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

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 t...

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Autores principales: Lee, Brian R, Budzillo, Agata, Hadley, Kristen, Miller, Jeremy A, Jarsky, Tim, Baker, Katherine, Hill, DiJon, Kim, Lisa, Mann, Rusty, Ng, Lindsay, Oldre, Aaron, Rajanbabu, Ram, Trinh, Jessica, Vargas, Sara, Braun, Thomas, Dalley, Rachel A, Gouwens, Nathan W, Kalmbach, Brian E, Kim, Tae Kyung, Smith, Kimberly A, Soler-Llavina, Gilberto, Sorensen, Staci, Tasic, Bosiljka, Ting, Jonathan T, Lein, Ed, Zeng, Hongkui, Murphy, Gabe J, Berg, Jim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428855/
https://www.ncbi.nlm.nih.gov/pubmed/34387544
http://dx.doi.org/10.7554/eLife.65482
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author Lee, Brian R
Budzillo, Agata
Hadley, Kristen
Miller, Jeremy A
Jarsky, Tim
Baker, Katherine
Hill, DiJon
Kim, Lisa
Mann, Rusty
Ng, Lindsay
Oldre, Aaron
Rajanbabu, Ram
Trinh, Jessica
Vargas, Sara
Braun, Thomas
Dalley, Rachel A
Gouwens, Nathan W
Kalmbach, Brian E
Kim, Tae Kyung
Smith, Kimberly A
Soler-Llavina, Gilberto
Sorensen, Staci
Tasic, Bosiljka
Ting, Jonathan T
Lein, Ed
Zeng, Hongkui
Murphy, Gabe J
Berg, Jim
author_facet Lee, Brian R
Budzillo, Agata
Hadley, Kristen
Miller, Jeremy A
Jarsky, Tim
Baker, Katherine
Hill, DiJon
Kim, Lisa
Mann, Rusty
Ng, Lindsay
Oldre, Aaron
Rajanbabu, Ram
Trinh, Jessica
Vargas, Sara
Braun, Thomas
Dalley, Rachel A
Gouwens, Nathan W
Kalmbach, Brian E
Kim, Tae Kyung
Smith, Kimberly A
Soler-Llavina, Gilberto
Sorensen, Staci
Tasic, Bosiljka
Ting, Jonathan T
Lein, Ed
Zeng, Hongkui
Murphy, Gabe J
Berg, Jim
author_sort Lee, Brian R
collection PubMed
description 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.
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spelling pubmed-84288552021-09-13 Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization Lee, Brian R Budzillo, Agata Hadley, Kristen Miller, Jeremy A Jarsky, Tim Baker, Katherine Hill, DiJon Kim, Lisa Mann, Rusty Ng, Lindsay Oldre, Aaron Rajanbabu, Ram Trinh, Jessica Vargas, Sara Braun, Thomas Dalley, Rachel A Gouwens, Nathan W Kalmbach, Brian E Kim, Tae Kyung Smith, Kimberly A Soler-Llavina, Gilberto Sorensen, Staci Tasic, Bosiljka Ting, Jonathan T Lein, Ed Zeng, Hongkui Murphy, Gabe J Berg, Jim eLife Genetics and Genomics 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. eLife Sciences Publications, Ltd 2021-08-13 /pmc/articles/PMC8428855/ /pubmed/34387544 http://dx.doi.org/10.7554/eLife.65482 Text en © 2021, Lee et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Genetics and Genomics
Lee, Brian R
Budzillo, Agata
Hadley, Kristen
Miller, Jeremy A
Jarsky, Tim
Baker, Katherine
Hill, DiJon
Kim, Lisa
Mann, Rusty
Ng, Lindsay
Oldre, Aaron
Rajanbabu, Ram
Trinh, Jessica
Vargas, Sara
Braun, Thomas
Dalley, Rachel A
Gouwens, Nathan W
Kalmbach, Brian E
Kim, Tae Kyung
Smith, Kimberly A
Soler-Llavina, Gilberto
Sorensen, Staci
Tasic, Bosiljka
Ting, Jonathan T
Lein, Ed
Zeng, Hongkui
Murphy, Gabe J
Berg, Jim
Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization
title Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization
title_full Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization
title_fullStr Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization
title_full_unstemmed Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization
title_short Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization
title_sort scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization
topic Genetics and Genomics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428855/
https://www.ncbi.nlm.nih.gov/pubmed/34387544
http://dx.doi.org/10.7554/eLife.65482
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