Generalizing Bayesian phylogenetics to infer shared evolutionary events

点击翻译按钮获取中文摘要

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.