Enabling Discovery through GEnomics (EDGE)
|Theodore (Ted) J. Morganfirstname.lastname@example.org||(703) 292-7868|
|Edda (Floh) Thielsemail@example.com||(703) 292-8167|
|Douglas K. (Patrick) Abbotfirstname.lastname@example.org||(703) 292-7820|
|Ford Ballantyneemail@example.com||(703) 292-8037|
|Steven E. Ellisfirstname.lastname@example.org||(703) 292-7876|
|Anthony G. Garzaemail@example.com||(703) 292-8440|
|Diane Jofuku Okamurofirstname.lastname@example.org||(703) 292-4508|
General inquiries regarding this program should be made to:
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 20-1), is effective for proposals submitted, or due, on or after June 1, 2020. Please be advised that, depending on the specified due date, the guidelines contained in NSF 20-1 may apply to proposals submitted in response to this funding opportunity.
Full Proposal Accepted Anytime
The Enabling Discovery through GEnomic Tools (EDGE) program supports genomic research that addresses the mechanistic basis of complex traits in diverse organisms within the context (environmental, developmental, social, and/or genomic) in which they function. The EDGE program also continues to support the development of innovative tools, technologies, resources, and infrastructure that advance biological research focused on the identification of the causal mechanisms connecting genes and phenotypes. EDGE is designed to provide support for (1) the development of tools, approaches, and infrastructure aimed at testing cause and effect hypotheses between gene function and phenotypes in diverse plants, animals, microbes, viruses, or fungi for which these methods are presently unavailable, and (2) hypothesis-driven research that tests cause and effect relations between genotype(s) and phenotypes in non-model plants, animals, microbes, viruses, or fungi.
These goals are essential to uncovering the rules that underlie genomes-to-phenomes relationships, an area relevant to Understanding the Rules of Life: Predicting Phenotype, one of the 10 Big Ideas for future NSF investment.