Critical Expansions and Improvements to the Caenorhabditis Natural Strain Resource

Studies of conserved biological processes require model organisms, which share attributes with humans. Most model organisms are easily grown in the laboratory and enable experimental manipulations. Over the last forty years, the nematode Caenorhabditis elegans has been instrumental in numerous fundamental advances in genetics, developmental biology, and neurobiology. However, all of these discoveries come from studies of a single strain in the species. This limitation is similar to the argument that we can understand all of human biology by the study of a single person in our species. This project (1) strengthens the cloud-computing infrastructure and enable Amazon Web Services Open Data Initiative free data egress offering massive cost savings and a more robust website, (2) Updates the GWA mapping tool for all three Caenorhabditis species and create a simulation framework, (3) Adds four critical tools suggested by our users (genome-editing, RNA-seq browser, interface for user-supplied data, and linkage mapping), and (4) Integrates novel features where high levels of genetic differences impede experimental and computational approaches. These improvements will enable studies that can teach us a great deal about how the human population differs and evolution works. This project advances NSF’s Biotechnology priority area. The Caenorhabditis Natural Strain Resource (CaeNSR) has three major goals: (1) Collect, organize, and disseminate wild Caenorhabditis strains; (2) Organize and disseminate whole-genome sequence and variant data for wild strains; and (3) Provide a genetics portal to facilitate mappings and interpretations of results. The project will further increase the capacity of CaeNSR by expanding the computational infrastructure and add four user-requested tools. The extensive CaeNSR user-base is already addressing research questions focused on novel comparative approaches across the Caenorhabditis genus. Most research groups do not have the combination of experimental, computational, and statistical training to easily perform studies of natural variation. This project will continue to make these tools available and usable by the over 300 laboratories and 800 users across diverse model organism communities. This project aligns with the NSF’s biotechnology priority area. 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: 2534139 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Erik Andersen | Institution: Johns Hopkins University, BALTIMORE, MD | Award Amount: $898,939 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2534139 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2534139.html