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Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets
BACKGROUND: Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy—beyond those achievable with existing methods for mainly qualita...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201533/ https://www.ncbi.nlm.nih.gov/pubmed/32375897 http://dx.doi.org/10.1186/s13059-020-02006-2 |
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author | Marquina-Sanchez, Brenda Fortelny, Nikolaus Farlik, Matthias Vieira, Andhira Collombat, Patrick Bock, Christoph Kubicek, Stefan |
author_facet | Marquina-Sanchez, Brenda Fortelny, Nikolaus Farlik, Matthias Vieira, Andhira Collombat, Patrick Bock, Christoph Kubicek, Stefan |
author_sort | Marquina-Sanchez, Brenda |
collection | PubMed |
description | BACKGROUND: Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy—beyond those achievable with existing methods for mainly qualitative single-cell analysis. Here, we establish the use of standardized reference cells as spike-in controls for accurate and robust dissection of single-cell drug responses. RESULTS: We find that contamination by cell-free RNA can constitute up to 20% of reads in human primary tissue samples, and we show that the ensuing biases can be removed effectively using a novel bioinformatics algorithm. Applying our method to both human and mouse pancreatic islets treated ex vivo, we obtain an accurate and quantitative assessment of cell-specific drug effects on the transcriptome. We observe that FOXO inhibition induces dedifferentiation of both alpha and beta cells, while artemether treatment upregulates insulin and other beta cell marker genes in a subset of alpha cells. In beta cells, dedifferentiation and insulin repression upon artemether treatment occurs predominantly in mouse but not in human samples. CONCLUSIONS: This new method for quantitative, error-correcting, scRNA-seq data normalization using spike-in reference cells helps clarify complex cell-specific effects of pharmacological perturbations with single-cell resolution and high quantitative accuracy. |
format | Online Article Text |
id | pubmed-7201533 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72015332020-05-08 Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets Marquina-Sanchez, Brenda Fortelny, Nikolaus Farlik, Matthias Vieira, Andhira Collombat, Patrick Bock, Christoph Kubicek, Stefan Genome Biol Research BACKGROUND: Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy—beyond those achievable with existing methods for mainly qualitative single-cell analysis. Here, we establish the use of standardized reference cells as spike-in controls for accurate and robust dissection of single-cell drug responses. RESULTS: We find that contamination by cell-free RNA can constitute up to 20% of reads in human primary tissue samples, and we show that the ensuing biases can be removed effectively using a novel bioinformatics algorithm. Applying our method to both human and mouse pancreatic islets treated ex vivo, we obtain an accurate and quantitative assessment of cell-specific drug effects on the transcriptome. We observe that FOXO inhibition induces dedifferentiation of both alpha and beta cells, while artemether treatment upregulates insulin and other beta cell marker genes in a subset of alpha cells. In beta cells, dedifferentiation and insulin repression upon artemether treatment occurs predominantly in mouse but not in human samples. CONCLUSIONS: This new method for quantitative, error-correcting, scRNA-seq data normalization using spike-in reference cells helps clarify complex cell-specific effects of pharmacological perturbations with single-cell resolution and high quantitative accuracy. BioMed Central 2020-05-06 /pmc/articles/PMC7201533/ /pubmed/32375897 http://dx.doi.org/10.1186/s13059-020-02006-2 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Marquina-Sanchez, Brenda Fortelny, Nikolaus Farlik, Matthias Vieira, Andhira Collombat, Patrick Bock, Christoph Kubicek, Stefan Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets |
title | Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets |
title_full | Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets |
title_fullStr | Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets |
title_full_unstemmed | Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets |
title_short | Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets |
title_sort | single-cell rna-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201533/ https://www.ncbi.nlm.nih.gov/pubmed/32375897 http://dx.doi.org/10.1186/s13059-020-02006-2 |
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