Boross Gábor, Orosz Katalin, Farkas Illés J
Department of Biological Physics, Eötvös Loránd University and Statistical and Biological Physics Research Group and CellCom RET at the Hungarian Academy of Sciences, Budapest, Hungary.
Bioinformatics. 2009 Apr 15;25(8):1063-9. doi: 10.1093/bioinformatics/btp018. Epub 2009 Jan 8.
Short regulating RNAs guide many cellular processes. Compared with transcription factor proteins they appear to provide more specialized control and their deletions are less frequently lethal.
We find large differences between computationally predicted lists of human microRNA (miRNA)-target pairs. Instead of integrating these lists we use the two most accurate of them. Next, we construct the co-regulation network of human miRNAs as nodes by computing the correlation (link weight) between the gene silencing scores of individual miRNAs. In this network, we locate groups of tightly co-regulating nodes (modules). Despite explicitly allowing overlaps the co-regulation modules of miRNAs are well separated. We use the modules and miRNA co-expression data to define and compute miRNA essentiality. Instead of focusing on particular biological functions we identify a miRNA as essential, if it has a low co-expression with the miRNAs in its module. This may be thought of as having many workers performing the same tasks together in one place (non-essential miRNAs) as opposed to a single worker performing those tasks alone (essential miRNA).
On the system level, we quantitatively confirm previous findings about the specialized control provided by miRNAs. For knock-out tests we list the groups of our predicted most and least essential miRNAs. In addition, we provide possible explanations for (i) the low number of individually essential miRNAs in Caenorhabdtits elegans and (ii) the high number of ubiquitous miRNAs influencing cell and tissue-specific miRNA expression patterns in mouse and human.
短调节RNA指导许多细胞过程。与转录因子蛋白相比,它们似乎能提供更具特异性的控制,并且其缺失导致致死的频率较低。
我们发现计算预测的人类微小RNA(miRNA)-靶标对列表之间存在很大差异。我们没有整合这些列表,而是使用其中最准确的两个。接下来,我们通过计算单个miRNA基因沉默分数之间的相关性(链接权重),构建以人类miRNA为节点的共调控网络。在这个网络中,我们定位紧密共调控节点组(模块)。尽管明确允许重叠,但miRNA的共调控模块仍能很好地分离。我们使用这些模块和miRNA共表达数据来定义和计算miRNA的必要性。如果一个miRNA与其模块中的miRNA共表达水平较低,我们就将其鉴定为必需的,而不是关注特定的生物学功能。这可以被认为是有许多工人在一个地方一起执行相同的任务(非必需miRNA),而不是一个工人单独执行这些任务(必需miRNA)。
在系统层面,我们定量地证实了先前关于miRNA提供特异性控制的发现。对于基因敲除测试,我们列出了预测的最必需和最非必需miRNA组。此外,我们还为(i)秀丽隐杆线虫中单个必需miRNA数量少以及(ii)影响小鼠和人类细胞及组织特异性miRNA表达模式的普遍存在的miRNA数量多提供了可能的解释。