyotype change commonly generates reproductive isolation between diverging species, rapid karyotype evolution, like that seen in plants, may increase the total rate of diversification. However, few studies have investigated this predicted relationship. Tests of this prediction have identified a positive correlation between the rate of karyotype change (specifically whole genome duplications) and diversification, but tests have been restricted to relatively small and young clades. Fortunately, novel macroevolutionary models have recently become available to investigate patterns of karyotype evolution in large phylogenies, providing new opportunity to investigate variation in karyotype driven diversification. Ferns are one of the most karyotype rich …

Quantifying Effects Of Partial Genetic Backgrounds To Decode Genetic Drivers Of Clinical Phenotypes, Rini Pauly

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Understanding partial genetic backgrounds illuminates the genetic architecture of complex traits and diseases, revealing how diverse genetic backgrounds contribute to phenotypic diversity. With this approach we could advance personalized medicine by identifying population-specific variants affecting drug metabolism, tailoring medical treatments to individual genetic profiles. Additionally, it offers evolutionary insights into human history, shedding light on past migrations and the spread of genetic traits. This research leverages cutting-edge statistical genetics techniques and novel machine learning approaches to efficiently analyze extensive population genomic datasets, distilling complex admixture signals into meaningful genetic markers.

The study introduces Admix-AI, an innovative convolutional neural network-based tool …

Regulation Of Serpina1 Mrna Expression By Environmental Conditions In Hepatocyte Cells, Fnu Jiamutai

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The SERPINA1 gene encodes the critical protease inhibitor α-1-antitrypsin (A1AT). A1AT represses neutrophil elastase activity to protect lung tissue from inflammatory damage. A deficiency in α-1-antitrypsin can lead to chronic obstructive pulmonary disease (COPD). Pathogenic genetic variants in SERPINA1 are also associated with A1AT protein misfolding and liver cirrhosis. The regulatory mechanisms of SERPINA1 expression are not well understood, but previous studies suggest that alternative polyadenylation in the 3' untranslated region (3'UTR) affects A1AT protein expression. In this study, we used the liver cancer cell line HepG2 to determine how environmental conditions influence SERPINA1 mRNA expression and post-transcriptional regulation. We …

Genomic Data Science Approaches For Understanding Human Diseases, Snehal Shah

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The intricate interplay of genetic predisposition, environmental influences, and lifestyle acts as the multifactorial landscape of diseases. Understanding this complexity presents a significant challenge. Molecular insights into disease mechanisms, particularly the interactions of DNA, RNA, and proteins with environmental and lifestyle factors, have revolutionized disease diagnosis, prognosis, and treatment. High-throughput technologies, such as next-generation sequencing, generate large amounts of molecular data, holding a wealth of knowledge. These datasets unveil the roles of genes and their interactions with various factors through analysis, shedding light on previously unknown molecular mechanisms underlying disease pathogenesis. Furthermore, they facilitate the discovery of biomarkers crucial for …

Single Cell Pharmacodynamic Modeling Of Cancer Cell Lines, Arnab Mutsuddy

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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 …

Integrating Omim And Intact Data For The Analysis Of Gene-Phenotype Interactions In Complex Diseases: A Linux-Based Computational Tool For Network Analysis, Devin Keane

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The field of genetics is constantly evolving. New advances in bioinformatics and computational approaches are leading to exciting new developments in our ability to treat and prevent diseases. Computational genetics provides valuable insights into the complex mechanisms and layers of biological communication that shape an organism's phenotype. Understanding these mechanisms is critical to advancing human health.

The study of diseases in genetics requires a comprehensive understanding of the interactions between various biological processes, including gene expression, protein synthesis, RNA, metabolism, and cell-cell communication. To effectively address the root causes of such diseases, multi-disciplinary approaches that integrate information from different levels …

Acetate Metabolism In The Fungal Pathogen Cryptococcus Neoformans, Oly Ahmed

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Cryptococcus neoformans is an environmental basidiomycetous fungus with a worldwide distribution and a wide range of habitats. Inhalation of the desiccated yeasts or spores of C. neoformans often leads to opportunistic pulmonary infections in immunocompromised individuals, and in severe cases causes lethal meningitis following hematogenous dissemination. During infection, depending on the tissue and disease state, the invading fungi experience a range of nutrient microenvironments within the host body. As a result, rapid metabolic adaptations geared towards efficient utilization of carbon sources alternative to glucose become one of the prime determinants of survival and growth for the pathogen. Incidentally, cryptococcal infection …

Large Genomes Assembly Using Mapreduce Framework, Yuehua Zhang

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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

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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 …

Modeling Electrostatics In Molecular Biology And Its Relevance With Molecular Mechanisms Of Diseases, Mahesh Koirala

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Electrostatics plays an essential role in molecular biology. Modeling electrostatics in molecular biology is complicated due to the water phase, mobile ions, and irregularly shaped inhomogeneous biological macromolecules. This dissertation presents the popular DelPhi package that solves PBE and delivers the electrostatic potential distribution of biomolecules. We used the newly developed DelPhiForce steered Molecular Dynamics (DFMD) approach to model the binding of barstar to barnase and demonstrated that the first-principles method could also model the binding. This dissertation also reflects the use of existing computational approaches to model the effects of Single Amino Acid Variations (SAVs) to reveal molecular mechanisms …

Deciphering Medicago Truncatula Nodulation Using Time-Series Transcriptomic Data At Multiple Levels Of Resolution: Organ, Tissue, And Single-Cell, Yueyao Gao

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Use of chemical nitrogen fertilizers has environmental repercussions such as global warming, soil contamination, and aquatic eutrophication. Legumes form a symbiotic association with nitrogen-fixing bacteria (rhizobia sp.) to obtain atmospheric nitrogen through the formation of a specialized root structure called a nodule. Understanding the transcriptional reprogramming during nodulation is a powerful approach to decipher the genetic control of nodulation, with the goal of engineering nitrogen-fixing symbiosis into non-leguminous crops. This dissertation focuses on the analytics of bulk, tissue-specific, and single-cell RNA-seq technologies and how I utilized them to discover a collection of genes to aid in deciphering nodulation mechanisms in …