Aging organisms show declines in both physical and mental abilities. Epigenetic processes, such as those that control chromatin structure, have been associated with these age-related declines. The highly conserved chromosomal proteins of the Heterochromatin Protein 1 (HP1) family have a variety of functions, including in maintenance of chromatin structure, in transcription regulation, and in DNA repair. Disruption of HP1 localization is often associated with aberrant gene transcription, which can contribute to disease. In Drosophila melanogaster, there are three somatic HP1 proteins: HP1a, HP1B, and HP1C. These three proteins share a subset of binding sites despite the fact that initial reports suggest that HP1a localizes mainly to heterochromatin, HP1C localizes mainly to euchromatin, and HP1B localizes to both heterochromatin and euchromatin. Published data suggest that HP1a is redistributed during aging: while young individuals show a clear distinction between heterochromatin and euchromatin, this distinction disappears in older individuals. However, HP1a protein levels do not change with increased age. Moderate overexpression of HP1a in Drosophila increases lifespan (~23%), and under starvation conditions, flies lacking HP1B have a longer median lifespan (~24%) than control flies. These findings suggest that HP1 proteins impact longevity and health span. In order to address the roles of HP1 proteins in aging, we are investigating the HP1 distribution during aging and evaluating cognitive performance. In control, HP1a overexpressing, and Su(var)3-9 overexpressing Drosophila strains, the distribution of HP1a throughout lifespan will be determined via ChIP-seq. Using classical conditioning techniques with y-mazes, aversive and appetitive olfactory memory throughout lifespan will be assessed. HP1a overexpressing lines that show increased maximum lifespan will be tested to determine if memory is improved due to increased HP1a levels. Performance indices will be calculated from the behavior assay results, which will be analyzed via ANOVA and Chi-Square tests.