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Nat Biotechnol. 2019 Aug;37(8):916-924. doi: 10.1038/s41587-019-0147-6. Epub 2019 Jun 24.

Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility.

Author information

1
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
2
Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.
3
Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
4
Bio-Rad, Digital Biology Group, Pleasanton, CA, USA.
5
Illumina, San Diego, CA, USA.
6
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
7
Bio-Rad, Digital Biology Group, Pleasanton, CA, USA. ronald_lebofsky@bio-rad.com.
8
Broad Institute of MIT and Harvard, Cambridge, MA, USA. jason_buenrostro@harvard.edu.
9
Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA. jason_buenrostro@harvard.edu.

Abstract

Recent technical advancements have facilitated the mapping of epigenomes at single-cell resolution; however, the throughput and quality of these methods have limited their widespread adoption. Here we describe a high-quality (105 nuclear fragments per cell) droplet-microfluidics-based method for single-cell profiling of chromatin accessibility. We use this approach, named 'droplet single-cell assay for transposase-accessible chromatin using sequencing' (dscATAC-seq), to assay 46,653 cells for the unbiased discovery of cell types and regulatory elements in adult mouse brain. We further increase the throughput of this platform by combining it with combinatorial indexing (dsciATAC-seq), enabling single-cell studies at a massive scale. We demonstrate the utility of this approach by measuring chromatin accessibility across 136,463 resting and stimulated human bone marrow-derived cells to reveal changes in the cis- and trans-regulatory landscape across cell types and under stimulatory conditions at single-cell resolution. Altogether, we describe a total of 510,123 single-cell profiles, demonstrating the scalability and flexibility of this droplet-based platform.

PMID:
31235917
DOI:
10.1038/s41587-019-0147-6

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