Gene-by-Environment Interactions Associated with Inter-Individual Variation in Response to Chemical Exposur

Modern societies are exposed to vast numbers of potentially hazardous chemicals. Despite demonstrated linkages between chemical exposure and severe health effects, there are limited, often conflicting, data on how adverse health effects of exposure differ across individuals. We hypothesized that population variability in response to certain chemicals could elucidate a role for gene-environment interactions (GxE) in differential susceptibility. High throughput screening (HTS) data on thousands of chemicals in geneticallyheterogeneous zebrafish were leveraged to identify a candidate chemical (Abamectin) with response patterns indicative of population susceptibility differences. We tested this prediction by generating genome-wide sequence data for 276 individual Tropical 5D (T5D) zebrafish displaying susceptible ('Affected') versus resistant ('Unaffected') phenotypes following identical chemical exposure. We found GxE associated with differential susceptibility in the sox7 promoter region, then confirmed gene expression differences between phenotypic response classes. The results demonstrate that GxE associated with naturally-occurring, population genetic variation play a significant role in mediating individual responses to chemical exposure.;Additionally, the individual sequencing data from the GxE study was used to assess whether T5D natural diversity was in line with other zebrafish lines or representative of other species. Findings from pooled samples of zebrafish support a supposition of diversity yet cannot directly measure allele frequencies for reference versus alternate alleles. Individual T5D sequences were used to compare observed population genetic variation across species (humans, mice, zebrafish), then across lines within zebrafish. We found more single nucleotide polymorphisms (SNPs) in T5D than have been reported in SNP databases for any of the WIK, TU, TL, or AB lines. We theorize that some subset of the novel SNPs may be shared with other zebrafish lines but have not been identified in other studies due to the limitations of capturing population diversity in pooled sequencing strategies. We establish T5D as a model that is representative of diversity levels within laboratory zebrafish lines and demonstrate that experimental design and analysis can exert major effects when characterizing genetic diversity in heterogeneous populations.;Chapter 1 of the dissertation discusses computational methods for assessing individual and integrated "omic" data in a Systems Biology framework for environmental and toxicological science. Chapter 2 provides brief background on the specific topic of geneenvironment interactions (GxE), as well as the major considerations for mining big data to design a GxE study in a specific population of zebrafish. Chapter 3 discusses the study design, implementation, and results in detail. Chapter 4 looks deeper into population variability that this analysis has brought to the fore. Chapter 5 addresses the impacts of experimental design choices, as well as future directions for the work.