Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data

ABSTRACT: Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data

PROVIDER: PRJNA432102 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data

Project description:Linking regulatory DNA elements to their target genes, which may be located hundreds of kilobases away, remains challenging. Here, we introduce Cicero, an algorithm that identifies co-accessible pairs of DNA elements using single-cell chromatin accessibility data and so connects regulatory elements to their putative target genes. We apply Cicero to investigate how dynamically accessible elements orchestrate gene regulation in differentiating myoblasts. Groups of Cicero-linked regulatory elements meet criteria of “chromatin hubs”—they are enriched for physical proximity, interact with a common set of transcription factors, and undergo coordinated changes in histone marks that are predictive of changes in gene expression. Pseudotemporal analysis revealed that most DNA elements remain in chromatin hubs throughout differentiation. A subset of elements bound by MYOD1 in myoblasts exhibit early opening in a PBX1- and MEIS1-dependent manner. Our strategy can be applied to dissect the architecture, sequence determinants, and mechanisms of cis-regulation on a genome-wide scale.

2018-08-02 | GSE109828 | GEO

Cicero Predicts cis-Regulatory DNA Interactions from Single-Cell Chromatin Accessibility Data.

Project description: Not available

| S-EPMC6582963 | biostudies-literature

Cis-Regulatory Accessibility Directs Muller Glial Development and Regenerative Capacity

Project description:Cis-Regulatory Accessibility Directs Muller Glial Development and Regenerative Capacity

| PRJNA565157 | ENA

Identification of cis-regulatory elements affecting pancreatic Islet maturation using chromatin accessibility variations

Project description:we were able to find several known and unforeseen key transcriptional regulators acting at cis-regulatory sites and promoters which depicted a differential accessibility and induced differential gene expression along maturation.

2019-12-31 | GSE122747 | GEO

Tissue-specific chromatin accessibility cis-regulatory regions in rat white adipose and muscle

Project description:Chromatin accessibility is a key factor influencing gene expression. We developed a modified protocol, ruptor-ATAC, which with RNA-seq was used to investigate regulatory elements underlying gene expression in rat white adipose and skeletal muscle, two tissues with contrasting metabolic functions. Integration of both datasets showed that promoter accessibility correlated with RNA expression and identified 44,798 tissue-specific differentially accessible regions (DARs), predominantly localized in intergenic and intron regions. Tissue-specific DARs mapped to differentially expressed genes that were enriched in distinct biological processes. Motif enrichment analysis on DARs predicted binding sites for transcription factors (TFs). Significant up-regulation of 11 TFs recognizing enriched cis-motifs in each tissue indicated their functional relevance. Positive correlation between motif accessibility and target gene expression further supported the role of selected TFs as transcriptional regulators. Our study identifies non-promoter cis-regulatory regions that likely play a major role in the control of tissue-specific gene expression in adipose and muscle.

2022-02-07 | GSE168328 | GEO

Synergistic model of chromatin predicts Dnase-I accessibility

Project description:Enhancers and promoters commonly occur in accessible chromatin characterized by depleted nucleosome contact; however, it is unclear how chromatin accessibility is governed. We show that a logic of cis-acting DNA sequence features can predict the majority of chromatin accessibility at high spatial resolution. We develop a new type of high-dimensional machine learning model, the Cooperative Chromatin Model (CCM), that is capable of predicting a large fraction of genome-widepromoters chromatin accessibility at basepair-resolution in a range of human and mouse cell types from DNA sequence alone. We confirm that a CCM accurately predicts chromatin accessibility, even of a vast array of synthetic DNA sequences, with a novel CrispR-based method of highly efficient site-specific DNA library integration. CCMs are directly interpretable and reveal that a logic based on local, non-specific cooperation, largely among pioneer TFs, is sufficient to predict a large fraction of cellular chromatin accessibility in a wide variety of cell types.

2016-07-20 | GSE80105 | GEO

A cis-regulatory atlas of maize single cells

Project description:Cis-regulatory elements (CREs) encode the genomic blueprints for coordinating the spatiotemporal regulation of gene transcription programs necessary for highly specialized cellular functions. To identify cis-regulatory elements underlying cell-type specification and developmental transitions, we implemented single-cell sequencing of Assay for Transposase Accessible Chromatin (scATAC-seq) in an atlas of Zea mays tissues and organs. We describe 92 distinct patterns of chromatin accessibility across more than 165,913 putative CREs, greater than 56,575 cells, and 52 known cell-types using a novel regularized quasibinomial logistic model for estimating single cell accessibility. Cell-type specification could be largely explained by combinatorial accessibility of transcription factors (TFs) and their associated binding. Analysis of cell type-specific co-accessible chromatin recapitulated higher-order chromatin interactions, providing novel insight into cell type-specific regulatory dynamics. Integration of genetic diversity data revealed cell-type specific CREs contributed to specific morphological and molecular phenotypic traits indicative of their cellular functions, expanding our understanding of the molecular influence of complex traits in a eukaryotic species.

2020-09-30 | GSE155178 | GEO

Enhancer divergence and cis-regulatory evolution in the human and chimpanzee neural crest

Project description:Here we derive human and chimpanzee cranial neural crest cells (CNCCs) and profile histone modifications, transcription factors, chromatin accessibility and gene expression to systematically and quantitatively annotate evolutionary divergence of craniofacial cis-regulatory landscapes. Histone modifications (H3K27ac, H3K4me1, H3K4me3, H3K27me3), chromatin modifiers (p300), transcription factors (NR2F1, TFAP2A), chromatin accessibility (ATACseq) and gene expression (RNAseq) were assayed in CNCCs derived from iPSCs/ESCs from 2 chimpanzee and 3 human individuals.

2015-09-11 | E-GEOD-70751 | biostudies-arrayexpress

Spatially varying cis-regulatory divergence in Drosophila embryos elucidates cis-regulatory logic

Project description:Spatially varying cis-regulatory divergence in Drosophila embryos elucidates cis-regulatory logic

| PRJNA397062 | ENA

HiCAR analysis of zebrafish fin regeneration identifies cis-regulatory chromatin reorganization in response to injury

Project description:HiCAR (Hi-C on accessible regulatory DNA), which is a genome-wide profiling of chromatin accessibility and open chromatin anchored cis-regulatory element (cRE) interactions, identified 28690 calling loops from zebrafish caudal fins at three different time points (0, 1 and 4 day(s) post amputation (dpa)) including 5022 regeneration-responsive loops (17.5%).

2023-12-22 | GSE231771 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data