Electronic Thesis and Dissertation Repository

Degree

Master of Science

Program

Biology

Supervisor

Dr. Shiva M. Singh

Abstract

Genetic variability is essential to human individuality. Genetic variation includes differences in sequence at the single nucleotide level to structural variations of large segments of DNA called copy number variations (CNVs). CNVs within a genome can be identified using microarray technology; however, the analysis of microarray results resulting in the “calling” of CNVs is not always precise. The research included in this manuscript describes the identification and analysis of CNVs using three commercially-available packages, Affymetrix® Genotyping ConsoleTM, Partek® Genome SuiteTM and PennCNV, that are most commonly used in the analysis of SNP and CNV data. Specifically, this research assessed the ability of these platforms to successfully analyze Affymetrix® Genome-Wide Human SNP Array 6.0 data for CNVs within two families, each with a set of monozygotic twins discordant for schizophrenia. Results show that the three methods identified a set of CNVs in each individual, but the specific sets identified were not identical between softwares. Affymetrix® Genotyping ConsoleTM detected a wide variety of sizes of CNVs while the other two methods were able to identify only CNVs greater than 1 Mb in size. Interestingly, all platforms showed that monozygotic twins differ for some CNVs, a difference that may be acquired during their somatic development. This suggests that CNV differences between monozygotic twins may offer an explanation for discordance of phenotype, such as schizophrenia. Also, this analysis of CNVs within related individuals may identify previously unreported unusual features, including the repeated CNVs on chromosome 13q observed in the father of family 2. Such results support the use of CNV in familial studies, but argue for a careful assessment of CNVs including a careful selection of analysis tools and the necessity of independent confirmation.

Download

Included in

Life Sciences Commons

Share

COinS