Sun Qianru, Zeng Jinfeng, Tang Kang, Long Haoyu, Zhang Chi, Zhang Jie, Tang Jing, Xin Yuting, Zheng Jialu, Sun Litao, Liu Siyang, Du Xiangjun
School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China.
School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China.
Front Microbiol. 2023 Mar 9;14:1136386. doi: 10.3389/fmicb.2023.1136386. eCollection 2023.
Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Influential variants and mutants of this virus continue to emerge, and more effective virus-related information is urgently required for identifying and predicting new mutants. According to earlier reports, synonymous substitutions were considered phenotypically silent; thus, such mutations were frequently ignored in studies of viral mutations because they did not directly cause amino acid changes. However, recent studies have shown that synonymous substitutions are not completely silent, and their patterns and potential functional correlations should thus be delineated for better control of the pandemic.
In this study, we estimated the synonymous evolutionary rate (SER) across the SARS-CoV-2 genome and used it to infer the relationship between the viral RNA and host protein. We also assessed the patterns of characteristic mutations found in different viral lineages.
We found that the SER varies across the genome and that the variation is primarily influenced by codon-related factors. Moreover, the conserved motifs identified based on the SER were found to be related to host RNA transport and regulation. Importantly, the majority of the existing fixed-characteristic mutations for five important virus lineages (Alpha, Beta, Gamma, Delta, and Omicron) were significantly enriched in partially constrained regions.
Taken together, our results provide unique information on the evolutionary and functional dynamics of SARS-CoV-2 based on synonymous mutations and offer potentially useful information for better control of the SARS-CoV-2 pandemic.
2019冠状病毒病是由严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引起的一种传染病。该病毒的有影响力的变体和突变体不断出现，迫切需要更多有效的病毒相关信息来识别和预测新的突变体。根据早期报告，同义替换被认为在表型上是沉默的；因此，此类突变在病毒突变研究中经常被忽视，因为它们不会直接导致氨基酸变化。然而，最近的研究表明，同义替换并非完全沉默，因此应该描绘它们的模式和潜在的功能相关性，以便更好地控制这一流行病。
在本研究中，我们估计了SARS-CoV-2基因组的同义进化速率（SER），并利用它来推断病毒RNA与宿主蛋白之间的关系。我们还评估了在不同病毒谱系中发现的特征性突变模式。
我们发现SER在整个基因组中有所不同，并且这种变化主要受密码子相关因素的影响。此外，基于SER鉴定出的保守基序与宿主RNA转运和调控有关。重要的是，五个重要病毒谱系（阿尔法、贝塔、伽马、德尔塔和奥密克戎）现有的大多数固定特征突变在部分受限区域显著富集。
综上所述，我们的结果提供了基于同义突变的SARS-CoV-2进化和功能动态的独特信息，并为更好地控制SARS-CoV-2大流行提供了潜在有用的信息。
