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39 results on '"STARR-seq"'

1. Assessing genome-wide dynamic changes in enhancer activity during early mESC differentiation by FAIRE-STARR-seq.

Author

Glaser LV, Steiger M, Fuchs A, van Bömmel A, Einfeldt E, Chung HR, Vingron M, and Meijsing SH

Subjects
Animals, Cell Differentiation, Chromosome Mapping, Enhancer Elements, Genetic, Mice, Mouse Embryonic Stem Cells cytology, Receptors, Retinoic Acid metabolism
Abstract

Embryonic stem cells (ESCs) can differentiate into any given cell type and therefore represent a versatile model to study the link between gene regulation and differentiation. To quantitatively assess the dynamics of enhancer activity during the early stages of murine ESC differentiation, we analyzed accessible genomic regions using STARR-seq, a massively parallel reporter assay. This resulted in a genome-wide quantitative map of active mESC enhancers, in pluripotency and during the early stages of differentiation. We find that only a minority of accessible regions is active and that such regions are enriched near promoters, characterized by specific chromatin marks, enriched for distinct sequence motifs, and modeling shows that active regions can be predicted from sequence alone. Regions that change their activity upon retinoic acid-induced differentiation are more prevalent at distal intergenic regions when compared to constitutively active enhancers. Further, analysis of differentially active enhancers verified the contribution of individual TF motifs toward activity and inducibility as well as their role in regulating endogenous genes. Notably, the activity of retinoic acid receptor alpha (RARα) occupied regions can either increase or decrease upon the addition of its ligand, retinoic acid, with the direction of the change correlating with spacing and orientation of the RARα consensus motif and the co-occurrence of additional sequence motifs. Together, our genome-wide enhancer activity map elucidates features associated with enhancer activity levels, identifies regulatory regions disregarded by computational prediction tools, and provides a resource for future studies into regulatory elements in mESCs., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Published
2021
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23. New developments on the Encyclopedia of DNA Elements (ENCODE) data portal.

Author

Luo, Yunhai, Hitz, Benjamin C, Gabdank, Idan, Hilton, Jason A, Kagda, Meenakshi S, Lam, Bonita, Myers, Zachary, Sud, Paul, Jou, Jennifer, Lin, Khine, Baymuradov, Ulugbek K, Graham, Keenan, Litton, Casey, Miyasato, Stuart R, Strattan, J Seth, Jolanki, Otto, Lee, Jin-Wook, Tanaka, Forrest Y, Adenekan, Philip, and O'Neill, Emma

Published
2020
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25. Esearch3D: propagating gene expression in chromatin networks to illuminate active enhancers

Author

Maninder Heer, Luca Giudice, Claudia Mengoni, Rosalba Giugno, and Daniel Rico

Subjects
Genetics, network bioinformatics
Abstract

Most cell type-specific genes are regulated by the interaction of enhancers with their promoters. The identification of enhancers is not trivial as enhancers are diverse in their characteristics and dynamic in their interaction partners. Currently, enhancer-associated features such as histone modifications, co-activators or bi-directional transcription are used in lieu of any definitive and universal enhancer feature. We present Esearch3D, a new approach that leverages network theory approaches to identify active enhancers. Our work is based on the fact that enhancers act as a source of regulatory information to increase the rate of transcription of their target genes and that the flow of this information is mediated by the folding of chromatin in the three-dimensional (3D) nuclear space between the enhancer and the target gene promoter. Esearch3D reverse engineers this flow of information to calculate the likelihood of enhancer activity in intergenic regions by propagating the transcription levels of genes across 3D-genome networks. Regions predicted to have high enhancer activity are shown to be enriched in annotations indicative of enhancer activity. These include: enhancer-associated histone marks, bi-directional CAGE-seq, STARR-seq, P300 and RNA polymerase II ChIP-seq, and expression quantitative trait loci (eQTL). Esearch3D successfully leverages the relationship between chromatin architecture and global transcription and represents a novel approach to predict active enhancers and understand the complex underpinnings of regulatory networks. The method is available at: https://github.com/InfOmics/Esearch3D.

Published
2023

28. Master lineage transcription factors anchor trans mega transcriptional complexes at highly accessible enhancer sites to promote long-range chromatin clustering and transcription of distal target genes

Author

Michael Snyder, Shannon M White, and Chunling Yi

Subjects
animal structures, Lineage (genetic), AcademicSubjects/SCI00010, Gene regulation, Chromatin and Epigenetics, genetic processes, Computational biology, Biology, Mega, Chromatin, Enhancer Elements, Genetic, Mediator, Gene Expression Regulation, Transcription (biology), Cell Line, Tumor, Genetics, Humans, natural sciences, Enhancer, Gene, Transcription factor, Transcription Factors
Abstract

The term ‘super enhancers’ (SE) has been widely used to describe stretches of closely localized enhancers that are occupied collectively by large numbers of transcription factors (TFs) and co-factors, and control the transcription of highly-expressed genes. Through integrated analysis of >600 DNase-seq, ChIP-seq, GRO-seq, STARR-seq, RNA-seq, Hi-C and ChIA-PET data in five human cancer cell lines, we identified a new class of autonomous SEs (aSEs) that are excluded from classic SE calls by the widely used Rank Ordering of Super-Enhancers (ROSE) method. TF footprint analysis revealed that compared to classic SEs and regular enhancers, aSEs are tightly bound by a dense array of master lineage TFs, which serve as anchors to recruit additional TFs and co-factors in trans. In addition, aSEs are preferentially enriched for Cohesins, which likely involve in stabilizing long-distance interactions between aSEs and their distal target genes. Finally, we showed that aSEs can be reliably predicted using a single DNase-seq data or combined with Mediator and/or P300 ChIP-seq. Overall, our study demonstrates that aSEs represent a unique class of functionally important enhancer elements that distally regulate the transcription of highly expressed genes.

Published
2021

36. EnhancerAtlas 2.0: an updated resource with enhancer annotation in 586 tissue/cell types across nine species

Author

Jiang Qian and Tianshun Gao

Subjects
Cell type, Computational Biology, Molecular Sequence Annotation, Computational biology, Genomics, Biology, Models, Theoretical, Web Browser, Genome, Annotation, User-Computer Interface, Enhancer Elements, Genetic, Species Specificity, Transcription (biology), Genetics, Tissue cell, Database Issue, Animals, Humans, Candidate Disease Gene, Enhancer, Databases, Nucleic Acid, Gene, Algorithms, Software
Abstract

Enhancers are distal cis-regulatory elements that activate the transcription of their target genes. They regulate a wide range of important biological functions and processes, including embryogenesis, development, and homeostasis. As more and more large-scale technologies were developed for enhancer identification, a comprehensive database is highly desirable for enhancer annotation based on various genome-wide profiling datasets across different species. Here, we present an updated database EnhancerAtlas 2.0 (http://www.enhanceratlas.org/indexv2.php), covering 586 tissue/cell types that include a large number of normal tissues, cancer cell lines, and cells at different development stages across nine species. Overall, the database contains 13 494 603 enhancers, which were obtained from 16 055 datasets using 12 high-throughput experiment methods (e.g. H3K4me1/H3K27ac, DNase-seq/ATAC-seq, P300, POLR2A, CAGE, ChIA-PET, GRO-seq, STARR-seq and MPRA). The updated version is a huge expansion of the first version, which only contains the enhancers in human cells. In addition, we predicted enhancer–target gene relationships in human, mouse and fly. Finally, the users can search enhancers and enhancer–target gene relationships through five user-friendly, interactive modules. We believe the new annotation of enhancers in EnhancerAtlas 2.0 will facilitate users to perform useful functional analysis of enhancers in various genomes.

Published
2019

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