We introduce VERSO, a two-step framework for the characterization of viral evolution from sequencing data of viral genomes, which improves over phylogenomic approaches for consensus sequences. VERSO exploits an efficient algorithmic strategy to return robust phylogenies from clonal variant profiles, also in conditions of sampling limitations. It then leverages variant frequency patterns to characterize the intra-host genomic diversity of samples, revealing undetected infection chains and pinpointing variants likely involved in homoplasies. On simulations, VERSO outperforms state-of-the-art tools for phylogenetic inference. Notably, the application to 6726 Amplicon and RNA-seq samples refines the estimation of SARS-CoV-2 evolution, while co-occurrence patterns of minor variants unveil undetected infection paths, which are validated with contact tracing data. Finally, the analysis of SARS-CoV-2 mutational landscape uncovers a temporal increase of overall genomic diversity, and highlights variants transiting from minor to clonal state and homoplastic variants, some of which falling on the spike gene. Available at: https://github.com/BIMIB-DISCo/VERSO.

中文翻译：

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VERSO：推断鲁棒系统发育和定量病毒样品宿主内基因组多样性的综合框架

我们介绍了VERSO，这是一个从病毒基因组测序数据表征病毒进化的两步框架，它比共识序列的植物学方法有所改进。VERSO利用有效的算法策略，即使在采样受限的情况下，也可以从克隆变异谱中返回强大的系统发育。然后，它利用变异的频率模式来表征样品的宿主内部基因组多样性，揭示未检测到的感染链，并查明可能与同源性有关的变异。在仿真中，VERSO优于最新的系统发育推断工具。值得注意的是，对6726扩增子和RNA-seq样品的应用完善了SARS-CoV-2进化的估计，而次要变体的共现模式揭示了未发现的感染途径，通过联系人跟踪数据进行了验证。最后，对SARS-CoV-2突变态势的分析揭示了总体基因组多样性随时间的增加，并突出了从小状态过渡到克隆状态的变异和同型变异，其中一些落在穗基因上。可在以下网址获得：https：//github.com/BIMIB-DISCo/VERSO。