Hottel Wesley, Reeb Valerie, Twait Erik, Zanon Kristen, Hwang Munok, Choi Hosoon, Chatterjee Piyali, Xiang Jinhua, Meier Jeffery, Pentella Michael, McIndoo Eric, Ammons Mary Cloud B, Jinadatha Chetan, Stapleton Jack T
Research Service, Iowa City Veterans Healthcare System, Iowa City, Iowa, USA.
University of Iowa State Hygienic Laboratory, Iowa City, Iowa, USA.
Microbiol Spectr. 2025 Sep 2;13(9):e0042725. doi: 10.1128/spectrum.00427-25. Epub 2025 Aug 12.
There are limited data directly comparing SARS-CoV-2 sequencing methods using two major commercial approaches, Oxford Nanopore Technologies Clear DX (ONTDX) and Illumina. RNA was extracted from 1,513 SARS-CoV-2 RNA-positive respiratory samples, split into two aliquots, and sequenced using both ONTDX and Illumina sequencing methods. FASTQ sequences generated by the ONTDX and Illumina (550 or 2,000) platforms used to test these samples were analyzed using either the same assembly and alignment strategy or using the platform default methodologies. ONTDX and Illumina sequencing results were not significantly different in generating consensus genomes, though slightly better coverage was obtained with ONTDX compared to Illumina. The results were similar using the harmonized assembly and alignment strategy and using the "real-world" platform default assembly and alignment. Approximately 2.5% of samples sequenced were assigned to different sublineages by the different methods, and two samples were assigned to different clades. Median sample storage time ranged from 594 to 970 days before RNA extraction and sequencing, yet >90% genome coverage was achieved in >91.5% of samples. ONTDX and Illumina-based deep sequencing platforms both generate high coverage sequences for SARS-CoV-2. ONTDX performed slightly better than Illumina-based sequencing. Despite a high degree of overall agreement, lineage and clade assignment may differ based on the sequencing and alignment methods used, illustrating the need for caution when comparing phylogenetic relationships based on sequences generated by different platforms. Respiratory samples were also stable and provided high-quality sequencing results following storage for up to 970 days.IMPORTANCESARS-CoV-2-positive respiratory samples from 1,513 individuals were sequenced using the Oxford Nanopore Clear DX platform. Matching aliquots for these were sequenced using either Illumina NextSeq 550 or NextSeq 2000. A harmonized bioinformatic approach compared raw FASTQ files generated by each platform. Differences in coverage and, surprisingly, phylogenetic lineage assignments were observed; thus, assembly and alignments were also compared using the platform default methods. Both platforms generated high coverage for SARS-CoV-2; the Nanopore method was as good, if not slightly better, than Illumina-based sequencing in these studies. Two of 1,546 samples were assigned to different clades by different platforms, and 2.5% of sequences were assigned to different sub-lineages when sequenced by different platforms. These data illustrate that different methods may lead to small differences in phylogenetic assignments and highlight one limitation in the interpretation of outbreak diversity.
关于使用两种主要商业方法(牛津纳米孔技术公司的Clear DX(ONTDX)和Illumina)对严重急性呼吸综合征冠状病毒2(SARS-CoV-2)测序方法进行直接比较的数据有限。从1513份SARS-CoV-2 RNA阳性呼吸道样本中提取RNA,分成两份等分试样,并用ONTDX和Illumina测序方法进行测序。使用相同的组装和比对策略或平台默认方法,对由ONTDX和Illumina(550或2000)平台生成的用于检测这些样本的FASTQ序列进行分析。在生成共有基因组方面,ONTDX和Illumina测序结果没有显著差异,不过与Illumina相比,ONTDX的覆盖度略好。使用统一的组装和比对策略以及使用“实际应用”的平台默认组装和比对,结果相似。约2.5%的测序样本通过不同方法被归为不同的亚谱系,两个样本被归为不同的进化枝。在RNA提取和测序前,样本的中位储存时间为594至970天,但超过91.5%的样本实现了>90%的基因组覆盖。基于ONTDX和Illumina的深度测序平台均能为SARS-CoV-2生成高覆盖度序列。ONTDX的表现略优于基于Illumina的测序。尽管总体一致性程度较高,但根据所使用的测序和比对方法,进化枝和进化分支的归属可能不同,这说明在比较基于不同平台生成的序列的系统发育关系时需要谨慎。呼吸道样本也很稳定,在储存长达970天后仍能提供高质量的测序结果。重要性对1513名个体的SARS-CoV-2阳性呼吸道样本使用牛津纳米孔Clear DX平台进行测序。对这些样本的匹配等分试样使用Illumina NextSeq 550或NextSeq 2000进行测序。一种统一的生物信息学方法对每个平台生成的原始FASTQ文件进行了比较。观察到覆盖度的差异,令人惊讶的是,还有系统发育谱系归属的差异;因此,还使用平台默认方法对组装和比对进行了比较。两个平台都为SARS-CoV-2生成了高覆盖度;在这些研究中,纳米孔方法即便不比基于Illumina的测序略好,也与之一样好。1546个样本中有两个通过不同平台被归为不同的进化枝,当用不同平台测序时,2.5%的序列被归为不同的亚谱系。这些数据表明,不同方法可能导致系统发育归属上的细微差异,并突出了在解释疫情多样性方面的一个局限性。