PRPTree: Novel bioinformatics software for improved understanding of the temporal context of evolutionary divergence

在生命科学领域，生物信息学领域涉及汇编关于生物的大型信息数据库--如DNA或基因序列--并开发分析这些数据库的方法。由于所有生物都通过其共同的祖先相互联系，所以最常见的生物信息学任务之一是建立一棵进化树或一组物种的“系统发育”。系统发育就像一棵家谱，但它追溯了从较老的物种到较年轻的物种的历史血统，而不是从父母到他们的后代。科学家通过研究物种间DNA序列的相似性和差异性来重建它们。然后，他们使用系统发生学来描述数百万年来可能的进化过程，观察物种如何进化和适应，研究基因和蛋白质的进化方式，并重建过去事件的时间和变化速度。这个项目的首席研究员已经得出了一种新的统计方法，它可能会极大地提高我们在系统发育树上估计过去进化事件的日期和时间的能力。拟议的研究是为了i)实施和测试这一新方法，ii)汇编物种进化速度的数据库，以及iii)将新方法和数据库作为易于使用的生物信息学工具提供给其他人。关于第一个目标，我们将开发的新方法通过允许研究人员更准确地测量DNA序列获得差异的速度或速度，提高了我们估计过去进化事件的时间的能力。这一改进的年代测定使系统发育对科学研究更有用。反过来，改进的系统发育将使科学家能够提供更好的答案，比如人类和黑猩猩的祖先是什么时候生活的？或者寨卡或埃博拉病毒是在何时何地出现的？我们工作的第二个目标是汇编一个数据库，记录在包括植物、动物、细菌和病毒在内的各种物种中观察到的进化速度。我们的初步工作表明，一些非常高的进化速度可能会发生--是背景速度的10倍或更多。了解这些比率对于确定系统发生的年代很重要，也有助于理解细菌多快能对抗生素产生抗药性，或病毒能以多快的速度智胜我们的免疫系统，或者物种是否能进化得足够快，以应对气候变化。我们的第三个目标是让其他研究人员可以免费使用我们的新方法，作为一种名为PRPTree的生物信息学工具。我们制作了一个软件包，和其他几个小组一样，用于推断系统发育树，我们将与其他开发人员分享我们的方法。

In the life sciences, the field of bioinformatics is concerned with compiling large databases of information on organisms - such as DNA or gene sequences - and with developing methods for analysing those databases. Because all living things are connected to each other by their common ancestry, one of the most common bioinformatics tasks is to develop an evolutionary tree or 'phylogeny' of a group of species. A phylogeny is like a family tree but traces the historical lines of descent from older to younger species rather than from parents to their offspring. Scientists reconstruct them by studying the similarities and differences among species in their DNA sequences. They then use the phylogenies to describe the probable course of evolution over millions of years, to see how species evolve and adapt, to study the ways genes and proteins evolve and to reconstruct the timings and pace of change of past events. The Principal Investigator of this project has derived a new statistical method that can potentially greatly improve our ability to estimate the dates and timings of past events of evolution on phylogenetic trees. The proposed research is to i) implement and test this new method, ii) to compile a database of the rates at which species evolve and iii) to make the new method and the database available to others as an easy-to-use bioinformatics tool. Regarding the first goal, the new method we will develop improves our ability to estimate the timings of past events of evolution by allowing investigators to measure more accurately the rate or speed with which DNA sequences acquire differences. This improved dating makes the phylogenies more useful for scientific research. In turn, improved phylogenies will allow scientists to provide better answers to questions like when did the ancestor to humans and chimpanzees live? Or when and where did the Zika or Ebola viruses emerge? The second goal of our work is to compile a database of the rates of evolution observed across a variety of species including plants, animals, bacteria and viruses. Our preliminary work suggests that some extraordinarily highly elevated rates of evolution can occur - 10 or more times the background rate. Knowledge of these rates is important for dating phylogenies, but also for understanding questions like how quickly can bacteria acquire resistance to antibiotics, or viruses outwit our immune systems or whether species can evolve fast enough to respond to climate change.Our third goal is to make our new method freely available to other researchers as a bioinformatics tool known as PRPTree. We produce a software package, as do several other groups, for inferring phylogenetic trees, and we will share our methods with those other developers.