Single-Cell RNA Sequencing: Unraveling the Brain One Cell at a Time

Abstract

Single-cell RNA sequencing (scRNA-seq) is an exciting new technology allowing the analysis of transcriptomes from individual cells, and is ideally suited to address the inherent complexity and dynamics of the central nervous system. scRNA-seq has already been applied to the study of molecular taxonomy of the brain. These works have paved the way to expanding our understanding of the nervous system and provide insights into cellular susceptibilities and molecular mechanisms in neurological and neurodegenerative diseases. We discuss recent progress and challenges in applying this technology to advance our understanding of the brain. We advocate the application of scRNA-seq in the discovery of targets and biomarkers as a new approach in developing novel therapeutics for the treatment of neurodegenerative diseases.

Figure 1. Single Cell Sequencing Technology

A) schematic representation of a microfluidics chip with multiple devices (microfluidics chambers that are necessary to perform an individual experiment) on a single chip (i.e. usually a single chip can be used for multiple experiments. B) A single device has three input ports (oil, barcoded beads in lysis buffer, and cells of interest) and a single output port used for collecting bead- cell containing lipid droplets. Then each cell (or RNA in the cell) is marked by the unique barcode and processed on the bead for sequencing.

Figure 2. Single Cell Sequencing Data Analysis Workflow

The Unique molecular identifier (UMI) is extracted from raw data, facilitating efficient filtering of duplicate transcripts from the PCR and sequencing steps. Cell-gene expression tables are then generated. Cells are clustered based on different gene expression profiles. With known cell-type specific gene markers, cell clusters can be identified as individual cell populations. Single cell differential gene expression or pathway overdispersion analysis can be applied to specific cell populations.