Single-cell RNA sequencing of fluorescently labeled mouse neurons using manual sorting and double in vitro transcription with absolute counts sequencing (DIVA-seq)

Anirban Paul, Z. Josh Huang

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Single-cell RNA sequencing (RNA-seq) is now a widely implemented tool for assaying gene expression. Commercially available single-cell RNA-sequencing platforms process all input cells indiscriminately. Sometimes, fluorescence-activated cell sorting (FACS) is used upstream to isolate a specifically labeled population of interest. A limitation of FACS is the need for high numbers of input cells with significantly labeled fractions, which is impractical for collecting and profiling rare or sparsely labeled neuron populations from the mouse brain. Here, we describe a method for manually collecting sparse fluorescently labeled single neurons from freshly dissociated mouse brain tissue. This process allows for capturing single-labeled neurons with high purity and subsequent integration with an in vitro transcription-based amplification protocol that preserves endogenous transcript ratios. We describe a double linear amplification method that uses unique molecule identifiers (UMIs) to generate individual mRNA counts. Two rounds of amplification results in a high degree of gene detection per single cell.

Original languageEnglish (US)
Article numbere58690
JournalJournal of Visualized Experiments
Volume2018
Issue number140
DOIs
StatePublished - Jan 1 2018

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Chemical Engineering(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

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