Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ∼250 disease-risk genes and drug targets with associated cell types. ![Figure][1] ### Competing Interest Statement Z. Weng (UMass Chan Medical School) co-founded and serves as a scientific advisor for Rgenta Inc. From April 11, 2022, N.L. Jorstad (Allen Institute for Brain Science) has been an employee of Genentech. K.P.W. (National University of Singapore) is a shareholder in Tempus AI and Provaxus Inc. The other authors declare no competing interests. [1]: pending:yes