Computational Methods for Analyzing Gene Regulation in Model Organisms Research Thesis In Partial Fulfillment of the Requirements for the Degree of Master of Science in Computer Science

Acknowledged. We thank Merck for a small grant and the CGC for strains used in " A Genomic Bias for Genotype-environment Interactions in C. elegans. ". Spatial localization of co-regulated genes is greater than genomic gene clustering in the S. cerevisae genome. " Figure S5 The effect of a permutation on gene identities to the enrichment of co-localized targets of GLN-3. As is evident in this figure, there are no significant enrichments once running a permutation on the gene identities, indicating that the enrichment of gene co-localization is statistically significant and stems from non-random proximity. Figure S6 Expression of genes which participate in many co-localized regions compared to genes which participate in few co-localized regions.1 Abstract This dissertation embodies two separate research projects with a common goal-exploring gene regulation. In Biology, gene regulation encompasses a broad field which attempts to describe the molecular interactions between various cellular factors that conspire to silence or activate the machinery in charge of compiling a gene from its source code – the DNA, to an executable thread – Protein, which in turn works in cohort with other active machinery in the cell to determine the organism's phenotype. In the first project, we examine the environment's' effect on gene regulation through the lens of evolution, comparing gene expression of 5 strains of the nematode C. elegans grown in 5 different mediums. We use robust statistical methods to show that highly regulated genes, as distinguished by intergenic lengths, motif concentration, and expression levels, are particularly biased towards genotype-environment interactions. Sequencing these strains, we find that genes with expression variation across genotypes are enriched for promoter SNPs, as expected. However, genes with genotype-environment interactions do not significantly differ from background in terms of their promoter SNPs. Collectively, these results suggest that the highly-regulated nature of particular genes predispose them for exhibiting genotype-environment interaction as a consequence of changes to upstream regulators. This observation may provide a deeper understanding into the origin of the extraordinary gene expression diversity present in even closely related species.. In the second project, we take a pragmatic approach and provide an analytical framework of exploring both the structure of DNA and of detecting spatial co-localization of genomic markers. We go on to deploy this framework and provide a 3D structural model of the Saccharomyces Cerevisae genome, and use it to provide evidence of widespread co-localization of the targets of cellular factors, termed Transcription …