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Q&A: using Patch-seq to profile single cells
Individual neurons vary widely in terms of their gene expression, morphology, and electrophysiological properties. While many techniques exist to study single-cell variability along one or two of these dimensions, very few techniques can assess all three features for a single cell. We recently devel...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5499043/ https://www.ncbi.nlm.nih.gov/pubmed/28679385 http://dx.doi.org/10.1186/s12915-017-0396-0 |
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author | Cadwell, Cathryn R. Sandberg, Rickard Jiang, Xiaolong Tolias, Andreas S. |
author_facet | Cadwell, Cathryn R. Sandberg, Rickard Jiang, Xiaolong Tolias, Andreas S. |
author_sort | Cadwell, Cathryn R. |
collection | PubMed |
description | Individual neurons vary widely in terms of their gene expression, morphology, and electrophysiological properties. While many techniques exist to study single-cell variability along one or two of these dimensions, very few techniques can assess all three features for a single cell. We recently developed Patch-seq, which combines whole-cell patch clamp recording with single-cell RNA-sequencing and immunohistochemistry to comprehensively profile the transcriptomic, morphologic, and physiologic features of individual neurons. Patch-seq can be broadly applied to characterize cell types in complex tissues such as the nervous system, and to study the transcriptional signatures underlying the multidimensional phenotypes of single cells. |
format | Online Article Text |
id | pubmed-5499043 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54990432017-07-10 Q&A: using Patch-seq to profile single cells Cadwell, Cathryn R. Sandberg, Rickard Jiang, Xiaolong Tolias, Andreas S. BMC Biol Question and Answer Individual neurons vary widely in terms of their gene expression, morphology, and electrophysiological properties. While many techniques exist to study single-cell variability along one or two of these dimensions, very few techniques can assess all three features for a single cell. We recently developed Patch-seq, which combines whole-cell patch clamp recording with single-cell RNA-sequencing and immunohistochemistry to comprehensively profile the transcriptomic, morphologic, and physiologic features of individual neurons. Patch-seq can be broadly applied to characterize cell types in complex tissues such as the nervous system, and to study the transcriptional signatures underlying the multidimensional phenotypes of single cells. BioMed Central 2017-07-06 /pmc/articles/PMC5499043/ /pubmed/28679385 http://dx.doi.org/10.1186/s12915-017-0396-0 Text en © Tolias et al. 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Question and Answer Cadwell, Cathryn R. Sandberg, Rickard Jiang, Xiaolong Tolias, Andreas S. Q&A: using Patch-seq to profile single cells |
title | Q&A: using Patch-seq to profile single cells |
title_full | Q&A: using Patch-seq to profile single cells |
title_fullStr | Q&A: using Patch-seq to profile single cells |
title_full_unstemmed | Q&A: using Patch-seq to profile single cells |
title_short | Q&A: using Patch-seq to profile single cells |
title_sort | q&a: using patch-seq to profile single cells |
topic | Question and Answer |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5499043/ https://www.ncbi.nlm.nih.gov/pubmed/28679385 http://dx.doi.org/10.1186/s12915-017-0396-0 |
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