Snir Sagi
Department of Evolutionary Biology, University of Haifa , Haifa, Israel.
Mob Genet Elements. 2015 Dec 30;6(6):e1120576. doi: 10.1080/2159256X.2015.1120576. eCollection 2016.
Molecular data is accumulated at exponentially increasing pace. This deluge of information should have brought us closer to resolving one of the most fundamental issues in biology - deciphering the history of life on Earth. So far, however, this abundance of data only seems to blur our understanding of the problem. This is largely due to horizontal gene transfer (HGT), the transfer of genetic material between evolutionarily unrelated organisms that transforms the prokaryotic tree into a network of relationships. Recently, we developed a method to infer evolutionary relationships among closely related species where the conventional evolutionary markers do not provide a strong enough signal. The method relies on the loss of synteny, gene order conservation among species that provides a stronger signal, sufficient to classify even strains of a given species. Here we elaborate on this method and suggest further uses of it in the context of detecting HGT events and genome architecture.
分子数据正以指数级增长的速度积累。这大量的信息本应使我们更接近于解决生物学中最基本的问题之一——解读地球上生命的历史。然而，到目前为止，如此丰富的数据似乎只是模糊了我们对这个问题的理解。这在很大程度上是由于水平基因转移（HGT），即进化上不相关的生物体之间的遗传物质转移，它将原核生物树转变为一个关系网络。最近，我们开发了一种方法来推断密切相关物种之间的进化关系，而传统的进化标记无法提供足够强的信号。该方法依赖于同线性的丧失，即物种间基因顺序的保守性，它提供了更强的信号，足以对给定物种的菌株进行分类。在这里，我们详细阐述这种方法，并提出它在检测水平基因转移事件和基因组结构方面的进一步应用。
