Highly scalable generation of DNA methylation profiles in single cells.
basic_science · Level V
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- Record sourced from PubMed, PMID 29644997.
- Also identified by DOI 10.1038/nbt.4112 and PMC identifier 5938134.
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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.
Medical subject headings
- DNA Methylation
- Sequence Alignment
- Single-Cell Analysis