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剖析真核生物转录后调控网络中RNA结合蛋白与其同源靶标之间的表达关系。

Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks.

作者信息

Nishtala Sneha, Neelamraju Yaseswini, Janga Sarath Chandra

机构信息

Department of Bio Health Informatics, School of Informatics and Computing, Indiana University Purdue University, 719 Indiana Ave Ste 319, Walker Plaza Building, Indianapolis, Indiana 46202, USA.

Centre for Computational Biology and Bioinformatics, Indiana University School of Medicine, 5021 Health Information and Translational Sciences (HITS), 410 West 10th Street, Indianapolis, Indiana, 46202, USA.

出版信息

Sci Rep. 2016 May 10;6:25711. doi: 10.1038/srep25711.

Abstract

RNA-binding proteins (RBPs) are pivotal in orchestrating several steps in the metabolism of RNA in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Here, we employed CLIP (cross-linking immunoprecipitation)-seq datasets for 60 human RBPs and RIP-ChIP (RNP immunoprecipitation-microarray) data for 69 yeast RBPs to construct a network of genome-wide RBP- target RNA interactions for each RBP. We show in humans that majority (~78%) of the RBPs are strongly associated with their target transcripts at transcript level while ~95% of the studied RBPs were also found to be strongly associated with expression levels of target transcripts when protein expression levels of RBPs were employed. At transcript level, RBP - RNA interaction data for the yeast genome, exhibited a strong association for 63% of the RBPs, confirming the association to be conserved across large phylogenetic distances. Analysis to uncover the features contributing to these associations revealed the number of target transcripts and length of the selected protein-coding transcript of an RBP at the transcript level while intensity of the CLIP signal, number of RNA-Binding domains, location of the binding site on the transcript, to be significant at the protein level. Our analysis will contribute to improved modelling and prediction of post-transcriptional networks.

摘要

RNA结合蛋白(RBPs)在协调真核生物RNA代谢的多个步骤中起着关键作用,从而控制着广泛的RBP-RNA相互作用网络。在此,我们利用60种人类RBPs的CLIP(交联免疫沉淀)-seq数据集和69种酵母RBPs的RIP-ChIP(RNP免疫沉淀-微阵列)数据,为每种RBP构建全基因组RBP-靶标RNA相互作用网络。我们在人类中发现,大多数(约78%)的RBPs在转录水平上与其靶标转录本强烈相关,而当采用RBPs的蛋白质表达水平时,约95%的研究RBPs也被发现与靶标转录本的表达水平强烈相关。在转录水平上,酵母基因组的RBP-RNA相互作用数据显示,63%的RBPs存在强关联,证实这种关联在较大的系统发育距离上是保守的。为揭示促成这些关联的特征所做的分析表明,在转录水平上,RBP的靶标转录本数量和所选蛋白质编码转录本的长度有影响,而在蛋白质水平上,CLIP信号强度、RNA结合结构域数量、转录本上结合位点的位置有显著影响。我们的分析将有助于改进转录后网络的建模和预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9efe/4861959/4ecd8e1d4431/srep25711-f1.jpg

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