In vivo identification of therapeutic constructs from pooled candidates in HD model mice

Rapidly identifying targets for Huntington's Disease (HD) therapeutics in relevant mouse models could hasten the development of patient interventions. We have recently described a method for rapidly and quantitatively measuring the progression of HD-like symptoms in mouse models. Because this method uses flow cytometry to measure GFP levels in affected neurons, it is amenable to pooled approaches. Here we describe a continuation of this work, using pools of shRNA-delivering AAV vectors and high throughput sequencing to determine which hairpins in a mixed population are most effective at preventing the transcriptional dysregulation phenotype of R6/2 mice.