Computational Evolutionary Approaches to Disease

Vanderbilt University, Nashville TN

Investigators

Abstract

Computational evolutionary principles and methods are fundamental to understanding, preventing, and treating genetic and infectious diseases, but formal graduate training is lacking in many institutions, including Vanderbilt University (VU). This proposal seeks to establish a new training program on Computational Evolutionary Approaches to Disease (CoEvoD) at VU. The goal of our program will be to train students to employ or develop computational and bioinformatic-based evolutionary approaches to understand disease biology. Compared to typical domain-specific programs, the CoEvoD will occupy a unique niche, providing a deeper grounding in evolutionary and computational principles than typically received by trainees from life sciences backgrounds, and a more thorough exposure to biomedicine than is usual for students from computational or quantitative backgrounds. VU is uniquely suited to hosting a long-term program on CoEvoD. Both VU and VU Medical Center (VUMC) are on the same campus and are home to a stellar set of preceptors that use and develop computational evolutionary approaches in both basic and clinical settings; most preceptors hold appointments in multiple departments and schools. Our program will draw its training faculty from 10 different departments in the School of Medicine, the College of Arts & Science, and the School of Engineering, and will be rooted in an already established network of collaborative research and training activities. Our program is new, but we have a great track record of highly productive past VU trainees that have landed outstanding positions in leading universities and companies. Training on CoEvoD is not part of existing VU/VUMC training programs and will be highly complementary to existing ones. We will train students to employ or develop a wide range of computational approaches (e.g., phylogenetics, evolutionary epidemiology, disease ecology, evolutionary genomics, population genetics, and evolutionary biochemistry), often in combination with the use of state-of-the-art core facilities (e.g., for computing, genomics, proteomics) and resources (e.g., the large-scale biobank BioVU). We expect that trainees will engage with many of these approaches, facilities, and resources in their research. Trainees will join CoEvoD at the end of their first year of graduate training and will typically be supported for two years. T32 support will cover specialized didactic training, graduate research initiation, and professional development for 6 trainees. Whether T32-funded or not, all trainees (and their preceptors) will be active in CoEvoD program activities throughout their graduate training. Overall, the CoEvoD will enrich each student’s research and training experience and foster the development of the future of US biomedical science.