Article

Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain

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Abstract

Detailed characterization of the cell types in the human brain requires scalable experimental approaches to examine multiple aspects of the molecular state of individual cells, as well as computational integration of the data to produce unified cell-state annotations. Here we report improved high-throughput methods for single-nucleus droplet-based sequencing (snDrop-seq) and single-cell transposome hypersensitive site sequencing (scTHS-seq). We used each method to acquire nuclear transcriptomic and DNA accessibility maps for >60,000 single cells from human adult visual cortex, frontal cortex, and cerebellum. Integration of these data revealed regulatory elements and transcription factors that underlie cell-type distinctions, providing a basis for the study of complex processes in the brain, such as genetic programs that coordinate adult remyelination. We also mapped disease-associated risk variants to specific cellular populations, which provided insights into normal and pathogenic cellular processes in the human brain. This integrative multi-omics approach permits more detailed single-cell interrogation of complex organs and tissues.

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Acknowledgements

Flow cytometry was done at both the UCSD Human Embryonic Stem Cell Core and the TSRI Flow Cytometry Core. We thank T.F. Osothprarop and M.M. He (Illumina, San Diego, California, USA) for providing Tn5059 transposase; N. Salathia for assistance in sequencing; Y. Wu, T. Pakozdi, and Z. Chiang for assistance in sequencing analysis; and G. Kennedy for help on RNAscope. Funding support was provided by the NIH Common Fund Single Cell Analysis Program (1U01MH098977 to K.Z. and J.C.). T.E.D. is a fellow in the Pediatric Scientist Development Program and is supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (award no. K12-HD000850). G.E.K. was supported by a Neuroplasticity of Aging Training Grant (5T32AG000216-24). P.V.K. was supported by the NIH Centers for Excellence in Genomic Science (P50MH106933), NIH grant 1R01HL131768, and an NSF CAREER award (NSF-14-532). J.F. was supported by NIH grant F31 CA206236. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The GTEx samples used for the analyses described in this study were obtained from the University of Miami Brain Endowment Bank.

Author information

Author notes

    • Blue B Lake
    • , Song Chen
    • , Brandon C Sos
    •  & Jean Fan

    These authors contributed equally to this work.

Affiliations

  1. Department of Bioengineering, University of California San Diego, La Jolla, California, USA.

    • Blue B Lake
    • , Song Chen
    • , Brandon C Sos
    • , Thu E Duong
    • , Derek Gao
    •  & Kun Zhang
  2. UC San Diego School of Medicine, La Jolla, California, USA.

    • Brandon C Sos
    •  & Gwendolyn E Kaeser
  3. Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.

    • Jean Fan
    •  & Peter V Kharchenko
  4. Sanford Burnham Prebys Medical Discovery Institute, La Jolla, California, USA.

    • Gwendolyn E Kaeser
    • , Yun C Yung
    •  & Jerold Chun
  5. Department of Pediatric Respiratory Medicine, University of California San Diego, La Jolla, California, USA.

    • Thu E Duong

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Contributions

K.Z., P.V.K., and J.C. oversaw the study. B.B.L., S.C., B.C.S., G.E.K., Y.C.Y., T.E.D., and D.G. performed experiments. J.F., B.B.L., S.C., and B.C.S. performed bioinformatics analyses. B.B.L., S.C., B.C.S., J.F., J.C., P.V.K., and K.Z. wrote the manuscript, with input from all other co-authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Jerold Chun or Peter V Kharchenko or Kun Zhang.

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