PROJECT SUMMARY Our understanding of the genetics of schizophrenia is advancing at a rapid pace and an increasing number of risk-associated polymorphisms and variants have been discovered. Because the majority of these variants reside in intergenic, intronic and other non-coding sequences, a precise variant or target gene for schizophrenia has not been identified. Therefore, a major challenge lies in designing testable hypotheses to elucidate the potential function of disease-associated non-coding DNA. Many of the risk variants are thought to affect gene expression through alterations of regulatory elements, including long-range enhancer sequences physically interacting with transcription start sites separated along the linear genome of DNA. The aim of this proposal is to map the regulatory sequences (or open chromatin) in discrete cellular populations (neurons and glia) derived from two human cortical brain regions in a large cohort of cases with schizophrenia and controls, followed by generation of a high-resolution quantitative trait loci (QTL) map of regulatory sequences. In addition, high resolution expression quantitative trait loci (eQTLs), mapped in the same samples and brain regions, will be leveraged to identify schizophrenia associated non-coding regions that are simultaneously associated with differential exposure of regulatory regions (open chromatin) and gene expression of nearby genes (eQTLs). Long-range enhancer-promoter interactions of genes potentially regulated by open chromatin sequences will be mapped in human postmortem brain tissue using chromosome conformation capture. Using the existing schizophrenia-related large-scale molecular data and the high-impact, high-resolution, complementary datasets generated through the proposed studies, we will develop multiscale network models causally linked to schizophrenia. The action of individual genes on molecular and cellular schizophrenia- associated processes and the molecular networks identified in our studies will be validated using iPS-cell- derived cultures of human neuronal cell systems. The multidimensional approach presented here provides a roadmap to place schizophrenia genetic risk variants in molecular contexts to help identify the underlying regulatory and expression mechanisms through which they act.