CIRI: an efficient and unbiased algorithm for de novo circular RNA identification

被引：1043

作者：

Gao, Yuan ^{[1
,2
]}

Wang, Jinfeng ^{[1
]}

Zhao, Fangqing ^{[1
]}

机构：

[1] Chinese Acad Sci, Beijing Inst Life Sci, Computat Genom Lab, Beijing 100101, Peoples R China

[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

来源：

GENOME BIOLOGY | 2015年 / 16卷

关键词：

DISCOVERY; MOUSE; INGAP;

D O I：

10.1186/s13059-014-0571-3

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 [微生物学]; 090105 [作物生产系统与生态工程];

摘要：

Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals. Comprehensive detection of circRNAs from high-throughput transcriptome data is an initial and crucial step to study their biogenesis and function. Here, we present a novel chiastic clipping signal-based algorithm, CIRI, to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. By applying CIRI to ENCODE RNA-seq data, we for the first time identify and experimentally validate the prevalence of intronic/intergenic circRNAs as well as fragments specific to them in the human transcriptome.

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页数：16

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