Highly scalable generation of DNA methylation profiles in single cells

Nat Biotechnol. 2018 Jun;36(5):428-431. doi: 10.1038/nbt.4112. Epub 2018 Apr 9.

Abstract

We present a highly scalable assay for whole-genome methylation profiling of single cells. We use our approach, single-cell combinatorial indexing for methylation analysis (sci-MET), to produce 3,282 single-cell bisulfite sequencing libraries and achieve read alignment rates of 68 ± 8%. We apply sci-MET to discriminate the cellular identity of a mixture of three human cell lines and to identify excitatory and inhibitory neuronal populations from mouse cortical tissue.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • DNA Methylation / genetics*
  • Humans
  • Mice
  • Sequence Alignment / methods*
  • Sequence Analysis, DNA / methods
  • Single-Cell Analysis / methods*