背景:准确的基因组序列构成了基因组监测计划的基础,其附加值在COVID-19大流行期间通过追踪传播链得到了令人印象深刻的证明,发现新的病毒谱系和突变,并评估它们的传染性和对现有治疗的抵抗力。采用Illumina测序的扩增子策略已被广泛建立,用于SARS-CoV-2基因组的变异检测和基于参考的重建。是常规的生物信息学任务。然而,分析扩增子数据时会出现特定的挑战,例如,当关键甚至谱系决定突变发生在引物位点附近时。方法:我们介绍了CoVpipe2,这是德国公共卫生研究所开发的生物信息学工作流程,用于根据短读取测序数据准确重建SARS-CoV-2基因组。这里的决定性因素是可靠的,准确,快速重建基因组,考虑所用测序方案的细节。除了质量控制等基本任务,映射,变体调用,和共识一代,我们还实施了其他功能,以简化混合样品和重组体的检测。结果:我们强调了引物剪切中的常见陷阱,检测杂合子变异,处理低覆盖率区域和删除。我们引入CoVpipe2来解决上述挑战,并将管道与选定的公开可用基准数据集进行了比较并成功验证。CoVpipe2具有高可用性,再现性,和模块化设计,专门解决短读取扩增子方案的特征,但也可用于全基因组短读取测序数据。结论:CoVpipe2经历了多个改进周期,并与不断更新的引物方案和科学界的新进展一起持续维护。我们的管道易于设置和使用,由于其灵活性和模块化,可以作为未来其他病原体的蓝图,为持续支持提供长期视角。CoVpipe2是在Nextflow中编写的,可根据GPL3许可证从\\href{https://github.com/rki-mf1/CoVpipe2}{github.com/rki-mf1/CoVpipe2}自由访问。
UNASSIGNED: Accurate genome sequences form the basis for genomic surveillance programs, the added value of which was impressively demonstrated during the COVID-19 pandemic by tracing transmission chains, discovering new viral lineages and mutations, and assessing them for infectiousness and resistance to available treatments. Amplicon strategies employing Illumina sequencing have become widely established for variant detection and reference-based reconstruction of SARS-CoV-2 genomes, and are routine bioinformatics tasks. Yet, specific challenges arise when analyzing amplicon data, for example, when crucial and even lineage-determining mutations occur near primer sites.
UNASSIGNED: We present CoVpipe2, a bioinformatics workflow developed at the Public Health Institute of Germany to reconstruct SARS-CoV-2 genomes based on short-read sequencing data accurately. The decisive factor here is the reliable, accurate, and rapid reconstruction of genomes, considering the specifics of the used sequencing protocol. Besides fundamental tasks like quality control, mapping, variant calling, and consensus generation, we also implemented additional features to ease the detection of mixed samples and recombinants.
UNASSIGNED: We highlight common pitfalls in primer clipping, detecting heterozygote variants, and dealing with low-coverage regions and deletions. We introduce CoVpipe2 to address the above challenges and have compared and successfully validated the pipeline against selected publicly available benchmark datasets. CoVpipe2 features high usability, reproducibility, and a modular design that specifically addresses the characteristics of short-read amplicon protocols but can also be used for whole-genome short-read sequencing data.
UNASSIGNED: CoVpipe2 has seen multiple improvement cycles and is continuously maintained alongside frequently updated primer schemes and new developments in the scientific community. Our pipeline is easy to set up and use and can serve as a blueprint for other pathogens in the future due to its flexibility and modularity, providing a long-term perspective for continuous support. CoVpipe2 is written in Nextflow and is freely accessible from \\href{https://github.com/rki-mf1/CoVpipe2}{github.com/rki-mf1/CoVpipe2} under the GPL3 license.