Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics

Sophia K. Longo, Margaret G. Guo, Andrew L. Ji, Paul A. Khavari

Research output: Contribution to journalReview articlepeer-review

431 Scopus citations

Abstract

Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but does not capture their spatial distribution nor reveal local networks of intercellular communication acting in situ. A suite of recently developed techniques that localize RNA within tissue, including multiplexed in situ hybridization and in situ sequencing (here defined as high-plex RNA imaging) and spatial barcoding, can help address this issue. However, no method currently provides as complete a scope of the transcriptome as does scRNA-seq, underscoring the need for approaches to integrate single-cell and spatial data. Here, we review efforts to integrate scRNA-seq with spatial transcriptomics, including emerging integrative computational methods, and propose ways to effectively combine current methodologies.

Original languageEnglish
Pages (from-to)627-644
Number of pages18
JournalNature Reviews Genetics
Volume22
Issue number10
DOIs
StatePublished - Oct 2021
Externally publishedYes

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