Abstract
Human induced pluripotent and embryonic stem cell cultures (hiPSC/hESC) are phenotypically heterogeneous and prone to clonal deviations during subculturing and differentiation. Clonal deviations often emerge unnoticed, but they can change the biology of the cell culture with a negative impact on experimental reproducibility. Here, we describe a computational workflow to profile the bulk clonal composition in a hiPSC/hESC culture that can also be used to infer clonal deviations. This workflow processes data obtained with two versions of the same method. The two versions-epigenetic and transcriptomic-rely on a mechanism of stochastic H3K4me3 deposition during hiPSC/hESC derivation. This mechanism generates a signature of ten or more H3K4me3-enriched clustered protocadherin (PCDH) promoters distinct in every single cell. The aggregate of single-cell signatures provides an identificatory feature in every hiPSC/hESC line. This feature is stably transmitted to the cell progeny of the culture even after differentiation unless there is a clonal deviation event that changes the internal balance of single-cell signatures. H3K4me3 signatures can be profiled by chromatin immunoprecipitation and next-generation sequencing (ChIP-seq). Alternatively, an equivalent PCDH-expression version can be profiled by RNA-seq in PCDH-expressing hiPSC/hESC-derived cells (such as neurons, astrocytes, and cardiomyocytes; and, in long-term cultures, such as cerebral organoids). Notably, our workflow can also distinguish genetically identical hiPSC/hESC lines derived from the same patient or generated in the same editing process. Together, we propose a method to improve data sharing and reproducibility in the hiPSC and hESC fields.
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