The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Studying lncRNAs is challenging due to their low expression level, cell type-specific occurrence, poor sequence conservation between orthologs, and lack of information about RNA domains. LncRNAs direct the regulatory factors in the locations that are in cis to their transcription sites. We designed a model to predict if an lncRNA acts in cis based on its features and trained it using RNA-chromatin interaction data. The trained model is cell type-independent and does not require RNA-chromatin data. Combining RNA-chromatin and Hi-C data, we showed that lncRNA-chromatin binding sites are determined by chromosome conformation. For each lncRNA, the spatially proximal genes were identified as their potential targets by combining Hi-C and Cap Analysis Gene Expression (CAGE) data in 18 human cell types. RNA-protein and RNA-chromatin interaction data suggested that lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. We provide the data through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

中文翻译：

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独联体相互作用 lncRNA 及其靶标的系统鉴定

人类基因组被普遍转录并产生多种长链非编码 RNA (lncRNA)，构成人类细胞类型的大部分转录本。研究 lncRNA 具有挑战性，因为它们的表达水平低、存在细胞类型特异性、直向同源物之间的序列保守性差以及缺乏关于 RNA 结构域的信息。LncRNA 将顺式位置的调节因子引导至其转录位点。我们设计了一个模型来预测 lncRNA 是否基于其特征以顺式作用，并使用 RNA-染色质相互作用数据对其进行训练。训练后的模型与细胞类型无关，不需要 RNA 染色质数据。结合 RNA-染色质和 Hi-C 数据，我们发现 lncRNA-染色质结合位点由染色体构象决定。对于每个 lncRNA，通过结合 18 种人类细胞类型中的 Hi-C 和 Cap 分析基因表达 (CAGE) 数据，将空间邻近基因确定为其潜在目标。RNA-蛋白质和RNA-染色质相互作用数据表明lncRNAs充当支架来招募调节蛋白以靶向启动子和增强子。我们通过位于 https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA 的交互式可视化门户网站提供数据。