Patch-seq: Past, Present, and Future

J Neurosci. 2021 Feb 3;41(5):937-946. doi: 10.1523/JNEUROSCI.1653-20.2020. Epub 2021 Jan 11.


Single-cell transcriptomic approaches are revolutionizing neuroscience. Integrating this wealth of data with morphology and physiology, for the comprehensive study of neuronal biology, requires multiplexing gene expression data with complementary techniques. To meet this need, multiple groups in parallel have developed "Patch-seq," a modification of whole-cell patch-clamp protocols that enables mRNA sequencing of cell contents after electrophysiological recordings from individual neurons and morphologic reconstruction of the same cells. In this review, we first outline the critical technical developments that enabled robust Patch-seq experimental efforts and analytical solutions to interpret the rich multimodal data generated. We then review recent applications of Patch-seq that address novel and long-standing questions in neuroscience. These include the following: (1) targeted study of specific neuronal populations based on their anatomic location, functional properties, lineage, or a combination of these factors; (2) the compilation and integration of multimodal cell type atlases; and (3) the investigation of the molecular basis of morphologic and functional diversity. Finally, we highlight potential opportunities for further technical development and lines of research that may benefit from implementing the Patch-seq technique. As a multimodal approach at the intersection of molecular neurobiology and physiology, Patch-seq is uniquely positioned to directly link gene expression to brain function.

Keywords: electrophysiology; multi-modal; neuronal morphology; patch-clamp; single cell; transcriptomics.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Cells, Cultured
  • Electrophysiological Phenomena / physiology
  • Forecasting
  • Humans
  • Neurons / physiology*
  • Patch-Clamp Techniques / methods*
  • Patch-Clamp Techniques / trends
  • Sequence Analysis, RNA / methods
  • Sequence Analysis, RNA / trends
  • Single-Cell Analysis / methods*
  • Single-Cell Analysis / trends
  • Transcriptome / physiology*