Genomic determinants in pathogenicity of SARS-CoV-2 versa common cold coronaviruses

Determination of the different short oligonucleotide features in the full genome of fatal and mild coronavirus strains can show the researchers how these viruses evolved and became virulent strains. To this aim, at first, in the full genome of all coronavirus strains included in this study, the observed and expected frequency of dinucleotide to hexanucleotide was obtained using Markov method. Then odds ratio (observed/expected abundances) of short oligonucleotide was computed and considered as the raw data (features). Finally, ten distinct weighting algorithms approaches (Information Gain, Information Gain Ratio, Rule, Deviation, Chi Squared, Gini Index, Uncertainty, Relief, Support Vector Machine (SVM), and PCA) was employed on the features to identify oligonucleotide distribution differences across the full genome of SARS-related viruses compared to common cold coronaviruses. Totally among 5440 features (16 dinucleotides, 64 trinucleotides, 256 tetra nucleotides, 1024 penta-nucleotides, and 4096 Hexa-nucleotides), CC, CCA, CCAC, ACCAC, and CACCAC motifs were selected by 80 -90% of all weighting algorithms models to distinguish virulent strains from mild coronaviruses. These remarkable oligonucleotides might point toward the existence of some particular RNA elements that might be involved in viral virulence and thus can be targeted for viral treatment in the future.

对致死性与轻症冠状病毒毒株全基因组中各类短寡核苷酸（oligonucleotide）特征进行解析，可帮助研究者揭示这类病毒的演化历程及其向强毒株转化的分子机制。为此，本研究首先基于马尔可夫（Markov）方法，获取纳入研究的所有冠状病毒毒株全基因组中二核苷酸（dinucleotide）至六核苷酸（hexanucleotide）的观测频率与期望频率；随后计算短寡核苷酸的比值比（观测丰度/期望丰度），并将其作为原始数据（特征）。最后，本研究采用10种不同的特征加权算法（信息增益(Information Gain)、信息增益比(Information Gain Ratio)、规则(Rule)、偏差(Deviation)、卡方检验(Chi Squared)、基尼指数(Gini Index)、不确定性系数(Uncertainty)、Relief算法、支持向量机(SVM)、主成分分析(PCA)）对上述特征进行分析，以区分SARS相关冠状病毒与普通感冒冠状病毒在全基因组水平上的寡核苷酸分布差异。在总计5440个特征（16个二核苷酸、64个三核苷酸、256个四核苷酸、1024个五核苷酸及4096个六核苷酸）中，80%~90%的加权算法模型均筛选出CC、CCA、CCAC、ACCAC及CACCAC基序，用于区分强毒株与轻症冠状病毒毒株。上述筛选得到的特征寡核苷酸，或提示存在与病毒毒力相关的特定RNA元件，未来可作为病毒治疗的潜在靶点。