Three-dimensional intact-tissue sequencing of single-cell transcriptional states

Xiao Wang(Stanford University), William E. Allen(Neurosciences Institute), Matthew A. Wright(Stanford University), Emily Sylwestrak(Stanford University), Nikolay Samusik(Stanford University), Sam Vesuna(Stanford University), Kathryn E. Evans(Stanford University), Cindy Liu(Stanford University), Charu Ramakrishnan(Stanford University), Jia Liu(Stanford University), Garry P. Nolan(Stanford University), Felice-Alessio Bava(Stanford University), Karl Deisseroth(Howard Hughes Medical Institute)
Science
June 21, 2018
Cited by 1,695Open Access
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Abstract

Retrieving high-content gene-expression information while retaining three-dimensional (3D) positional anatomy at cellular resolution has been difficult, limiting integrative understanding of structure and function in complex biological tissues. We developed and applied a technology for 3D intact-tissue RNA sequencing, termed STARmap (spatially-resolved transcript amplicon readout mapping), which integrates hydrogel-tissue chemistry, targeted signal amplification, and in situ sequencing. The capabilities of STARmap were tested by mapping 160 to 1020 genes simultaneously in sections of mouse brain at single-cell resolution with high efficiency, accuracy, and reproducibility. Moving to thick tissue blocks, we observed a molecularly defined gradient distribution of excitatory-neuron subtypes across cubic millimeter-scale volumes (>30,000 cells) and a short-range 3D self-clustering in many inhibitory-neuron subtypes that could be identified and described with 3D STARmap.


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