TY - JOUR

T1 - Crops in silico

T2 - Generating virtual crops using an integrative and multi-scale modeling platform

AU - Marshall-Colon, A.

AU - Long, S.P.

AU - Allen, D.K.

AU - Allen, G.

AU - Beard, D.A.

AU - Benes, B.

AU - Von Caemmerer, S.

AU - Christensen, A.J.

AU - Cox, D.J.

AU - Hart, J.C.

AU - Hirst, P.M.

AU - Kannan, K.

AU - Katz, D.S.

AU - Lynch, J.P.

AU - Millar, A.J.

AU - Panneerselvam, B.

AU - Price, N.D.

AU - Prusinkiewicz, P.

AU - Raila, D.

AU - Shekar, R.G.

AU - Shrivastava, S.

AU - Shukla, D.

AU - Srinivasan, V.

AU - Stitt, M.

AU - Turk, M.J.

AU - Voit, E.O.

AU - Wang, Y.

AU - Yin, X.

AU - Zhu, X.-G.

PY - 2017/5/15

Y1 - 2017/5/15

N2 - 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. © 2017 Marshall-Colon, Long, Allen, Allen, Beard, Benes, von Caemmerer, Christensen, Cox, Hart, Hirst, Kannan, Katz, Lynch, Millar, Panneerselvam, Price, Prusinkiewicz, Raila, Shekar, Shrivastava, Shukla, Srinivasan, Stitt, Turk, Voit, Wang, Yin and Zhu.

AB - 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. © 2017 Marshall-Colon, Long, Allen, Allen, Beard, Benes, von Caemmerer, Christensen, Cox, Hart, Hirst, Kannan, Katz, Lynch, Millar, Panneerselvam, Price, Prusinkiewicz, Raila, Shekar, Shrivastava, Shukla, Srinivasan, Stitt, Turk, Voit, Wang, Yin and Zhu.

KW - Computational framework

KW - Crop yield

KW - Integration

KW - Model

KW - Multiscale

U2 - 10.3389/fpls.2017.00786

DO - 10.3389/fpls.2017.00786

M3 - Journal article

VL - 8

JO - Frontiers in Plant Science

JF - Frontiers in Plant Science

SN - 1664-462X

M1 - 786

ER -