Martirosyan Araks, Del Giudice Marco, Bena Chiara Enrico, Pagnani Andrea, Bosia Carla, De Martino Andrea
Laboratory of Glia Biology, VIB-KU Leuven Center for Brain and Disease Research, Leuven, Belgium.
KU Leuven, Department of Neuroscience, Leuven, Belgium.
Methods Mol Biol. 2019;1912:367-409. doi: 10.1007/978-1-4939-8982-9_15.
Non-coding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting, e.g., the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.
非编码RNA在真核生物mRNA翻译和周转的转录后调控中起关键作用。特别是微小RNA(miRNA),它们通过蛋白质介导的序列特异性结合与其靶RNA相互作用,形成扩展的、高度异质的miRNA-RNA相互作用网络。在这样的网络中,与miRNA结合的竞争可以在其靶标之间产生有效的正向偶联。竞争性内源RNA(ceRNA)进而可以通过miRNA介导的串扰相互调节。尽管ceRNA相互作用可能较弱,但它既可以动态发生,例如影响调节时钟,也可以在稳态时发生,在这种情况下,整个ceRNA网络可能与细胞蛋白质组的组成有关。ceRNA相互作用的许多特征,包括它们变得显著的条件,可以通过数学和计算机模拟模型来阐明。我们综述了在此类框架内对ceRNA效应的理解,重点关注用于量化它的方法、它在基因表达噪声处理中的作用,以及网络拓扑结构如何决定其影响范围。