Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state

Abstract

Chromatin profiling provides a versatile means to investigate functional genomic elements and their regulation. However, current methods yield ensemble profiles that are insensitive to cell-to-cell variation. Here we combine microfluidics, DNA barcoding and sequencing to collect chromatin data at single-cell resolution. We demonstrate the utility of the technology by assaying thousands of individual cells, and using the data to deconvolute a mixture of ES cells, fibroblasts and hematopoietic progenitors into high-quality chromatin state maps for each cell type. The data from each single cell is sparse, comprising on the order of 1000 unique reads. However, by assaying thousands of ES cells, we identify a spectrum of sub-populations defined by differences in chromatin signatures of pluripotency and differentiation priming. We corroborate these findings by comparison to orthogonal single-cell gene expression data. Our method for single-cell analysis reveals aspects of epigenetic heterogeneity not captured by transcriptional analysis alone.

Epigenetic Transitions and Knotted Solitons in Stretched Chromatin

“…In principle, one may even be able to observe the transition from one to the other by increasing the stretching force in the single molecule assay. Another possibility to assess the degree of epigenetic order is to use single-cell chromatin immunoprecipitation [71] (ChIP) on the reconstituted chromatin, to quantify histone modifications along the fibres. Note that, for this approach to be viable, one would have to use genomic DNA to reconstitute chromatin (rather than repeating, such as 601, sequences), so that locations along the DNA can be mapped uniquely.…”

Manifold alignment reveals correspondence between single cell transcriptome and epigenome dynamics

“…Several high-throughput single cell versions of epigenetic assays have been developed, including single cell bisulfite sequencing (DNA methylation) [14], ATAC-seq (chromatin accessibility) [13], and ChIP-seq (histone modification) [12]. Each of the initial studies that pioneered these methods applied them to mouse embryonic stem cells (mESCs) grown in serum, a classic model system of stem cell biology.…”

“…In total, we have four kinds of single cell data from a total of 4,974 cells: 250 cells with gene expression data [37], 61 with DNA methylation [14], 76 with chromatin accessibility [13], and 4,587 with H3K4me2 ChIP [12]. The DNA methylation data were collected using the scM&T-seq protocol, which measures gene expression and DNA methylation simultaneously in a single cell [14].…”

“…We obtained the processed data from Rotem et al [12], which consists of H3K4me2 ChIP-seq reads from 4587 cells, aggregated using 91 chromatin signatures. We found that these data required further…”

“…In such experiments, each sequenced cell is assumed to be at one point in the process, and sequencing enough cells can reveal the progression of gene expression changes that occur during the process [8,9]. More recently, several experimental techniques for performing single cell epigenetic have been developed [10][11][12][13][14][15][16][17], and initial analyses have demonstrated that single cell epigenetic data can be used to elucidate the series of changes in a sequential process [16,18,19].…”