Project description:Cell-to-cell variation is a universal feature of life that impacts a wide range of biological phenomena, from developmental plasticity to tumor heterogeneity. While recent advances have improved our ability to document cellular phenotypic variation the fundamental mechanisms that generate variability from identical DNA sequences remain elusive. Here we reveal the landscape and principles of cellular DNA regulatory variation by developing a robust method for mapping the accessible genome of individual cells via assay of transposase accessible chromatin sequencing (ATAC-seq). Single-cell ATAC-seq (scATAC-seq) maps from hundreds of single-cells in aggregate closely resemble accessibility profiles from tens of millions of cells and provides insights into cell-to-cell variation. Accessibility variance is systematically associated with specific trans-factors and cis-elements, and we discover combinations of trans-factors associated with either induction or suppression of cell-to-cell variability. We further identify sets of trans-factors associated with cell-type specific accessibility variance across 6 cell types. Targeted perturbations of cell cycle or transcription factor signaling evoke stimulus-specific changes in this observed variability. The pattern of accessibility variation in cis across the genome recapitulates chromosome topological domains de novo, linking single-cell accessibility variation to three-dimensional genome organization. All together, single-cell analysis of DNA accessibility provides new insight into cellular variation of the “regulome.” Profiles of single cell epigenomes, assayed using scATAC-seq, across 8 cell types and 4 targeted cell manipulations. The complete data set contains a total of 1,632 assayed wells.
Project description:Single cell sequencing technology has been widely used for understanding the heterogeneity of complex tissue and for identifying novel cell types or cell states. Previous efforts of single cell profiling are mostly performed by measuring transcriptomes using single cell RNA sequencing (scRNA-seq). scRNA-seq is relatively well developed and around 500 analysis tools are currently available for performing different tasks. In the past five years, assays for profiling the single cell chromatin accessibility landscape have emerged and provide extra information about gene regulation at the epigenetic level. Due to its simplicity and sensitivity, single cell Assays for Transposase-Accessible Chromatin using sequencing (scATAC-seq) is widely used to obtain chromatin accessibility. This data will be used to comprehensively evaluate scATAC-seq data analysis tools and gaps in analysis workflows together with publicly available bulk ATAC-Seq and scATAC-seq data using optimised universal evaluation metrics.
Project description:Single cell sequencing technology has been widely used for understanding the heterogeneity of complex tissue and for identifying novel cell types or cell states. Previous efforts of single cell profiling are mostly performed by measuring transcriptomes using single cell RNA sequencing (scRNA-seq). scRNA-seq is relatively well developed and around 500 analysis tools are currently available for performing different tasks. In the past five years, assays for profiling the single cell chromatin accessibility landscape have emerged and provide extra information about gene regulation at the epigenetic level. Due to its simplicity and sensitivity, single cell Assays for Transposase-Accessible Chromatin using sequencing (scATAC-seq) is widely used to obtain chromatin accessibility. This data will be used to comprehensively evaluate scATAC-seq data analysis tools and gaps in analysis workflows together with publicly available bulk ATAC-Seq and scATAC-seq data using optimised universal evaluation metrics. Furthermore, this data will be used to validate novel isoforms identified from long-read scRNA-Seq study.
Project description:Single cell sequencing technology has been widely used for understanding the heterogeneity of complex tissue and for identifying novel cell types or cell states. Previous efforts of single cell profiling are mostly performed by measuring transcriptomes using single cell RNA sequencing (scRNA-seq). scRNA-seq is relatively well developed and around 500 analysis tools are currently available for performing different tasks. In the past five years, assays for profiling the single cell chromatin accessibility landscape have emerged and provide extra information about gene regulation at the epigenetic level. Due to its simplicity and sensitivity, single cell Assays for Transposase-Accessible Chromatin using sequencing (scATAC-seq) is widely used to obtain chromatin accessibility. This data will be used to comprehensively evaluate scATAC-seq data analysis tools and gaps in analysis workflows together with publicly available bulk ATAC-Seq and scATAC-seq data using optimised universal evaluation metrics. Furthermore, this data will be used to validate novel isoforms identified from long-read scRNA-Seq study.
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.
Project description:We used single cell Assay for Transposase-Accessible Chromatin with high-throughput sequencing (scATAC-seq) to generate chromatin accessibility profiles of mouse splenic regulatory T cells from B6 mice.