ScHiCAR: a tri-modal single-cell genomics technology for integrated transcriptome, epigenome, and 3D genome analysis in complex tissues [cellline_scHiCAR]
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE267117 | GEO | 2025/08/30
REPOSITORIES: GEO
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Project description:The three-dimensional (3D) organization of cis-regulatory elements (CREs) plays a central role in transcription control. However, capturing transcriptome, epigenome, and 3D genome from the same single cells remains technically challenging. Here, we present scHiCAR (single-cell Hi-C with ATAC and RNA-seq), a combinatorial barcoding-based method that simultaneously profiles mRNA, open chromatin, and chromosome-conformation-capture from the same cells. Compared to existing single-cell 3D genome methods, scHiCAR more efficiently enriches long-range cis-interactions anchored at candidate CREs (cCREs). Applied to 1.62 million mouse brain cells and complemented with a deep learning-based loop caller, scHiCAR accurately defines cell-type-specific transcriptomes, accessible cCREs, and 5kb-resolution enhancer-promoter pairs across 22 brain cell types. scHiCAR also performs robustly in challenging tissues such as skeletal muscle, enabling tri-modal single-cell level analysis of gene regulation dynamics during muscle stem cell regeneration. scHiCAR offers a scalable, efficient, and cost-effective platform for studying gene regulatory landscapes in complex tissues at single-cell resolution.
2025-08-30 | GSE267126 | GEO
Project description:The three-dimensional (3D) organization of cis-regulatory elements (CREs) plays a central role in transcription control. However, capturing transcriptome, epigenome, and 3D genome from the same single cells remains technically challenging. Here, we present scHiCAR (single-cell Hi-C with ATAC and RNA-seq), a combinatorial barcoding-based method that simultaneously profiles mRNA, open chromatin, and chromosome-conformation-capture from the same cells. Compared to existing single-cell 3D genome methods, scHiCAR more efficiently enriches long-range cis-interactions anchored at candidate CREs (cCREs). Applied to 1.62 million mouse brain cells and complemented with a deep learning-based loop caller, scHiCAR accurately defines cell-type-specific transcriptomes, accessible cCREs, and 5kb-resolution enhancer-promoter pairs across 22 brain cell types. scHiCAR also performs robustly in challenging tissues such as skeletal muscle, enabling tri-modal single-cell level analysis of gene regulation dynamics during muscle stem cell regeneration. scHiCAR offers a scalable, efficient, and cost-effective platform for studying gene regulatory landscapes in complex tissues at single-cell resolution.
2025-08-30 | GSE267118 | GEO
Project description:The three-dimensional (3D) organization of cis-regulatory elements (CREs) plays a central role in transcription control. However, capturing transcriptome, epigenome, and 3D genome from the same single cells remains technically challenging. Here, we present scHiCAR (single-cell Hi-C with ATAC and RNA-seq), a combinatorial barcoding-based method that simultaneously profiles mRNA, open chromatin, and chromosome-conformation-capture from the same cells. Compared to existing single-cell 3D genome methods, scHiCAR more efficiently enriches long-range cis-interactions anchored at candidate CREs (cCREs). Applied to 1.62 million mouse brain cells and complemented with a deep learning-based loop caller, scHiCAR accurately defines cell-type-specific transcriptomes, accessible cCREs, and 5kb-resolution enhancer-promoter pairs across 22 brain cell types. scHiCAR also performs robustly in challenging tissues such as skeletal muscle, enabling tri-modal single-cell level analysis of gene regulation dynamics during muscle stem cell regeneration. scHiCAR offers a scalable, efficient, and cost-effective platform for studying gene regulatory landscapes in complex tissues at single-cell resolution.
2025-08-30 | GSE305439 | GEO
Project description:The three-dimensional (3D) organization of cis-regulatory elements (CREs) plays a central role in transcription control. However, capturing transcriptome, epigenome, and 3D genome from the same single cells remains technically challenging. Here, we present scHiCAR (single-cell Hi-C with ATAC and RNA-seq), a combinatorial barcoding-based method that simultaneously profiles mRNA, open chromatin, and chromosome-conformation-capture from the same cells. Compared to existing single-cell 3D genome methods, scHiCAR more efficiently enriches long-range cis-interactions anchored at candidate CREs (cCREs). Applied to 1.62 million mouse brain cells and complemented with a deep learning-based loop caller, scHiCAR accurately defines cell-type-specific transcriptomes, accessible cCREs, and 5kb-resolution enhancer-promoter pairs across 22 brain cell types. scHiCAR also performs robustly in challenging tissues such as skeletal muscle, enabling tri-modal single-cell level analysis of gene regulation dynamics during muscle stem cell regeneration. scHiCAR offers a scalable, efficient, and cost-effective platform for studying gene regulatory landscapes in complex tissues at single-cell resolution.
2025-08-30 | GSE304674 | GEO
Project description:Background: Cis-regulatory elements (CREs) control oncogene expression and malignant phenotypes. The high clinicopathological heterogeneity of cancer cannot be explained by gene expression alone, being attributed to CRE heterogeneity. However, characterizing cancer-associated CRE is challenging. To address this issue, we performed a single-cell epigenomic analysis of clinical specimens. Methods: To map the multicellular ecosystem of BC and identify candidate CREs (cCREs), we performed a single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq) of 38 prospectively collected breast cancer (BC) samples with various clinicopathological characteristics. Results: First, we performed single-cell chromatin accessibility profiling of a high-quality set of 22,775 cells from BC samples. Cells were accurately annotated using marker gene accessibility and integration with existing single-cell RNA sequencing data. By predicting copy number variants, epithelial cells were classified into non-malignant and malignant cells. The chromatin accessibility patterns exhibited by malignant cells were consistent with the clinicopathological features of each tumor. We identified 224,585 cCREs across the BC ecosystem. By identifying cluster-specific differentially accessible cCREs (DA-cCREs) and constructing a putative enhancer-promoter network, we mapped the cis-regulatory landscape for cancer cells and the tumor microenvironment. In this dataset, we identified changes in the cis-regulatory landscape associated with cancer progression. In particular, estrogen receptor (ER)-positive tumors have increased accessibility of ER binding motifs during the cell transition from non-cancerous to cancerous and increased accessibility of Kruppel like factor motifs during the transition from cancerous to metastatic. Furthermore, the accessibility of putative enhancers targeting the same gene differed within or between tumors, highlighting intra- and inter-cis-regulatory tumor heterogeneity. Conclusions: This study provides a valuable resource for future epigenetic research on BC and highlights the diverse regulatory landscape within or among tumor(s), suggesting that cCREs regulate tumor progression and intra- and inter-tumor heterogeneity.
2025-06-25 | GSE299408 | GEO
Project description:Cis-regulatory elements (CREs) are essential in precisely regulating gene expression, contributing significantly to the evolution of species. Identifying cell-type-specific CREs is essential for understanding plant evolution, domestication, and improving crops through genome editing. Here, we built a cis-regulatory atlas in Oryza sativa, encompassing 106,143 nuclei representing 138 discrete cell states from nine distinct organs. Within syntenic regions shared with four other grass species (Zea mays, Sorghum bicolor, Panicum miliaceum, and Urochloa fusca), we identified 10,219 cell-type-specific accessible chromatin regions (ACRs), serving as sources for investigating divergence of these species. To elucidate the roles of cell-type-specific ACRs in species divergence, we focused on leaf cells in O. sativa and the aforementioned grass species. We observed species-specific candidate CREs (cCREs) potentially associated with cell differentiation, especially in epidermal cells across species. These data also revealed presence of H3K27me3-associated ACRs in the majority of cell types across different organs and species, potentially harboring silencer cCREs. Together, this study significantly advances our understanding of the role of cCREs during cell differentiation, shedding light on their contribution to species divergence in plants
2024-09-04 | GSE252040 | GEO
Project description:Knowledge of the locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to better understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using multiple epigenetic features in cell types from one species at a time, but such an approach can make it difficult to compare results across species. In contrast, we conducted a cross-species study defining epigenetic states and identifying cCREs in blood cell types to generate maps of the regulatory landscapes and cCREs that are comparable across species. This study used integrative modeling of eight epigenetic features jointly in both human and mouse in our Validated Systematic Integration (VISION) Project. The accuracy of the cCRE predictions was supported by orthogonal function-related data. The contribution of each epigenetic state in cCREs to gene regulation was estimated from a multivariate regression against gene expression across cell types, and these values were used to estimate an epigenetic state Regulatory Potential (esRP) score for each cCRE in each cell type. These esRP scores have broad utility for visualizing and categorizing the dynamic changes in cCREs during hematopoietic differentiation. After jointly clustering cCREs based on their esRP scores across human and mouse cell types, we found distinctive transcription factor binding motifs associated with each group of cCREs with similar patterns of regulatory activity; these associations are similar between human and mouse. Genetic variants associated with blood cell phenotypes (from the GWAS Catalog and the UK Biobank study) were highly and specifically enriched in the catalog of human VISION cCREs, indicating the utility of our cCRE predictions for understanding the impact of noncoding genetic variants on both physiologic and pathologic blood cell-related traits. The cross-species joint modeling enabled a comparison of cCREs that revealed both conserved and lineage-specific patterns of epigenetic evolution, even in the absence of genomic sequence alignment. The VISION project resources are accessible through a suite of tools and browsers at http://usevision.org.
2023-04-10 | GSE229099 | GEO
Project description:Knowledge of the locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to better understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using multiple epigenetic features in cell types from one species at a time, but such an approach can make it difficult to compare results across species. In contrast, we conducted a cross-species study defining epigenetic states and identifying cCREs in blood cell types to generate maps of the regulatory landscapes and cCREs that are comparable across species. This study used integrative modeling of eight epigenetic features jointly in both human and mouse in our Validated Systematic Integration (VISION) Project. The accuracy of the cCRE predictions was supported by orthogonal function-related data. The contribution of each epigenetic state in cCREs to gene regulation was estimated from a multivariate regression against gene expression across cell types, and these values were used to estimate an epigenetic state Regulatory Potential (esRP) score for each cCRE in each cell type. These esRP scores have broad utility for visualizing and categorizing the dynamic changes in cCREs during hematopoietic differentiation. After jointly clustering cCREs based on their esRP scores across human and mouse cell types, we found distinctive transcription factor binding motifs associated with each group of cCREs with similar patterns of regulatory activity; these associations are similar between human and mouse. Genetic variants associated with blood cell phenotypes (from the GWAS Catalog and the UK Biobank study) were highly and specifically enriched in the catalog of human VISION cCREs, indicating the utility of our cCRE predictions for understanding the impact of noncoding genetic variants on both physiologic and pathologic blood cell-related traits. The cross-species joint modeling enabled a comparison of cCREs that revealed both conserved and lineage-specific patterns of epigenetic evolution, even in the absence of genomic sequence alignment. The VISION project resources are accessible through a suite of tools and browsers at http://usevision.org.
2023-04-10 | GSE229098 | GEO
Project description:Knowledge of the locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to better understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using multiple epigenetic features in cell types from one species at a time, but such an approach can make it difficult to compare results across species. In contrast, we conducted a cross-species study defining epigenetic states and identifying cCREs in blood cell types to generate maps of the regulatory landscapes and cCREs that are comparable across species. This study used integrative modeling of eight epigenetic features jointly in both human and mouse in our Validated Systematic Integration (VISION) Project. The accuracy of the cCRE predictions was supported by orthogonal function-related data. The contribution of each epigenetic state in cCREs to gene regulation was estimated from a multivariate regression against gene expression across cell types, and these values were used to estimate an epigenetic state Regulatory Potential (esRP) score for each cCRE in each cell type. These esRP scores have broad utility for visualizing and categorizing the dynamic changes in cCREs during hematopoietic differentiation. After jointly clustering cCREs based on their esRP scores across human and mouse cell types, we found distinctive transcription factor binding motifs associated with each group of cCREs with similar patterns of regulatory activity; these associations are similar between human and mouse. Genetic variants associated with blood cell phenotypes (from the GWAS Catalog and the UK Biobank study) were highly and specifically enriched in the catalog of human VISION cCREs, indicating the utility of our cCRE predictions for understanding the impact of noncoding genetic variants on both physiologic and pathologic blood cell-related traits. The cross-species joint modeling enabled a comparison of cCREs that revealed both conserved and lineage-specific patterns of epigenetic evolution, even in the absence of genomic sequence alignment. The VISION project resources are accessible through a suite of tools and browsers at http://usevision.org.
2023-04-10 | GSE229097 | GEO
Project description:Knowledge of the locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to better understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using multiple epigenetic features in cell types from one species at a time, but such an approach can make it difficult to compare results across species. In contrast, we conducted a cross-species study defining epigenetic states and identifying cCREs in blood cell types to generate maps of the regulatory landscapes and cCREs that are comparable across species. This study used integrative modeling of eight epigenetic features jointly in both human and mouse in our Validated Systematic Integration (VISION) Project. The accuracy of the cCRE predictions was supported by orthogonal function-related data. The contribution of each epigenetic state in cCREs to gene regulation was estimated from a multivariate regression against gene expression across cell types, and these values were used to estimate an epigenetic state Regulatory Potential (esRP) score for each cCRE in each cell type. These esRP scores have broad utility for visualizing and categorizing the dynamic changes in cCREs during hematopoietic differentiation. After jointly clustering cCREs based on their esRP scores across human and mouse cell types, we found distinctive transcription factor binding motifs associated with each group of cCREs with similar patterns of regulatory activity; these associations are similar between human and mouse. Genetic variants associated with blood cell phenotypes (from the GWAS Catalog and the UK Biobank study) were highly and specifically enriched in the catalog of human VISION cCREs, indicating the utility of our cCRE predictions for understanding the impact of noncoding genetic variants on both physiologic and pathologic blood cell-related traits. The cross-species joint modeling enabled a comparison of cCREs that revealed both conserved and lineage-specific patterns of epigenetic evolution, even in the absence of genomic sequence alignment. The VISION project resources are accessible through a suite of tools and browsers at http://usevision.org.
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