Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

In this study, we used a cross-species network approach to uncover nitrogen (N)-regulated network modules conserved across a model and a crop species. By translating gene network knowledge from the data-rich model Arabidopsis (Arabidopsis thaliana) to a crop, rice (Oryza sativa), we identified evolutionarily conserved N-regulatory modules as targets for translational studies to improve N use efficiency in transgenic plants. To uncover such conserved N-regulatory network modules, we first generated an N-regulatory network based solely on rice transcriptome and gene interaction data. Next, we enhanced the network knowledge in the rice N-regulatory network using transcriptome and gene interaction data from Arabidopsis and new data from Arabidopsis and rice plants exposed to the same N treatment conditions. This cross-species network analysis uncovered a set of N-regulated transcription factors (TFs) predicted to target the same genes and network modules in both species. Supernode analysis of the TFs and their targets in these conserved network modules uncovered genes directly related to N use (e.g. N assimilation) and to other shared biological processes indirectly related to N. This cross-species network approach was validated with members of two TF families in the supernode network, BASIC-LEUCINE ZIPPER TRANSCRIPTION FACTOR1-TGA and HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY ROOT SHORTENING1 (HRS1)/HRS1 Homolog family, which have recently been experimentally validated to mediate the N response in Arabidopsis.

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Out of the three aromatic amino acids, the highest flux in plants is directed towards phenylalanine, which is utilized to synthesize proteins and thousands of phenolic metabolites contributing to plant fitness. Phenylalanine is produced predominantly in plastids via the shikimate pathway and subsequent arogenate pathway, both of which are subject to complex transcriptional and post-transcriptional regulation. Previously, it was shown that allosteric feedback inhibition of arogenate dehydratase (ADT), which catalyzes the final step of the arogenate pathway, restricts flux through phenylalanine biosynthesis. Here, we show that in petunia (Petunia hybrida) flowers, which typically produce high phenylalanine levels, ADT regulation is relaxed, but not eliminated. Moderate expression of a feedback-insensitive ADT increased flux towards phenylalanine, while high overexpression paradoxically reduced phenylalanine formation. This reduction could be partially, but not fully, recovered by bypassing other known metabolic flux control points in the aromatic amino acid network. Using comparative transcriptomics, reverse genetics, and metabolic flux analysis, we discovered that transcriptional regulation of the D-ribulose-5-phosphate 3-epimerase gene in the pentose phosphate pathway controls flux into the shikimate pathway. Taken together, our findings reveal that regulation within and upstream of the shikimate pathway shares control over phenylalanine biosynthesis in the plant cell.