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  Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq

Cadwell, C., Palasantza, A., Jiang, X., Berens, P., Deng, Q., Yilmaz, M., et al. (2016). Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq. Nature Biotechnology, 34(2), 199-203. doi:10.1038/nbt.3445.

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Cadwell, CR, Autor
Palasantza, A, Autor
Jiang, X, Autor
Berens, P1, 2, Autor           
Deng, Q, Autor
Yilmaz, M, Autor
Reimer, J, Autor
Shen, S, Autor
Bethge, M1, 2, Autor           
Tolias, KF, Autor
Sandberg, R, Autor
Tolias, AS2, 3, Autor           
Affiliations:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              

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 Zusammenfassung: Despite the importance of the mammalian neocortex for complex cognitive processes, we still lack a comprehensive description of its cellular components. To improve the classification of neuronal cell types and the functional characterization of single neurons, we present Patch-seq, a method that combines whole-cell electrophysiological patch-clamp recordings, single-cell RNA-sequencing and morphological characterization. Following electrophysiological characterization, cell contents are aspirated through the patch-clamp pipette and prepared for RNA-sequencing. Using this approach, we generate electrophysiological and molecular profiles of 58 neocortical cells and show that gene expression patterns can be used to infer the morphological and physiological properties such as axonal arborization and action potential amplitude of individual neurons. Our results shed light on the molecular underpinnings of neuronal diversity and suggest that Patch-seq can facilitate the classification of cell types in the nervous system.

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 Datum: 2016-02
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1038/nbt.3445
BibTex Citekey: CadwellPJBDYRSBTST2015
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Titel: Nature Biotechnology
Genre der Quelle: Zeitschrift
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Seiten: - Band / Heft: 34 (2) Artikelnummer: - Start- / Endseite: 199 - 203 Identifikator: -