PRIMES: Practical Inference Algorithms to Detect Hybridization

University Enterprises Corporation At Csusb, San Bernardino CA

Investigators

Abstract

Phylogenetics is the branch of evolutionary biology whose main objective is understanding the evolutionary relationships between species. Inferring such relations is crucial for important areas of current concern, such as conservation efforts, understanding infectious disease dynamics, and improving agricultural practices. Hybrid speciation, or hybridization, occurs when two distinct species merge genetically to create a new one, and it is known to have played an important role in the evolution of many species, including butterflies, salamanders, sunflowers, and primroses, among many others. In this project, the Principal Investigator will develop much-needed algorithms to be used by the biological community as a tool to detect hybridization between species. Additionally, the PI will design and conduct multiple activities to encourage aspiring scholars, especially those belonging to minority groups, to pursue a career in STEM. The theoretical foundation of the algorithms that will be developed in this proposal will be the Network Multispecies Coalescent model (NMSC), a standard stochastic model describing the distinct evolutionary relationships between species’ genes in the presence of incomplete lineage sorting and hybridization. Current statistically consistent methods to infer species networks under the NMSC are restricted to a rather simple family of networks known as level-1. The PI will develop and implement fast and consistent algorithms to infer more general species networks under the NMSC from genomic data. This will be achieved with three aims: (1) Expand current identifiability results to a more general family of networks; (2) Develop algorithms to infer statistically consistent estimators of species networks; and (3) Implement algorithms that are useful, reliable, and easy to use. Software implementations will handle large datasets under attainable running times, be made publicly available, and include extensive novel functionalities that will be widely useful to the biological community. This work will advance both theoretical and practical methods for phylogenetic inference. To increase underrepresented groups’ participation in biomathematics, the PI will organize and host a seminar series entitled “Biomathematics for All: Celebrating Diversity.” In these lectures, invited speakers will discuss their research together with the challenges and opportunities they have faced. Furthermore, the PI will design and conduct the summer week-long program “Introduction to the Mathematical Modeling of Evolution: A Week-long Course for Beginners” for the diverse student community of California State University San Bernardino, a minority-serving institution. The PI will attend the Fall 2024 semester program: “Theory, Methods, and Applications of Quantitative Phylogenomics” at ICERM. 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.