Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1784651657342091264 |
---|---|
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. |
format | Online Article Text |
id | pubmed-8845350 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT wangyihan computationalidentificationofclonalcellsinsinglecellcrisprscreens AT xieshiqi computationalidentificationofclonalcellsinsinglecellcrisprscreens AT armendarizdaniel computationalidentificationofclonalcellsinsinglecellcrisprscreens AT hongaryc computationalidentificationofclonalcellsinsinglecellcrisprscreens |