Sharma Disha, Sehgal Paras, Hariprakash Judith, Sivasubbu Sridhar, Scaria Vinod
G.N. Ramachandran Knowledge Center for Bioinformatics, CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
Academy of Scientific and Innovative Research (AcSIR), CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.
Methods Mol Biol. 2019;1912:55-76. doi: 10.1007/978-1-4939-8982-9_3.
Circular RNAs are an emerging class of transcript isoforms created by unique back splicing of exons to form a closed covalent circular structure. While initially considered as product of aberrant splicing, recent evidence suggests unique functions and conservation across evolution. While circular RNAs could be largely attributed to have little or no potential to encode for proteins, recent evidence points to at least a small subset of circular RNAs which encode for peptides. Circular RNAs are also increasingly shown to be biomarkers for a number of diseases including neurological disorders and cancer. The advent of deep sequencing has enabled large-scale identification of circular RNAs in human and other genomes. A number of computational approaches have come up in recent years to query circular RNAs on a genome-wide scale from RNA-seq data. In this chapter, we describe the application and methodology of identifying circular RNAs using three popular computational tools: FindCirc, Segemehl, and CIRI along with approaches for experimental validation of the unique splice junctions.
环状RNA是一类新兴的转录本异构体，由外显子独特的反向剪接形成封闭的共价环状结构。虽然最初被认为是异常剪接的产物，但最近的证据表明其具有独特的功能且在进化过程中保守。虽然环状RNA在很大程度上被认为几乎没有或根本没有编码蛋白质的潜力，但最近的证据指出至少有一小部分环状RNA编码肽。环状RNA也越来越多地被证明是包括神经疾病和癌症在内的多种疾病的生物标志物。深度测序的出现使得在人类和其他基因组中大规模鉴定环状RNA成为可能。近年来出现了许多计算方法，用于从RNA测序数据中在全基因组范围内查询环状RNA。在本章中，我们描述了使用三种流行的计算工具FindCirc、Segemehl和CIRI识别环状RNA的应用和方法，以及对独特剪接接头进行实验验证的方法。
