Phenotypic presentation of cognitive traits and disorders are driven by multiple factors including genomic makeup, environmental factors, and gene-environment interactions, therefore are considered complex multifactorial traits. Due to these many factors there is often variability in phenotypic presentation between individuals. While variation plays a critical role in our overall understanding of the genotype to phenotype axis, the mechanisms underlying this variation is still largely unknown. The aim of my dissertation work is to further our understanding of the role of genetic variability in the diversity of phenotypic presentation seen in learning, memory, and neurodegenerative mutations using the Drosophila Synthetic Population Resource (DSPR). 

I utilized quantitative trait loci (QTL) mapping and directional selection methods to identify genomic regions contributing to olfactory learning and memory using an appetitive olfactory conditioning Y-maze behavior assay for phenotyping. After phenotyping 50 recombinant inbred lines (RILs) I conducted high resolution genome wide scans to identify quantitative trait loci (QTL) with contribution to both phenotypes which established these behaviors are odor dependent. I developed an analysis method which scores flies individually at each decision point providing better phenotype resolution leading to the identification of five genomic regions likely contributing to behavioral response differences between odor trials. Using directional selection, I aimed to increase olfactory learning and memory capabilities to evaluate changes in allele frequency, however this experiment failed to produce this change. Instead, I found significant changes in climbing behavior, a subcomponent of the assay, which was applicable in multiple climbing formats and persisted in isofemale lines for generations after the selective pressure subsided. 

Lastly, I investigated how genetic background modifies the presentation of locomotor phenotypes associated with presenilin mutations, a gene linked to development of multiple neurodegenerative diseases including Alzheimer’s. I showed that genetic background causes variation in deficit level with some backgrounds performing similarly or better than their paired control highlighting the importance of genetic context behind mutation phenotypes. Overall, my work emphasizes genomic variability is an important factor to consider in studies of complex traits. 

Committee Members

• Dr. Elizabeth King, Chair
• Dr. David Schulz
• Dr. Anand Chandrasekhar 
• Dr. Kristina Aldridge 
• Dr. Ryan Williams