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EnhFFL：人类和小鼠增强子介导的前馈环数据库。

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

作者信息

Kang Ran, Tan Zhengtang, Lang Mei, Jin Linqi, Zhang Yin, Zhang Yiming, Guo Tailin, Guo Zhiyun

机构信息

School of Life Sciences and Engineering, Southwest Jiaotong University, Chengdu 610031, China.

College of Medicine, Southwest Jiaotong University, Chengdu 610031, China.

出版信息

Precis Clin Med. 2021 Apr 14;4(2):129-135. doi: 10.1093/pcmedi/pbab006. eCollection 2021 Jun.

DOI:10.1093/pcmedi/pbab006
PMID:35694152
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8982537/
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 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. http://lcbb.swjtu.edu.cn/EnhFFL/.

摘要

前馈环（FFL）被认为是参与各种疾病的转录网络基序中最常见且最重要的类别之一。增强子是顺式调控元件，通过招募DNA结合转录因子（TF）来正向调控蛋白质编码基因或微小RNA（miRNA）。然而，目前尚无用于识别、存储和分析典型增强子和超级增强子FFL的综合资源。在此，我们展示了EnhFFL，这是一个在线数据库，为用户提供用于浏览和搜索典型增强子和超级增强子FFL的数据资源。当前数据库分别涵盖了人类和小鼠91种组织/细胞系中的46280/7000个TF - 增强子 - miRNA FFL、9997/236个增强子 - miRNA - 基因FFL、3561164/3193182个TF - 增强子 - 基因FFL以及1259/235个TF - 增强子反馈环（FBL）。用户可以通过选择物种、组织/细胞系类型和FFL类型来浏览环。EnhFFL支持按名称/ID、基因组位置以及miRNA靶基因的保守性等元素进行搜索。我们还开发了工具，供用户使用 值阈值以及miRNA靶基因的置信度分数来筛选定制的FFL。疾病和功能富集分析表明，广泛参与包括TF - 增强子 - miRNA和增强子 - miRNA - 基因在内的FFL的主要miRNA在肿瘤发生中显著相关。http://lcbb.swjtu.edu.cn/EnhFFL/

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2d1/8982537/b77bad8b5394/pbab006fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2d1/8982537/c759a6d2d3b4/pbab006fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2d1/8982537/b77bad8b5394/pbab006fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2d1/8982537/c759a6d2d3b4/pbab006fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2d1/8982537/b77bad8b5394/pbab006fig2.jpg

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本文引用的文献

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Genomics Proteomics Bioinformatics. 2020 Apr;18(2):120-128. doi: 10.1016/j.gpb.2019.09.006. Epub 2020 Aug 26.
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FFLtool: a web server for transcription factor and miRNA feed forward loop analysis in human.FFLtool：一个用于人类转录因子和 miRNA 前馈回路分析的网络服务器。
Bioinformatics. 2020 Apr 15;36(8):2605-2607. doi: 10.1093/bioinformatics/btz929.
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TransmiR v2.0: an updated transcription factor-microRNA regulation database.
整合增强子和拓扑关联域的染色体位置和功能方面，使知识图谱能够灵活地查询基因调控。
Nucleic Acids Res. 2024 Aug 27;52(15):e69. doi: 10.1093/nar/gkae566.
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Acta Biochim Biophys Sin (Shanghai). 2024 Feb 25;56(2):151-161. doi: 10.3724/abbs.2023268.
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Identification and characteristic analysis of enhancers across 13 major cancer types.13种主要癌症类型中增强子的鉴定与特征分析
Precis Clin Med. 2021 Aug 2;4(3):204-208. doi: 10.1093/pcmedi/pbab019. eCollection 2021 Sep.
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Analysis of the landscape of human enhancer sequences in biological databases.生物数据库中人类增强子序列景观分析。
Comput Struct Biotechnol J. 2022 May 30;20:2728-2744. doi: 10.1016/j.csbj.2022.05.045. eCollection 2022.
TransmiR v2.0：一个更新的转录因子- microRNA 调控数据库。
Nucleic Acids Res. 2019 Jan 8;47(D1):D253-D258. doi: 10.1093/nar/gky1023.
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