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利用嵌合比对信息重建全长 circRNA 序列。

Reconstruction of Full-Length circRNA Sequences Using Chimeric Alignment Information.

机构信息

Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Int J Mol Sci. 2022 Jun 17;23(12):6776. doi: 10.3390/ijms23126776.

Abstract

Circular RNAs (circRNAs) are RNA molecules formed by joining a downstream 3 splice donor site and an upstream 5 splice acceptor site. Several recent studies have identified circRNAs as potential biomarker for different diseases. A number of methods are available for the identification of circRNAs. The circRNA identification methods cannot provide full-length sequences. Reconstruction of the full-length sequences is crucial for the downstream analyses of circRNA research including differential expression analysis, circRNA-miRNA interaction analysis and other functional studies of the circRNAs. However, a limited number of methods are available in the literature for the reconstruction of full-length circRNA sequences. We developed a new method, circRNA-full, for full-length circRNA sequence reconstruction utilizing chimeric alignment information from the STAR aligner. To evaluate our method, we used full-length circRNA sequences produced by isocirc and ciri-long using long-reads RNA-seq data. Our method achieved better reconstruction rate, precision, sensitivity and F1 score than the existing full-length circRNA sequence reconstruction tool ciri-full for both human and mouse data.

摘要

环状 RNA(circRNAs)是由下游 3 个剪接供体位点和上游 5 个剪接受体位点连接形成的 RNA 分子。最近的几项研究已经将 circRNAs 鉴定为不同疾病的潜在生物标志物。有多种方法可用于鉴定 circRNAs。circRNA 鉴定方法无法提供全长序列。circRNA 研究的下游分析(包括差异表达分析、circRNA-miRNA 相互作用分析和 circRNAs 的其他功能研究)需要重建全长序列,这至关重要。然而,文献中仅有少数方法可用于全长 circRNA 序列的重建。我们开发了一种新方法 circRNA-full,利用 STAR 比对器的嵌合比对信息进行全长 circRNA 序列重建。为了评估我们的方法,我们使用了 isocirc 和 ciri-long 利用长读 RNA-seq 数据生成的全长 circRNA 序列。与现有的全长 circRNA 序列重建工具 ciri-full 相比,我们的方法在人类和小鼠数据上的重建率、精度、灵敏度和 F1 评分均有显著提高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/caf9/9223815/9f16dfa5f215/ijms-23-06776-g001.jpg

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