Hoffmann Markus, Schwartz Leon, Ciora Octavia-Andreea, Trummer Nico, Willruth Lina-Liv, Jankowski Jakub, Lee Hye Kyung, Baumbach Jan, Furth Priscilla, Hennighausen Lothar, List Markus
Big Data in BioMedicine Group, Chair of Experimental Bioinformatics, TUM School of Life Sciences, Technical University of Munich, Munich, Germany.
Institute for Advanced Study (Lichtenbergstrasse 2a, D-85748 Garching, Germany), Technical University of Munich, Germany.
bioRxiv. 2023 Jun 23:2023.01.19.524495. doi: 10.1101/2023.01.19.524495.
Circular RNAs (circRNAs) are long non-coding RNAs (lncRNAs) often associated with diseases and considered potential biomarkers for diagnosis and treatment. Among other functions, circRNAs have been shown to act as microRNA (miRNA) sponges, preventing the role of miRNAs that repress their targets. However, there is no pipeline to systematically assess the sponging potential of circRNAs.
We developed circRNA-sponging, a nextflow pipeline that (1) identifies circRNAs via backsplicing junctions detected in RNA-seq data, (2) quantifies their expression values in relation to their linear counterparts spliced from the same gene, (3) performs differential expression analysis, (4) identifies and quantifies miRNA expression from miRNA-sequencing (miRNA-seq) data, (5) predicts miRNA binding sites on circRNAs, (6) systematically investigates potential circRNA-miRNA sponging events, (7) creates a network of competing endogenous RNAs, and (8) identifies potential circRNA biomarkers. We showed the functionality of the circRNA-sponging pipeline using RNA sequencing data from brain tissues, where we identified two distinct types of circRNAs characterized by a specific ratio of the number of the binding site to the length of the transcript. The circRNA-sponging pipeline is the first end-to-end pipeline to identify circRNAs and their sponging systematically with raw total RNA-seq and miRNA-seq files, allowing us to better indicate the functional impact of circRNAs as a routine aspect in transcriptomic research.
https://github.com/biomedbigdata/circRNA-sponging Contact: markus.daniel.hoffmann@tum.de; markus.list@tum.de Supplementary Material: Supplementary data are available at Bioinformatic Advances online.
环状RNA(circRNA)是一类长链非编码RNA(lncRNA),常与疾病相关,被认为是诊断和治疗的潜在生物标志物。除其他功能外,circRNA已被证明可作为微小RNA(miRNA)海绵,阻止miRNA对其靶标的抑制作用。然而,目前尚无系统评估circRNA海绵化潜力的流程。
我们开发了circRNA-sponging,这是一个Nextflow流程,它(1)通过在RNA测序数据中检测到的反向剪接接头来识别circRNA,(2)相对于从同一基因剪接的线性对应物量化其表达值,(3)进行差异表达分析,(4)从miRNA测序(miRNA-seq)数据中识别和量化miRNA表达,(5)预测circRNA上的miRNA结合位点,(6)系统研究潜在的circRNA-miRNA海绵化事件,(7)创建竞争性内源性RNA网络,以及(8)识别潜在的circRNA生物标志物。我们使用脑组织的RNA测序数据展示了circRNA-sponging流程的功能,在该数据中我们识别出两种不同类型的circRNA,其特征在于结合位点数量与转录本长度的特定比例。circRNA-sponging流程是首个利用原始总RNA-seq和miRNA-seq文件系统识别circRNA及其海绵化作用的端到端流程,使我们能够更好地在转录组学研究的常规层面上表明circRNA的功能影响。
https://github.com/biomedbigdata/circRNA-sponging 联系方式:markus.daniel.hoffmann@tum.de;markus.list@tum.de 补充材料:补充数据可在《生物信息学进展》在线获取。