Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization.

Autor:	Lee BR; Allen Institute for Brain Science, Seattle, United States., Budzillo A; Allen Institute for Brain Science, Seattle, United States., Hadley K; Allen Institute for Brain Science, Seattle, United States., Miller JA; Allen Institute for Brain Science, Seattle, United States., Jarsky T; Allen Institute for Brain Science, Seattle, United States., Baker K; Allen Institute for Brain Science, Seattle, United States., Hill D; Allen Institute for Brain Science, Seattle, United States., Kim L; Allen Institute for Brain Science, Seattle, United States., Mann R; Allen Institute for Brain Science, Seattle, United States., Ng L; Allen Institute for Brain Science, Seattle, United States., Oldre A; Allen Institute for Brain Science, Seattle, United States., Rajanbabu R; Allen Institute for Brain Science, Seattle, United States., Trinh J; Allen Institute for Brain Science, Seattle, United States., Vargas S; Allen Institute for Brain Science, Seattle, United States., Braun T; Byte Physics, Berlin, Germany., Dalley RA; Allen Institute for Brain Science, Seattle, United States., Gouwens NW; Allen Institute for Brain Science, Seattle, United States., Kalmbach BE; Allen Institute for Brain Science, Seattle, United States.; Department of Physiology and Biophysics, University of Washington, Seattle, United States., Kim TK; Allen Institute for Brain Science, Seattle, United States., Smith KA; Allen Institute for Brain Science, Seattle, United States., Soler-Llavina G; Allen Institute for Brain Science, Seattle, United States., Sorensen S; Allen Institute for Brain Science, Seattle, United States., Tasic B; Allen Institute for Brain Science, Seattle, United States., Ting JT; Allen Institute for Brain Science, Seattle, United States.; Department of Physiology and Biophysics, University of Washington, Seattle, United States., Lein E; Allen Institute for Brain Science, Seattle, United States., Zeng H; Allen Institute for Brain Science, Seattle, United States., Murphy GJ; Allen Institute for Brain Science, Seattle, United States.; Department of Physiology and Biophysics, University of Washington, Seattle, United States., Berg J; Allen Institute for Brain Science, Seattle, United States.
Jazyk:	angličtina
Zdroj:	ELife [Elife] 2021 Aug 13; Vol. 10. Date of Electronic Publication: 2021 Aug 13.
DOI:	10.7554/eLife.65482
Abstrakt:	The Patch-seq approach is a powerful variation of the patch-clamp technique that allows for the combined electrophysiological, morphological, and transcriptomic characterization of individual neurons. To generate Patch-seq datasets at scale, we identified and refined key factors that contribute to the efficient collection of high-quality data. We developed patch-clamp electrophysiology software with analysis functions specifically designed to automate acquisition with online quality control. We recognized the importance of extracting the nucleus for transcriptomic success and maximizing membrane integrity during nucleus extraction for morphology success. The protocol is generalizable to different species and brain regions, as demonstrated by capturing multimodal data from human and macaque brain slices. The protocol, analysis and acquisition software are compiled at https://githubcom/AllenInstitute/patchseqtools. This resource can be used by individual labs to generate data across diverse mammalian species and that is compatible with large publicly available Patch-seq datasets. Competing Interests: BL, AB, JM, TJ, KB, DH, LK, RM, LN, AO, RR, JT, SV, TB, RD, NG, BK, TK, KS, GS, SS, BT, JT, EL, HZ, GM, JB None, KH none (© 2021, Lee et al.)
Databáze:	MEDLINE
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