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Nat Neurosci. 2016 Aug 26;19(9):1131-41. doi: 10.1038/nn.4366.

Disentangling neural cell diversity using single-cell transcriptomics.

Author information

1
Department of Neurology, Northwestern University, Chicago, Illinois, USA.
2
Department of Molecular Genetics, Allen Institute for Brain Science, Seattle, Washington, USA.
3
Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
4
Department of Genetics, Development and Cell Biology, Iowa State University, Ames, Iowa, USA.

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.

PMID:
27571192
DOI:
10.1038/nn.4366
[Indexed for MEDLINE]

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