A comparative atlas of single-cell chromatin accessibility in the human brain

Recent advances in single-cell transcriptomics have illuminated the diverse neuronal and glial cell types within the human brain. However, the regulatory programs governing cell identity and function remain unclear. Using a single-nucleus assay for transposase-accessible chromatin using sequencing (...

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Published inScience (American Association for the Advancement of Science) Vol. 382; no. 6667; p. eadf7044
Main Authors Li, Yang Eric, Preissl, Sebastian, Miller, Michael, Johnson, Nicholas D., Wang, Zihan, Jiao, Henry, Zhu, Chenxu, Wang, Zhaoning, Xie, Yang, Poirion, Olivier, Kern, Colin, Pinto-Duarte, Antonio, Tian, Wei, Siletti, Kimberly, Emerson, Nora, Osteen, Julia, Lucero, Jacinta, Lin, Lin, Yang, Qian, Zhu, Quan, Zemke, Nathan, Espinoza, Sarah, Yanny, Anna Marie, Nyhus, Julie, Dee, Nick, Casper, Tamara, Shapovalova, Nadiya, Hirschstein, Daniel, Hodge, Rebecca D., Linnarsson, Sten, Bakken, Trygve, Levi, Boaz, Keene, C. Dirk, Shang, Jingbo, Lein, Ed, Wang, Allen, Behrens, M. Margarita, Ecker, Joseph R., Ren, Bing
Format Journal Article
LanguageEnglish
Published United States The American Association for the Advancement of Science 13.10.2023
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Summary:Recent advances in single-cell transcriptomics have illuminated the diverse neuronal and glial cell types within the human brain. However, the regulatory programs governing cell identity and function remain unclear. Using a single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq), we explored open chromatin landscapes across 1.1 million cells in 42 brain regions from three adults. Integrating this data unveiled 107 distinct cell types and their specific utilization of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly a third of the cCREs demonstrated conservation and chromatin accessibility in the mouse brain cells. We reveal strong links between specific brain cell types and neuropsychiatric disorders including schizophrenia, bipolar disorder, Alzheimer’s disease (AD), and major depression, and have developed deep learning models to predict the regulatory roles of noncoding risk variants in these disorders.
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Present address: Department of Neurosurgery and Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
Conceptualization: B.R. Y.E.L. Contribution to data analysis: Y.E.L., Z.W., H.J., O.P., C.K., W.T., K.S. Contribution to data generation: S.P., M.M., Y.E.L., A.W., N.D.J., C.Z., Z.W., Y.X., A.P-D., N.E., J.O., J.L., L.L., Q.Y., Q.Z., S.E., A.M.Y., J.N., N.D., T.C., N.S., D.H., R.D.H. B.L., C.D.K. Contribution to web portal and software: Y.E.L. Contribution to data interpretation: Y.E.L., Z.W., W.T., K.S., S.L., T.B., J.S., E.S.L., M.M.B., J.R.E., B.R. Contribution to writing the manuscript: Y.E.L., B.R. All authors edited and approved the manuscript.
Author contributions
ISSN:0036-8075
1095-9203
1095-9203
DOI:10.1126/science.adf7044