Project description:Proper regulation of genome architecture and activity is essential for the development and function of multicellular organisms. Histone modifications, acting in combination, specify these activity states at individual genomic loci. However, the methods used to study these modifications often require either a large number of cells or are limited to targeting one histone mark at a time. Here, we developed a new method called Single Cell Evaluation of Post-TRanslational Epigenetic Encoding (SCEPTRE) that uses Expansion Microscopy (ExM) to visualize and quantify multiple histone modifications at non-repetitive genomic regions in single cells at a spatial resolution of ∼75 nm. Using SCEPTRE, we distinguished multiple histone modifications at a single housekeeping gene, quantified histone modification levels at multiple developmentally-regulated genes in individual cells, and evaluated the relationship between histone modifications and RNA polymerase II loading at individual loci. We find extensive variability in epigenetic states between individual gene loci hidden from current population-averaged measurements. These findings establish SCEPTRE as a new technique for multiplexed detection of combinatorial chromatin states at single genomic loci in single cells.
Project description:Regulation of chromatin states involves the dynamic interplay between different histone modifications to control gene expression. Recent advances have enabled mapping of histone marks in single cells, but most methods are constrained to profile only one histone mark per cell. Here we present an integrated experimental and computational framework, scChIX-seq (single-cell chromatin immunocleavage and unmixing), to map multiple histone marks in single cells. scChIX-seq multiplexes two histone marks together in single cells, then computationally deconvolves the signal using training data from respective histone mark profiles. This framework learns the cell type-specific correlation structure between histone marks, and therefore does not require a priori assumptions of their genomic distributions. Using scChIX-seq, we demonstrate multimodal analysis of histone marks in single cells across a range of mark combinations: two repressive marks, two active marks, and an active plus a repressive mark. In mouse gastrulation, we find that cell type-specific regulation in active chromatin can be accompanied by stable heterochromatin landscapes that are shared across cell types. Applying scChIX-seq to two active marks during macrophage differentiation, we find H3K4me1 dynamics preceding H3K36me3. Modeling these dynamics enables integrated analysis of chromatin velocity during differentiation. Overall, scChIX-seq unlocks systematic interrogation of the interplay between histone modifications in single cells.
Project description:Recently, multiple single cell assays were developed for detecting histone marks at the single cell levels. These techniques are either limited by the low cell throughput or sparse reads which limit their applications. To address these problems, we introduce indexing single-cell immunocleavage sequencing (iscChIC-seq), a multiplex indexing method based on TdT terminal transferase and T4 DNA ligase mediated barcoding strategy and single-cell ChIC-seq, which is capable of readily analyzing histone modifications across tens of thousands of single cells in one experiment. Application of iscChIC-seq to profiling H3K4me3 and H3K27me3 in human white blood cells (WBCs) enabled successful detection of more than 10,000 single cells for each histone modification with 11K and 45K non-redundant reads per cell, respectively. Cluster analysis of these data allowed identification of monocytes, T cells, B cells, and NK cells from WBCs. The cell types annotated from H3K4me3 single cell data are specifically correlated with the cell types annotated from H3K27me3 single cell data. Our data indicate that iscChIC-seq is a reliable technique for profiling histone modifications in a large number of single cells, which may find broad applications in studying cellular heterogeneity and differentiation status in complex developmental and disease systems.
Project description:Knowledge of the expression profile and spatial landscape of the transcriptome in individual cells is essential for understanding the rich repertoire of cellular behaviors. Here we report multiplexed error-robust fluorescence in situ hybridization (MERFISH), a single-molecule imaging approach that allows the copy numbers and spatial localizations of thousands of RNA species to be determined in single cells. Using error-robust encoding schemes to combat single-molecule labeling and detection errors, we demonstrated the imaging of 100 – 1000 unique RNA species in hundreds of individual cells. Correlation analysis of the ~10^4 – 10^6 pairs of genes allowed us to constrain gene regulatory networks, predict novel functions for many unannotated genes, and identify distinct spatial distribution patterns of RNAs that correlate with properties of the encoded proteins. A single sample is analyzed