A large-scale RNAi screen to identify novel modifiers of polyglutamine toxicity in Drosophila. Sara Imarisio¹, Ashley R. Winslow², Benjamin R. Underwood³, Wun Lam¹, Evangelia K. Ttofi², Viktor I. Korolchuk⁴, Jörg Gsponer⁵, M. Madan Babu⁶, David C. Rubinsztein². 1) Department of Genetics, University of Cambridge, Cambridge , UK; 2) Department of Medical Genetics, University of Cambridge, Cambridge Institute for Medical Research,Addenbrookes Hospital, Hills Road, Cambridge, CB2 0XY, UK; 3) Norfolk and Suffolk Huntingtons Disease Service, Mental Health Team, Newmarket Hospital, Newmarket, Suffolk CB8 7JG, UK; 4) Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, UK; 5) Centre for High-Throughput Biology, The University of British Columbia, 2125 East Mall, Vancouver, BC V6T 1Z4, Canada; 6) Medical Research Council (MRC) Laboratory of Molecular Biology, Hills Road, Cambridge CB2 0QH, UK.

   Polyglutamine (PolyQ) diseases are a family of neurodegenerative disorders caused by an expanded CAG repeat in the target gene. Mutant proteins form toxic intracellular aggregates, associated with cell death. To date there is no cure or treatment that delays the progression of degeneration. With the aim to identify genes and pathways affecting polyQ toxicity, we analysed the loss-of-function of almost half of the Drosophila genome in a line carrying 48 glutamines, which has a severe eye phenotype. We identified 174 suppressors and 748 enhancers that we extensively validated, i.e. using an independent RNAi library to minimise the possibility of off-target effects, and confirmed 76% of the hits. Moreover,being aggregate formation a hallmarks of polyQ toxicity, we checked whether the suppressors reduced the number of aggregates in a line expressing expanded huntingtin in the eye, finding that 70% of them significantly reduced the number of inclusions. To get a better understanding of the biological processes affected by our modifiers, we used a bioinformatic approach to categorise gene ontologies that were over-represented amongst modifiers, such as members of proteolysis, transcription regulation and apoptosis. Thus, our screen results a valuable resource to study polyQ diseases, highlighting novel genes and processes regulating toxicity.