Sevillya Gur
Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
Access Microbiol. 2022 Feb 16;4(2):000265. doi: 10.1099/acmi.0.000265. eCollection 2022.
New insights in evolution are available thanks to next-generation sequencing technologies in recent years. However, due to the network of complex relations between species, caused by the intensive horizontal gene transfer (HGT) between different bacterial species, it is difficult to discover bacterial evolution. This difficulty leads to new research in the field of phylogeny, including the gene-based phylogeny, in contrast to sequence-based phylogeny. In previous articles, we presented evolutionary insights of Synteny Index (SI) study on a large biological dataset. We showed that the SI approach naturally clusters 1133 species into 39 cliques of closely related species. In addition, we presented a model that enables calculation of the number of translocation events between genomes based on their SI distance. Here, these two studies are combined together and lead to new insights. A principal result is the relation between two evolutionary clocks: the well-known sequence-based clock influenced by point mutations, and SI distance clock influenced by translocation events. A surprising linear relation between these two evolutionary clocks rising for closely related species across all genus. In other words, these two different clocks are ticking at the same rate inside the genus level. Conversely, a phase-transition manner discovered between these two clocks across non-closely related species. This may suggest a new genus definition based on an analytic approach, since the phase-transition occurs where each gene, on average, undergoes one translocation event. In addition, rare cases of HGT among highly conserved genes can be detected as outliers from the phase-transition pattern.
近年来,得益于新一代测序技术,我们对进化有了新的认识。然而,由于不同细菌物种之间密集的水平基因转移(HGT)导致物种间存在复杂的关系网络,因此很难发现细菌的进化过程。这一难题促使了系统发育领域的新研究,包括与基于序列的系统发育不同的基于基因的系统发育。在之前的文章中,我们展示了关于一个大型生物数据集的共线性指数(SI)研究的进化见解。我们表明,SI方法自然地将1133个物种聚类为39个亲缘关系密切的物种团。此外,我们提出了一个模型,该模型能够根据基因组之间的SI距离计算基因组间易位事件的数量。在此,这两项研究结合在一起并带来了新的见解。一个主要结果是两个进化时钟之间的关系:一个是受点突变影响的著名的基于序列的时钟,另一个是受易位事件影响的SI距离时钟。在所有属中,这两个进化时钟之间对于亲缘关系密切的物种呈现出惊人的线性关系。换句话说,在属的层面内,这两个不同的时钟以相同的速率运行。相反,在亲缘关系不密切的物种之间,这两个时钟呈现出一种相变方式。这可能暗示了一种基于分析方法的新的属的定义,因为相变发生在每个基因平均经历一次易位事件的地方。此外,高度保守基因之间罕见的HGT情况可以作为相变模式的异常值被检测到。