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Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2
medRxiv - Genetic and Genomic Medicine Pub Date : 2021-10-19 , DOI: 10.1101/2020.12.23.20248612
Dalang Yu , Xiao Yang , Bixia Tang , Yi-Hsuan Pan , Jianing Yang , Junwei Zhu , Guangya Duan , Zi-Qian Hao , Hailong Mu , Long Dai , Wangjie Hu , Xiao Su , Guo-Qing Zhang , Wenming Zhao , Haipeng Li ,

Genomic epidemiology is important to study the COVID-19 pandemic and more than two million SARS-CoV-2 genomic sequences were deposited into public databases. However, the exponential increase of sequences invokes unprecedented bioinformatic challenges. Here, we present the Coronavirus GenBrowser (CGB) based on a highly efficient analysis framework and a movie maker strategy. In total, 1,002,739 high quality genomic sequences with the transmission-related metadata were analyzed and visualized. The size of the core data file is only 12.20 MB, efficient for clean data sharing. Quick visualization modules and rich interactive operations are provided to explore the annotated SARS-CoV-2 evolutionary tree. CGB binary nomenclature is proposed to name each internal lineage. The pre-analyzed data can be filtered out according to the user-defined criteria to explore the transmission of SARS-CoV-2. Different evolutionary analyses can also be easily performed, such as the detection of accelerated evolution and on-going positive selection. Moreover, the 75 genomic spots conserved in SARS-CoV-2 but non-conserved in other coronaviruses were identified, which may indicate the functional elements specifically important for SARS-CoV-2. The CGB not only enables users who have no programming skills to analyze millions of genomic sequences, but also offers a panoramic vision of the transmission and evolution of SARS-CoV-2.

中文翻译:

用于监测 SARS-CoV-2 传播和进化的冠状病毒 GenBrowser

基因组流行病学对于研究 COVID-19 大流行很重要,超过 200 万个 SARS-CoV-2 基因组序列已存入公共数据库。然而,序列的指数增长引发了前所未有的生物信息学挑战。在这里,我们展示了基于高效分析框架和电影制作者策略的冠状病毒 GenBrowser (CGB)。总共分析和可视化了 1,002,739 个具有传输相关元数据的高质量基因组序列。核心数据文件大小仅为12.20 MB,高效干净的数据共享。提供快速可视化模块和丰富的交互操作来探索带注释的 SARS-CoV-2 进化树。建议使用 CGB 二进制命名法来命名每个内部谱系。可以根据用户定义的标准过滤掉预先分析的数据,以探索 SARS-CoV-2 的传播。还可以轻松执行不同的进化分析,例如检测加速进化和持续的正选择。此外,鉴定了在 SARS-CoV-2 中保守但在其他冠状病毒中不保守的 75 个基因组点,这可能表明对 SARS-CoV-2 特别重要的功能元件。CGB 不仅可以让没有编程技能的用户分析数百万个基因组序列,还可以提供 SARS-CoV-2 传播和进化的全景图。鉴定了在 SARS-CoV-2 中保守但在其他冠状病毒中不保守的 75 个基因组点,这可能表明对 SARS-CoV-2 特别重要的功能元件。CGB 不仅可以让没有编程技能的用户分析数百万个基因组序列,还可以提供 SARS-CoV-2 传播和进化的全景图。鉴定了在 SARS-CoV-2 中保守但在其他冠状病毒中不保守的 75 个基因组点,这可能表明对 SARS-CoV-2 特别重要的功能元件。CGB 不仅可以让没有编程技能的用户分析数百万个基因组序列,还可以提供 SARS-CoV-2 传播和进化的全景图。
更新日期:2021-10-22
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