Disentangling neural cell diversity using single-cell transcriptomics

Autor: Jens Hjerling-Leffler, Jeffrey M. Trimarchi, Jean-François Poulin, Bosiljka Tasic, Rajeshwar Awatramani
Rok vydání: 2016
Předmět:
Zdroj: Nature Neuroscience. 19:1131-1141
ISSN: 1546-1726
1097-6256
Popis: Although single-cell gene expression profiling has been possible for the past two decades, a number of recent technological advances in microfluidic and sequencing technology have recently made the procedure much easier and less expensive. Awatramani and colleagues discuss the use of single-cell gene expression profiling for classifying neuronal cell types. 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.
Databáze: OpenAIRE
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