Dataset Information

Single-cell chromatin profiles reveal a spectrum of stem cell epigenetic states

ABSTRACT: Chromatin profiling provides a versatile means to chart gene regulatory elements and investigate their mechanisms of regulation. However, current methods yield ensemble profiles that are insensitive to cell-to-cell variation. This is a major limitation as transcriptional states and phenotypes vary markedly across individual cells. Here we combined microfluidics, DNA barcoding and sequencing to profile chromatin at single-cell resolution. We demonstrate the technology by profiling a mixture of ES cells, fibroblasts and hematopoietic progenitors, and deconvoluting in silico high-quality maps for each cell type. We find that regulatory elements differ in their variability, with bivalent promoters showing particularly heterogeneous patterns across single-cells that in contrast with to the relative stability of active promoters and enhancers. Finally, we document a spectrum of ES cell states whose chromatin landscapes exhibit varying degrees of pluripotency and priming signatures. Our study presents an innovative single-cell analysis tool for single-cell analysis, and reveals aspects of epigenetic heterogeneity not be captured by transcriptional analysis alone.

ORGANISM(S): Mus musculus

PROVIDER: GSE70253 | GEO | 2015/10/12

SECONDARY ACCESSION(S): PRJNA288086

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Chromatin profiling has emerged as a powerful means for annotating genomic elements and detecting regulatory activity. Here we generate and analyze a compendium of epigenomic maps for nine chromatin marks across nine cell types, in order to systematically characterize cis-regulatory elements, their cell type-specificities, and their functional interactions. We first identify recurrent combinations of histone modifications and use them to annotate diverse regulatory elements including promoters, enhancers, transcripts and insulators in each cell type. We next characterize the dynamics of these elements, revealing meaningful patterns of activity for promoter states and exquisite cell type-selectivity for enhancer states. We define multi-cell activity profiles that reflect the patterns of enhancer state activity across cell types, as well as analogous profiles for gene expression, regulatory motif enrichments, and expression of the corresponding regulators. We use correlations between these profiles to link enhancers to putative target genes, to infer cell type-specific activators and repressors, and to predict and validate functional regulator binding motifs in specific chromatin states. These functional annotations and regulatory predictions enable us to revisit intergenic single-nucleotide polymorphisms (SNPs) associated with human disease in genome-wide association studies (GWAS). We find that for several diseases, top-scoring SNPs are precisely positioned within enhancer elements specifically active in relevant cell types. In several cases a disease variant affects a motif instance for one of the predicted causal regulators, thus providing a potential mechanistic explanation for the disease association. Our study presents a general framework for applying multi-cell chromatin state analysis to decipher cis-regulatory connections and their role in health and disease. 9 human cell types were cultured in duplicate and subject to Affymetrix profiling

Dataset Information

Single-cell chromatin profiles reveal a spectrum of stem cell epigenetic states

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets