eRNAbase: a comprehensive database for decoding the regulatory eRNAs in human and mouse.
Chao SongGuorui ZhangXinxin MuChenchen FengQinyi ZhangShuang SongYuexin ZhangMingxue YinHang ZhangHuifang TangChun-Quan LiPublished in: Nucleic acids research (2023)
Enhancer RNAs (eRNAs) transcribed from distal active enhancers serve as key regulators in gene transcriptional regulation. The accumulation of eRNAs from multiple sequencing assays has led to an urgent need to comprehensively collect and process these data to illustrate the regulatory landscape of eRNAs. To address this need, we developed the eRNAbase (http://bio.liclab.net/eRNAbase/index.php) to store the massive available resources of human and mouse eRNAs and provide comprehensive annotation and analyses for eRNAs. The current version of eRNAbase cataloged 10 399 928 eRNAs from 1012 samples, including 858 human samples and 154 mouse samples. These eRNAs were first identified and uniformly processed from 14 eRNA-related experiment types manually collected from GEO/SRA and ENCODE. Importantly, the eRNAbase provides detailed and abundant (epi)genetic annotations in eRNA regions, such as super enhancers, enhancers, common single nucleotide polymorphisms, expression quantitative trait loci, transcription factor binding sites, CRISPR/Cas9 target sites, DNase I hypersensitivity sites, chromatin accessibility regions, methylation sites, chromatin interactions regions, topologically associating domains and RNA spatial interactions. Furthermore, the eRNAbase provides users with three novel analyses including eRNA-mediated pathway regulatory analysis, eRNA-based variation interpretation analysis and eRNA-mediated TF-target gene analysis. Hence, eRNAbase is a powerful platform to query, browse and visualize regulatory cues associated with eRNAs.
Keyphrases
- transcription factor
- genome wide
- endothelial cells
- crispr cas
- dna methylation
- induced pluripotent stem cells
- copy number
- dna binding
- pluripotent stem cells
- dna damage
- single cell
- genome editing
- high resolution
- drug induced
- mass spectrometry
- long non coding rna
- electronic health record
- data analysis
- machine learning
- rna seq
- binding protein
- genome wide analysis