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Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations
Multipotent neural stem cells (NSCs) are found in several isolated niches of the adult mammalian brain where they have unique potential to assist in tissue repair. Modern transcriptomics offer high-throughput methods for identifying disease or injury associated gene expression signatures in endogeno...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842474/ https://www.ncbi.nlm.nih.gov/pubmed/35173579 http://dx.doi.org/10.3389/fnmol.2022.810722 |
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author | Denninger, Jiyeon K. Walker, Logan A. Chen, Xi Turkoglu, Altan Pan, Alex Tapp, Zoe Senthilvelan, Sakthi Rindani, Raina Kokiko-Cochran, Olga N. Bundschuh, Ralf Yan, Pearlly Kirby, Elizabeth D. |
author_facet | Denninger, Jiyeon K. Walker, Logan A. Chen, Xi Turkoglu, Altan Pan, Alex Tapp, Zoe Senthilvelan, Sakthi Rindani, Raina Kokiko-Cochran, Olga N. Bundschuh, Ralf Yan, Pearlly Kirby, Elizabeth D. |
author_sort | Denninger, Jiyeon K. |
collection | PubMed |
description | Multipotent neural stem cells (NSCs) are found in several isolated niches of the adult mammalian brain where they have unique potential to assist in tissue repair. Modern transcriptomics offer high-throughput methods for identifying disease or injury associated gene expression signatures in endogenous adult NSCs, but they require adaptation to accommodate the rarity of NSCs. Bulk RNA sequencing (RNAseq) of NSCs requires pooling several mice, which impedes application to labor-intensive injury models. Alternatively, single cell RNAseq can profile hundreds to thousands of cells from a single mouse and is increasingly used to study NSCs. The consequences of the low RNA input from a single NSC on downstream identification of differentially expressed genes (DEGs) remains insufficiently explored. Here, to clarify the role that low RNA input plays in NSC DEG identification, we directly compared DEGs in an oxidative stress model of cultured NSCs by bulk and single cell sequencing. While both methods yielded DEGs that were replicable, single cell sequencing using the 10X Chromium platform yielded DEGs derived from genes with higher relative transcript counts compared to non-DEGs and exhibited smaller fold changes than DEGs identified by bulk RNAseq. The loss of high fold-change DEGs in the single cell platform presents an important limitation for identifying disease-relevant genes. To facilitate identification of such genes, we determined an RNA-input threshold that enables transcriptional profiling of NSCs comparable to standard bulk sequencing and used it to establish a workflow for in vivo profiling of endogenous NSCs. We then applied this workflow to identify DEGs after lateral fluid percussion injury, a labor-intensive animal model of traumatic brain injury. Our work joins an emerging body of evidence suggesting that single cell RNA sequencing may underestimate the diversity of pathologic DEGs. However, our data also suggest that population level transcriptomic analysis can be adapted to capture more of these DEGs with similar efficacy and diversity as standard bulk sequencing. Together, our data and workflow will be useful for investigators interested in understanding and manipulating adult hippocampal NSC responses to various stimuli. |
format | Online Article Text |
id | pubmed-8842474 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88424742022-02-15 Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations Denninger, Jiyeon K. Walker, Logan A. Chen, Xi Turkoglu, Altan Pan, Alex Tapp, Zoe Senthilvelan, Sakthi Rindani, Raina Kokiko-Cochran, Olga N. Bundschuh, Ralf Yan, Pearlly Kirby, Elizabeth D. Front Mol Neurosci Neuroscience Multipotent neural stem cells (NSCs) are found in several isolated niches of the adult mammalian brain where they have unique potential to assist in tissue repair. Modern transcriptomics offer high-throughput methods for identifying disease or injury associated gene expression signatures in endogenous adult NSCs, but they require adaptation to accommodate the rarity of NSCs. Bulk RNA sequencing (RNAseq) of NSCs requires pooling several mice, which impedes application to labor-intensive injury models. Alternatively, single cell RNAseq can profile hundreds to thousands of cells from a single mouse and is increasingly used to study NSCs. The consequences of the low RNA input from a single NSC on downstream identification of differentially expressed genes (DEGs) remains insufficiently explored. Here, to clarify the role that low RNA input plays in NSC DEG identification, we directly compared DEGs in an oxidative stress model of cultured NSCs by bulk and single cell sequencing. While both methods yielded DEGs that were replicable, single cell sequencing using the 10X Chromium platform yielded DEGs derived from genes with higher relative transcript counts compared to non-DEGs and exhibited smaller fold changes than DEGs identified by bulk RNAseq. The loss of high fold-change DEGs in the single cell platform presents an important limitation for identifying disease-relevant genes. To facilitate identification of such genes, we determined an RNA-input threshold that enables transcriptional profiling of NSCs comparable to standard bulk sequencing and used it to establish a workflow for in vivo profiling of endogenous NSCs. We then applied this workflow to identify DEGs after lateral fluid percussion injury, a labor-intensive animal model of traumatic brain injury. Our work joins an emerging body of evidence suggesting that single cell RNA sequencing may underestimate the diversity of pathologic DEGs. However, our data also suggest that population level transcriptomic analysis can be adapted to capture more of these DEGs with similar efficacy and diversity as standard bulk sequencing. Together, our data and workflow will be useful for investigators interested in understanding and manipulating adult hippocampal NSC responses to various stimuli. Frontiers Media S.A. 2022-01-31 /pmc/articles/PMC8842474/ /pubmed/35173579 http://dx.doi.org/10.3389/fnmol.2022.810722 Text en Copyright © 2022 Denninger, Walker, Chen, Turkoglu, Pan, Tapp, Senthilvelan, Rindani, Kokiko-Cochran, Bundschuh, Yan and Kirby. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Denninger, Jiyeon K. Walker, Logan A. Chen, Xi Turkoglu, Altan Pan, Alex Tapp, Zoe Senthilvelan, Sakthi Rindani, Raina Kokiko-Cochran, Olga N. Bundschuh, Ralf Yan, Pearlly Kirby, Elizabeth D. Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations |
title | Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations |
title_full | Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations |
title_fullStr | Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations |
title_full_unstemmed | Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations |
title_short | Robust Transcriptional Profiling and Identification of Differentially Expressed Genes With Low Input RNA Sequencing of Adult Hippocampal Neural Stem and Progenitor Populations |
title_sort | robust transcriptional profiling and identification of differentially expressed genes with low input rna sequencing of adult hippocampal neural stem and progenitor populations |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8842474/ https://www.ncbi.nlm.nih.gov/pubmed/35173579 http://dx.doi.org/10.3389/fnmol.2022.810722 |
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