Scalable and efficient single-cell DNA methylation sequencing by combinatorial indexing.. Homo sapiens and Mus musculus Cell Lines and Primary Tissue

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.