SG: Inferring phylogenies under ancestral population structure

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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.