Cell Genomics (Mar 2022)
Single nucleus multi-omics identifies human cortical cell regulatory genome diversity
- Chongyuan Luo,
- Hanqing Liu,
- Fangming Xie,
- Ethan J. Armand,
- Kimberly Siletti,
- Trygve E. Bakken,
- Rongxin Fang,
- Wayne I. Doyle,
- Tim Stuart,
- Rebecca D. Hodge,
- Lijuan Hu,
- Bang-An Wang,
- Zhuzhu Zhang,
- Sebastian Preissl,
- Dong-Sung Lee,
- Jingtian Zhou,
- Sheng-Yong Niu,
- Rosa Castanon,
- Anna Bartlett,
- Angeline Rivkin,
- Xinxin Wang,
- Jacinta Lucero,
- Joseph R. Nery,
- David A. Davis,
- Deborah C. Mash,
- Rahul Satija,
- Jesse R. Dixon,
- Sten Linnarsson,
- Ed Lein,
- M. Margarita Behrens,
- Bing Ren,
- Eran A. Mukamel,
- Joseph R. Ecker
Affiliations
- Chongyuan Luo
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA; Corresponding author
- Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92037, USA
- Fangming Xie
- Department of Physics, University of California, San Diego, La Jolla, CA 92037, USA; Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA
- Ethan J. Armand
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA
- Kimberly Siletti
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, 17177 Stockholm, Sweden
- Trygve E. Bakken
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- Rongxin Fang
- Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA; Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
- Wayne I. Doyle
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA
- Tim Stuart
- New York Genome Center, New York, NY 10013, USA
- Rebecca D. Hodge
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- Lijuan Hu
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, 17177 Stockholm, Sweden
- Bang-An Wang
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Zhuzhu Zhang
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Sebastian Preissl
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
- Dong-Sung Lee
- Peptide Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Sheng-Yong Niu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Rosa Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Angeline Rivkin
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Xinxin Wang
- Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA; Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
- Jacinta Lucero
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Joseph R. Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- David A. Davis
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Deborah C. Mash
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Rahul Satija
- New York Genome Center, New York, NY 10013, USA
- Jesse R. Dixon
- Peptide Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Sten Linnarsson
- Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, 17177 Stockholm, Sweden
- Ed Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- M. Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA 92093, USA; Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
- Eran A. Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA; Corresponding author
- Joseph R. Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Corresponding author
- Journal volume & issue
-
Vol. 2,
no. 3
p. 100107
Abstract
Summary: Single-cell technologies measure unique cellular signatures but are typically limited to a single modality. Computational approaches allow the fusion of diverse single-cell data types, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells, we devised single-nucleus methylcytosine, chromatin accessibility, and transcriptome sequencing (snmCAT-seq) and applied it to postmortem human frontal cortex tissue. We developed a cross-validation approach using multi-modal information to validate fine-grained cell types and assessed the effectiveness of computational data fusion methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility, and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling the prediction of cell types that are associated with diseases.
