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Single-neuron RNA-Seq: technical feasibility and reproducibility

Understanding brain function involves improved knowledge about how the genome specifies such a large diversity of neuronal types. Transcriptome analysis of single neurons has been previously described using gene expression microarrays. Using high-throughput transcriptome sequencing (RNA-Seq), we hav...

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Autores principales: Qiu, Shenfeng, Luo, Shujun, Evgrafov, Oleg, Li, Robin, Schroth, Gary P., Levitt, Pat, Knowles, James A., Wang, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3407998/
https://www.ncbi.nlm.nih.gov/pubmed/22934102
http://dx.doi.org/10.3389/fgene.2012.00124
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author Qiu, Shenfeng
Luo, Shujun
Evgrafov, Oleg
Li, Robin
Schroth, Gary P.
Levitt, Pat
Knowles, James A.
Wang, Kai
author_facet Qiu, Shenfeng
Luo, Shujun
Evgrafov, Oleg
Li, Robin
Schroth, Gary P.
Levitt, Pat
Knowles, James A.
Wang, Kai
author_sort Qiu, Shenfeng
collection PubMed
description Understanding brain function involves improved knowledge about how the genome specifies such a large diversity of neuronal types. Transcriptome analysis of single neurons has been previously described using gene expression microarrays. Using high-throughput transcriptome sequencing (RNA-Seq), we have developed a method to perform single-neuron RNA-Seq. Following electrophysiology recording from an individual neuron, total RNA was extracted by aspirating the cellular contents into a fine glass electrode tip. The mRNAs were reverse transcribed and amplified to construct a single-neuron cDNA library, and subsequently subjected to high-throughput sequencing. This approach was applied to both individual neurons cultured from embryonic mouse hippocampus, as well as neocortical neurons from live brain slices. We found that the average pairwise Spearman’s rank correlation coefficient of gene expression level expressed as RPKM (reads per kilobase of transcript per million mapped reads) was 0.51 between five cultured neuronal cells, whereas the same measure between three cortical layer 5 neurons in situ was 0.25. The data suggest that there may be greater heterogeneity of the cortical neurons, as compared to neurons in vitro. The results demonstrate the technical feasibility and reproducibility of RNA-Seq in capturing a part of the transcriptome landscape of single neurons, and confirmed that morphologically identical neurons, even from the same region, have distinct gene expression patterns.
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spelling pubmed-34079982012-08-29 Single-neuron RNA-Seq: technical feasibility and reproducibility Qiu, Shenfeng Luo, Shujun Evgrafov, Oleg Li, Robin Schroth, Gary P. Levitt, Pat Knowles, James A. Wang, Kai Front Genet Genetics Understanding brain function involves improved knowledge about how the genome specifies such a large diversity of neuronal types. Transcriptome analysis of single neurons has been previously described using gene expression microarrays. Using high-throughput transcriptome sequencing (RNA-Seq), we have developed a method to perform single-neuron RNA-Seq. Following electrophysiology recording from an individual neuron, total RNA was extracted by aspirating the cellular contents into a fine glass electrode tip. The mRNAs were reverse transcribed and amplified to construct a single-neuron cDNA library, and subsequently subjected to high-throughput sequencing. This approach was applied to both individual neurons cultured from embryonic mouse hippocampus, as well as neocortical neurons from live brain slices. We found that the average pairwise Spearman’s rank correlation coefficient of gene expression level expressed as RPKM (reads per kilobase of transcript per million mapped reads) was 0.51 between five cultured neuronal cells, whereas the same measure between three cortical layer 5 neurons in situ was 0.25. The data suggest that there may be greater heterogeneity of the cortical neurons, as compared to neurons in vitro. The results demonstrate the technical feasibility and reproducibility of RNA-Seq in capturing a part of the transcriptome landscape of single neurons, and confirmed that morphologically identical neurons, even from the same region, have distinct gene expression patterns. Frontiers Research Foundation 2012-07-06 /pmc/articles/PMC3407998/ /pubmed/22934102 http://dx.doi.org/10.3389/fgene.2012.00124 Text en Copyright © Qiu, Luo, Evgrafov, Li, Schroth, Levitt, Knowles and Wang. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) , which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Genetics
Qiu, Shenfeng
Luo, Shujun
Evgrafov, Oleg
Li, Robin
Schroth, Gary P.
Levitt, Pat
Knowles, James A.
Wang, Kai
Single-neuron RNA-Seq: technical feasibility and reproducibility
title Single-neuron RNA-Seq: technical feasibility and reproducibility
title_full Single-neuron RNA-Seq: technical feasibility and reproducibility
title_fullStr Single-neuron RNA-Seq: technical feasibility and reproducibility
title_full_unstemmed Single-neuron RNA-Seq: technical feasibility and reproducibility
title_short Single-neuron RNA-Seq: technical feasibility and reproducibility
title_sort single-neuron rna-seq: technical feasibility and reproducibility
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3407998/
https://www.ncbi.nlm.nih.gov/pubmed/22934102
http://dx.doi.org/10.3389/fgene.2012.00124
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