Abstract

Changes in cell identities and positions underlie tissue development and disease progression. Although single-cell mRNA sequencing (scRNA-Seq) methods rapidly generate extensive lists of cell states, spatially resolved single-cell mapping presents a challenging task. We developed SCRINSHOT (Single-Cell Resolution IN Situ Hybridization On Tissues), a sensitive, multiplex RNA mapping approach. Direct hybridization of padlock probes on mRNA is followed by circularization with SplintR ligase and rolling circle amplification (RCA) of the hybridized padlock probes. Sequential detection of RCA-products using fluorophore-labeled oligonucleotides profiles thousands of cells in tissue sections. We evaluated SCRINSHOT specificity and sensitivity on murine and human organs. SCRINSHOT quantification of marker gene expression shows high correlation with published scRNA-Seq data over a broad range of gene expression levels. We demonstrate the utility of SCRINSHOT by mapping the locations of abundant and rare cell types along the murine airways. The amenability, multiplexity, and quantitative qualities of SCRINSHOT facilitate single-cell mRNA profiling of cell-state alterations in tissues under a variety of native and experimental conditions.

Highlights

  • Recent advances in single-cell RNA sequencing technologies enabled transcriptome analysis of individual cells and the identification of new cellular states in healthy and diseased conditions [1]

  • SCRINSHOT evolved from our attempts to improve the detection sensitivity and reduce the cost of the in situ sequencing method, using PFA-fixed material

  • We focused on stringent padlock probe hybridization to RNA targets and omitted the inefficient in situ complementary DNA (cDNA) synthesis step (Fig 1 and S1 Fig)

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Summary

Introduction

Recent advances in single-cell RNA sequencing (scRNA-Seq) technologies enabled transcriptome analysis of individual cells and the identification of new cellular states in healthy and diseased conditions [1]. These methods, fail to capture the spatial cellular organization in tissues due to cell dissociation. All scripts are available at: https://github.com/ AlexSount/SCRINSHOT Single cell RNA Sequencing data of AT2 cells (Liu et al, 2019) are freely accessible from authors at Gene Expression Omnibus (GEO) repository (GSE118891). Single cell RNA Sequencing data of tracheal cells (Montoro et al, 2018) are freely accessible from authors at Gene Expression Omnibus (GEO) repository (GSE103354)

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