Mapping the Shapes of Phylogenetic Trees from Human and Zoonotic RNA Viruses

A phylogeny is a tree-based model of common ancestry that is an indispensable tool for studying biological variation. Phylogenies play a special role in the study of rapidly evolving populations such as viruses, where the proliferation of lineages is constantly being shaped by the mode of virus transmission, by adaptation to immune systems, and by patterns of human migration and contact. These processes may leave an imprint on the shapes of virus phylogenies that can be extracted for comparative study; however, tree shapes are intrinsically difficult to quantify. Here we present a comprehensive study of phylogenies reconstructed from 38 different RNA viruses from 12 taxonomic families that are associated with human pathologies. To accomplish this, we have developed a new procedure for studying phylogenetic tree shapes based on the ‘kernel trick’, a technique that maps complex objects into a statistically convenient space. We show that our kernel method outperforms nine different tree balance statistics at correctly classifying phylogenies that were simulated under different evolutionary scenarios. Using the kernel method, we observe patterns in the distribution of RNA virus phylogenies in this space that reflect modes of transmission and pathogenesis. For example, viruses that can establish persistent chronic infections (such as HIV and hepatitis C virus) form a distinct cluster. Although the visibly ‘star-like’ shape characteristic of trees from these viruses has been well-documented, we show that established methods for quantifying tree shape fail to distinguish these trees from those of other viruses. The kernel approach presented here potentially represents an important new tool for characterizing the evolution and epidemiology of RNA viruses.系统发育（phylogeny）是一种基于树结构的共同祖先模型，是研究生物变异不可或缺的工具。系统发育在病毒等快速演化种群的研究中具有特殊价值：病毒谱系的增殖始终受病毒传播方式、宿主免疫系统适应性以及人类迁徙与接触模式的共同塑造。上述过程会在病毒系统发育树的形态上留下特定印记，可用于后续比较研究；然而，树的形态本质上难以量化分析。本研究针对来自12个分类科、与人类疾病相关的38种不同RNA病毒（RNA viruses）的重建系统发育树开展了全面分析。为此，我们开发了一种基于核技巧（kernel trick）的全新分析流程以研究系统发育树形态——核技巧是一种将复杂对象映射至统计上便于处理的空间的技术手段。我们证实，相较于9种不同的树平衡统计量（tree balance statistics），本研究提出的核方法能够更精准地对不同演化场景下模拟生成的系统发育树进行分类。借助该核方法，我们观察到本研究收录的RNA病毒系统发育树在该映射空间中的分布模式可反映其传播方式与致病机制。例如，能够建立持续性慢性感染的病毒（如人类免疫缺陷病毒（HIV）与丙型肝炎病毒（hepatitis C virus））形成了独立的聚类簇。尽管这类病毒的系统发育树所具有的典型“星状”形态已被广泛记录，但现有树形态量化方法无法将这类树与其他病毒的树结构有效区分。本文提出的核方法有望成为表征RNA病毒演化与流行病学特征的重要新型工具。