Deciphering Cell-type Specific Regulatory Landscape in Human Brain Human brain is comprised of an extremely heterogeneous mixture of cell types that exhibit distinct molecular profiles, which complicates efforts to establish the reliable molecular and cellular substrates of brain disorders. Therefore, the reconstruction of a complete cell atlas of human brain is critical to delineate cellular etiology and neurobiological mechanisms of brain disorders, given that brain disorders often exhibit cell-type specific expression signatures and selective vulnerability. Recent advances in single cell transcriptomics have revolutionized our understanding of the cellular and molecular diversity of the human brain. However, the regulatory landscape that shapes cell-type specific expression signatures is not well understood. My central vision is to decipher regulatory relationships controlling gene expression in human brain to identify molecular and cellular substrates of brain disorders. To achieve this goal, I will develop a novel method, single-cell combinatorial indexed DNase Hi-C (sciDNase-Hi-C), to profile regulatory landscape at a single cell level that is not dependent on the sorting procedure or known cell-type specific epigenomic profiles. Cell-type specific regulatory maps will allow us to (1) decipher regulatory mechanisms underlying cell-type specific expression signatures, (2) deconvolve regulatory codes (transcription factor binding sites) and variants (expression quantitative trait loci, eQTLs) into their corresponding cell types, and (3) refine biological hypotheses on the underlying mechanisms of brain disorders by prioritizing cell types fundamental to the disease pathogenesis and map risk variants to their target genes. Collectively, the successful completion of this project will engender powerful new tools and databases to contemplate fundamental questions in the field: how regulatory relationships in different cell types drive cell-type specific gene expression signatures and selective vulnerability to different brain disorders. Page 1
Human brain exhibits cellular heterogeneity that obscures the identification of robust regulatory networks. In order to study regulatory landscape governing complex expression signatures in human brain, we will develop a novel technique to decipher regulatory landscape at a cell-type specific resolution. Cell-type specific regulatory landscape will permit the large-scale cell-type specific annotation of previously uncharacterized gene regulatory relationships relevant to brain disorders, which may lead to a better understanding of the cellular and molecular mechanisms of brain disorders. Page 1
