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Evolutionary Frequency of Initially Sequenced Human Coronavirus Genomes 初步测序的人类冠状病毒基因组的进化频率
Pub Date : 2021-08-01 DOI: 10.32350/cto.11.02
Hamid Ur Rahman, Sidra Majaz, Aamir Saeed, Ashfaq Ahmad
A novel, human-infecting coronavirus causing COVID-19 was first identified in Wuhan, China in December 2019. Within a short span of time the virus recorded more than 1 million deaths, worldwide. This study addresses the overall evolutionary process from complete genomes of COVID-19. Addressing the complexity of the task, network-based approaches were used in mapping samples to their reported locations. A total of 473 complete human coronavirus genomes from 20 different countries were studied, including samples from 17 states of the United States and samples from the Cruise-Diamond Princess. The phylodynamic network of a global scale was classified into five clusters containing two clusters of the samples from the USA. Cluster B was a shared cluster of samples from China and the USA, while clusters A and C were of a diverse nature. Chinese samples aggregated in clusters A and B which aided in retaining the homogeneous viral genomic pool. In contrast, samples from the USA and Spain were split into distinct clusters which indicated multiple port entries and a possibility of implying a delay in quarantine measures. In the intra-USA samples, we found that sequences reported from Washington and Virginia were scattered indicating evolutionary diversity. This report provides an insight into the transmission pattern of CoV2, which is complicated to evaluate exclusively through the conventional surveillance means.
2019年12月,一种导致COVID-19的新型人类感染冠状病毒首次在中国武汉被发现。在很短的时间内,该病毒在全球造成了100多万人死亡。本研究解决了COVID-19全基因组的整体进化过程。为了解决任务的复杂性,基于网络的方法被用于将样本映射到其报告的位置。研究人员共研究了来自20个不同国家的473个完整的人类冠状病毒基因组,其中包括来自美国17个州的样本和来自钻石公主号游轮的样本。全球尺度的系统动力学网络被划分为5个集群,其中包括来自美国的2个集群。聚类B是来自中国和美国的样本的共享聚类,而聚类a和C具有多样性。中国样本聚集在聚类A和B中,这有助于保持同质病毒基因组库。相比之下,来自美国和西班牙的样本被分成不同的聚集群,这表明有多个港口入境,可能意味着检疫措施的延迟。在美国内部的样本中,我们发现来自华盛顿和弗吉尼亚的序列是分散的,表明进化多样性。该报告提供了对冠状病毒2的传播模式的深入了解,仅通过常规监测手段很难对其进行评估。
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Current Trends in OMICS
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