Liu Ying, Pan Chu, Kong Dehan, Luo Jiawei, Zhang Zhaolei
College of Computer Science and Electronic Engineering, Hunan University, Changsha, China.
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.
Front Genet. 2020 Sep 8;11:515094. doi: 10.3389/fgene.2020.515094. eCollection 2020.
Recent advances in genomics and proteomics generated a large amount of regulatory data such as those mediated by RNA binding proteins (RBPs) and microRNAs. Since many regulators target 3' UTR of mRNA transcripts, it is likely that there would be interactions, i.e., competitive or cooperative effect, among these factors. We compiled the available RBP and microRNA binding sites, mapped them to the mRNA transcripts, and correlated the binding data with mRNA expression data generated by The Cancer Genome Atlas (TCGA). We separated pairs of RBPs and microRNAs into three scenarios: those that have overlapping target sites on the same mRNA transcript (), those that have target sites on the same mRNA transcript but non-overlapping (), and those that do not target the same mRNA transcript (). Through a regression analysis on expression profiles, we indeed observed interaction effect between RBPs and microRNAs in the majority of the cancer expression data sets. We further discussed implication of such widespread interactions in the context of cancer and diseases.
基因组学和蛋白质组学的最新进展产生了大量调控数据,如由RNA结合蛋白(RBPs)和微小RNA介导的数据。由于许多调控因子靶向mRNA转录本的3'UTR,这些因子之间很可能存在相互作用,即竞争或协同效应。我们汇编了可用的RBP和微小RNA结合位点,将它们映射到mRNA转录本上,并将结合数据与癌症基因组图谱(TCGA)生成的mRNA表达数据相关联。我们将RBP和微小RNA对分为三种情况:那些在同一mRNA转录本上具有重叠靶位点的(),那些在同一mRNA转录本上具有靶位点但不重叠的(),以及那些不靶向同一mRNA转录本的()。通过对表达谱的回归分析,我们确实在大多数癌症表达数据集中观察到了RBP和微小RNA之间的相互作用效应。我们进一步讨论了这种广泛相互作用在癌症和疾病背景下的意义。