The emergence of high-fitness variants accelerates the slowdown of genome heterogeneity in the coronavirus

Supplement of the paper “The emergence of high-fitness variants accelerates the slowdown of genome heterogeneity in the coronavirus” Since the outbreak of the COVID-19 pandemic, the SARS-CoV-2 coronavirus accumulated an important amount of genome variability through mutation and recombination. To test evolutionary trends that could inform us on the adaptive process of the virus to its human host, we compute a genome-wide measure of Sequence Compositional Complexity (<em>SCC</em>) in high-quality coronavirus genomes from across the globe, covering the full span of the pandemic. By using phylogenetic ridge regression, a method able to reveal both macro- and microevolutionary trends, we present evidence for a long-term tendency of decreasing genome sequence heterogeneity in SARS-CoV-2. In early samples, we find no statistical support for any trend in <em>SCC</em> values over time, although the virus genome appears to evolve faster than Brownian Motion expectation. However, in samples taken after the emergence of Variants of Concern with higher transmissibility, and controlling for phylogenetic and sampling effects, we detect a declining trend for <em>SCC</em> and an increasing one for its absolute evolutionary rate. This means that the decline in <em>SCC</em> itself accelerated over time, and that increasing fitness of variant genomes lead to a reduction of their genome sequence heterogeneity. Supplementary files <strong>File</strong> <strong>Description</strong> SupplementaryTables S1-S18.xlsx The strain name, the collection date, and the SCC values for each analyzed genome. SupplementaryTableS19.pdf A complete list acknowledging all originating and submitting laboratories for the sequence data in GISAID EpiCoV on which these analyses are based. 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. PhylogeneticTimetrees_NexusFormat.zip Phylogenetic timetrees (Nexus format). PhylogeneticTimetrees_NewickFormat.zip Phylogenetic timetrees (Newick format).本补充材料为论文《高适应性变异株的出现加速冠状病毒基因组异质性衰减》（The emergence of high-fitness variants accelerates the slowdown of genome heterogeneity in the coronavirus）的补充材料。自新型冠状病毒肺炎（COVID-19）疫情暴发以来，严重急性呼吸综合征冠状病毒2（SARS-CoV-2）通过突变与重组积累了大量具有重要研究价值的基因组变异。为探究能够揭示该病毒对人类宿主适应进程的演化趋势，我们针对覆盖全球疫情全周期的高质量冠状病毒基因组，计算了全基因组范围的序列组成复杂性（Sequence Compositional Complexity，SCC）指标。本研究采用可同时揭示宏观与微观演化趋势的系统发育岭回归方法，为SARS-CoV-2基因组序列异质性长期呈下降趋势提供了实证支撑。在早期样本中，尽管病毒基因组的演化速率看似高于布朗运动的预期水平，但未检测到SCC值随时间变化存在统计学显著趋势。然而，在高传播性关切变异株出现后采集的样本中，在控制系统发育与采样效应的前提下，我们观测到SCC呈下降趋势，而其绝对演化速率则呈上升趋势。这意味着SCC的衰减本身随时间不断加快，且变异株基因组适应性的提升会导致其基因组序列异质性降低。 补充文件： 1. SupplementaryTables S1-S18.xlsx：包含所有分析基因组的毒株名称、采集日期及对应SCC值。 2. SupplementaryTableS19.pdf：完整列出本研究分析所依托的GISAID EpiCoV数据库中序列数据的所有来源实验室与提交实验室。 3. SupplementaryTable S20.pdf：完整列出本研究用于Nextstrain样本分析的遗传序列的作者、来源实验室及提交实验室。 4. PhylogeneticTimetrees_NexusFormat.zip：Nexus格式的系统发育时间树压缩包。 5. PhylogeneticTimetrees_NewickFormat.zip：Newick格式的系统发育时间树压缩包。