CAREER: Identification of causal relationships between epigenetic regulation, gene expression, and phenotypic diversity within and across generations using Caenorhabditis nematodes

Genetically identical individuals, such as human twins, are expected to be very similar, but they nonetheless exhibit substantial differences in traits and diseases throughout their lives. In controlled laboratory settings where all individuals experience the same environment, genetically identical animals also exhibit differences in important traits, including fertility and lifespan. However, why genetically identical individuals differ from each other for these traits remains incompletely understood. In addition, how non-genetic differences that arise in one generation impact subsequent generations is not well understood. This research builds upon the principal investigator’s prior work, which revealed that differences in how genes are regulated are linked to differences in fertility across genetically identical individuals and that non-genetic differences in one generation can lead to predictable differences in subsequent generations. Using a powerful set of experiments, this project will investigate how DNA and other factors interact to control differences among genetically identical individuals. This research priority will advance scientific progress in biotechnology and artificial intelligence, as well as contribute to national health, because many diseases are not just regulated by the DNA sequence alone, but by interactions with other factors. Genetically identical, i.e. isogenic, individuals exposed to the same environment can develop at different rates, grow to different sizes, and produce differing numbers of progeny. Such phenotypic variability raises key questions: 1) what drives variability across isogenic individuals in the same environment?; 2) how do populations differentially evolve when they are isogenic but epigenetically distinct?; and 3) how can phenotypes of isogenic individuals be better predicted? This research will use a highly integrated set of three objectives to answer each of these questions, all using isogenic populations within the roundworm Caenorhabditis genus, including the widely used genetic model, C. elegans. The project will specifically identify conserved genomic and epigenomic features that control gene expression variation in isogenic populations, elucidate how isogenic individuals with distinct epigenetic states evolve over hundreds of generations, and improve phenotypic predictions using reproductive and transcriptomic data. This project will integrate high-throughput sequencing data, causal analysis of gene function (RNA interference), and advanced analytic tools (artificial intelligence/machine learning) to gain insights on these objectives. Integrated with these research objectives, this project will implement an educational plan to provide meaningful research experiences, individual mentoring, and bioinformatics training to high school students, undergraduate students, graduate students, and postdoctoral researchers, contributing to the advancement of the STEM workforce of the United States. Collectively, the questions posed are of high interest for fundamental understanding how an individual develops its traits from a combination of its genome, epigenome, and transcriptome. The proposed objectives are carefully designed to address this using cutting-edge high-throughput approaches and novel analytical methods while encouraging the development of talent in STEM fields. 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. NSF Award ID: 2543711 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT,01003031DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Amy Webster | Institution: Florida State University, TALLAHASSEE, FL | Award Amount: $864,959 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2543711 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2543711.html