five

Wild-type Heterogeneity Contributes to Clonal Variability in Genome-Edited Cells

收藏
NIAID Data Ecosystem2026-03-14 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE196762
下载链接
链接失效反馈
官方服务:
资源简介:
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 when comparing two populations of wild-type 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. Expression profiling of polyclonal vs. monoclonal mIMCD-3 wild-type cells and expression profiling of monoclonal vs. subclone mIMCD-3 cells. Data of polyclonal wild-type cells have been analyzed in a different context before (GSE179947).
创建时间:
2022-11-17
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作