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.

从遗传数据中对种群和物种关系的准确估计对于理解从流感病毒到人类的所有事物的进化历史至关重要。但是，随着由于技术进步而遗传数据集的规模迅速增长，试图估计这种关系时会出现许多障碍。尽管已经开发了许多方法来应对这些挑战，但是在古代人群中，未通过可用方法考虑的错误来源是非随机交配。因为个人通常不会随机交配，并且由于种群和物种关系用于回答从基础科学到流行病学的各种研究问题，所以解决这种错误来源至关重要。该项目的主要目的是设计统计方法，用于估计古代人群中非随机交配的种群和物种关系，从而提高了估计的准确性。此外，科学界和公众都参与该项目的进步是很高的优先事项。为此，研究人员将在此项目中开发所有方法，以供更广泛的科学界免费使用。此外，研究人员将与K-12学生一起从事动手活动，以学习为什么以及如何通过Penn State Science-U计划建立人口和物种关系。最后，研究人员将参与土著人民作为暑期实习的基因组学（SING）研讨会的一部分，该研讨会研究了基因组数据在科学和社会中的使用。在许多多样化的物种中发现的，可以在许多多样化的物种中发现，可以歪曲基因频率，从而缩减用于估计物种树木树木的性能。这项研究试图开发新的可能性方法，可以在这种情况下推断系统发育，并将这些方法应用于几种模型和非模型生物中关于祖先结构和基因流的进化假设。所考虑的模型生物将是小鼠，酵母和蚊子，对于以前的研究观察到偏斜的基因频率，这些基因频率归因于基因流过通过杂交，但可能是祖先结构的结果。研究人员还将将这些方法应用于非模型珊瑚系统，这特别是因为形态学和化石数据提供了杂交的证据，这表明该系统可能表现出偏斜的基因树频率。对这些系统的应用将有助于阐明和完善对这些谱系演变的事件的了解。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。