Abstract

The lineage relationships among the hundreds of cell types generated during development are difficult to reconstruct. A recent method, GESTALT, used CRISPR–Cas9 barcode editing for large-scale lineage tracing, but was restricted to early development and did not identify cell types. Here we present scGESTALT, which combines the lineage recording capabilities of GESTALT with cell-type identification by single-cell RNA sequencing. The method relies on an inducible system that enables barcodes to be edited at multiple time points, capturing lineage information from later stages of development. Sequencing of 60,000 transcriptomes from the juvenile zebrafish brain identified >100 cell types and marker genes. Using these data, we generate lineage trees with hundreds of branches that help uncover restrictions at the level of cell types, brain regions, and gene expression cascades during differentiation. scGESTALT can be applied to other multicellular organisms to simultaneously characterize molecular identities and lineage histories of thousands of cells during development and disease.

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Acknowledgements

We thank G. Findlay and members of the Schier laboratory, particularly J. Farrell, for discussion and advice, the Bauer Core Facility (Harvard) and the Molecular Biology Core Facility (Dana Farber Cancer Institute) for sequencing services, and the Harvard zebrafish facility staff for technical support. This work was supported by a postdoctoral fellowship from the Canadian Institutes of Health Research to B.R., an HHMI Fellowship from the Life Sciences Research Foundation and 1K99GM121852 to D.E.W., a fellowship from the NIH/NHLBI (T32HL007312) to A.M., a Burroughs-Wellcome Fund CASI award and an Edward Mallinckrodt, Jr. Foundation grant to A.M.K., a Paul G. Allen Family Foundation grant and an NIH Director's Pioneer Award (DP1HG007811) to J.S., a postdoctoral fellowship from the American Cancer Society to J.A.G., NIH grants U01MH109560, R01HD85905 and DP1 HD094764-01 to A.F.S., and an Allen Discovery Center grant to A.F.S. and J.S. J.S. is an investigator of the Howard Hughes Medical Institute.

Author information

Author notes

    • Daniel E Wagner
    •  & Aaron McKenna

    These authors contributed equally to this work.

Affiliations

  1. Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA.

    • Bushra Raj
    • , Shristi Pandey
    • , James A Gagnon
    •  & Alexander F Schier
  2. Allen Discovery Center for Cell Lineage Tracing, Seattle, Washington, USA.

    • Bushra Raj
    • , Aaron McKenna
    • , Jay Shendure
    • , James A Gagnon
    •  & Alexander F Schier
  3. Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.

    • Daniel E Wagner
    •  & Allon M Klein
  4. Department of Genome Sciences, University of Washington, Seattle, Washington, USA.

    • Aaron McKenna
    •  & Jay Shendure
  5. Howard Hughes Medical Institute, Seattle, Washington, USA.

    • Jay Shendure
  6. Department of Biology, University of Utah, Salt Lake City, Utah, USA.

    • James A Gagnon
  7. Biozentrum, University of Basel, Switzerland.

    • Alexander F Schier
  8. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Alexander F Schier
  9. Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, USA.

    • Alexander F Schier
  10. Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA.

    • Alexander F Schier

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Contributions

B.R., J.A.G., and A.F.S. designed the study, interpreted the data and wrote the manuscript. B.R. and J.A.G. generated transgenic lines and GESTALT genomic DNA libraries. B.R. performed barcode editing experiments for inDrops and performed data analysis with assistance from J.A.G. D.E.W. performed inDrops encapsulation, inDrops library preparations, and upstream bioinformatic processing of transcriptome and scGESTALT libraries. B.R. and D.E.W. developed the targeted scGESTALT amplification protocol. A.M. developed the scGESTALT processing pipeline and generated lineage trees. B.R. performed downstream processing of scGESTALT data. S.P. established the zebrafish neuron dissociation protocol. A.M.K. and J.S. provided resources and critical insights.

Competing interests

A.M.K. is a co-inventor on a patent application (PCT/US2015/026443) that includes some of the ideas described in this article. A.M.K. is a cofounder and science advisory board member of 1CellBio. The rest of the authors declare no competing interests.

Corresponding authors

Correspondence to James A Gagnon or Alexander F Schier.

Integrated supplementary information

Supplementary information

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  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–9

  2. 2.

    Life Sciences Reporting Summary

  3. 3.

    Supplementary Table 1

    Sequences of oligonucleotides used in this study.

  4. 4.

    Supplementary Note 1

    Glossary of Terms

Excel files

  1. 1.

    Supplementary Dataset 1

    Description of samples for transcriptome and scGESTALT analyses.

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    Supplementary Dataset 2

    Differential gene expression analysis of broadly defined cell type clusters and their proportions as a percentage of the total dataset.

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    Supplementary Dataset 3

    Regional and marker description of broadly defined cell type clusters.

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    Supplementary Dataset 4

    Differential gene expression analysis of subclusters resulting from iterative clustering.

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DOI

https://doi.org/10.1038/nbt.4103

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