[论文解读] MicroRNA Interaction network in human: implications of clustered microRNA in biological pathways and genetic diseases

Sushmita Mookherjee, Mithun Sinha+3 more|arXiv (Cornell University)|Jan 27, 2009

MicroRNA in disease regulation参考文献 25被引用 5

一句话总结

本研究基于 miRBase v10 中的 711 个 miRNA 及其 34,525 个预测靶基因，构建了人类 miRNA 相互作用网络，揭示了簇状 miRNA 会共同靶向特定生物通路中的基因。包含 479 个 miRNA 的最大连通子图包含了超过 75% 的疾病相关失调 miRNA，且 70 个共靶向 miRNA 簇与富集的通路相关联，表明 miRNA 簇而非单个 miRNA 是遗传疾病中的关键调控因子。

ABSTRACT

A novel group of small non-coding RNA, known as microRNA (miRNA) is predicted to regulate as high as 90% of the coding genes in human. The diversity and abundance of miRNA targets offer an enormous level of combinatorial possibilities and suggest that miRNAs and their targets form a complex regulatory network. In the present study, we analyzed 711 miRNAs and their 34, 525 predicted targets in the miRBase database which generate a complex bipartite network having numerous numbers of genes forming the hub. Genes at the hub (total 9877) are significantly over represented in genes with specific molecular functions, biological processes and biological pathways as revealed from the analysis using PANTHER. We further construct a miRNA co-target network by linking every pair of miRNAs which co-target at least one gene. The weight of the link, which is taken to be the number of co-targets of the pair of miRNAs vary widely, and we could erase several links while keeping the relevant features of the network intact. The largest connected sub-graph, thus obtained, contains 479 miRNAs. More than 75% of the miRNAs deregulated in 15 different diseases collected from published data are found to be in this largest sub graph. We further analyze this sub-graph to obtain 70 small clusters containing total 330 miRNAs of 479. We identified the biological pathways where the co-targeted genes in the clusters are significantly over- represented in comparison to that obtained with that are not co-targeted by the miRNAs in the cluster. Using published data, we identified that specific clusters of miRNAs are associated with specific diseases by altering particular pathways. We propose that instead of single miRNA, clusters of miRNA that co-targets the genes are important for the regulation of miRNA in diseases.

研究动机与目标

• 绘制人类 microRNA 及其预测靶基因之间复杂调控网络的图谱。
• 研究簇状 miRNA 在共同调控基因和生物通路中的作用。
• 通过网络拓扑结构与通路富集分析，识别与遗传疾病相关的功能 miRNA 簇。
• 确定 miRNA 簇而非单个 miRNA 是否在疾病相关基因调控中处于核心地位。

提出的方法

• 基于 miRBase v10 中的 711 个 miRNA 和 34,525 个预测靶基因，构建了二部图网络。
• 识别出具有高连通性的枢纽基因（9,877 个），并利用 PANTHER 分析其功能富集性。
• 通过连接至少共享一个共同靶标的 miRNA 对，构建 miRNA 共靶向网络，权重基于共靶向数量。
• 通过移除低权重连接来简化网络，同时保持结构完整性，最终获得包含 479 个 miRNA 的最大连通子图。
• 基于基因组邻近性（10 kb 内）和种子序列相似性，将 479 个 miRNA 聚类为 70 组。
• 对每个簇的共同靶基因进行通路富集分析，以识别显著富集的生物通路。

实验结果

研究问题

• RQ1 哪些生物通路在 miRNA 簇共靶向的基因中显著富集？
• RQ2 miRNA 簇与人类遗传疾病中失调的 miRNA 之间存在何种相关性？
• RQ3 miRNA 共靶向模式在多大程度上反映了基因调控中的功能冗余或协同作用？
• RQ4 与单个 miRNA 相比，miRNA 簇是否更具预测疾病关联性的能力？
• RQ5 miRNA 基因组簇化与靶基因功能共调控之间存在何种关系？

主要发现

• miRNA 共靶向网络中的最大连通子图包含 479 个 miRNA，占研究中总 miRNA 数的 67%。
• 超过 75% 的来自 15 种不同疾病的 156 个实验验证失调的 miRNA 位于最大连通子图中。
• 共鉴定出 70 个不同的 miRNA 簇，涵盖最大子图中 479 个 miRNA 中的 330 个，且在 10 kb 内具有显著的基因组聚集性。
• 与非共靶向基因相比，miRNA 簇共靶向的基因在特定生物通路中显著富集，p 值 ≤ 0.05。
• 共靶向基因中富集的通路包括癌症、细胞凋亡和细胞发育相关通路，且与实验观察到的疾病通路存在重叠。
• 特定 miRNA 簇通过共享的靶向通路与特定疾病相关联，提示其在疾病机制中具有协调调控作用。