Maimaiti Mulatijiang, Kong Lingjun, Yu Qi, Wang Ziyi, Liu Yiwei, Yang Chenglin, Guo Wenhu, Jin Lijun, Yi Jie
Department of Clinical Laboratory, Peking Union Medical College Hospital, Beijing, China.
R&D center, Fuzhou Agenmic Biotechnology Co. Ltd., Fuzhou, China.
J Med Virol. 2024 Dec;96(12):e70108. doi: 10.1002/jmv.70108.
The genomic analysis of SARS-CoV-2 has served as a crucial tool for generating invaluable data that fulfils both epidemiological and clinical necessities. Long-read sequencing technology (e.g., ONT) has been widely used, providing a real-time and faster response when necessitated. A novel nanopore-based long-read sequencing platform named QNome nanopore has been successfully used for bacterial genome sequencing and assembly; however, its performance in the SARS-CoV-2 genomic surveillance is still lacking. Synthetic SARS-CoV-2 controls and 120 nasopharyngeal swab (NPS) samples that tested positive by real-time polymerase chain reaction were sequenced on both QNome and MGI platforms in parallel. The analytical performance of QNome was compared to the short-read sequencing on MGI. For the synthetic SARS-CoV-2 controls, despite the increased error rates observed in QNome nanopore sequencing reads, accurate consensus-level sequence determination was achieved with an average mapping quality score of approximately 60 (i.e., a mapping accuracy of 99.9999%). For the NPS samples, the average genomic coverage was 89.35% on the QNome nanopore platform compared with 90.39% for MGI. In addition, fewer consensus genomes from QNome were determined to be good by Nextclade compare with MGI (p < 0.05). A total of 9004 mutations were identified using QNome sequencing, with substitutions being the most prevalent, in contrast, 10 997 mutations were detected on MGI (p < 0.05). Furthermore, 23 large deletions (i.e., deletions≥ 10 bp) were identified by QNome while 19/23 were supported by evidence from short-read sequencing. Phylogenetic analysis revealed that the Pango lineage of consensus genomes for SARS-CoV-2 sequenced by QNome concorded 83.04% with MGI. QNome nanopore sequencing, though challenged by read quality and accuracy compared to MGI, is overcoming these issues through bioinformatics and computational advances. The advantage of structure variation (SV) detection capabilities and real-time data analysis renders it a promising alternative nanopore platform for the surveillance of the SARS-CoV-2.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）的基因组分析已成为生成满足流行病学和临床需求的宝贵数据的关键工具。长读长测序技术（如ONT）已被广泛应用，在必要时能提供实时且更快的响应。一种名为QNome纳米孔的新型基于纳米孔的长读长测序平台已成功用于细菌基因组测序和组装；然而，其在SARS-CoV-2基因组监测中的性能仍有待提高。在QNome和MGI平台上对合成的SARS-CoV-2对照品以及120份经实时聚合酶链反应检测呈阳性的鼻咽拭子（NPS）样本进行了平行测序。将QNome的分析性能与MGI上的短读长测序进行了比较。对于合成的SARS-CoV-2对照品，尽管在QNome纳米孔测序读数中观察到错误率增加，但通过平均映射质量得分约为60（即映射准确率为99.9999%）实现了准确的一致性水平序列测定。对于NPS样本，QNome纳米孔平台上的平均基因组覆盖率为89.35%，而MGI为90.39%。此外，与MGI相比，Nextclade判定QNome的一致性基因组中优质基因组较少（p < 0.05）。使用QNome测序共鉴定出9004个突变，其中替换最为常见，相比之下，在MGI上检测到10997个突变（p < 0.05）。此外，QNome鉴定出23个大缺失（即缺失≥ 10 bp），其中19/23得到短读长测序证据的支持。系统发育分析表明，QNome测序的SARS-CoV-2一致性基因组的Pango谱系与MGI的一致性为83.04%。QNome纳米孔测序虽然与MGI相比受到读数质量和准确性的挑战，但正在通过生物信息学和计算方面的进展克服这些问题。其结构变异（SV）检测能力和实时数据分析的优势使其成为SARS-CoV-2监测的一个有前景的替代纳米孔平台。
