Multiplex Single Cell Profiling of Chromatin Accessibility by Combinatorial Cellular Indexing

By D. Cusanovich, R. Daza, Andrew C. Adey, Hannah A. Pliner, Lena Christiansen, Kevin L. Gunderson, Frank Steemers, Cole Trapnell, Jay Shendure. Science, 2015

1,147 citations recorded by the source corpus.

Chromatin state and the single cell Identifying the chromatin state of any single cell, which may or may not have a different function or represent different stages relative to others collected within any single culture, experiment, or tissue, has been challenging. Cusanovitch et al. skirted previously identified technological limitations to identify regions of accessible chromatin at single-cell resolution. Combinatorial cellular indexing, a strategy for multiplex barcoding of thousands of single cells per experiment, was successfully used to investigate the genome-wide chromatin accessibility landscape in each of over 15,000 single cells. Science, this issue p. 910 Combinatorial indexing can identify chromatin states at single-cell resolution. Technical advances have enabled the collection of genome and transcriptome data sets with single-cell resolution. However, single-cell characterization of the epigenome has remained challenging. Furthermore, because cells must be physically separated before biochemical processing, conventional single-cell preparatory methods scale linearly. We applied combinatorial cellular indexing to measure chromatin accessibility in thousands of single cells per assay, circumventing the need for compartmentalization of individual cells. We report chromatin accessibility profiles from more than 15,000 single cells and use these data to cluster cells on the basis of chromatin accessibility landscapes. We identify modules of coordinately regulated chromatin accessibility at the level of single cells both between and within cell types, with a scalable method that may accelerate progress toward a human cell atlas.

Subfields: Biophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5fe8ed6e2c75a3b352be695f423cc2fac19446fa

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Citations in the corpus

Revealing the vectors of cellular identity with single-cell genomics (2016, methodology): “Challenges in single-cell epigenome analysis Although most high-throughput single-cell profiling studies to date have focused on RNA and protein, recent progress in epigenome analysis 192 has included assays for single-cell ChIP-seq (Drop-ChIP 26 ), single-cell ATAC-seq 27,28 , single-cell Hi-C 29 (”
Chromatin Potential Identified by Shared Single-Cell Profiling of RNA and Chromatin (2020, result): “, 2019), and compared with published datasets, including Cusanovich et al .(Cusanovich et al., 2015) (GSE67446), Pliner et al.”
A survey of best practices for RNA-seq data analysis (2016, methodology): “Other single-cell methods have been developed to measure single-cell DNA methylation [182] and single-cell open chromatin using ATAC-seq [183, 184].”