Most traits show a quantitative phenotypic expression, which results from the impact of many genes and molecular networks. Furthermore the digital output of these networks upon changing environments hampers the identification and characterization of genes contributing to natural trait variation. In order to gain insights about the mentioned networks and pathways as well as the underlying genes we dissect agronomic important plant traits by combined omics. In this respect, maize iron homeostasis is investigated by exploiting the natural variation of genotypes differing in their potential to deal with iron starvation. Root tissue from plants grown in hydroponics at limiting (10µM) and non-limiting (300µM) iron concentrations is analyzed by proteomics (2D-DIGE and LC-MS/MS) as well as transcriptomics (RNASeq). The comparative proteome survey enabled us to detect differentially expressed proteins that might present novel candidate genes. Furthermore, label-free quantification by LC-MS/MS not only yielded the differential protein profiles but it also accounted for allelic diversity leading to qualitative peptide differences that might have an impact on functional variation. In addition, the root transcriptome in response to iron starvation of the genotypes is determined and used as reference to assign differentially expressed peptides to corresponding protein alleles. The established procedures might present a conceptual design to investigate quantitative plant traits at the molecular level by combined omics.