Identification of spatially associated subpopulations by combining scRNA-seq and sequential fluorescence in situ hybridization
Abstract
How intrinsic gene-regulatory networks interact with a cell's spatial environment to define its identity remains poorly understood. We developed an approach to distinguish between intrinsic and extrinsic effects on global gene expression by integrating analysis of sequencing-based and imaging-based single-cell transcriptomic profiles, using cross-platform cell type mapping combined with a hidden Markov random field model. We applied this approach to dissect the cell-type- and spatial-domain-associated heterogeneity in the mouse visual cortex region. Our analysis identified distinct spatially associated, cell-type-independent signatures in the glutamatergic and astrocyte cell compartments. Using these signatures to analyze single-cell RNA sequencing data, we identified previously unknown spatially associated subpopulations, which were validated by comparison with anatomical structures and Allen Brain Atlas images.
Additional Information
© 2018 Springer Nature Limited. Received 21 December 2017; accepted 27 August 2018; published online 29 October 2018. Code availability: Code has been deposited at https://bitbucket.org/qzhudfci/smfishhmrf-py. Data availability: Expression data, spatial coordinates, SVM predictions, HMRF domains, expression box plots categorized by domains and cell types, and interactive visualizations are available at http://spatial.rc.fas.harvard.edu. The scRNA-seq dataset referenced in this study is GSE71585. This research was supported by a Claudia Barr Award, a Chan Zuckerberg Initiative Award, and NIH grant R01HL119099 to G.-C.Y., and by grants from the Paul G. Allen Foundation Discovery Center, NIH HD075605 and TR01 OD024686 to L.C. Author Contributions: G.-C.Y. and L.C. conceived and supervised the project. Q.Z. and G.-C.Y. conceived the HMRF and SVM models. Q.Z. and G.-C.Y. conducted and supervised the computational analyses. S.S. and L.C. conducted and supervised the seqFISH experiments. Q.Z., S.S., R.D., G.-C.Y. and L.C. wrote the manuscript. All of the authors contributed ideas for this work. All of the authors reviewed and approved the manuscript. The authors declare no competing financial interests.Attached Files
Accepted Version - nihms-1505041.pdf
Supplemental Material - nbt.4260-S1.pdf
Supplemental Material - nbt.4260-S2.pdf
Supplemental Material - nbt.4260-S3.pdf
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Additional details
- PMCID
- PMC6488461
- Eprint ID
- 88987
- DOI
- 10.1038/nbt.4260
- Resolver ID
- CaltechAUTHORS:20180821-132916530
- Claudia Barr Award
- Chan Zuckerberg Initiative
- R01HL119099
- NIH
- Paul G. Allen Family Foundation
- HD075605
- NIH
- TR01 OD024686
- NIH
- Created
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2018-10-29Created from EPrint's datestamp field
- Updated
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2022-03-02Created from EPrint's last_modified field