EnhFFL: A database of enhancer mediated feed-forward loops for human and mouse

IF 5.1 4区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
Ran Kang, Zhengtang Tan, Mei Lang, Linqi Jin, Yin Zhang, Yiming Zhang, T. Guo, Zhiyun Guo
{"title":"EnhFFL: A database of enhancer mediated feed-forward loops for human and mouse","authors":"Ran Kang, Zhengtang Tan, Mei Lang, Linqi Jin, Yin Zhang, Yiming Zhang, T. Guo, Zhiyun Guo","doi":"10.1093/pcmedi/pbab006","DOIUrl":null,"url":null,"abstract":"Abstract Feed-forward loops (FFLs) are thought to be one of the most common and important classes of transcriptional network motifs involved in various diseases. Enhancers are cis-regulatory elements that positively regulate protein-coding genes or microRNAs (miRNAs) by recruiting DNA-binding transcription factors (TFs). However, a comprehensive resource to identify, store, and analyze the FFLs of typical enhancer and super-enhancer FFLs is not currently available. Here, we present EnhFFL, an online database to provide a data resource for users to browse and search typical enhancer and super-enhancer FFLs. The current database covers 46 280/7000 TF-enhancer-miRNA FFLs, 9997/236 enhancer-miRNA-gene FFLs, 3 561 164/3 193 182 TF-enhancer-gene FFLs, and 1259/235 TF-enhancer feed-back loops (FBLs) across 91 tissues/cell lines of human and mouse, respectively. Users can browse loops by selecting species, types of tissue/cell line, and types of FFLs. EnhFFL supports searching elements including name/ID, genomic location, and the conservation of miRNA target genes. We also developed tools for users to screen customized FFLs using the threshold of q value as well as the confidence score of miRNA target genes. Disease and functional enrichment analysis showed that master miRNAs that are widely engaged in FFLs including TF-enhancer-miRNAs and enhancer-miRNA-genes are significantly involved in tumorigenesis. Database URL:http://lcbb.swjtu.edu.cn/EnhFFL/.","PeriodicalId":33608,"journal":{"name":"Precision Clinical Medicine","volume":"46 1","pages":"129 - 135"},"PeriodicalIF":5.1000,"publicationDate":"2021-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Precision Clinical Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/pcmedi/pbab006","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 3

Abstract

Abstract Feed-forward loops (FFLs) are thought to be one of the most common and important classes of transcriptional network motifs involved in various diseases. Enhancers are cis-regulatory elements that positively regulate protein-coding genes or microRNAs (miRNAs) by recruiting DNA-binding transcription factors (TFs). However, a comprehensive resource to identify, store, and analyze the FFLs of typical enhancer and super-enhancer FFLs is not currently available. Here, we present EnhFFL, an online database to provide a data resource for users to browse and search typical enhancer and super-enhancer FFLs. The current database covers 46 280/7000 TF-enhancer-miRNA FFLs, 9997/236 enhancer-miRNA-gene FFLs, 3 561 164/3 193 182 TF-enhancer-gene FFLs, and 1259/235 TF-enhancer feed-back loops (FBLs) across 91 tissues/cell lines of human and mouse, respectively. Users can browse loops by selecting species, types of tissue/cell line, and types of FFLs. EnhFFL supports searching elements including name/ID, genomic location, and the conservation of miRNA target genes. We also developed tools for users to screen customized FFLs using the threshold of q value as well as the confidence score of miRNA target genes. Disease and functional enrichment analysis showed that master miRNAs that are widely engaged in FFLs including TF-enhancer-miRNAs and enhancer-miRNA-genes are significantly involved in tumorigenesis. Database URL:http://lcbb.swjtu.edu.cn/EnhFFL/.
EnhFFL:人类和小鼠增强子介导的前馈回路数据库
前馈回路(ffl)被认为是参与各种疾病的转录网络基序中最常见和最重要的一类。增强子是通过募集dna结合转录因子(TFs)正向调节蛋白质编码基因或microRNAs (miRNAs)的顺式调控元件。然而,目前还没有一个全面的资源来识别、存储和分析典型增强子和超级增强子ffl的ffl。在这里,我们提出了一个在线数据库EnhFFL,为用户提供浏览和搜索典型增强子和超级增强子ffl的数据资源。目前的数据库涵盖了46 280/7000个tf -增强子- mirna ffl, 9997/236个增强子- mirna基因ffl, 3 561 164/3 193 182个tf -增强子基因ffl和1259/235个tf -增强子反馈回路(FBLs),分别跨越人和小鼠91个组织/细胞系。用户可以通过选择种类、组织/细胞系类型和ffl类型来浏览循环。EnhFFL支持搜索元素,包括名称/ID、基因组位置和miRNA靶基因的保守性。我们还为用户开发了使用q值阈值和miRNA靶基因置信度评分筛选定制ffl的工具。疾病和功能富集分析表明,广泛参与ffl的主要mirna,包括tf -增强mirna和增强mirna -基因,在肿瘤发生过程中具有重要作用。数据库的URL: http://lcbb.swjtu.edu.cn/EnhFFL/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Precision Clinical Medicine
Precision Clinical Medicine MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
10.80
自引率
0.00%
发文量
26
审稿时长
5 weeks
期刊介绍: Precision Clinical Medicine (PCM) is an international, peer-reviewed, open access journal that provides timely publication of original research articles, case reports, reviews, editorials, and perspectives across the spectrum of precision medicine. The journal's mission is to deliver new theories, methods, and evidence that enhance disease diagnosis, treatment, prevention, and prognosis, thereby establishing a vital communication platform for clinicians and researchers that has the potential to transform medical practice. PCM encompasses all facets of precision medicine, which involves personalized approaches to diagnosis, treatment, and prevention, tailored to individual patients or patient subgroups based on their unique genetic, phenotypic, or psychosocial profiles. The clinical conditions addressed by the journal include a wide range of areas such as cancer, infectious diseases, inherited diseases, complex diseases, and rare diseases.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信