State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, 210023, China.
Department for Plant Cell and Molecular Biology, Institute for Biology, Humboldt-Universität zu Berlin, 10115, Berlin, Germany.
Nat Commun. 2022 Jun 14;13(1):3413. doi: 10.1038/s41467-022-30770-1.
Plant genomes encode a complex and evolutionary diverse regulatory grammar that forms the basis for most life on earth. A wealth of regulome and epigenome data have been generated in various plant species, but no common, standardized resource is available so far for biologists. Here, we present ChIP-Hub, an integrative web-based platform in the ENCODE standards that bundles >10,000 publicly available datasets reanalyzed from >40 plant species, allowing visualization and meta-analysis. We manually curate the datasets through assessing ~540 original publications and comprehensively evaluate their data quality. As a proof of concept, we extensively survey the co-association of different regulators and construct a hierarchical regulatory network under a broad developmental context. Furthermore, we show how our annotation allows to investigate the dynamic activity of tissue-specific regulatory elements (promoters and enhancers) and their underlying sequence grammar. Finally, we analyze the function and conservation of tissue-specific promoters, enhancers and chromatin states using comparative genomics approaches. Taken together, the ChIP-Hub platform and the analysis results provide rich resources for deep exploration of plant ENCODE. ChIP-Hub is available at https://biobigdata.nju.edu.cn/ChIPHub/ .
植物基因组编码了一套复杂且具有进化多样性的调控语法,为地球上的大多数生命形式奠定了基础。目前已经在各种植物物种中生成了大量的调控组和表观基因组数据,但生物学家尚未拥有通用的标准化资源。在这里,我们展示了 ChIP-Hub,这是一个基于 ENCODE 标准的集成式网络平台,它整合了来自超过 40 个植物物种的 >10000 个公开可用的重新分析数据集,允许进行可视化和元分析。我们通过评估约 540 篇原始出版物来手动整理这些数据集,并全面评估其数据质量。作为概念验证,我们广泛调查了不同调控因子的共同关联,并在广泛的发育背景下构建了一个分层调控网络。此外,我们展示了我们的注释如何用于研究组织特异性调控元件(启动子和增强子)及其潜在序列语法的动态活性。最后,我们使用比较基因组学方法分析组织特异性启动子、增强子和染色质状态的功能和保守性。总之,ChIP-Hub 平台和分析结果为深入探索植物 ENCODE 提供了丰富的资源。ChIP-Hub 可在 https://biobigdata.nju.edu.cn/ChIPHub/ 上获取。