Guo Xiaoyu, Wu Zhenming, Zhang Shu, Zhao Jin
School of Computer Science and Technology, Qingdao University, Ningxia Road, Qingdao, Shandong Province, 266071, China.
BMC Genomics. 2024 Dec 30;25(1):1257. doi: 10.1186/s12864-024-11179-0.
Discontinuous transcription allows coronaviruses to efficiently replicate and transmit within host cells, enhancing their adaptability and survival. Assembling viral transcripts is crucial for virology research and the development of antiviral strategies. However, traditional transcript assembly methods primarily designed for variable alternative splicing events in eukaryotes are not suitable for the viral transcript assembly problem. The current algorithms designed for assembling viral transcripts often struggle with low accuracy in determining the transcript boundaries. There is an urgent need to develop a highly accurate viral transcript assembly algorithm.
In this work, we propose Cov-trans, a reference-based transcript assembler specifically tailored for the discontinuous transcription of coronaviruses. Cov-trans first identifies canonical transcripts based on discontinuous transcription mechanisms, start and stop codons, as well as reads alignment information. Subsequently, it formulates the assembly of non-canonical transcripts as a path extraction problem, and introduces a mixed integer linear programming to recover these non-canonical transcripts.
Experimental results show that Cov-trans outperforms other assemblers in both accuracy and recall, with a notable strength in accurately identifying the boundaries of transcripts. Cov-trans is freely available at https://github.com/computer-Bioinfo/Cov-trans.git .
不连续转录使冠状病毒能够在宿主细胞内高效复制和传播，增强其适应性和生存能力。组装病毒转录本对于病毒学研究和抗病毒策略的开发至关重要。然而，传统的转录本组装方法主要是为真核生物中可变的可变剪接事件设计的，不适用于病毒转录本组装问题。当前设计用于组装病毒转录本的算法在确定转录本边界时往往准确性较低。迫切需要开发一种高度准确的病毒转录本组装算法。
在这项工作中，我们提出了Cov-trans，一种专门为冠状病毒的不连续转录量身定制的基于参考的转录本组装器。Cov-trans首先基于不连续转录机制、起始和终止密码子以及读段比对信息识别标准转录本。随后，它将非标准转录本的组装表述为一个路径提取问题，并引入混合整数线性规划来恢复这些非标准转录本。
实验结果表明，Cov-trans在准确性和召回率方面均优于其他组装器，在准确识别转录本边界方面具有显著优势。Cov-trans可在https://github.com/computer-Bioinfo/Cov-trans.git上免费获取。
