Systems biology is the integration of multiple levels of omics data with environmental factors and phenotypic responses. C. elegans is an ideal organism for these studies. There are several obstacles to a complete systems biology analysis, especially at the level of metabolomic analysis. Metabolites span a range of chemical classes including amino acids, sugars, lipids, organic acids and are expressed in a very wide range of concentrations ranging from <fM to >mM. There are no existing methods to cover this broad metabolite diversity. Mass spectrometry is extremely sensitive but is not able to reliably identify unknown metabolites that are not well characterized in databases. NMR is capable of unknown metabolite identification but suffers from low sensitivity. We are developing several approaches to help address these problems: “Deep annotation” is a chemical approach to combine the strengths of NMR and MS to relate molecular formulas to compound identifications using large pooled cultures of worms and preparative chemical fractionation techniques. “Developmental distribution” is an approach to extract developmental stage-specific analytical data from several replicates of mixed population cultures that are characterized by a worm sorter. We are applying these approaches to targeted mutations in glycosyltransferases as well as other systems such as recombinant inbred and mutation accumulation lines. I will provide an overview of how these approaches fit together to relate metabolites to genes and phenotypes.