A domain-specific embedded language for probabilistic programming

Functional programming is concerned with referential transparency, that is, given a certain function and its parameter, that the result will always be the same. However, it seems that this is violated in applications involving uncertainty, such as rolling a dice. This thesis defines the background of probabilistic programming and domain-specific languages, and builds on these ideas to construct a domain-specific embedded language (DSEL) for probabilistic programming in a purely functional language. This DSEL is then applied in a real-world setting to develop an application in use by the Center for Gene Research at Oregon State University. The process and results of this development are discussed.Keywords: Modeling, Functional, Probabilistic, DSE

Structured clustering representations and methods

Rather than designing focused experiments to test individual hypotheses, scientists now commonly acquire measurements using massively parallel techniques, for post hoc interrogation. The resulting data is both high-dimensional and structured, in that observed variables are grouped and ordered into related subspaces, reflecting both natural physical organization and factorial experimental designs. Such structure encodes critical constraints and clues to interpretation, but typical unsupervised learning methods assume exchangeability and fail to account adequately for the structure of data in a flexible and interpretable way. In this thesis, I develop computational methods for exploratory analysis of structured high-dimensional data, and apply them to study gene expression regulation in Parkinson’s (PD) and Huntington’s diseases (HD). BOMBASTIC (Block-Organized, Model-Based, Tree-Indexed Clustering) is a methodology to cluster and visualize data organized in pre-specified subspaces, by combining independent clusterings of blocks into hierarchies. BOMBASTIC provides a formal specification of the block-clustering problem and a modular implementation that facilitates integration, visualization, and comparison of diverse datasets and rapid exploration of alternative analyses. These tools, along with standard methods, were applied to study gene expression in mouse models of neurodegenerative diseases, in collaboration with Dr. Myriam Heiman and Dr. Robert Fenster. In PD, I analyzed cell-type-specific expression following levodopa treatment to study mechanisms underlying levodopa-induced dyskinesia (LID). I identified likely regulators of the transcriptional changes leading to LID and implicated signaling pathways amenable to pharmacological modulation (Heiman, Heilbut et al, 2014). In HD, I analyzed multiple mouse models (Kuhn, 2007), cell-type specific profiles of medium spiny neurons (Fenster, 2011), and an RNA-Seq dataset profiling multiple tissue types over time and across an mHTT allelic series (CHDI, 2015). I found evidence suggesting that altered activity of the PRC2 complex significantly contributes to the transcriptional dysregulation observed in striatal neurons in HD

CLUSTER HOMOLOG OF IMMUNOGLOBULIN-LIKE RECEPTOR GENES IN CHICKEN IMMUNE RESPONSES

This dissertation explores the identity and role of immunoglobulin-like (Ig-like) receptors in chickens, with focus on their implications in disease and disease progression. These receptors, wisely expressed across immune cells, interact with the major histocompatibility complex (MHC) class I molecules to modulate immune responses in mammals. Due to the insufficient representation of chicken Ig-like receptors in online databases, this study systematically annotates the chicken Cluster Homolog of Immunoglobulin-like Receptors (CHIR) genes using advanced bioinformatic techniques, aligning with the release of the 7th edition of the chicken genome assembly that comprises builds for a broiler and layer chicken. The analysis identifies over 150 CHIR genes, refining functional classifications of activatory (CHIRA), inhibitory (CHIRB), bifunctional (CHIRAB), and CHIR-like (CHIRL) genes through InterProScan, phylogeny and motif searches. Variations in CHIR gene counts across different chicken lines (broiler, N = 124, layer, N = 70) suggest links to selective breeding demands, emphasizing their importance in poultry health and production. Phylogenetically, CHIRs show close relationships with other poultry Ig-like receptors, and structural comparisons indicate analogous roles to Ig-like receptors in the human and rat. As an outcome of the analysis, CHIR genes were renamed with the Chicken Genome Nomenclature Consortium from “chicken homolog of Ig-like receptors” to “cluster homolog of Ig-like receptors”. Reanalyzing next-generation sequencing data reveals CHIR genes are expressed across all tissues of a UCD001 line, with generally higher expression in blood-containing organs. Examination of CHIR gene single nucleotide polymorphisms across various in inbred lines (UCD001, UCD003, Line 0, Line 6, Line 7, Line 15, Line N, Line P, Line C, and Line W) indicates an overall variant rarity and slightly more occurrence in CHIRB genes. Over 1,000 protein-encoding variants are associated with differential resistance and susceptibility to Marek’s disease (P \u3c 0.05). Two in vitro approaches assessed the roles of CHIR molecules in modulating immune responses or targeting pathogens. Re-examination of RNA-sequencing data of MHC-I types B2 and B19 macrophages, temporally stimulated with interferon-gamma, revealed dynamic and opposite CHIR expression trends, with B2s showing an increase and B19s displaying a decrease until returning to basal levels at 24 to 48 hours. These findings suggest nuanced and distinct regulatory patterns of CHIRs in different haplotypes during immune responses. Additionally, CHIR sequences were aligned for the design of small interfering RNA molecules targeting the CHIRB functional group on macrophages retrieved from birds of congenic (UCD331 and UCD335) and mixed (WVU1952) backgrounds. CHIRB silencing was observed to enhance cellular nitrate release and impact H2O2, particularly in specific MHC-I haplotypes and in different genetic backbones, in avian influenza virus infection. While this dissertation enhances our understanding of chicken Ig-like receptors and cellular involvement, it also acknowledges certain limitations, such as variations in gene annotations. Nevertheless, CHIRs merit a sizeable acknowledgment as pivotal contributors to the immune response, particularly in their intricate interactions with the MHC. Future studies integrating this understanding into breeding plans or other interventions becomes a strategic imperative for optimizing poultry health and immunity, ensuring wellbeing, and in turn, a more resilient and sustainable food supply