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SG: Inferring phylogenies under ancestral population structure

SG：推断祖先种群结构下的系统发育

基本信息

批准号：
1753489
负责人：
Michael DeGiorgio
金额：
$ 20万
依托单位：
Pennsylvania State Univ University Park
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-03-01 至 2019-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1753489&HistoricalAwards=false
关键词：
SG Inferring phylogenies under ancestral

项目摘要

Accurate estimation of population and species relationships from genetic data is essential for understanding the evolutionary history of everything from influenza viruses to humans. However, as genetic datasets rapidly grow in size due to technological advances, a number of hurdles arise when trying to estimate such relationships. Though many methods have been developed to address these challenges, one source of error that is not accounted for by available methods is non-random mating in ancient populations. Because individuals generally do not mate randomly, and because population and species relationships are used to answer diverse research questions from basic science to epidemiology, addressing this source of error is critical. The primary goal of this project is to design statistical methods for estimating population and species relationships that account for non-random mating in ancient populations, thereby increasing the accuracy of estimation. Moreover, it is of high priority that both the scientific community and the public are engaged in the advances of this project. To this end, the researchers will make all approaches developed during this project freely available for use by the wider scientific community. Also, the researchers will work with K-12 students in hands-on activities for learning why and how to build population and species relationships through the Penn State Science-U program. Finally, the researchers will engage indigenous peoples as part of the Summer internship for INdigenous peoples in Genomics (SING) Workshop which examines the use of genomic data in science and society.Ancestral structure, which has been uncovered in many diverse species, can skew gene tree frequencies, thereby hindering the performance of methods for estimating species trees. This research seeks to develop novel likelihood methods that can infer phylogenies under such scenarios, and apply these methods to test evolutionary hypotheses about ancestral structure and gene flow in several model and non-model organisms. The model organisms considered will be mouse, yeast, and mosquito, for which previous studies have observed skewed gene tree frequencies that were attributed to gene flow through hybridization, but may instead be the result of ancestral structure. The researchers will also apply these methods to a non-model coral system, which is of particular interest because morphological and fossil data provide evidence of hybridization, suggesting that this system may exhibit skewed gene tree frequencies. Application to these systems will serve to elucidate and refine knowledge of the events shaping the evolution of these lineages.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.

从遗传数据中准确估计种群和物种关系对于理解从流感病毒到人类的一切进化历史至关重要。然而，由于技术进步，遗传数据集的规模迅速增长，在试图估计这种关系时出现了许多障碍。虽然已经开发了许多方法来解决这些挑战，但现有方法没有考虑到的一个错误来源是古代种群中的非随机交配。由于个体通常不会随机交配，而且种群和物种关系被用来回答从基础科学到流行病学的各种研究问题，因此解决这一错误来源至关重要。该项目的主要目标是设计统计方法，用于估计古代种群中非随机交配的种群和物种关系，从而提高估计的准确性。此外，科学界和公众参与推进这一项目是高度优先事项。为此，研究人员将免费提供该项目期间开发的所有方法，供更广泛的科学界使用。此外，研究人员将与K-12学生一起参加实践活动，学习为什么以及如何通过宾夕法尼亚州立大学科学项目建立种群和物种关系。最后，研究人员将让土著人民参与基因组学（SING）研讨会的暑期实习，该研讨会研究基因组数据在科学和社会中的使用。在许多不同物种中发现的祖先结构可能会扭曲基因树频率，从而阻碍估计物种树的方法的性能。本研究旨在开发新的可能性方法，可以推断在这种情况下的遗传，并应用这些方法来测试几个模型和非模型生物的祖先结构和基因流的进化假说。考虑的模式生物将是小鼠，酵母和蚊子，以前的研究已经观察到倾斜的基因树频率归因于通过杂交的基因流，但可能是祖先结构的结果。研究人员还将这些方法应用于非模型珊瑚系统，这是特别感兴趣的，因为形态和化石数据提供了杂交的证据，表明该系统可能表现出倾斜的基因树频率。应用于这些系统将有助于阐明和完善这些谱系演变的事件的知识。该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。