Literature DB >> 25023306

Single-cell RT-PCR, a technique to decipher the electrical, anatomical, and genetic determinants of neuronal diversity.

Maria Toledo-Rodriguez1, Henry Markram.   

Abstract

The patch-clamp technique has allowed for detailed studies on the electrical properties of neurons. Dye loading through patch pipettes enabled characterizing the morphological properties of the neurons. In addition, the patch-clamp technique also allows for harvesting mRNA from single cells to study gene expression at the single cell level (known as single-cell RT-PCR). The combination of these three approaches makes possible the study of the GEM profile of neurons (gene expression, electrophysiology, and morphology) using a single patch pipette and patch-clamp recording. This combination provides a powerful technique to investigate and correlate the neuron's gene expression with its phenotype (electrical behavior and morphology). The harvesting and amplification of single cell mRNA for gene expression studies is a challenging task, especially for researchers with sparse or no training in molecular biology (see Notes 1,2 and 5). Here we describe in detail the GEM profiling approach with special attention to the gene expression profiling.

Mesh:

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Year:  2014        PMID: 25023306     DOI: 10.1007/978-1-4939-1096-0_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  11 in total

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

Authors:  Cathryn R Cadwell; Athanasia Palasantza; Xiaolong Jiang; Philipp Berens; Qiaolin Deng; Marlene Yilmaz; Jacob Reimer; Shan Shen; Matthias Bethge; Kimberley F Tolias; Rickard Sandberg; Andreas S Tolias
Journal:  Nat Biotechnol       Date:  2015-12-21       Impact factor: 54.908

2.  Patch-seq: Past, Present, and Future.

Authors:  Marcela Lipovsek; Cedric Bardy; Cathryn R Cadwell; Kristen Hadley; Dmitry Kobak; Shreejoy J Tripathy
Journal:  J Neurosci       Date:  2021-01-11       Impact factor: 6.167

3.  Multimodal profiling of single-cell morphology, electrophysiology, and gene expression using Patch-seq.

Authors:  Cathryn R Cadwell; Federico Scala; Shuang Li; Giulia Livrizzi; Shan Shen; Rickard Sandberg; Xiaolong Jiang; Andreas S Tolias
Journal:  Nat Protoc       Date:  2017-11-16       Impact factor: 13.491

Review 4.  Different Peas in the Same Pod: The Histaminergic Neuronal Heterogeneity.

Authors:  Gustavo Provensi; M Beatrice Passani; Patrizio Blandina
Journal:  Curr Top Behav Neurosci       Date:  2022

5.  VGLUT3 neurons in median raphe control the efficacy of spatial memory retrieval via ETV4 regulation of VGLUT3 transcription.

Authors:  Aodi He; Chen Zhang; Xiao Ke; Yao Yi; Quntao Yu; Tongmei Zhang; Hongyan Yu; Huiyun Du; Hao Li; Qing Tian; Ling-Qiang Zhu; Youming Lu
Journal:  Sci China Life Sci       Date:  2022-01-20       Impact factor: 10.372

6.  A RNA-Seq Analysis of the Rat Supraoptic Nucleus Transcriptome: Effects of Salt Loading on Gene Expression.

Authors:  Kory R Johnson; C C T Hindmarch; Yasmmyn D Salinas; YiJun Shi; Michael Greenwood; See Ziau Hoe; David Murphy; Harold Gainer
Journal:  PLoS One       Date:  2015-04-21       Impact factor: 3.240

7.  Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks.

Authors:  Marijn B Martens; Arthur R Houweling; Paul H E Tiesinga
Journal:  J Comput Neurosci       Date:  2016-11-04       Impact factor: 1.621

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

Authors:  Cathryn R Cadwell; Rickard Sandberg; Xiaolong Jiang; Andreas S Tolias
Journal:  BMC Biol       Date:  2017-07-06       Impact factor: 7.431

9.  Assessing Transcriptome Quality in Patch-Seq Datasets.

Authors:  Shreejoy J Tripathy; Lilah Toker; Claire Bomkamp; B Ogan Mancarci; Manuel Belmadani; Paul Pavlidis
Journal:  Front Mol Neurosci       Date:  2018-10-08       Impact factor: 5.639

10.  Homogeneity or heterogeneity, the paradox of neurovascular pericytes in the brain.

Authors:  Huimin Zhang; Xiao Zhang; Xiaoqi Hong; Xiaoping Tong
Journal:  Glia       Date:  2021-06-21       Impact factor: 7.452

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