Shao Yanwen, Guo Zhihao, Chen Jinpeng, Li Runsheng
Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China.
Department of Computer Science, College of Computing, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China.
Brief Bioinform. 2025 Aug 31;26(5). doi: 10.1093/bib/bbaf437.
Spliced leader (SL) trans-splicing occurs in a wide range of eukaryotes and plays a critical role in processing mRNAs derived from operon structures. However, current research on this mechanism remains limited, partly due to the difficulty in accurately identifying genuine SL trans-splicing events. The advent of long-read RNA sequencing technologies, such as direct RNA sequencing by Oxford Nanopore Technologies, offers a more promising avenue for detecting these events with greater resolution. Here, we present SLRanger, an integrated tool to detect SL sequences and predict operon structures in eukaryotic transcriptomes. SLRanger improves upon the traditional Smith-Waterman (SW) alignment framework by incorporating an optimized scoring scheme tailored to SL detection in native long RNA reads. We primarily validated our method using direct RNA sequencing data from Caenorhabditis elegans, a well-established model organism for studying trans-splicing. Through a dynamic cutoff strategy, SLRanger robustly identified high-confidence SL-carrying reads. Leveraging the SL information, SLRanger achieved over 80% accuracy in operon gene prediction, recovering more than 70% of known operon genes in C. elegans. SLRanger was also applied to detect SL from cDNA long RNA reads and another trans-spliced species. Our results demonstrate that SLRanger not only provides a reliable approach for characterizing SL trans-splicing events but also serves as an effective framework for operon discovery, enabling transcriptomic analysis for operons and facilitating downstream data-mining applications.
剪接前导序列（SL）反式剪接发生在广泛的真核生物中，在处理源自操纵子结构的mRNA过程中发挥着关键作用。然而，目前对这种机制的研究仍然有限，部分原因是难以准确识别真正的SL反式剪接事件。长读长RNA测序技术的出现，如牛津纳米孔技术公司的直接RNA测序，为以更高分辨率检测这些事件提供了更有前景的途径。在这里，我们介绍了SLRanger，这是一种用于检测真核转录组中SL序列并预测操纵子结构的集成工具。SLRanger通过纳入一种针对天然长RNA reads中SL检测量身定制的优化评分方案，对传统的史密斯-沃特曼（SW）比对框架进行了改进。我们主要使用秀丽隐杆线虫的直接RNA测序数据验证了我们的方法，秀丽隐杆线虫是研究反式剪接的成熟模式生物。通过动态截止策略，SLRanger稳健地识别出高置信度的携带SL的reads。利用SL信息，SLRanger在操纵子基因预测中达到了80%以上的准确率，在秀丽隐杆线虫中找回了70%以上的已知操纵子基因。SLRanger还被应用于从cDNA长RNA reads和另一种反式剪接物种中检测SL。我们的结果表明，SLRanger不仅为表征SL反式剪接事件提供了一种可靠的方法，而且还作为操纵子发现的有效框架，实现了对操纵子的转录组分析，并促进了下游数据挖掘应用。
