CoBATCH for High-Throughput Single-Cell Epigenomic Profiling
An efficient, generalizable method for genome-wide mapping of single-cell histone modifications or chromatin-binding proteins is lacking. Here, we develop CoBATCH, combinatorial barcoding and targeted chromatin release, for single-cell profiling of genomic distribution of chromatin-binding proteins...
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Veröffentlicht in: | Molecular cell 2019-10, Vol.76 (1), p.206-216.e7 |
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Zusammenfassung: | An efficient, generalizable method for genome-wide mapping of single-cell histone modifications or chromatin-binding proteins is lacking. Here, we develop CoBATCH, combinatorial barcoding and targeted chromatin release, for single-cell profiling of genomic distribution of chromatin-binding proteins in cell culture and tissue. Protein A in fusion to Tn5 transposase is enriched through specific antibodies to genomic regions, and Tn5 generates indexed chromatin fragments ready for library preparation and sequencing. Importantly, this strategy enables not only low-input epigenomic profiling in intact tissues but also measures scalable up to tens of thousands of single cells per experiment under both native and cross-linked conditions. CoBATCH produces ∼12,000 reads/cell with extremely low background. Mapping of endothelial cell lineages from ten embryonic mouse organs through CoBATCH allows for efficient deciphering of epigenetic heterogeneity of cell populations and cis-regulatory mechanisms. Thus, obviating specialized devices, CoBATCH is broadly applicable and easily deployable for single-cell profiling of protein-DNA interactions.
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•Development of an immunoprecipitation-free single-cell ChIP-seq technology•CoBATCH acquires ∼12,000 usable reads per cell with extremely low background•CoBATCH reveals multi-layer epigenetic heterogeneity during cell lineage diversification
Wang et al. developed a high-throughput, single-cell CoBATCH for profiling various histone modifications and DNA-binding proteins in both fixed and native conditions, uncovering epigenetic heterogeneity and inferring cell lineage diversification. |
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ISSN: | 1097-2765 1097-4164 |
DOI: | 10.1016/j.molcel.2019.07.015 |