scholarly journals Multi-scale annotations of chromatin states in 127 human cell-types

2020 ◽  
Author(s):  
Yan Kai ◽  
Stephanos Tsoucas ◽  
Shengbao Suo ◽  
Guo-Cheng Yuan
Keyword(s):  
Human Cell ◽  
Biological Function ◽  
Cell Types ◽  
Chromatin State ◽  
Cell Type ◽  
Chromatin States ◽  
Multi Scale ◽  
Public Data ◽  
Domain State ◽  
Cell Type Specific

AbstractGenome-wide profiling of chromatin states has been widely used to characterize the biological function of non-coding genomic sequences in a cell-type specific manner. However, the systematic, comprehensive annotations of chromatin states from experimental data are challenging and require not just extensive biological knowledge but also sophisticated computational modeling. Previously we developed a hierarchical hidden Markov model, named diHMM, to systematically annotate chromatin states at multiple scales based on the combination of histone mark and chromatin regulator binding profiles. Here, we have improved the method by optimizing computational efficiency and using an ensemble-clustering approach to achieve a unified annotation by integrating information from cell-type-specific models. We then applied this improved method to generate a unified multi-scale chromatin state map in 127 human cell types, based on public data generated by the Epigenome Roadmap and ENCODE consortia. We found cell types with similar origin are typically associated with similar chromatin states, but cultured cell lines have distinct structures than primary cells. The contribution of enhancer elements to gene regulation is mediated by the broader context of domain-state organization. Distinct domain-state patterns are associated with various 3D chromatin structures. As such, we have demonstrated the utility of the multi-scale chromatin state map in characterizing the biological function of the human genome.

scholarly journals Universal annotation of the human genome through integration of over a thousand epigenomic datasets

2020 ◽  
Author(s):  
Ha Vu ◽  
Jason Ernst
Keyword(s):  
Human Genome ◽  
Large Scale ◽  
Cell Types ◽  
Chromatin State ◽  
Open Chromatin ◽  
Cell Type ◽  
Chromatin States ◽  
Modeling Approach ◽  
Cell Type Specific ◽  
Stack Model

AbstractGenome-wide maps of chromatin marks such as histone modifications and open chromatin sites provide valuable information for annotating the non-coding genome, including identifying regulatory elements. Computational approaches such as ChromHMM have been applied to discover and annotate chromatin states defined by combinatorial and spatial patterns of chromatin marks within the same cell type. An alternative ‘stacked modeling’ approach was previously suggested, where chromatin states are defined jointly from datasets of multiple cell types to produce a single universal genome annotation based on all datasets. Despite its potential benefits for applications that are not specific to one cell type, such an approach was previously applied only for small-scale specialized purposes. Large-scale applications of stacked modeling have previously posed scalability challenges. In this paper, using a version of ChromHMM enhanced for large-scale applications, we applied the stacked modeling approach to produce a universal chromatin state annotation of the human genome using over 1000 datasets from more than 100 cell types, denoted the full-stack model. The full-stack model states show distinct enrichments for external genomic annotations, which we used in characterizing each state. Compared to cell-type-specific annotations, the full-stack annotation directly differentiates constitutive from cell-type-specific activity and is more predictive of locations of external genomic annotations. Overall, the full-stack ChromHMM model provides a universal chromatin state annotation of the genome and a unified global view of over 1000 datasets. We expect this to be a useful resource that complements existing cell-type-specific annotations for studying the non-coding human genome.

scholarly journals MSTD: an efficient method for detecting multi-scale topological domains from symmetric and asymmetric 3D genomic maps

2018 ◽  
Author(s):  
Yusen Ye ◽  
Lin Gao ◽  
Shihua Zhang
Keyword(s):  
Efficient Method ◽  
Three Dimensional ◽  
Cell Types ◽  
Cell Type ◽  
Range Interaction ◽  
Distinct Cell Type ◽  
Chromosome Conformation ◽  
Topological Domains ◽  
Multi Scale ◽  
Cell Type Specific

AbstractThe chromosome conformation capture (3C) technique and its variants have been employed to reveal the existence of a hierarchy of structures in three-dimensional (3D) chromosomal architecture, including compartments, topologically associating domains (TADs), sub-TADs and chromatin loops. However, existing methods for domain detection were only designed based on symmetric Hi-C maps, ignoring long-range interaction structures between domains. To this end, we proposed a generic and efficient method to identify multi-scale topological domains (MSTD), including cis- and trans-interacting regions, from a variety of 3D genomic datasets. We first applied MSTD to detect promoter-anchored interaction domains (PADs) from promoter capture Hi-C datasets across 17 primary blood cell types. The boundaries of PADs are significantly enriched with one or the combination of multiple epigenetic factors. Moreover, PADs between functionally similar cell types are significantly conserved in terms of domain regions and expression states. Cell type-specific PADs involve in distinct cell type-specific activities and regulatory events by dynamic interactions within them. We also employed MSTD to define multi-scale domains from typical symmetric Hi-C datasets and illustrated its distinct superiority to the-state-of-art methods in terms of accuracy, flexibility and efficiency.

scholarly journals A human cell atlas of fetal chromatin accessibility

Science ◽  
2020 ◽  
Vol 370 (6518) ◽  
pp. eaba7612 ◽  
Author(s):  
Silvia Domcke ◽  
Andrew J. Hill ◽  
Riza M. Daza ◽  
Junyue Cao ◽  
Diana R. O’Day ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Cell ◽  
Single Cells ◽  
Complex Trait ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Cell Type ◽  
Cell Type Specific

The chromatin landscape underlying the specification of human cell types is of fundamental interest. We generated human cell atlases of chromatin accessibility and gene expression in fetal tissues. For chromatin accessibility, we devised a three-level combinatorial indexing assay and applied it to 53 samples representing 15 organs, profiling ~800,000 single cells. We leveraged cell types defined by gene expression to annotate these data and cataloged hundreds of thousands of candidate regulatory elements that exhibit cell type–specific chromatin accessibility. We investigated the properties of lineage-specific transcription factors (such as POU2F1 in neurons), organ-specific specializations of broadly distributed cell types (such as blood and endothelial), and cell type–specific enrichments of complex trait heritability. These data represent a rich resource for the exploration of in vivo human gene regulation in diverse tissues and cell types.

scholarly journals CSEA-DB: an omnibus for human complex trait and cell type associations

2020 ◽  
Vol 49 (D1) ◽  
pp. D862-D870
Author(s):  
Yulin Dai ◽  
Ruifeng Hu ◽  
Astrid Marilyn Manuel ◽  
Andi Liu ◽  
Peilin Jia ◽  
...  
Keyword(s):  
Single Cell ◽  
Human Cell ◽  
Cell Types ◽  
Genome Wide Association Studies ◽  
Cell Type ◽  
Human Organ ◽  
Organ Systems ◽  
Wide Range ◽  
Cell Type Specific ◽  
Human Complex

Abstract During the past decade, genome-wide association studies (GWAS) have identified many genetic variants with susceptibility to several thousands of complex diseases or traits. The genetic regulation of gene expression is highly tissue-specific and cell type-specific. Recently, single-cell technology has paved the way to dissect cellular heterogeneity in human tissues. Here, we present a reference database for GWAS trait-associated cell type-specificity, named Cell type-Specific Enrichment Analysis DataBase (CSEA-DB, available at https://bioinfo.uth.edu/CSEADB/). Specifically, we curated total of 5120 GWAS summary statistics data for a wide range of human traits and diseases followed by rigorous quality control. We further collected >900 000 cells from the leading consortia such as Human Cell Landscape, Human Cell Atlas, and extensive literature mining, including 752 tissue cell types from 71 adult and fetal tissues across 11 human organ systems. The tissues and cell types were annotated with Uberon and Cell Ontology. By applying our deTS algorithm, we conducted 10 250 480 times of trait-cell type associations, reporting a total of 598 (11.68%) GWAS traits with at least one significantly associated cell type. In summary, CSEA-DB could serve as a repository of association map for human complex traits and their underlying cell types, manually curated GWAS, and single-cell transcriptome resources.

scholarly journals An atlas of lamina-associated chromatin across thirteen human cell types reveals cell-type-specific and multiple subtypes of peripheral heterochromatin

2020 ◽  
Author(s):  
Kathleen C. Keough ◽  
Parisha P. Shah ◽  
Nadeera M. Wickramasinghe ◽  
Carolyn E. Dundes ◽  
Angela Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Human Cell ◽  
Regulation Of Gene Expression ◽  
Nuclear Periphery ◽  
Cell Types ◽  
Specific Gene ◽  
Cell Type ◽  
Cell Type Specific ◽  
Cellular Identity ◽  
Peripheral Heterochromatin

AbstractThree-dimensional genome organization, specifically organization of heterochromatin at the nuclear periphery, coordinates cell type-specific gene regulation. While defining various histone modifications and chromatin-associated proteins in multiple cell types has provided important insights into epigenetic regulation of gene expression and cellular identity, peripheral heterochromatin has not been mapped comprehensively and relatively few examples have emerged detailing the role of peripheral heterochromatin in cellular identity, cell fate choices, and/or organogenesis. In this study, we define nuclear peripheral heterochromatin organization signatures based on association with LAMIN B1 and/or dimethylation of lysine 9 on H3 (H3K9me2) across thirteen human cell types encompassing pluripotent stem cells, intermediate progenitors and differentiated cells from all three germ layers. Genomic analyses across this atlas reveal that lamin-associated chromatin is organized into at least two different compartments, defined by differences in genome coverage, chromatin accessibility, residence of transposable elements, replication timing domains, and gene complements. Our datasets reveal that only a small subset of lamin-associated chromatin domains are cell type invariant, underscoring the complexity of peripheral heterochromatin organization. Moreover, by integrating peripheral chromatin maps with transcriptional data, we find evidence of cooperative shifts between chromatin structure and gene expression associated with each cell type. This atlas of peripheral chromatin provides the largest resource to date for peripheral chromatin organization and a deeper appreciation for how this organization may impact the establishment and maintenance of cellular identity.

scholarly journals Single cell epigenomic atlas of the developing human brain and organoids

2019 ◽  
Author(s):  
Ryan S. Ziffra ◽  
Chang N. Kim ◽  
Amy Wilfert ◽  
Tychele N. Turner ◽  
Maximilian Haeussler ◽  
...  
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
Cell Fate ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Chromatin State ◽  
Cell Type ◽  
Fate Specification ◽  
Cell Type Specific

AbstractDynamic changes in chromatin accessibility coincide with important aspects of neuronal differentiation, such as fate specification and arealization and confer cell type-specific associations to neurodevelopmental disorders. However, studies of the epigenomic landscape of the developing human brain have yet to be performed at single-cell resolution. Here, we profiled chromatin accessibility of >75,000 cells from eight distinct areas of developing human forebrain using single cell ATAC-seq (scATACseq). We identified thousands of loci that undergo extensive cell type-specific changes in accessibility during corticogenesis. Chromatin state profiling also reveals novel distinctions between neural progenitor cells from different cortical areas not seen in transcriptomic profiles and suggests a role for retinoic acid signaling in cortical arealization. Comparison of the cell type-specific chromatin landscape of cerebral organoids to primary developing cortex found that organoids establish broad cell type-specific enhancer accessibility patterns similar to the developing cortex, but lack many putative regulatory elements identified in homologous primary cell types. Together, our results reveal the important contribution of chromatin state to the emerging patterns of cell type diversity and cell fate specification and provide a blueprint for evaluating the fidelity and robustness of cerebral organoids as a model for cortical development.

scholarly journals Universal annotation of the human genome through integration of over a thousand epigenomic datasets

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Ha Vu ◽  
Jason Ernst
Keyword(s):  
Human Genome ◽  
Large Scale ◽  
Cell Types ◽  
Chromatin State ◽  
Small Scale ◽  
Open Chromatin ◽  
Cell Type ◽  
Chromatin States ◽  
Modeling Approach ◽  
Stack Model

Abstract Background Genome-wide maps of chromatin marks such as histone modifications and open chromatin sites provide valuable information for annotating the non-coding genome, including identifying regulatory elements. Computational approaches such as ChromHMM have been applied to discover and annotate chromatin states defined by combinatorial and spatial patterns of chromatin marks within the same cell type. An alternative “stacked modeling” approach was previously suggested, where chromatin states are defined jointly from datasets of multiple cell types to produce a single universal genome annotation based on all datasets. Despite its potential benefits for applications that are not specific to one cell type, such an approach was previously applied only for small-scale specialized purposes. Large-scale applications of stacked modeling have previously posed scalability challenges. Results Using a version of ChromHMM enhanced for large-scale applications, we apply the stacked modeling approach to produce a universal chromatin state annotation of the human genome using over 1000 datasets from more than 100 cell types, with the learned model denoted as the full-stack model. The full-stack model states show distinct enrichments for external genomic annotations, which we use in characterizing each state. Compared to per-cell-type annotations, the full-stack annotations directly differentiate constitutive from cell type-specific activity and is more predictive of locations of external genomic annotations. Conclusions The full-stack ChromHMM model provides a universal chromatin state annotation of the genome and a unified global view of over 1000 datasets. We expect this to be a useful resource that complements existing per-cell-type annotations for studying the non-coding human genome.

scholarly journals Integrative analysis of 3604 GWAS reveals multiple novel cell type-specific regulatory associations

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Charles E. Breeze ◽  
Eric Haugen ◽  
Alex Reynolds ◽  
Andrew Teschendorff ◽  
Jenny van Dongen ◽  
...  
Keyword(s):  
Disease Risk ◽  
Cell Types ◽  
Regulatory Elements ◽  
Integrative Analysis ◽  
Cell Type ◽  
Web Tool ◽  
Tissue Specific ◽  
Chromatin States ◽  
Disease Aetiology ◽  
Cell Type Specific

Abstract Background Genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) are known to preferentially co-locate to active regulatory elements in tissues and cell types relevant to disease aetiology. Further characterisation of associated cell type-specific regulation can broaden our understanding of how GWAS signals may contribute to disease risk. Results To gain insight into potential functional mechanisms underlying GWAS associations, we developed FORGE2 (https://forge2.altiusinstitute.org/), which is an updated version of the FORGE web tool. FORGE2 uses an expanded atlas of cell type-specific regulatory element annotations, including DNase I hotspots, five histone mark categories and 15 hidden Markov model (HMM) chromatin states, to identify tissue- and cell type-specific signals. An analysis of 3,604 GWAS from the NHGRI-EBI GWAS catalogue yielded at least one significant disease/trait-tissue association for 2,057 GWAS, including > 400 associations specific to epigenomic marks in immune tissues and cell types, > 30 associations specific to heart tissue, and > 60 associations specific to brain tissue, highlighting the key potential of tissue- and cell type-specific regulatory elements. Importantly, we demonstrate that FORGE2 analysis can separate previously observed accessible chromatin enrichments into different chromatin states, such as enhancers or active transcription start sites, providing a greater understanding of underlying regulatory mechanisms. Interestingly, tissue-specific enrichments for repressive chromatin states and histone marks were also detected, suggesting a role for tissue-specific repressed regions in GWAS-mediated disease aetiology. Conclusion In summary, we demonstrate that FORGE2 has the potential to uncover previously unreported disease-tissue associations and identify new candidate mechanisms. FORGE2 is a transparent, user-friendly web tool for the integrative analysis of loci discovered from GWAS.

scholarly journals Connectivity characterization of the mouse basolateral amygdalar complex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Houri Hintiryan ◽  
Ian Bowman ◽  
David L. Johnson ◽  
Laura Korobkova ◽  
Muye Zhu ◽  
...  
Keyword(s):  
Granular Cell ◽  
Cell Types ◽  
Projection Neurons ◽  
Cell Type ◽  
Connectivity Map ◽  
Analysis Techniques ◽  
Domain Specific ◽  
Cell Type Specific ◽  
Unique Domain

AbstractThe basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.

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