Disentangling neural cell diversity using single-cell transcriptomics

Jean Francois Poulin, Bosiljka Tasic, Jens Hjerling-Leffler, Jeffrey M. Trimarchi, Rajeshwar Awatramani*

*Corresponding author for this work

Research output: Contribution to journalReview article

147 Scopus citations

Abstract

Cellular specialization is particularly prominent in mammalian nervous systems, which are composed of millions to billions of neurons that appear in thousands of different 'flavors' and contribute to a variety of functions. Even in a single brain region, individual neurons differ greatly in their morphology, connectivity and electrophysiological properties. Systematic classification of all mammalian neurons is a key goal towards deconstructing the nervous system into its basic components. With the recent advances in single-cell gene expression profiling technologies, it is now possible to undertake the enormous task of disentangling neuronal heterogeneity. High-throughput single-cell RNA sequencing and multiplexed quantitative RT-PCR have become more accessible, and these technologies enable systematic categorization of individual neurons into groups with similar molecular properties. Here we provide a conceptual and practical guide to classification of neural cell types using single-cell gene expression profiling technologies.

Original languageEnglish (US)
Pages (from-to)1131-1141
Number of pages11
JournalNature Neuroscience
Volume19
Issue number9
DOIs
StatePublished - Sep 1 2016

ASJC Scopus subject areas

  • Neuroscience(all)

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  • Cite this

    Poulin, J. F., Tasic, B., Hjerling-Leffler, J., Trimarchi, J. M., & Awatramani, R. (2016). Disentangling neural cell diversity using single-cell transcriptomics. Nature Neuroscience, 19(9), 1131-1141. https://doi.org/10.1038/nn.4366