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EnhancerAtlas 2.0: an updated resource with enhancer annotation in 586 tissue/cell types across nine species
- Source :
- Nucleic Acids Research
- Publication Year :
- 2019
- Publisher :
- Oxford University Press, 2019.
-
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.
- 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
Subjects
Details
- Language :
- English
- ISSN :
- 13624962 and 03051048
- Volume :
- 48
- Issue :
- D1
- Database :
- OpenAIRE
- Journal :
- Nucleic Acids Research
- Accession number :
- edsair.doi.dedup.....d35397d7e8834feaa56727d6da90a45d