Increasing seed oil content by plant breeding has resulted in trade-offs or penalties with respect to protein content, seed size, or seed set. The molecular basis for this impasse is mostly speculative. Use of current global profiling approaches to better understand both the metabolic consequences of higher oil and the basis for reduced yield must also deal with off-target genetic mutations (even in near-isogenic lines), ultimately confounding cause-effect interpretations. We propose a diverse, integrated strategy to study the consequences of higher lipid production by studying transgenic plants specifically engineered to produce higher seed oil. As a part of this collaborative project, we are trying developing a “one-stop-shop” community web resource (www.fatplants.net) for all data pertaining to enhancing oil content in plants to leverage data generated from this project with curated forms of public data other funded web sites, and the literature. We have currently expanded FatPlants framework and tools to Glycine max, Arabidopsis thaliana and Camelina sativa. We currently provide all fatty acid related proteins and genes retrieve search of these 3 species, also of most fatty acid chemical properties. As for analysis tools, FatPlants includes pathway viewer, protein structure viewer, Blast, protein-protein Interaction viewer, and GO enrichment viewer. To help our collaborators work tightly, an user authentication internal data sharing space was provided to all collaborative labs. Users will soon be able to access our website at www.fatplants.net.