Combinatorial labeling of single cells for gene expression cytometry

Single-cell expression analysis on a large scaleTo understand why cells differ from each other, we need to understand which genes are transcribed at a single-cell level. Several methods measure messenger RNA (mRNA) expression in single cells, but most are limited to relatively low numbers of cells o...

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Published in:Science (American Association for the Advancement of Science) 2015-02, Vol.347 (6222), p.628-628
Main Authors: Fan, H. Christina, Fu, Glenn K., Fodor, Stephen P. A.
Format: Article
Language:English
Subjects:
Automation
Bar codes
Beads
Cells
Cellular
Coding
Combinatorial analysis
Combinatorics
Cytometry
Gene expression
Genes
Heterogeneity
Libraries
RESEARCH ARTICLE SUMMARY
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description Single-cell expression analysis on a large scaleTo understand why cells differ from each other, we need to understand which genes are transcribed at a single-cell level. Several methods measure messenger RNA (mRNA) expression in single cells, but most are limited to relatively low numbers of cells or genes. Fan et al. labeled each mRNA molecule in a cell with both a cellular barcode and a molecular barcode. Further analysis did not then require single-cell technologies. Instead, the labeled mRNA from all cells was pooled, amplified, and sequenced, and the gene expression profile of individual cells was reconstructed based on the barcodes. The technique successfully revealed heterogeneity across several thousand blood cells.Science, this issue 10.1126/science.1258367 We present a technically simple approach for gene expression cytometry combining next-generation sequencing with stochastic barcoding of single cells. A combinatorial library of beads bearing cell- and molecular-barcoding capture probes is used to uniquely label transcripts and reconstruct the digital gene expression profile of thousands of individual cells in a single experiment without the need for robotics or automation. We applied the technology to dissect the human hematopoietic system and to characterize heterogeneous response to in vitro stimulation. High sensitivity is demonstrated by detection of low-abundance transcripts and rare cells. Under current implementation, the technique can analyze a few thousand cells simultaneously and can readily scale to 10,000s or 100,000s of cells.
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subjects Automation
Bar codes
Beads
Cells
Cellular
Coding
Combinatorial analysis
Combinatorics
Cytometry
Gene expression
Genes
Heterogeneity
Libraries
RESEARCH ARTICLE SUMMARY
Transcripts (Written Records)
title Combinatorial labeling of single cells for gene expression cytometry
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