Supplementary data of the paper 'Adaptive trends of sequence compositional complexity over pandemic time in the SARS CoV 2 coronavirus'

Supplement of the paper<br> "Adaptive trends of sequence compositional complexity over pandemic time in the SARS-CoV-2 coronavirus”<br> During the spread of the COVID-19 pandemic, the SARS-CoV-2 coronavirus underwent mutation and recombination events that altered its genome compositional structure, thus providing an unprecedented opportunity to check an evolutionary process in real time. The mutation rate is known to be lower than expected for neutral evolution, suggesting natural selection and convergent evolution. We begin by summarizing the compositional heterogeneity of each viral genome by computing its Sequence Compositional Complexity (SCC). To analyze the full range of SCC diversity, we select random samples of high quality coronavirus genomes covering the full span of the pandemic. We then search for evolutionary trends that could inform us on the adaptive process of the virus to its human host by computing the phylogenetic ridge regression of SCC against time (i.e., the collection date of each viral isolate). In early samples, we find no statistical support for any trend in SCC values, although the viral genome appears to evolve faster than Brownian Motion (BM) expectation. However, in samples taken after the emergence of high fitness variants, and despite the brief time span elapsed, a driven decreasing trend for SCC and an increasing one for its absolute evolutionary rate are detected, pointing to a role for selection in the evolution of SCC in the coronavirus. We conclude that the higher fitness of variant genomes may have leads to adaptive trends of SCC over pandemic time in the coronavirus. Supplementary files <strong>File</strong> <strong>Description</strong> SupplementaryTables S1-S19.zip Excel supplementary tables: The strain name, the collection date, and the SCC values for each analyzed genome. nextstrain_ncov_open_global_timetree.nwk ML phylodynamic tree for the Nextstrain sample SupplementaryTable S20.pdf A complete list acknowledging the authors, originating and submitting laboratories of the genetic sequences we used for the analysis of the Nextstrain sample. Nextstrain_sample_fasta_3059.zip Nextstrain sample (sequences in Fasta format) PhylogeneticTimetrees_NewickFormat.zip Phylogenetic timetrees (Newick format).本文件为论文《新冠病毒大流行时期序列组成复杂度的自适应演化趋势》（"Adaptive trends of sequence compositional complexity over pandemic time in the SARS-CoV-2 coronavirus"）的补充材料。 新冠疫情全球大流行期间，严重急性呼吸综合征冠状病毒2型（SARS-CoV-2）先后发生突变与重组事件，改变了其基因组的组成结构，为实时观测病毒演化过程提供了前所未有的契机。现有研究显示，该病毒的突变率低于中性演化的预期水平，这提示自然选择与趋同演化的存在。 本研究首先通过计算每条病毒基因组的序列组成复杂度（Sequence Compositional Complexity, SCC），对其组成异质性进行量化总结。为全面分析SCC的多样性分布，我们选取了覆盖大流行全周期的高质量冠状病毒基因组随机样本。随后，我们以SCC为响应变量、采样时间（即每株病毒分离株的收集日期）为预测变量开展系统发育岭回归分析，以此探寻病毒适应人类宿主的演化趋势。 在早期样本中，尽管病毒基因组的演化速率似乎快于布朗运动（Brownian Motion, BM）的预期值，但未检测到SCC值存在统计学意义上的显著趋势。然而，在高适应性变异株出现后的样本中，尽管时间跨度较短，我们仍观测到SCC呈现显著下降趋势，而其绝对演化速率则呈上升趋势，这表明选择作用在该冠状病毒SCC的演化中发挥了关键作用。 综上，我们认为变异株基因组的更高适应性，可能推动了新冠病毒在大流行时期SCC的自适应演化趋势。 ### 补充文件说明 - **SupplementaryTables S1-S19.zip**：Excel格式补充表格，包含本次分析所用每条基因组的毒株名称、收集日期及SCC数值。 - **nextstrain_ncov_open_global_timetree.nwk**：用于Nextstrain样本分析的最大似然法系统发育动力学树（ML phylodynamic tree） - **SupplementaryTable S20.pdf**：完整致谢列表，涵盖本研究所用遗传序列的作者、来源实验室及提交实验室信息，用于Nextstrain样本分析。 - **Nextstrain_sample_fasta_3059.zip**：Nextstrain样本（序列格式为Fasta） - **PhylogeneticTimetrees_NewickFormat.zip**：系统发育时间树（格式为Newick格式）