Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

• Authors: Amy Marshall-Colon, University of Illinois at Urbana–Champaign; Stephen P. Long, University of Illinois at Urbana–Champaign; Douglas K. Allen, Donald Danforth Plant Science Center; Gabrielle Allen, University of Illinois; Daniel A. Beard, University of Michigan; Bedrich Benes, Purdue University; Susanne von Caemmerer, Australian National University; A.J Christensen, University of Illinois; Donna J. Cox, University of Illinois; John C. Hart, University of Illinois; Peter M. Hirst, Purdue University; Kavya Kannan, University of Illinois at Urbana–Champaign; Daniel S. Katz, University of Illinois; Jonathan P. Lynch, Pennsylvania State University; Andrew J. Millar, Edinburgh University; Balaji Panneerselvam, University of Illinois; Nathan D. Price, Institute for Systems Biology, Seattle; Przemyslaw Prusinkiewicz, University of Calgary; David Raila, University of Illinois; Rachel G. Shekar, University of Illinois; Stuti Shrivastava, University of Illinois at Urbana–Champaign; Diwakar Shukla, University of Illinois; Venkatraman Srinivasan, University of Illinois; Mark Stitt, Max Planck Institute of Molecular Plant Physiology, Golm, Germany; Matthew J. Turk, University of Illinois; Eberhard Voit, Emory University; Yu Wang, University of Illinois; Xinyou Yin, Wageningen University & Research; Xin-Guang Zhu, Chinese Academy of Sciences
• Journal Title: Frontiers in Plant Science
• Volume: Volume 8
• Publisher: Frontiers Media | 2017-05-15
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.3389/fpls.2017.00786
• Subjects: Agriculture, Plant Culture; Biology, Genetics
• Keywords: Crop yield; Multiscale; Computational framework; Model; Integration

Abstract

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.