Single-cell DNA methylome sequencing and bioinformatic inference of epigenetic cell state dynamics

ABSTRACT: Here we describe a method for whole genome bisulfite sequencing in very small cell populations (µWGBS) and in single cells (scWGBS). Our method is optimized for profiling DNA methylation in many samples at low coverage, and we developed a bioinformatic method that uses collections of single-cell methylomes to infer cell state dynamics. Using these technological advances, we studied epigenetic cell state dynamics in three in vitro models of cellular differentiation and pluripotency and identified patterns of epigenetic remodeling and cell-to-cell heterogeneity. 1-cell or 4-cell samples were collected from a variety of human and mouse cell lines (KBM7, CCE, K562, 32D, HL60). We also included negative controls (no cells), and cross controls (cells of one species aligned to the other). K562 ce

ORGANISM(S): Mus musculus

SUBMITTER: Christoph Bock 

PROVIDER: E-GEOD-65196 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress