RNA barcode segments for SARS-CoV-2 identification from HCoVs and SARSr-CoV-2 lineages

Changqiao You; Shuai Jiang; Yunyun Ding; Shunxing Ye; Xiaoxiao Zou; Hongming Zhang; Zeqi Li; Fenglin Chen; Yongliang Li; Xingyi Ge; Xinhong Guo

doi:10.1016/j.virs.2024.01.006

February 2024

. doi: 10.1016/j.virs.2024.01.006

Citation: Changqiao You, Shuai Jiang, Yunyun Ding, Shunxing Ye, Xiaoxiao Zou, Hongming Zhang, Zeqi Li, Fenglin Chen, Yongliang Li, Xingyi Ge, Xinhong Guo. RNA barcode segments for SARS-CoV-2 identification from HCoVs and SARSr-CoV-2 lineages .VIROLOGICA SINICA, 2024, 39(1) : 156-168. http://dx.doi.org/10.1016/j.virs.2024.01.006

鉴定HCoVs和SARSr-CoV-2中SARS-CoV-2的RNA条形码片段

游昌乔 ^a ,
蒋帅 ^a ,
丁云云 ^a ,
叶顺兴 ^b ,
邹肖肖 ^a ,
张红明 ^a ,
李泽琦 ^a ,
陈丰林 ^a ,
李永亮 ^a,, ,
葛行义 ^a,, ,
郭新红 ^a,,

a. 湖南大学生物学院, 湖南长沙, 410082;
b. 湖南农业大学生物科学技术学院, 湖南长沙, 410128

通讯作者： 李永亮, lyl13618481357@hnu.edu.cn; 葛行义, xyge@hnu.edu.cn; 郭新红, gxh@hnu.edu.cn
收稿日期： 2023-04-08
录用日期： 2024-01-17

摘要

新型冠状病毒（SARS-CoV-2）作为引起新型冠状病毒感染（COVID-19）的病原体，不断进化产生新变异体，进而导致全球范围内的疫情复发。先前研究表明，条形码片段可以在具有密切系统发育关系的群体中高效、低成本地识别特定物种。在本研究中，基于物种的遗传演化关系，我们构建并测试了SARS-CoV-2的RNA条形码片段，便于从大规模的病毒样本中（例如HCoVs和SARSr-CoV-2谱系）高效且准确地识别SARS-CoV-2。我们从NCBI和GISAID数据库筛选并整理了1733个HCoVs和SARSr-CoV-2谱系的全基因组核苷酸序列用以构建测试集。通过物种的遗传水平测试，验证了条形码片段识别SARS-CoV-2的准确性和可靠性。随后，基于单核苷酸多态性位点和加权分数值大小，我们截取并筛选了75个位于ORF1ab、S、E、ORF7a和N编码区的主要和次要物种SARS-CoV-2特异性条形码片段。经测试，这些片段在鉴定性能上的召回率（接近100%），核苷酸水平上的特异性（接近30%）和精度（100%）表现优秀。最终，以上片段以一维和二维组合条形码的形式实现可视化，并存储至在线数据库（http://virusbarcodedatabase.top/）中。条形码技术鉴定SARS-CoV-2的成功应用不仅为涉及完整基因组序列多态性分析的研究提供有价值的见解。此外，这种高效且具有成本效益的鉴定方法也为未来病毒监测相关研究工作提供了一定参考价值。
- RNA条形码片段
- , 条形码技术
- , 新冠病毒变异株及其相关谱系
- , 人冠状病毒
- , 遗传测试
- , 全基因组序列

RNA barcode segments for SARS-CoV-2 identification from HCoVs and SARSr-CoV-2 lineages

a. College of Biology, Hunan University, Changsha, 410082, China;
b. College of Bioscience and Biotechnology, Hunan Agricultural University, Changsha, 410128, China

Corresponding author: Yongliang Li, lyl13618481357@hnu.edu.cn Xingyi Ge, xyge@hnu.edu.cn Xinhong Guo, gxh@hnu.edu.cn
Received Date: 08 April 2023
Accepted Date: 17 January 2024

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible for coronavirus disease 2019 (COVID-19), continues to evolve, giving rise to more variants and global reinfections. Previous research has demonstrated that barcode segments can effectively and cost-efficiently identify specific species within closely related populations. In this study, we designed and tested RNA barcode segments based on genetic evolutionary relationships to facilitate the efficient and accurate identification of SARS-CoV-2 from extensive virus samples, including human coronaviruses (HCoVs) and SARSr-CoV-2 lineages. Nucleotide sequences sourced from NCBI and GISAID were meticulously selected and curated to construct training sets, encompassing 1733 complete genome sequences of HCoVs and SARSr-CoV-2 lineages. Through genetic-level species testing, we validated the accuracy and reliability of the barcode segments for identifying SARS-CoV-2. Subsequently, 75 main and subordinate species-specific barcode segments for SARS-CoV-2, located in ORF1ab, S, E, ORF7a, and N coding sequences, were intercepted and screened based on single-nucleotide polymorphism sites and weighted scores. Post-testing, these segments exhibited high recall rates (nearly 100%), specificity (almost 30% at the nucleotide level), and precision (100%) performance on identification. They were eventually visualized using one and two-dimensional combined barcodes and deposited in an online database (http://virusbarcodedatabase.top/). The successful integration of barcoding technology in SARS-CoV-2 identification provides valuable insights for future studies involving complete genome sequence polymorphism analysis. Moreover, this cost-effective and efficient identification approach also provides valuable reference for future research endeavors related to virus surveillance.
- RNA barcode segments
- , SARS-CoV-2 variants and related lineages
- , HCoVs
- , Genetic tests
- , Complete genome sequences

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