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问答:使用 Patch-seq 技术进行单细胞分析。

Q&A: using Patch-seq to profile single cells.

机构信息

Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, Texas, 77030, USA.

Ludwig Institute for Cancer Research, Stockholm, Sweden.

出版信息

BMC Biol. 2017 Jul 6;15(1):58. doi: 10.1186/s12915-017-0396-0.

DOI:10.1186/s12915-017-0396-0
PMID:28679385
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5499043/
Abstract

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.

摘要

个体神经元在基因表达、形态和电生理特性方面存在广泛差异。虽然有许多技术可以研究这些维度中的一个或两个方面的单细胞变异性,但很少有技术可以评估单个细胞的所有三个特征。我们最近开发了 Patch-seq,它将全细胞膜片钳记录与单细胞 RNA 测序和免疫组织化学相结合,全面分析单个神经元的转录组、形态和生理特征。Patch-seq 可以广泛应用于描述神经系统等复杂组织中的细胞类型,并研究单细胞多维表型的转录特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5639/5499043/2a59ad171e23/12915_2017_396_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5639/5499043/b47de79df5eb/12915_2017_396_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5639/5499043/4d2816df29e5/12915_2017_396_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5639/5499043/2a59ad171e23/12915_2017_396_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5639/5499043/b47de79df5eb/12915_2017_396_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5639/5499043/4d2816df29e5/12915_2017_396_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5639/5499043/2a59ad171e23/12915_2017_396_Fig3_HTML.jpg

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