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Computational identification of clonal cells in single-cell CRISPR screens

BACKGROUND: Single-cell CRISPR screens are powerful tools to understand genome function by linking genetic perturbations to transcriptome-wide phenotypes. However, since few cells can be affordably sequenced in these screens, biased sampling of cells could affect data interpretation. One potential s...

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Autores principales: Wang, Yihan, Xie, Shiqi, Armendariz, Daniel, Hon, Gary C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845350/
https://www.ncbi.nlm.nih.gov/pubmed/35168568
http://dx.doi.org/10.1186/s12864-022-08359-1
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author Wang, Yihan
Xie, Shiqi
Armendariz, Daniel
Hon, Gary C.
author_facet Wang, Yihan
Xie, Shiqi
Armendariz, Daniel
Hon, Gary C.
author_sort Wang, Yihan
collection PubMed
description BACKGROUND: Single-cell CRISPR screens are powerful tools to understand genome function by linking genetic perturbations to transcriptome-wide phenotypes. However, since few cells can be affordably sequenced in these screens, biased sampling of cells could affect data interpretation. One potential source of biased sampling is clonal cell expansion. RESULTS: Here, we identify clonal cells in single cell screens using multiplexed sgRNAs as barcodes. We find that the cells in each clone share transcriptional similarities and bear segmental copy number changes. These analyses suggest that clones are genetically distinct. Finally, we show that the transcriptional similarities of clonally expanded cells contribute to false positives in single-cell CRISPR screens. CONCLUSIONS: Experimental conditions that reduce clonal expansion or computational filtering of clonal cells will improve the reliability of single-cell CRISPR screens. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08359-1.
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spelling pubmed-88453502022-02-16 Computational identification of clonal cells in single-cell CRISPR screens Wang, Yihan Xie, Shiqi Armendariz, Daniel Hon, Gary C. BMC Genomics Research Article BACKGROUND: Single-cell CRISPR screens are powerful tools to understand genome function by linking genetic perturbations to transcriptome-wide phenotypes. However, since few cells can be affordably sequenced in these screens, biased sampling of cells could affect data interpretation. One potential source of biased sampling is clonal cell expansion. RESULTS: Here, we identify clonal cells in single cell screens using multiplexed sgRNAs as barcodes. We find that the cells in each clone share transcriptional similarities and bear segmental copy number changes. These analyses suggest that clones are genetically distinct. Finally, we show that the transcriptional similarities of clonally expanded cells contribute to false positives in single-cell CRISPR screens. CONCLUSIONS: Experimental conditions that reduce clonal expansion or computational filtering of clonal cells will improve the reliability of single-cell CRISPR screens. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08359-1. BioMed Central 2022-02-15 /pmc/articles/PMC8845350/ /pubmed/35168568 http://dx.doi.org/10.1186/s12864-022-08359-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Article
Wang, Yihan
Xie, Shiqi
Armendariz, Daniel
Hon, Gary C.
Computational identification of clonal cells in single-cell CRISPR screens
title Computational identification of clonal cells in single-cell CRISPR screens
title_full Computational identification of clonal cells in single-cell CRISPR screens
title_fullStr Computational identification of clonal cells in single-cell CRISPR screens
title_full_unstemmed Computational identification of clonal cells in single-cell CRISPR screens
title_short Computational identification of clonal cells in single-cell CRISPR screens
title_sort computational identification of clonal cells in single-cell crispr screens
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845350/
https://www.ncbi.nlm.nih.gov/pubmed/35168568
http://dx.doi.org/10.1186/s12864-022-08359-1
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