Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution

Author:

Rodriques Samuel G.123ORCID,Stickels Robert R.345ORCID,Goeva Aleksandrina3ORCID,Martin Carly A.3ORCID,Murray Evan3,Vanderburg Charles R.3ORCID,Welch Joshua3,Chen Linlin M.3ORCID,Chen Fei3ORCID,Macosko Evan Z.36ORCID

Affiliation:

1. Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

2. MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

3. Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.

4. Graduate School of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA.

5. Division of Medical Science, Harvard Medical School, Boston, MA 02115, USA.

6. Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA.

Abstract

Gene expression at fine scale Mapping gene expression at the single-cell level within tissues remains a technical challenge. Rodriques et al. developed a method called Slide-seq, whereby RNA was spatially resolved from tissue sections by transfer onto a surface covered with DNA-barcoded beads. Applying Slide-seq to regions of a mouse brain revealed spatial gene expression patterns in the Purkinje layer of the cerebellum and axes of variation across Purkinje cell compartments. The authors used this method to dissect the temporal evolution of cell type–specific responses in a mouse model of traumatic brain injury. Science , this issue p. 1463

Funder

NIH Office of the Director

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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