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A probabilistic framework for cellular lineage reconstruction using integrated single-cell 5-hydroxymethylcytosine and genomic DNA sequencing

ABSTRACT: Lineage reconstruction is central to understanding tissue development and maintenance. While powerful tools to infer cellular relationships have been developed, these methods typically have a clonal resolution and require a transgene. Here, we report scPECLR, a probabilistic algorithm to endogenously infer lineage trees at a single cell-division resolution using 5-hydroxymethylcytosine (5hmC). When applied to 8-cell mouse embryos, scPECLR predicts the full lineage tree with greater than 95% accuracy, with the ability to infer larger lineage trees depending on the distribution of 5hmC patterns. Finally, we show that scPECLR can also be used to test the "immportal strand" hypothesis in stem cell biology. Thus, scPECLR provides a generalized method to endogenously reconstruct lineage trees at an individual cell-division resolution.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE131678 | GEO | 2021/07/08

REPOSITORIES: GEO

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