SARS-CoV-2 单核苷酸多态性与感染期间病毒拷贝之间的全基因组关联研究。

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
PLoS Computational Biology Pub Date : 2024-09-17 eCollection Date: 2024-09-01 DOI:10.1371/journal.pcbi.1012469
Ke Li, Chrispin Chaguza, Julian Stamp, Yi Ting Chew, Nicholas F G Chen, David Ferguson, Sameer Pandya, Nick Kerantzas, Wade Schulz, Anne M Hahn, C Brandon Ogbunugafor, Virginia E Pitzer, Lorin Crawford, Daniel M Weinberger, Nathan D Grubaugh
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引用次数: 0

摘要

据观察,SARS-CoV-2 感染期间产生的病毒拷贝有很大差异。然而,影响病毒拷贝和感染动态的因素还不完全清楚,而且可能与不同的病毒和宿主因素有内在联系。在这里,我们对病毒进行了全基因组测序,并使用 RT-qPCR 对 2 年内 9902 例 SARS-CoV-2 感染者的病毒拷贝进行了测量,以研究病毒基因变异对病毒拷贝变化的影响,并对宿主年龄和疫苗接种情况进行了调整。通过全基因组关联研究(GWAS)方法,我们确定了与病毒拷贝变化相关的 SARS-CoV-2 基因组氨基酸变化相对应的多个单核苷酸多态性(SNPs)。我们进一步应用边际外显率检验来检测 SNP 之间的相互作用,并确定了位于尖峰基因中的多对取代对病毒拷贝具有非线性影响。我们还分析了时间模式,发现与病毒拷贝增加相关的 SNPs 主要出现在 Delta 和 Omicron BA.2/BA.4/BA.5/XBB 感染中,而与病毒拷贝减少相关的 SNPs 仅出现在 Omicron BA.1 变异感染中。我们的工作展示了 GWAS 如何成为一种有用的工具,用于探测与病毒基因组中值得进一步探索的 SNP 相关的表型。我们认为,这种方法可以更广泛地应用于各种病原体,以描述新出现的变异并监测治疗干预措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections.

Significant variations have been observed in viral copies generated during SARS-CoV-2 infections. However, the factors that impact viral copies and infection dynamics are not fully understood, and may be inherently dependent upon different viral and host factors. Here, we conducted virus whole genome sequencing and measured viral copies using RT-qPCR from 9,902 SARS-CoV-2 infections over a 2-year period to examine the impact of virus genetic variation on changes in viral copies adjusted for host age and vaccination status. Using a genome-wide association study (GWAS) approach, we identified multiple single-nucleotide polymorphisms (SNPs) corresponding to amino acid changes in the SARS-CoV-2 genome associated with variations in viral copies. We further applied a marginal epistasis test to detect interactions among SNPs and identified multiple pairs of substitutions located in the spike gene that have non-linear effects on viral copies. We also analyzed the temporal patterns and found that SNPs associated with increased viral copies were predominantly observed in Delta and Omicron BA.2/BA.4/BA.5/XBB infections, whereas those associated with decreased viral copies were only observed in infections with Omicron BA.1 variants. Our work showcases how GWAS can be a useful tool for probing phenotypes related to SNPs in viral genomes that are worth further exploration. We argue that this approach can be used more broadly across pathogens to characterize emerging variants and monitor therapeutic interventions.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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