Gao Yuan, Wang Jinfeng, Zhao Fangqing
Computational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
University of Chinese Academy of Sciences, Beijing, 100049, China.
Genome Biol. 2015 Jan 13;16(1):4. doi: 10.1186/s13059-014-0571-3.
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.
近期研究表明，环状RNA（circRNAs）是动物中一类新型的丰富、稳定且普遍存在的非编码RNA分子。从高通量转录组数据中全面检测circRNAs是研究其生物合成和功能的首要关键步骤。在此，我们提出了一种基于新型交叉剪接信号的算法CIRI，通过采用多种过滤策略，从转录组数据中无偏差且准确地检测circRNAs。通过将CIRI应用于ENCODE RNA测序数据，我们首次在人类转录组中鉴定并通过实验验证了内含子/基因间circRNAs及其特异性片段的普遍性。
