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

Highly scalable generation of DNA methylation profiles in single cells.

Author information

1
Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, Oregon, USA.
2
Illumina, Inc., San Diego, California, USA.
3
Department of Molecular Microbiology & Immunology, Oregon Health & Science University, Portland, Oregon, USA.
4
Computational Biology Program, Oregon Health & Science University, Portland, Oregon, USA.
5
Vollum Institute, Oregon Health & Science University, Portland, Oregon, USA.
6
Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
7
Howard Hughes Medical Institute, Seattle, Washington, USA.
8
Knight Cardiovascular Institute, Portland, Oregon, USA.

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.

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