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.
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We would like to thank L. Laboissonniere, R. Chowdhury, N. Skene, V. Menon and G. Caronia-Brown for comments on the manuscript. J.-F.P. is supported by FRSQ and CIHR. R.A. is supported by the Paul Ruby Foundation, NARSAD, NIH R21NS092034-01A1 and R01 NS096240-01. B.T. is supported by the Allen Institute for Brain Science. J.H.-L. is supported by Swedish Research Council (VR), StratNeuro, Hjärnfonden, and EU FP7/Marie Curie Actions.
The authors declare no competing financial interests.
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Poulin, JF., Tasic, B., Hjerling-Leffler, J. et al. Disentangling neural cell diversity using single-cell transcriptomics. Nat Neurosci 19, 1131–1141 (2016). https://doi.org/10.1038/nn.4366
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