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Highly scalable generation of DNA methylation profiles in single cells

ABSTRACT: We present a novel method: single-cell combinatorial indexing for methylation analysis (sci-MET), which is the first highly scalable assay for whole genome methylation profiling of single cells. We use sci-MET to produce 3,282 total single-cell bisulfite sequencing libraries and achieve read alignment rates of 68± 8%, comparable to those of bulk cell methods. As a proof of concept, we applied sci-MET to deconvolve the cellular identity of a mixture of three human cell lines. Next, we applied sci-MET to mouse cortical tissue, which successfully identified excitatory and inhibitory neuronal populations as well as non-neuronal cell types.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE112554 | GEO | 2018/04/12

REPOSITORIES: GEO

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