Genetic variability of proteome expression and metabolic control

Quantitative proteomics, the technology for high-throughput measurement of protein concentrations from 2-D electrophoresis, often reveals high levels of genetic variability of proteome expression in the species studied. A majority of proteins, including enzymes, display quantitative variation, the extent of which may exceed an order of magnitude. As can be attested in various studies, and most notably in maize, the concentration of individual proteins appears to be a polygenic trait, whose loci may be distributed throughout the genome, with possibly large effects and frequent epistatic interactions. In order to analyse the genetic consequences of these variations, we used the metabolic control theory, developing equations that explicitly incorporate the enzyme concentration as the relevant variable. The metabolic fluxes were modelled as quantitative traits affected by genes modulating enzyme quantities. We showed that, in addition to the classical positive dominance of a large concentration over a small concentration, heterosis for the flux is observed in cases of complementary dominance at different loci. Constraints on the total quantity of enzymes may produce overdominance, reinforcing heterosis. Beyond these genetic aspects, biochemical modelling appears as an important component of genomic and post-genomic approaches, allowing the integration of data generated in those high-throughput programs.