2Global population increase coupled with rising urbanization underlies the predicted need for 2 3 60% more food by 2050, but produced on the same amount of land as today. Improving 2 4 photosynthetic efficiency is a largely untapped approach to addressing this problem. Here, we 2 5 scale modeling processes from gene expression through photosynthetic metabolism to predict 2 6 leaf physiology in evaluating acclimation of photosynthesis to rising [CO 2 ]. Model integration 2 7with the yggdrasil interface enabled asynchronous message passing between models. The 2 8 multiscale model of soybean photosynthesis calibrated to physiological measures at ambient 2 9[CO 2 ] successfully predicted the acclimatory changes in the photosynthetic apparatus that 3 0 were observed at 550 ppm [CO 2 ] in the field. We hypothesized that genetic alteration is 3 1 1 necessary to achieve optimal photosynthetic efficiency under global change. Flux control 3 2 analysis in the metabolic system under elevated [CO 2 ] identified enzymes requiring the 3 3 greatest change to adapt optimally to the new conditions. This predicted that Rubisco was less 3 4 limiting under elevated [CO 2 ] and should be down-regulated allowing re-allocation of 3 5 resource to enzymes controlling the rate of regeneration of ribulose-1:5 bisphosphate (RubP). 3 6 By linking the GRN through protein concentration to the metabolic model it was possible to 3 7 identify transcription factors (TF) that matched the up-and down-regulation of genes needed 3 8 to improve photosynthesis. Most striking was TF GmGATA2, which down-regulated genes 3 9 for Rubisco synthesis while up-regulating key genes controlling RubP regeneration and starch 4 0 synthesis. The changes predicted for this TF most closely matched the physiological ideotype 4 1that the modeling predicted as optimal for the future elevated [CO 2 ] world. 4 2 4 3 KEYWORDS: Gene network model, metabolic model, photosynthesis, global change, Soybean, 4 4 transcription factors, multiscale modeling, model integration 4 5 4 6As the world's most important seed legume and most widely grown dicotyledonous crop, 4 7 the future-proofing of photosynthesis in soybean (Glycine max (L.) Merr.) under rising 4 8 atmospheric concentrations of CO 2 ([CO 2 ]) is of importance. Down-regulation of light-saturated 4 9net leaf CO 2 uptake (A sat ) at elevated [CO 2 ] has been reported for many C 3 crops, yet the 5 0 mechanism underlying this response is poorly understood. Under current [CO 2 ], A sat in C 3 crops 5 1 is most commonly limited by the in vivo Rubsico activity (V c,max ) (Long et al., 2004). However, 5 2 as [CO 2 ] continues to rise, it follows from the steady-state biochemical model of photosynthesis 5 3 of (Farquhar et al., 1980) and its subsequent modifications (Von Caemmerer, 2000) that control 5 4 will shift from Rubisco to RubP regeneration (Long et al., 2004), which is represented by the 5 5maximum in vivo rate of whole chain electron transport (J max ). While described by electron 5 6 transport, most evidence now points to t...