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Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations

Single-cell transcriptomics are powerful tools to define neuronal cell types based on co-expressed gene clusters. Limited RNA input in these technologies necessarily compromises transcriptome coverage and accuracy of differential expression analysis. We propose that bulk RNA-Seq of neuronal pools de...

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Autores principales: Rumpler, Éva, Göcz, Balázs, Skrapits, Katalin, Sárvári, Miklós, Takács, Szabolcs, Farkas, Imre, Póliska, Szilárd, Papp, Márton, Solymosi, Norbert, Hrabovszky, Erik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Biochemistry and Molecular Biology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10477691/
https://www.ncbi.nlm.nih.gov/pubmed/37536628
http://dx.doi.org/10.1016/j.jbc.2023.105121
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author Rumpler, Éva
Göcz, Balázs
Skrapits, Katalin
Sárvári, Miklós
Takács, Szabolcs
Farkas, Imre
Póliska, Szilárd
Papp, Márton
Solymosi, Norbert
Hrabovszky, Erik
author_facet Rumpler, Éva
Göcz, Balázs
Skrapits, Katalin
Sárvári, Miklós
Takács, Szabolcs
Farkas, Imre
Póliska, Szilárd
Papp, Márton
Solymosi, Norbert
Hrabovszky, Erik
author_sort Rumpler, Éva
collection PubMed
description Single-cell transcriptomics are powerful tools to define neuronal cell types based on co-expressed gene clusters. Limited RNA input in these technologies necessarily compromises transcriptome coverage and accuracy of differential expression analysis. We propose that bulk RNA-Seq of neuronal pools defined by spatial position offers an alternative strategy to overcome these technical limitations. We report a laser-capture microdissection (LCM)-Seq method which allows deep transcriptome profiling of fluorescently tagged neuron populations isolated with LCM from histological sections of transgenic mice. Mild formaldehyde fixation of ZsGreen marker protein, LCM sampling of ∼300 pooled neurons, followed by RNA isolation, library preparation and RNA-Seq with methods optimized for nanogram amounts of moderately degraded RNA enabled us to detect ∼15,000 different transcripts in fluorescently labeled cholinergic neuron populations. The LCM-Seq approach showed excellent accuracy in quantitative studies, allowing us to detect 2891 transcripts expressed differentially between the spatially defined and clinically relevant cholinergic neuron populations of the dorsal caudate-putamen and medial septum. In summary, the LCM-Seq method we report in this study is a versatile, sensitive, and accurate bulk sequencing approach to study the transcriptome profile and differential gene expression of fluorescently tagged neuronal populations isolated from transgenic mice with high spatial precision.
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spelling pubmed-104776912023-09-06 Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations Rumpler, Éva Göcz, Balázs Skrapits, Katalin Sárvári, Miklós Takács, Szabolcs Farkas, Imre Póliska, Szilárd Papp, Márton Solymosi, Norbert Hrabovszky, Erik J Biol Chem Methods and Resources Single-cell transcriptomics are powerful tools to define neuronal cell types based on co-expressed gene clusters. Limited RNA input in these technologies necessarily compromises transcriptome coverage and accuracy of differential expression analysis. We propose that bulk RNA-Seq of neuronal pools defined by spatial position offers an alternative strategy to overcome these technical limitations. We report a laser-capture microdissection (LCM)-Seq method which allows deep transcriptome profiling of fluorescently tagged neuron populations isolated with LCM from histological sections of transgenic mice. Mild formaldehyde fixation of ZsGreen marker protein, LCM sampling of ∼300 pooled neurons, followed by RNA isolation, library preparation and RNA-Seq with methods optimized for nanogram amounts of moderately degraded RNA enabled us to detect ∼15,000 different transcripts in fluorescently labeled cholinergic neuron populations. The LCM-Seq approach showed excellent accuracy in quantitative studies, allowing us to detect 2891 transcripts expressed differentially between the spatially defined and clinically relevant cholinergic neuron populations of the dorsal caudate-putamen and medial septum. In summary, the LCM-Seq method we report in this study is a versatile, sensitive, and accurate bulk sequencing approach to study the transcriptome profile and differential gene expression of fluorescently tagged neuronal populations isolated from transgenic mice with high spatial precision. American Society for Biochemistry and Molecular Biology 2023-08-01 /pmc/articles/PMC10477691/ /pubmed/37536628 http://dx.doi.org/10.1016/j.jbc.2023.105121 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Methods and Resources
Rumpler, Éva
Göcz, Balázs
Skrapits, Katalin
Sárvári, Miklós
Takács, Szabolcs
Farkas, Imre
Póliska, Szilárd
Papp, Márton
Solymosi, Norbert
Hrabovszky, Erik
Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations
title Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations
title_full Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations
title_fullStr Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations
title_full_unstemmed Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations
title_short Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations
title_sort development of a versatile lcm-seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations
topic Methods and Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10477691/
https://www.ncbi.nlm.nih.gov/pubmed/37536628
http://dx.doi.org/10.1016/j.jbc.2023.105121
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