Department of Bioinformatics and Molecular Neuropathology, Meiji Pharmaceutical University, 2-522-1 Noshio, Kiyose, Tokyo 204-8588, Japan.
BioData Min. 2011 Jun 17;4:17. doi: 10.1186/1756-0381-4-17.
MicroRNAs (miRNAs) mediate posttranscriptional regulation of protein-coding genes by binding to the 3' untranslated region of target mRNAs, leading to translational inhibition, mRNA destabilization or degradation, depending on the degree of sequence complementarity. In general, a single miRNA concurrently downregulates hundreds of target mRNAs. Thus, miRNAs play a key role in fine-tuning of diverse cellular functions, such as development, differentiation, proliferation, apoptosis and metabolism. However, it remains to be fully elucidated whether a set of miRNA target genes regulated by an individual miRNA in the whole human microRNAome generally constitute the biological network of functionally-associated molecules or simply reflect a random set of functionally-independent genes.
The complete set of human miRNAs was downloaded from miRBase Release 16. We explored target genes of individual miRNA by using the Diana-microT 3.0 target prediction program, and selected the genes with the miTG score ≧ 20 as the set of highly reliable targets. Then, Entrez Gene IDs of miRNA target genes were uploaded onto KeyMolnet, a tool for analyzing molecular interactions on the comprehensive knowledgebase by the neighboring network-search algorithm. The generated network, compared side by side with human canonical networks of the KeyMolnet library, composed of 430 pathways, 885 diseases, and 208 pathological events, enabled us to identify the canonical network with the most significant relevance to the extracted network.
Among 1,223 human miRNAs examined, Diana-microT 3.0 predicted reliable targets from 273 miRNAs. Among them, KeyMolnet successfully extracted molecular networks from 232 miRNAs. The most relevant pathway is transcriptional regulation by transcription factors RB/E2F, the disease is adult T cell lymphoma/leukemia, and the pathological event is cancer.
The predicted targets derived from approximately 20% of all human miRNAs constructed biologically meaningful molecular networks, supporting the view that a set of miRNA targets regulated by a single miRNA generally constitute the biological network of functionally-associated molecules in human cells.
微小 RNA（miRNA）通过与靶 mRNA 的 3'非翻译区结合，介导蛋白质编码基因的转录后调控，从而导致翻译抑制、mRNA 不稳定或降解，这取决于序列互补程度。一般来说，单个 miRNA 同时下调数百个靶 mRNA。因此，miRNA 在精细调节多种细胞功能中发挥着关键作用，如发育、分化、增殖、凋亡和代谢。然而，仍然需要充分阐明，由单个 miRNA 在整个人类 microRNA 组中调控的一组 miRNA 靶基因是否通常构成功能相关分子的生物学网络，或者只是反映一组随机的功能不相关基因。
从 miRBase Release 16 下载完整的人类 miRNA 集。我们使用 Diana-microT 3.0 靶标预测程序探索单个 miRNA 的靶基因，并选择 miTG 评分≧20 的基因作为高度可靠靶标的集合。然后，将 miRNA 靶基因的 Entrez Gene IDs 上传到 KeyMolnet，这是一种通过邻域网络搜索算法分析综合知识库中分子相互作用的工具。生成的网络与 KeyMolnet 库中包含 430 条途径、885 种疾病和 208 种病理事件的人类典型网络进行了比较，使我们能够识别与提取网络最相关的典型网络。
在所检查的 1223 个人类 miRNA 中，Diana-microT 3.0 从 273 个 miRNA 中预测出可靠的靶标。其中，KeyMolnet 成功地从 232 个 miRNA 中提取了分子网络。最相关的途径是转录因子 RB/E2F 的转录调控，疾病是成人 T 细胞淋巴瘤/白血病，病理事件是癌症。
从大约 20%的人类 miRNA 中预测出的靶标构建了具有生物学意义的分子网络，支持了这样一种观点，即由单个 miRNA 调控的一组 miRNA 靶标通常构成人类细胞中功能相关分子的生物学网络。
