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全基因组CLIP实验的设计与生物信息学分析。

Design and bioinformatics analysis of genome-wide CLIP experiments.

作者信息

Wang Tao, Xiao Guanghua, Chu Yongjun, Zhang Michael Q, Corey David R, Xie Yang

机构信息

Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.

Departments of Pharmacology and Biochemistry, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.

出版信息

Nucleic Acids Res. 2015 Jun 23;43(11):5263-74. doi: 10.1093/nar/gkv439. Epub 2015 May 9.

Abstract

The past decades have witnessed a surge of discoveries revealing RNA regulation as a central player in cellular processes. RNAs are regulated by RNA-binding proteins (RBPs) at all post-transcriptional stages, including splicing, transportation, stabilization and translation. Defects in the functions of these RBPs underlie a broad spectrum of human pathologies. Systematic identification of RBP functional targets is among the key biomedical research questions and provides a new direction for drug discovery. The advent of cross-linking immunoprecipitation coupled with high-throughput sequencing (genome-wide CLIP) technology has recently enabled the investigation of genome-wide RBP-RNA binding at single base-pair resolution. This technology has evolved through the development of three distinct versions: HITS-CLIP, PAR-CLIP and iCLIP. Meanwhile, numerous bioinformatics pipelines for handling the genome-wide CLIP data have also been developed. In this review, we discuss the genome-wide CLIP technology and focus on bioinformatics analysis. Specifically, we compare the strengths and weaknesses, as well as the scopes, of various bioinformatics tools. To assist readers in choosing optimal procedures for their analysis, we also review experimental design and procedures that affect bioinformatics analyses.

摘要

在过去几十年里,大量发现揭示了RNA调控在细胞过程中起着核心作用。RNA在转录后各个阶段,包括剪接、运输、稳定和翻译,均受RNA结合蛋白(RBP)调控。这些RBP功能缺陷是多种人类疾病的基础。系统鉴定RBP功能靶点是关键的生物医学研究问题之一,也为药物发现提供了新方向。交联免疫沉淀结合高通量测序(全基因组CLIP)技术的出现,使得人们能够在单碱基对分辨率水平上研究全基因组范围内的RBP-RNA结合情况。该技术通过三个不同版本的发展而不断演进:HITS-CLIP、PAR-CLIP和iCLIP。与此同时,也开发了众多用于处理全基因组CLIP数据的生物信息学流程。在本综述中,我们讨论全基因组CLIP技术,并着重于生物信息学分析。具体而言,我们比较了各种生物信息学工具的优缺点及适用范围。为帮助读者选择最佳分析流程,我们还回顾了影响生物信息学分析的实验设计和流程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d835/4477666/b0037ac73eb6/gkv439fig1.jpg

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