Evolutionary inference in the presence of gene tree discordance

大型DNA测序项目已经揭示，物种之间并不是只有一种联系方式。基因和相同基因组的片段可以有不同的关系。有时，这些关系的不同是因为物种之间古老的交配，称为杂交。当杂交发生时，重要的性状可以在不相关的物种之间共享。该项目将开发新的方法来确定不相关物种之间共有性状的历史。它还将开发更准确地确定物种之间关系的方法。这项研究将使研究人员能够识别出关键性状（如杀虫剂抗性）出现一次并在物种间传递的情况。这项研究结合了数学建模和新的统计方法。这些将结合在一起，产生用于执行分析的开源软件。该软件将确保所有科学家都能利用该研究开发的工具，通过实现新的生物学发现来增加国家基础设施。这项工作还将改善和加速具有多重社会效益的生物学研究，包括帮助识别控制重要性状的基因。该项目将支持培养一名博士后研究员、研究生和来自科学和技术职业中代表性不足群体的本科生。将举办讲习班，提供使用本项目开发的软件的培训。物种树使理解性状的进化史成为可能。先前的研究已经记录了与物种树不一致的基因树如何导致对性状转变的时间和方向、性状转变的数量、这种变化被认为是由适应性进化驱动的频率，甚至物种树本身的不准确推断。本研究不仅记录了基因树不一致的问题，还提供了解决这些问题的方法。所使用的理论方法将有可能将不一致的多种原因（包括基因渗入）整合到一个单一的框架中，使研究人员能够在不一致存在的情况下对进化过程做出严格的统计推断。将这些结果集成到单个软件包中，可以使这些见解和方法广泛应用于二进制和连续特征。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Large DNA sequencing projects have revealed that there is not just one way that species are related. Genes and pieces of the same genome can have different relationships. Sometimes these relationships differ because of ancient mating between species called hybridization. When hybridization occurs, important traits can be shared between unrelated species. This project will develop new methods to determine the history of traits shared between unrelated species. It also will develop methods to more accurately determine the relationships among species. The research will allow researchers to identify cases where key traits, such as insecticide resistance, arise once and are passed between species. The research combines mathematical modeling with new statistical approaches. These will be combined to produce open-source software for carrying out the analyses. The software will ensure that all scientists will be able to take advantage of the tools developed by the research, adding to the national infrastructure by enabling new biological discoveries. This work also will improve and accelerate biological research with multiple societal benefits, including helping to identify genes controlling important traits. This project will support the training of a postdoctoral researcher, graduate students, and undergraduates from groups that are underrepresented in science and technology careers. Workshops will be developed to provide training in the use of the software developed by this project.Species trees make it possible to understand the evolutionary history of traits. Previous work has documented how gene trees that are discordant with the species tree lead to inaccurate inferences about the timing and direction of trait transitions, the number of trait transitions, how often such changes are thought to be driven by adaptive evolution, and even the species tree itself. This research goes beyond documenting the problems of gene tree discordance, providing solutions to these problems. The theoretical approach used will make it possible to incorporate the multiple causes of discordance—including introgression—into a single framework, allowing researchers to make statistically rigorous inferences about evolutionary processes in the presence of discordance. Integrating these results into a single software package enables these insights and methods to be applied widely, for both binary and continuous traits.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.