Reyes-Herrera Paula H, Ficarra Elisa
Facultad de Ingeniería Electrónica y Biomédica, Universidad Antonio Nariño, Bogotá, Colombia.
Department of Control and Computer Engineering, Politecnico di Torino, TO, Italy.
Bioinform Biol Insights. 2014 Oct 1;8:199-207. doi: 10.4137/BBI.S16803. eCollection 2014.
RNA-binding proteins (RBPs) are at the core of post-transcriptional regulation and thus of gene expression control at the RNA level. One of the principal challenges in the field of gene expression regulation is to understand RBPs mechanism of action. As a result of recent evolution of experimental techniques, it is now possible to obtain the RNA regions recognized by RBPs on a transcriptome-wide scale. In fact, CLIP-seq protocols use the joint action of CLIP, crosslinking immunoprecipitation, and high-throughput sequencing to recover the transcriptome-wide set of interaction regions for a particular protein. Nevertheless, computational methods are necessary to process CLIP-seq experimental data and are a key to advancement in the understanding of gene regulatory mechanisms. Considering the importance of computational methods in this area, we present a review of the current status of computational approaches used and proposed for CLIP-seq data.
RNA结合蛋白(RBPs)是转录后调控的核心,因此也是RNA水平上基因表达控制的核心。基因表达调控领域的主要挑战之一是了解RBPs的作用机制。由于实验技术的最新发展,现在有可能在全转录组范围内获得被RBPs识别的RNA区域。事实上,CLIP-seq实验方案利用CLIP(交联免疫沉淀)和高通量测序的联合作用,来恢复特定蛋白质在全转录组范围内的相互作用区域集。然而,需要计算方法来处理CLIP-seq实验数据,并且这是推进对基因调控机制理解的关键。考虑到计算方法在该领域的重要性,我们对用于CLIP-seq数据的现有计算方法和提出的计算方法的现状进行综述。