Coronaviruses are responsible on respiratory diseases in animal and human. The combination of numerical encoding techniques and digital signal processing methods are becoming increasingly important in handling large genomic data. In this paper, we propose to analyze the SARS-CoV-2 genomic signature using the combination of different nucleotide representations and signal processing tools in the aim to identify its genetic origin. The sequence of SARS-CoV-2 was compared with 21 relevant sequences including Bat, Yak and Pangolin coronavirus sequences. In addition, we developed a new algorithm to locate the nucleotide modifications. The results show that the Bat and Pangolin coronaviruses were the most related to SARS-CoV-2 with 96% and 86% of identity all along the genome. Within the S gene sequence, the Pangolin sequence presents local highest nucleotide identity. Those findings suggest genesis of SARS-Cov-2 through evolution from Bat and Pangolin strains. This study offers new ways to automatically characterize viruses.

冠状病毒与动物和人类的呼吸系统疾病有关。在处理大型基因组数据中，数字编码技术和数字信号处理方法的结合变得越来越重要。在本文中，我们建议使用不同核苷酸表示法和信号处理工具的组合来分析SARS-CoV-2基因组特征，以鉴定其遗传起源。将SARS-CoV-2的序列与21个相关序列，包括蝙蝠，Ya牛和穿山甲冠状病毒序列进行了比较。此外，我们开发了一种新的算法来定位核苷酸修饰。结果表明，蝙蝠和穿山甲冠状病毒与SARS-CoV-2的关系最密切，在整个基因组中的同源性分别为96％和86％。在S基因序列中，穿山甲序列表现出局部最高的核苷酸同一性。这些发现表明SARS-Cov-2是通过从蝙蝠和穿山甲菌株进化而来的。这项研究提供了自动表征病毒的新方法。