Single-cell genomics and regulatory networks for 388 human brains

• 成果类型: Article
• 署名作者: Emani, Prashant S.; Liu, Jason J.; Clarke, Declan; Jensen, Matthew; Warrell, Jonathan; Gupta, Chirag; Meng, Ran; Lee, Che Yu; Xu, Siwei; Dursun, Cagatay; Lou, Shaoke; Chen, Yuhang; Chu, Zhiyuan; Galeev, Timur; Hwang, Ahyeon; Li, Yunyang; Ni, Pengyu; Zhou, Xiao; Bakken, Trygve E.; Bendl, Jaroslav; Bicks, Lucy; Chatterjee, Tanima; Cheng, Lijun; Cheng, Yuyan; Dai, Yi; Duan, Ziheng; Flaherty, Mary; Fullard, John F.; Gancz, Michael; Garrido-Martin, Diego; Gaynor-Gillett, Sophia; Grundman, Jennifer; Hawken, Natalie; Henry, Ella; Hoffman, Gabriel E.; Huang, Ao; Jiang, Yunzhe; Jin, Ting; Jorstad, Nikolas L.; Kawaguchi, Riki; Khullar, Saniya; Liu, Jianyin; Liu, Junhao; Liu, Shuang; Ma, Shaojie; Margolis, Michael; Mazariegos, Samantha; Moore, Jill; Moran, Jennifer R.; Nguyen, Eric; Phalke, Nishigandha; Pjanic, Milos; Pratt, Henry; Quintero, Diana; Rajagopalan, Ananya S.; Riesenmy, Tiernon R.; Shedd, Nicole; Shi, Manman; Spector, Megan; Terwilliger, Rosemarie; Travaglini, Kyle J.; Wamsley, Brie; Wang, Gaoyuan; Xia, Yan; Xiao, Shaohua; Yang, Andrew C.; Zheng, Suchen; Gandal, Michael J.; Lee, Donghoon; Lein, Ed S.; Roussos, Panos; Sestan, Nenad; Weng, Zhiping; White, Kevin P.; Won, Hyejung; Girgenti, Matthew J.; Zhang, Jing; Wang, Daifeng; Geschwind, Daniel; Gerstein, Mark
• 署名单位: Yale University; Yale University; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; University of California System; University of California Irvine; University of California System; University of California Irvine; Yale University; Allen Institute for Brain Science; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA; University of Pennsylvania; University of Barcelona; Cornell University; Weill Cornell Medical Center; US Department of Veterans Affairs; Veterans Health Administration (VHA); James J. Peters VA Medical Center; US Department of Veterans Affairs; Veterans Health Administration (VHA); James J. Peters VA Medical Center; University of California System; University of California Los Angeles; Yale University; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; University of Massachusetts System; UMass Chan Medical School; University of Massachusetts Worcester; Yale University; Yale University; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA; University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA; University of Pennsylvania; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; National University of Singapore; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Yale University; US Department of Veterans Affairs; Veterans Health Administration (VHA); VA Connecticut Healthcare System; University of Wisconsin System; University of Wisconsin Madison; University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA; Yale University
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-9600
• DOI: 10.1126/science.adi5199
• 发表日期: 2024-05-24
• 关键词: major psychiatric-disorders; gene-expression; bipolar disorder; enrichment analysis; wide association; growth-factor; motor cortex; risk loci; schizophrenia; disease

摘要

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, multiomics datasets into a resource comprising >2.8 million 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 >550,000 cell type-specific regulatory elements and >1.4 million 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 similar to 250 disease-risk genes and drug targets with associated cell types.