Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility
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 (10 5 nuclear fragments per cell) droplet-microfluidics-based method for si...
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Published in: | Nature biotechnology Vol. 37; no. 8; pp. 916 - 924 |
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Main Authors: | , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
New York
Nature Publishing Group US
01-08-2019
Nature Publishing Group |
Subjects: | |
Online Access: | Get full text |
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Summary: | 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 (10
5
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.
Combining microfluidics with combinatorial indexing enables rapid mapping of genome accessibility in hundreds of thousands of single cells. |
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Bibliography: | F.M.D., J.G.C. and A.S.K. generated the data. C.A.L., V.K.K. and Z.D.B. analyzed the data. F.J.S. proposed the droplet scATAC-seq approach and oversaw the proof-of-concept studies performed by D.P.M.J.A. assisted in the development of computational resources. C.A.L., F.M.D. and J.D.B. wrote the manuscript with input from all authors. R.L. and J.D.B. jointly supervised this work. Author contributions |
ISSN: | 1087-0156 1546-1696 |
DOI: | 10.1038/s41587-019-0147-6 |