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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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Detalles Bibliográficos
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
Descripción
Sumario: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.