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Abstract：
Recent studies on the regulatory networks implicated in Alzheimer\'s disease (AD) evince long non-coding RNAs (lncRNAs) as crucial regulatory players, albeit a poor understanding of the mechanism. Analyzing differential gene expression in the RNA-seq data from the post-mortem AD brain hippocampus, we categorized a list of AD-dysregulated lncRNA transcripts into functionally similar communities based on their k-mer profiles. Using machine-learning-based algorithms, their subcellular localizations were mapped. We further explored the functional relevance of each community through AD-dysregulated miRNA, RNA-binding protein (RBP) interactors, and pathway enrichment analyses. Further investigation of the miRNA-lncRNA and RBP-lncRNA networks from each community revealed the top RBPs, miRNAs, and lncRNAs for each cluster. The experimental validation community yielded ELAVL4 and miR-16-5p as the predominant RBP and miRNA, respectively. Five lncRNAs emerged as the top-ranking candidates from the RBP/miRNA-lncRNA networks. Further analyses of these networks revealed the presence of multiple regulatory triads where the RBP-lncRNA interactions could be augmented by the enhanced miRNA-lncRNA interactions. Our results advance the understanding of the mechanism of lncRNA-mediated AD regulation through their interacting partners and demonstrate how these functionally segregated but overlapping regulatory networks can modulate the disease holistically.
摘要：
最近对阿尔茨海默病（AD）涉及的调控网络的研究表明，长链非编码RNA（lncRNAs）是关键的调控参与者，尽管对机制的理解很差。分析来自死后AD脑海马的RNA-seq数据中的差异基因表达，我们根据k-mer谱将一系列AD失调的lncRNA转录本分类为功能相似的群落。使用基于机器学习的算法，他们的亚细胞定位被映射。我们通过AD失调的miRNA进一步探索了每个社区的功能相关性，RNA结合蛋白（RBP）相互作用物，和途径富集分析。对来自每个社区的miRNA-lncRNA和RBP-lncRNA网络的进一步调查显示，miRNA,和每个簇的lncRNAs。实验验证社区产生ELAVL4和miR-16-5p作为主要的RBP和miRNA，分别。五个lncRNA作为来自RBP/miRNA-lncRNA网络的顶级候选物出现。对这些网络的进一步分析揭示了多个调节三联体的存在，其中RBP-lncRNA相互作用可以通过增强的miRNA-lncRNA相互作用来增强。我们的结果通过其相互作用的伙伴促进了对lncRNA介导的AD调节机制的理解，并证明了这些功能分离但重叠的调节网络如何从整体上调节疾病。
