Cell Reports
Volume 10, Issue 8, 3 March 2015, Pages 1386-1397
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Single-Cell DNA Methylome Sequencing and Bioinformatic Inference of Epigenomic Cell-State Dynamics

https://doi.org/10.1016/j.celrep.2015.02.001Get rights and content
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Highlights

  • High-throughput bisulfite sequencing assay for low-input and single-cell samples

  • Single-cell methylomes for in vitro models (K562 AzaC, HL60 VitD, and mES 2i/ATRA/EB)

  • Bioinformatic method for inferring cell-state dynamics from sparse methylome data

  • Identification of genomic region types with consistent changes among single cells

Summary

Methods for single-cell genome and transcriptome sequencing have contributed to our understanding of cellular heterogeneity, whereas methods for single-cell epigenomics are much less established. Here, we describe a whole-genome bisulfite sequencing (WGBS) assay that enables DNA methylation mapping in very small cell populations (μWGBS) and single cells (scWGBS). Our assay is optimized for profiling many samples at low coverage, and we describe a bioinformatic method that analyzes collections of single-cell methylomes to infer cell-state dynamics. Using these technological advances, we studied epigenomic cell-state dynamics in three in vitro models of cellular differentiation and pluripotency, where we observed characteristic patterns of epigenome remodeling and cell-to-cell heterogeneity. The described method enables single-cell analysis of DNA methylation in a broad range of biological systems, including embryonic development, stem cell differentiation, and cancer. It can also be used to establish composite methylomes that account for cell-to-cell heterogeneity in complex tissue samples.

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This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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Co-first author