Generalizing Bayesian phylogenetics to infer shared evolutionary events

该项目将开发一种评估进化关系的新方法，该方法考虑到多个生物谱系同时分化的情况。基因组进化、微生物群进化、流行病学、寄生虫学和生物地理学等不同学科的生物学家将能够使用这种方法来测试对生命之树中这种模式的预测。在这项研究中，研究人员将使用这种新方法来测试过去2500万年来气候和海平面的变化是否对东南亚丰富的生物多样性的产生做出了贡献。该项目将通过为服务不足的监狱人口提供教育机会，产生深远的社会效益。为了将更多的STEM课程纳入阿拉巴马监狱+艺术教育项目的课程，研究人员将为阿拉巴马州的囚犯开发并教授一门为期14周的进化生物学课程。为了最大限度地提高该项目的再现性、透明度和研究和教育方面的效用，研究人员将遵循开放科学原则，使用软件实时记录他们的进展，并将其发布到互联网上。该项目的第一个目标是开发一个通用的统计框架来推断进化关系，该框架允许(1)谱系分化为两个以上的后代谱系（多功能）和(2)两个或更多的谱系在过去的同一时间分化（共同分化）。为了做到这一点，研究人员将在可能的进化关系的整个空间中开发一类概率分布，包括多功能和共发散，以及在估计基因，生物体或种群之间关系时探索该空间的数值方法。该项目的第二个目标是使用广泛的计算机模拟来评估该方法在广泛条件下的表现。特别令人感兴趣的是，当模拟中出现多功能和共发散时，确定新方法在多大程度上提高了系统发育推断的准确性和精度，以及当它们不发生时使用新方法是否有成本。该项目的第三个目标是更精确地推断东南亚景观的历史变化如何促成该地区丰富的生物多样性。为了解决这个问题，研究人员将从分布在东南亚的三种壁虎标本中提取基因组数据，并将他们的新方法应用于这些数据。这将使研究人员能够估计这些壁虎在进化史上的时间模式差异的概率，这些差异是由过去的景观变化预测的。正在产生的新方法将允许生物学家在一个新的框架下观察和修改生命之树，以更现实的祖先/后代关系序列，包括两个以上的后代从一个祖先进化而来的情况。

This project will develop a new method for estimating evolutionary relationships that takes into account situations where multiple lineages of organisms diverge at the same time. Biologists in disciplines as diverse as genome evolution, microbiome evolution, epidemiology, parasitology, and biogeography will be able to use this method to test predictions of such patterns across the Tree of Life. In this research, researchers will use the new method to test whether changes in climate and sea levels over the past 25 million years have contributed to the generation of the rich biodiversity of Southeast Asia. This project will have far-reaching societal benefits by providing educational opportunities to the under-served prison population. To initiate the incorporation of more STEM courses into the curriculum of the Alabama Prison + Arts Education Project, the researchers will develop and teach a 14-week evolutionary biology course to prisoners in Alabama. To maximize the reproducibility, transparency, and utility of the research and educational aspects of this project, the researchers will follow open-science principles by using software to record their progress in real time and make it publicly available on the Internet. The first aim of this project is to develop a general statistical framework for inferring evolutionary relationships that allows for (1) lineages to diverge into more than two descendant lineages (multifurcations) and (2) two or more lineages to diverge at the same time in the past (co-divergences). To do this, the researchers will develop a class of probability distributions over the entire space of possible evolutionary relationships, including multifurcations and co-divergences, and a numerical approach to explore this space while estimating the relationships among genes, organisms, or populations. The second aim of this project is to use extensive computer simulations to assess how well the method performs across a broad range of conditions. Of particular interest is determining how much the new method improves the accuracy and precision of phylogenetic inference when multifurcations and co-divergences occur in the simulations, and whether there is a cost to using the new method when they do not occur. The third aim of the project is to infer more precisely how historical changes to the landscape of Southeast Asia have contributed to the rich biodiversity of this region. To address this question, the researchers will extract genomic data from specimens of three genera of geckos distributed across Southeast Asia, and apply their new method to these data. This will allow the researchers to estimate the probability of temporal patterns of divergence during the evolutionary history of these geckos that are predicted by past changes to the landscape. The new methods being generated will allow biologists to see and modify the Tree of Life in a new framework with a more realistic sequence of ancestral/descendant relationships including cases where more than two descendants evolve from a single ancestor.