Single-neuron RNA-Seq: Technical feasibility and reproducibility

Shenfeng Qiu, Shujun Luo, Oleg Evgrafov, Robin Li, Gary P. Schroth, Pat Levitt, James A. Knowles, Kai Wang

Research output: Contribution to journalArticlepeer-review

57 Scopus citations


Understanding brain function involves improved knowledge about how the genome specifies such a large diversity of neuronal types. Transcriptome analysis of single neurons has been previously described using gene expression microarrays. Using high-throughput transcriptome sequencing (RNA-Seq), we have developed a method to perform single-neuron RNA-Seq. Following electrophysiology recording from an individual neuron, total RNA was extracted by aspirating the cellular contents into a fine glass electrode tip. The mRNAs were reverse transcribed and amplified to construct a single-neuron cDNA library, and subsequently subjected to high-throughput sequencing. This approach was applied to both individual neurons cultured from embryonic mouse hippocampus, as well as neocortical neurons from live brain slices. We found that the average pairwise Spearmans rank correlation coefficient of gene expression level expressed as RPKM (reads per kilobase of transcript per million mapped reads) was 0.51 between five cultured neuronal cells, whereas the same measure between three cortical layer 5 neurons in situ was 0.25. The data suggest that there may be greater heterogeneity of the cortical neurons, as compared to neurons in vitro. The results demonstrate the technical feasibility and reproducibility of RNA-Seq in capturing a part of the transcriptome landscape of single neurons, and confirmed that morphologically identical neurons, even from the same region, have distinct gene expression patterns.

Original languageEnglish (US)
Article numberArticle 124
JournalFrontiers in Genetics
Issue numberJUL
StatePublished - 2012
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Genetics
  • Genetics(clinical)


  • Cell culture
  • Electrophysiology
  • Gene expression
  • Neuron
  • RNA-Seq
  • Transcriptome


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