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R-loopBase:一个用于全基因组 R 环形成和调控的知识库。

R-loopBase: a knowledgebase for genome-wide R-loop formation and regulation.

机构信息

State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing 210023, China.

Ben May Department for Cancer Research, University of Chicago, Chicago, IL 60637, USA.

出版信息

Nucleic Acids Res. 2022 Jan 7;50(D1):D303-D315. doi: 10.1093/nar/gkab1103.

Abstract

R-loops play versatile roles in many physiological and pathological processes, and are of great interest to scientists in multiple fields. However, controversy about their genomic localization and incomplete understanding of their regulatory network raise great challenges for R-loop research. Here, we present R-loopBase (https://rloopbase.nju.edu.cn) to tackle these pressing issues by systematic integration of genomics and literature data. First, based on 107 high-quality genome-wide R-loop mapping datasets generated by 11 different technologies, we present a reference set of human R-loop zones for high-confidence R-loop localization, and spot conservative genomic features associated with R-loop formation. Second, through literature mining and multi-omics analyses, we curate the most comprehensive list of R-loop regulatory proteins and their targeted R-loops in multiple species to date. These efforts help reveal a global regulatory network of R-loop dynamics and its potential links to the development of cancers and neurological diseases. Finally, we integrate billions of functional genomic annotations, and develop interactive interfaces to search, visualize, download and analyze R-loops and R-loop regulators in a well-annotated genomic context. R-loopBase allows all users, including those with little bioinformatics background to utilize these data for their own research. We anticipate R-loopBase will become a one-stop resource for the R-loop community.

摘要

R 环在许多生理和病理过程中发挥着多样的作用,是多个领域科学家感兴趣的对象。然而,关于其基因组定位的争议以及对其调控网络认识的不完整,给 R 环研究带来了巨大的挑战。在这里,我们通过系统整合基因组学和文献数据,提出 R-loopBase(https://rloopbase.nju.edu.cn)来解决这些紧迫的问题。首先,基于 11 种不同技术生成的 107 个高质量全基因组 R 环作图数据集,我们为高可信度的 R 环定位提供了一个人类 R 环区的参考集,并发现了与 R 环形成相关的保守基因组特征。其次,通过文献挖掘和多组学分析,我们整理了迄今为止在多个物种中 R 环调控蛋白及其靶向 R 环的最全面列表。这些努力有助于揭示 R 环动力学的全局调控网络及其与癌症和神经疾病发展的潜在联系。最后,我们整合了数十亿个功能基因组注释,并开发了交互式界面,以便在注释良好的基因组背景下搜索、可视化、下载和分析 R 环和 R 环调控蛋白。R-loopBase 允许所有用户,包括那些具有较少生物信息学背景的用户,利用这些数据进行自己的研究。我们预计 R-loopBase 将成为 R 环研究社区的一站式资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/931d/8728142/fe3fab2d9ae6/gkab1103fig1.jpg

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