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Spatial reconstruction of single-cell gene expression data

Nature Biotechnology volume 33, pages 495–502 (2015)Cite this article

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Abstract

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

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Figure 1: Overview.
Figure 2: Single-cell RNA-seq from zebrafish embryos.
Figure 3: Seurat correctly infers the spatial position of cells.
Figure 4: Nine archetypal patterns discovered through spatial clustering.
Figure 5: Seurat spatially characterizes rare cell populations.

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Gene Expression Omnibus

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Acknowledgements

We thank members of the Regev and Schier laboratories for helpful discussion, O. Wurtzel for assistance with the R markdown scripts, A. Pauli for sharing the aplnrb plasmid, K. Rogers for donating superior, unpublished in situ hybridizations. This work was supported by F32 HD075541 (R.S.), the Jane Coffin Childs Memorial Fund for Medical Research (J.A.F.), the NIH (A.F.S.), National Human Genome Research Institute, Center of Excellence in Genome Science 1P50HG006193, the Klarman Cell Observatory and Howard Hughes Medical Institute (A.R.).

Author information

Author notes

  1. Rahul Satija

    Present address: Present address: New York Genome Center, New York, New York, USA and Department of Biology, New York University, New York, New York, USA.,

  2. Rahul Satija and Jeffrey A Farrell: These authors contributed equally to this work.

  3. Alexander F Schier and Aviv Regev: These authors jointly supervised this work.

Authors and Affiliations

  1. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    Rahul Satija, David Gennert, Alexander F Schier & Aviv Regev

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

    Jeffrey A Farrell & Alexander F Schier

  3. Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA

    Alexander F Schier

  4. Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, USA

    Alexander F Schier

  5. Center for Systems Biology, Harvard University, Cambridge, Massachusetts, USA

    Alexander F Schier

  6. Department of Biology, Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Aviv Regev

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Contributions

R.S., J.A.F., A.F.S. and A.R. conceived the research. R.S. and J.A.F. wrote the Seurat package and performed computational analysis of the RNA-seq data. J.A.F., D.G. and R.S. performed experimental work. J.A.F. and R.S. analyzed the data and produced figures. J.A.F., R.S., D.G., A.F.S. and A.R. wrote the manuscript.

Corresponding authors

Correspondence to Alexander F Schier or Aviv Regev.

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Competing interests

A.R. is a consultant to the Driver Group, which analyzes tumor samples, a potential sample fodder for spatial analysis.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7, Supplementary Tables 1 and 2, Supplementary Text and Supplementary Note (PDF 6126 kb)

Supplementary Code

Seurat source code (ZIP 28 kb)

Dissection of blastula cap from zebrafish embryos from yolk cell for dissociation (MOV 7676 kb)

41587_2015_BFnbt3192_MOESM13_ESM.mov

Animal cap depletion and dissection of margin-enriched cell population from zebrafish embryos for dissociation (MOV 9690 kb)

Isolation of single reference cells from zebrafish embryos (MOV 6469 kb)

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Satija, R., Farrell, J., Gennert, D. et al. Spatial reconstruction of single-cell gene expression data. Nat Biotechnol 33, 495–502 (2015). https://doi.org/10.1038/nbt.3192

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