Computational Prediction of N6-methyladenosine (m6A) RNA Methylation in SARS-CoV-2 Viral Transcripts

Qingru Xu, Xiangyu Wu, Jia Meng
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Abstract

SARS-CoV-2 caused atypical pneumonia (COVID-19) is an ongoing pandemic that seriously threat the global public health. Many people die from this disease with severe symptoms. The most prevalent m6A RNA modification may be involved in by assisting the virus escaping from the host cell immune system attack. We provided here the first computational prediction study of RNA methylation sites in SARS-CoV-2. Based on virus sequence information, we predict the potential virus m6A sites and hope to make anyhow contributions to this unprecedented situation. As a result, we found 27 most frequent m6A sequences (41 bp) in SARS-CoV-2, and two of them are quite near to the spike protein stop codon position.
SARS-CoV-2病毒转录物中n6 -甲基腺苷(m6A) RNA甲基化的计算预测
SARS-CoV-2引起的非典型肺炎(COVID-19)是一种严重威胁全球公共卫生的持续大流行。许多人死于这种疾病,症状严重。最常见的m6A RNA修饰可能是通过帮助病毒逃避宿主细胞免疫系统的攻击。我们在这里提供了SARS-CoV-2中RNA甲基化位点的首次计算预测研究。根据病毒序列信息,预测潜在的病毒m6A位点,希望对这一前所未有的局面有所贡献。结果,我们在SARS-CoV-2中发现了27个最常见的m6A序列(41 bp),其中两个序列非常接近刺突蛋白停止密码子位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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