Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified a viral load threshold that minimizes false positives. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.

中文翻译：

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SARS-CoV-2突变在宿主内和宿主间积累的时间动态

对受感染宿主内SARS-CoV-2遗传多样性的分析可以洞悉新病毒变体的产生和传播，并可以高分辨率推断出传播链。然而，关于SARS-CoV-2宿主内部多样性的时间方面以及共享多样性反映融合进化而不是传输链接的程度知之甚少。在这里，我们使用深度覆盖测序技术，从单个医疗中心的住院COVID-19患者和受感染员工的325个标本中鉴定出宿主内部的遗传变异。我们通过对定义的RNA混合物进行测序来验证我们的变异检测，并确定了将假阳性率降至最低的病毒载量阈值。通过利用临床元数据，我们发现宿主内部的多样性很低，并且从症状发作的时间来看并没有变化。这表明，变体在传输之前几乎不会上升到可观的频率。尽管总体上在测序队列中几乎没有共享的变异，但我们确定了个体之间共享的宿主内变异，这些变异不太可能与传播相关。这些变体并未出现在全球共有基因组频率上升之前，这表明宿主内变体在预测未来谱系方面的效用可能有限。这些结果为SARS-CoV-2进化和流行病学中基于序列的推断提供了重要背景。这些变体并未出现在全球共有基因组频率上升之前，这表明宿主内变体在预测未来谱系方面的效用可能有限。这些结果为SARS-CoV-2进化和流行病学中基于序列的推断提供了重要背景。这些变体并未出现在全球共有基因组频率上升之前，这表明宿主内变体在预测未来谱系方面的效用可能有限。这些结果为SARS-CoV-2进化和流行病学中基于序列的推断提供了重要背景。