Single-cell gene expression profiling using FACS and qPCR with internal standards

Joshua R. Porter, William G. Telford, Eric Batchelor

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Gene expression measurements from bulk populations of cells can obscure the considerable transcriptomic variation of individual cells within those populations. Single-cell gene expression measurements can help assess the role of noise in gene expression, identify correlations in the expression of pairs of genes, and reveal subpopulations of cells that respond differently to a stimulus. Here, we describe a procedure to measure the expression of up to 96 genes in single mammalian cells isolated from a population growing in tissue culture. Cells are sorted into lysis buffer by fluorescence-activated cell sorting (FACS), and the mRNA species of interest are reverse-transcribed and amplified. Gene expression is then measured using a microfluidic real-time PCR machine, which performs up to 96 qPCR assays on up to 96 samples at a time. We also describe the generation and use of PCR amplicon standards to enable the estimation of the absolute number of each transcript. Compared with other methods of measuring gene expression in single cells, this approach allows for the quantification of more distinct transcripts than RNA FISH at a lower cost than RNA-Seq.

Original languageEnglish (US)
Article numbere55219
JournalJournal of Visualized Experiments
Issue number120
StatePublished - Feb 25 2017
Externally publishedYes

Bibliographical note

Funding Information:
We would like to thank V. Kapoor in the CCR ETIB Flow Cytometry Core for her aid in performing the cell sorting during the development of this protocol. We also thank M. Raffeld and the CCR LP Molecular Diagnostics Unit and J. Zhu and the NHLBI DNA Sequencing and Genomics Core for their aid in performing the qPCR during the development of this protocol. This research was supported by the Intramural Program of the NIH.

Publisher Copyright:
© 2017 Journal of Visualized Experiments.


  • Cell fate decisions
  • Fluorescence-activated cell sorting
  • Genetics
  • Internal standards
  • Issue 120
  • Single cell
  • Stochasticity
  • qPCR


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