Date of Award
Doctor of Philosophy (PhD)
The field of human molecular genetics has undergone a substantial technological transformation in the past decade, allowing researchers to identify and analyze genetic variation across the human genome with unprecedented depth and precision. A central goal in utilizing this technological advancement is to discover the genetic variation that underlies complex heritable traits and disorders. In recent years, much of the focus has been on large-scale genome- wide association studies (GWAS) in an attempt to identify effects of common single nucleotide polymorphisms (SNPs) on a phenotype. Progress in this arena, however, has been limited, as validated findings for most phenotypes represent only a small fraction of the variance attributed to genetics known from family and twin studies, leaving a large proportion of heritability to be explained. My research is in large part motivated by the issues surrounding GWAS, as additional methodological techniques and population genetic theory can help explain phenotypic variance unaccounted for by the traditional genetic association design. In my first study, I look at a case/control sample of bipolar disorder, examining how prior information from linkage studies can inform GWAS signals. The primary aim is to ease the burden of multiple-testing correction applied in GWAS using empirically informed weighting to tease out true signals supported by prior genetic evidence. In my second study, I determine the best practices to detect signatures of distant inbreeding, via runs of homozygosity, in genome-wide SNP data. The motivation for studying this phenomenon is due to the extensive evidence of inbreeding depression on fitness related traits, where the effects of recessive or partially recessive alleles are expressed. Using an extensive simulation design, I test multiple programs to determine the optimal method to identify runs of homozygosity caused by distant inbreeding. In my third and final study, I apply my work from the second study to a comprehensive dataset of cognitive measures to understand the extent to which distant inbreeding affects variation in general cognitive ability.
Howrigan, Daniel Patrick, "Non-Traditional Approaches to Interrogating Genome-Wide SNP Data" (2012). Psychology and Neuroscience Graduate Theses & Dissertations. 33.