Abstract
Circular RNAs (circRNAs) are closed and stable RNA molecules, generated by back-splicing. On one hand, circRNA may be important in response to cell stress. Because of their circular structure, circRNAs are translated via cap-independent mechanisms, that are generally upregulated during cellular stress. circMbl is the most abundant circRNA in D. melanogaster heads and it is translated into a 10 – 37 KDa protein. Accordingly, circMbl protein accumulates during starvation. In the first project, to investigate the function of circMbl protein in starvation response, I monitored the survival of circMbl knockdown and overexpression flies upon food deprivation. Results show that there is no significant difference of survival time between the circMbl knockdown, overexpression, and control. Second, to study weather circMbl protein expression changes upon certain physiological conditions, such as starvation or aging, I prepared plasmids for generating two new fly-lines expressing either a circMbl-V5 (a tagged version of circMbl) or a super-foldGFP (that generates a circular GFP RNA containing the Internal Ribosome Entry Site of circMbl). On the other hand, they are evolutionary conserved, widely expressed in the neural tissue. miR-7, a microRNA regulated by CDR1as was mainly expressed in neurons and inhibited α-synuclein protein levels, suggesting CDR1as regulation by miR-7 might be associated with Parkinson’s Disease. In the second project, I aimed to see whether circRNAs in blood could be used to biomark the presence and progression of the diseases. So, the general aim of this part of my thesis was to determine whether the levels of specific circRNAs correlate with well-established physiological and behavioral defects observed in PD individuals. Before analyzing circRNA data, I started with linear RNA sequencing data analysis to solidify my sequencing data analysis skills and coding skills. In this project, I identified 13 progressive brain imaging markers, such as the left caudate density in striatum, which can be used to find correlation between both circRNAs and linear RNAs.