RegenerativeMedicine.net

Highly scalable generation of DNA methylation profiles in singles cells

Authors: Ryan M Mulqueen, Dmitry Pokholok, Steven J Norberg, Kristof A Torkenczy, Andrew J Fields, Duanchen Sun, John R Sinnamon, Jay Shendure, Cole Trapnell, Brian J O'Roak, Zheng Xia, Frank J Steemers, Andrew C Adey

Summary:

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.

Source: Nature Biotechnology, April 9, 2018