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Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics
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DOI：10.1038/s41576-021-00370-8.png)
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摘要
En 中文
Combining single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics can localize transcriptionally characterized single cells within their native tissue context. This Review discusses methodologies and tools to integrate scRNA-seq with spatial transcriptomics approaches, and illustrates the types of insights that can be gained. 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.
Keyword:
GENE-EXPRESSION
MESSENGER-RNA
SUBCELLULAR RESOLUTION
TUMOR MICROENVIRONMENT
MASS CYTOMETRY
IN-VIVO
SEQ
TECHNOLOGIES
MAP
DECONVOLUTION
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52
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4.0K
被引数:
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