Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA.
Division of Infectious Diseases, Department of Medicine, Stanford University, Stanford, CA, USA.
J Clin Virol. 2022 Dec;157:105323. doi: 10.1016/j.jcv.2022.105323. Epub 2022 Oct 22.
Although most laboratories are capable of employing established protocols to perform full-genome SARS-CoV-2 sequencing, many are unable to assess sequence quality, select appropriate mutation-detection thresholds, or report on the potential clinical significance of mutations in the targets of antiviral therapy METHODS: We describe the technical aspects and benchmark the performance of Sierra SARS-CoV-2, a program designed to perform these functions on user-submitted FASTQ and FASTA sequence files and lists of Spike mutations. Sierra SARS-CoV-2 indicates which sequences contain an unexpectedly large number of unusual mutations and which mutations are associated with reduced susceptibility to clinical stage mAbs, the RdRP inhibitor remdesivir, or the Mpro inhibitor nirmatrelvir RESULTS: To assess the performance of Sierra SARS-CoV-2 on FASTQ files, we applied it to 600 representative FASTQ sequences and compared the results to the COVID-19 EDGE program. To assess its performance on FASTA files, we applied it to nearly one million representative FASTA sequences and compared the results to the GISAID mutation annotation. To assess its performance on mutations lists, we applied it to 13,578 distinct Spike RBD mutation patterns and showed that exactly or partially matching annotations were available for 88% of patterns CONCLUSION: Sierra SARS-CoV-2 leverages previously published data to improve the quality control of submitted viral genomic data and to provide functional annotation on the impact of mutations in the targets of antiviral SARS-CoV-2 therapy. The program can be found at https://covdb.stanford.edu/sierra/sars2/ and its source code at https://github.com/hivdb/sierra-sars2.
虽然大多数实验室都能够采用既定的方案来进行全基因组 SARS-CoV-2 测序,但许多实验室无法评估序列质量、选择适当的突变检测阈值,或报告抗病毒治疗靶点突变的潜在临床意义。
我们描述了 Sierra SARS-CoV-2 的技术方面,并对其性能进行了基准测试,该程序旨在对用户提交的 FASTQ 和 FASTA 序列文件以及 Spike 突变列表执行这些功能。Sierra SARS-CoV-2 会指出哪些序列包含数量异常多的不寻常突变,以及哪些突变与降低对临床阶段单克隆抗体、RdRP 抑制剂瑞德西韦或 Mpro 抑制剂奈玛特韦的敏感性有关。
为了评估 Sierra SARS-CoV-2 在 FASTQ 文件上的性能,我们将其应用于 600 个代表性 FASTQ 序列,并将结果与 COVID-19 EDGE 程序进行比较。为了评估其在 FASTA 文件上的性能,我们将其应用于近 100 万个代表性 FASTA 序列,并将结果与 GISAID 突变注释进行比较。为了评估其在突变列表上的性能,我们将其应用于 13578 个不同的 Spike RBD 突变模式,并表明 88%的模式都有完全或部分匹配的注释。
Sierra SARS-CoV-2 利用先前发表的数据来改善提交的病毒基因组数据的质量控制,并提供抗病毒 SARS-CoV-2 治疗靶点突变影响的功能注释。该程序可在 https://covdb.stanford.edu/sierra/sars2/ 找到,其源代码可在 https://github.com/hivdb/sierra-sars2 找到。