Multiplex Single Cell Profiling of Chromatin Accessibility by Combinatorial Cellular Indexing
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ABSTRACT: 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 prior to 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 over 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. This SuperSeries is composed of the SubSeries listed below.
Project description: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 prior to 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 over 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. 3 replicates from GM12878 and HL-60 cell lines collected for differential gene expression analysis.
Project description: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 prior to 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 over 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.
Project description: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 prior to 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 over 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.
Project description:Single cell chromatin accessibility assays reveal epigenomic variability at cis-regulatory elements among individual cells. We previously developed a single-cell DNase-seq assay (scDNase-seq) to profile accessible chromatin in a limited number of single cells. Here, we report a novel indexing strategy to resolve single-cell DNase hypersensitivity profiles based on bulk cell analysis. This new technique, termed indexing single-cell DNase sequencing (iscDNase-seq), employs the activities of terminal DNA transferase (TdT) and T4 DNA ligase to add unique cell barcodes to DNase-digested chromatin ends. By a three-layer indexing strategy, it allows profiling genome-wide DHSs for more than 15,000 single-cells in a single experiment. Application of iscDNase-seq to human white blood cells accurately revealed specific cell types and inferred regulatory transcription factors (TF) specific to each cell type. We found that iscDNase-seq detected DHSs with specific properties related to gene expression and conservation missed by scATAC-seq for the same cell type. Also, we found that the cell-to-cell variation in accessibility computed using iscDNase-seq data is significantly correlated with the cell-to-cell variation in gene expression. Importantly, this correlation is significantly higher than that between scATAC-seq and scRNA-seq, suggesting that iscDNase-seq data can better predict the cellular heterogeneity in gene expression compared to scATAC-seq. Thus, iscDNase-seq is an attractive alternative method for single-cell epigenomics studies.