Wildtype heterogeneity contributes to clonal variability in genome edited cells

• Published in: Scientific reports Vol. 12; no. 1; p. 18211
• Main Authors: Westermann, Lukas, Li, Yong, Göcmen, Burulca, Niedermoser, Matthias, Rhein, Kilian, Jahn, Johannes, Cascante, Isabel, Schöler, Felix, Moser, Niklas, Neubauer, Björn, Hofherr, Alexis, Behrens, Yvonne Lisa, Göhring, Gudrun, Köttgen, Anna, Köttgen, Michael, Busch, Tilman
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 28.10.2022; Nature Publishing Group; Nature Portfolio
• Subjects: 631/80; 692/4022; Cell Line; Cell lines; Cells, Cultured; Cloning; CRISPR; CRISPR-Cas Systems - genetics; Gene Editing - methods; Genetic variability; Genome editing; Genomes; Genotypes; Heterogeneity; Humanities and Social Sciences; multidisciplinary; Phenotypes; Reproducibility; Reproducibility of Results; Science; Science (multidisciplinary)
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-22885-8

Genome editing tools such as CRISPR/Cas9 enable the rapid and precise manipulation of genomes. CRISPR-based genome editing has greatly simplified the study of gene function in cell lines, but its widespread use has also highlighted challenges of reproducibility. Phenotypic variability among different knockout clones of the same gene is a common problem confounding the establishment of robust genotype–phenotype correlations. Optimized genome editing protocols to enhance reproducibility include measures to reduce off-target effects. However, even if current state-of-the-art protocols are applied phenotypic variability is frequently observed. Here we identify heterogeneity of wild-type cells as an important and often neglected confounding factor in genome-editing experiments. We demonstrate that isolation of individual wild-type clones from an apparently homogenous stable cell line uncovers significant phenotypic differences between clones. Strikingly, we observe hundreds of differentially regulated transcripts (477 up- and 306 downregulated) when comparing two populations of wild-type cells. Furthermore, we show a variety of cellular and biochemical alterations in different wild-type clones in a range that is commonly interpreted as biologically relevant in genome-edited cells. Heterogeneity of wild-type cells thus contributes to variability in genome-edited cells when these are generated through isolation of clones. We show that the generation of monoclonal isogenic wild-type cells prior to genomic manipulation reduces phenotypic variability. We therefore propose to generate matched isogenic control cells prior to genome editing to increase reproducibility.