Applying modelling experiences from the past to shape crop systems biology: the need to converge crop physiology and functional genomics.

Functional genomics has been driven greatly by emerging experimental technologies. Its development as a scientific discipline will be enhanced by systems biology, which generates novel, quantitative hypotheses via modelling. However, in order to better assist crop improvement, the impact of developing functional genomics needs to be assessed at the crop level, given a projected diminishing effect of genetic alteration on phenotypes from the molecule to crop levels. This review illustrates a recently proposed research field, crop systems biology, which is located at the crossroads of crop physiology and functional genomics, and intends to promote communications between the two. Past experiences with modelling whole-crop physiology indicate that the layered structure of biological systems should be taken into account. Moreover, modelling not only plays a role in data synthesis and quantitative prediction, but certainly also in heuristics and system design. These roles of modelling can be applied to crop systems biology to enhance its contribution to our understanding of complex crop phenotypes and subsequently to crop improvement. The success of crop systems biology needs commitments from scientists along the entire knowledge chain of plant biology, from molecule or gene to crop and agro-ecosystem.

[1]  J. Lopreato,et al.  General system theory : foundations, development, applications , 1970 .

[2]  G. Johnson.  Cyclic electron transport in C3 plants: fact or artefact? , 2004, Journal of experimental botany.

[3]  T. Ideker,et al.  A new approach to decoding life: systems biology. , 2001, Annual review of genomics and human genetics.

[4]  Rodrigo A Gutiérrez,et al.  Systems Biology for the Virtual Plant1 , 2005, Plant Physiology.

[5]  H. H. Laar,et al.  Scale and Complexity in Plant Systems Research , 2007 .

[6]  Jeffrey W. White,et al.  Simulating effects of genes for physiological traits in a process-oriented crop model , 1996 .

[7]  T. Sinclair,et al.  Crop transformation and the challenge to increase yield potential. , 2004, Trends in plant science.

[8]  K. Boote,et al.  Physiology and modelling of traits in crop plants: implications for genetic improvement , 2001 .

[9]  J. Yamagishi,et al.  Flowering response of rice to photoperiod and temperature: a QTL analysis using a phenological model , 2005, Theoretical and Applied Genetics.

[10]  Xinyou Yin,et al.  Photoperiodically Sensitive and Insensitive Phases of Preflowering Development in Rice , 1997 .

[11]  Xinyou Yin,et al.  Role of crop physiology in predicting gene-to-phenotype relationships. , 2004, Trends in plant science.

[12]  C. T. Wit,et al.  Simulation of assimilation, respiration, and transpiration of crops , 1978 .

[13]  H. Berge,et al.  Simulating genotypic strategies for increasing rice yield potential in irrigated, tropical environments , 1997 .

[14]  Dean Podlich,et al.  Evaluating Plant Breeding Strategies by Simulating Gene Action and Dryland Environment Effects , 2003, Agronomy Journal.

[15]  Roberto Tuberosa,et al.  Genomics-based approaches to improve drought tolerance of crops. , 2006, Trends in plant science.

[16]  K. Cassman,et al.  A dialogue on interdisciplinary collaboration to bridge the gap between plant genomics and crop sciences , 2007 .

[17]  G. Coupland,et al.  Distinct photoperiodic responses are conferred by the same genetic pathway in Arabidopsis and in rice. , 2003, Trends in plant science.

[18]  R. Leuning.  A critical appraisal of a combined stomatal‐photosynthesis model for C3 plants , 1995 .

[19]  J. Dubcovsky,et al.  A NAC Gene Regulating Senescence Improves Grain Protein, Zinc, and Iron Content in Wheat , 2006, Science.

[20]  Martin J. Kropff,et al.  Use of component analysis in QTL mapping of complex crop traits : A case study on yield in barley , 2002 .

[21]  S. Long,et al.  Food for Thought: Lower-Than-Expected Crop Yield Stimulation with Rising CO2 Concentrations , 2006, Science.

[22]  G. Coruzzi,et al.  Achieving the in Silico Plant. Systems Biology and the Future of Plant Biological Research , 2003, Plant Physiology.

[23]  N. Yamamoto,et al.  Photosynthesis, plant growth and N allocation in transgenic rice plants with decreased Rubisco under CO2 enrichment. , 2000, Journal of experimental botany.

[24]  Thomas Lübberstedt,et al.  Need for multidisciplinary research towards a second green revolution. , 2005, Current opinion in plant biology.

[25]  M. Falque,et al.  Towards a better understanding of the genetic and physiological basis for nitrogen use efficiency in maize. , 2001, Plant physiology.

[26]  Alain Charcosset,et al.  Combining Quantitative Trait Loci Analysis and an Ecophysiological Model to Analyze the Genetic Variability of the Responses of Maize Leaf Growth to Temperature and Water Deficit1 , 2003, Plant Physiology.

[27]  Xinyou Yin,et al.  Mathematical review of literature to assess alternative electron transports and interphotosystem excitation partitioning of steady-state C3 photosynthesis under limiting light. , 2006, Plant, cell & environment.

[28]  Stephen M. Welch,et al.  A Genetic Neural Network Model of Flowering Time Control in , 2003 .

[29]  A. Aharoni,et al.  Improvement of water use efficiency in rice by expression of HARDY, an Arabidopsis drought and salt tolerance gene , 2007, Proceedings of the National Academy of Sciences.

[30]  F. Tardieu.  Virtual plants: modelling as a tool for the genomics of tolerance to water deficit. , 2003, Trends in plant science.

[31]  A. Laisk,et al.  C3 photosynthesis in silico , 2007, Photosynthesis Research.

[32]  A. Leopold,et al.  Plant Growth and Development , 2019, Stress Physiology of Woody Plants.

[33]  B. Miflin,et al.  Crop improvement in the 21st century. , 2000, Journal of experimental botany.

[34]  Xin-Guang Zhu,et al.  The slow reversibility of photosystem II thermal energy dissipation on transfer from high to low light may cause large losses in carbon gain by crop canopies: a theoretical analysis. , 2004, Journal of experimental botany.

[35]  M. Kropff,et al.  Possibility of Increasing Yield Potential of Rice by Reducing Panicle Height in the Canopy. I. Effects of Panicles on Light Interception and Canopy Photosynthesis. , 1995 .

[36]  G. Edmeades,et al.  Physiology, genomics and crop response to global change , 2004 .

[37]  H. H. Laar,et al.  Scale and Complexity in Plant Systems Research : Gene-Plant-Crop Relations , 2007 .

[38]  G. Hammer,et al.  On Systems Thinking, Systems Biology, and the in Silico Plant , 2004, Plant Physiology.

[39]  H. Berge,et al.  Simulation of Ecophysiological Processes of Growth in Several Annual Crops , 1989 .

[40]  Graeme L. Hammer,et al.  Preface to Special Issue: Complex traits and plant breeding—can we understand the complexities of gene-to-phenotype relationships and use such knowledge to enhance plant breeding outcomes? , 2005 .

[41]  P. S. Bindraban.  Bridging the gap between plant physiology and breeding : identifying traits to increase wheat yield potential using systems approaches , 1997 .

[42]  P. Jarvis.  The Interpretation of the Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in the Field , 1976 .

[43]  A. J. Haverkort,et al.  Using systems approaches to design and evaluate ideotypes for specific environments , 1995 .

[44]  L. Yan,et al.  The wheat and barley vernalization gene VRN3 is an orthologue of FT , 2006, Proceedings of the National Academy of Sciences.

[45]  G. C. Tucker.  Triticum aestivum L. , 2006 .

[46]  P. L. Mitchell,et al.  Supercharging rice photosynthesis to increase yield. , 2006, The New phytologist.

[47]  Prem S. Bindraban,et al.  A Generic Equation for Nitrogen-limited Leaf Area Index and its Application in Crop Growth Models for Predicting Leaf Senescence , 2000 .

[48]  P. C. Struik,et al.  Crop systems biology: an approach to connect functional genomics with crop modelling , 2007 .

[49]  H. Kitano.  Systems Biology: A Brief Overview , 2002, Science.

[50]  J. R. Evans,et al.  Nitrogen and Photosynthesis in the Flag Leaf of Wheat (Triticum aestivum L.). , 1983, Plant physiology.

[51]  Robert T. Furbank,et al.  6 – Modeling C4 Photosynthesis , 1999 .

[52]  Fabio Fornara,et al.  FT Protein Movement Contributes to Long-Distance Signaling in Floral Induction of Arabidopsis , 2007, Science.

[53]  F. W. T. Penning de Vries,et al.  SIMULATION TO SUPPORT EVALUATION OF THE PRODUCTION POTENTIAL OF RICE VARIETIES IN TROPICAL CLIMATES , 1990 .

[54]  C. Foyer,et al.  A re-evaluation of the ATP :NADPH budget during C3 photosynthesis: a contribution from nitrate assimilation and its associated respiratory activity? , 1998 .

[55]  Jeffrey W. White,et al.  Gene‐Based Approaches to Crop Simulation , 2003 .

[56]  Q. Qian,et al.  Cytokinin Oxidase Regulates Rice Grain Production , 2005, Science.

[57]  James W. Jones,et al.  Systems approaches for the design of sustainable agro-ecosystems , 2001 .

[58]  T. Sinclair,et al.  Photosynthate and Nitrogen Requirements for Seed Production by Various Crops , 1975, Science.

[59]  D. Normile.  Crossing Rice Strains to Keep Asia's Rice Bowls Brimming , 1999, Science.

[60]  B. Walsh,et al.  Models for navigating biological complexity in breeding improved crop plants. , 2006, Trends in plant science.

[61]  F. V. van Eeuwijk,et al.  QTL analysis and QTL-based prediction of flowering phenology in recombinant inbred lines of barley. , 2005, Journal of experimental botany.

[62]  Joanne Chory,et al.  Building Integrated Models of Plant Growth and Development1 , 2003, Plant Physiology.

[63]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.

[64]  A. Peeters,et al.  GENETIC CONTROL OF FLOWERING TIME IN ARABIDOPSIS. , 1998, Annual review of plant physiology and plant molecular biology.

[65]  Xinyou Yin,et al.  A Model of the Generalized Stoichiometry of Electron Transport Limited C3 Photosynthesis: Development and Applications , 2009 .

[66]  J. Kervella,et al.  Analysing the genetic control of peach fruit quality through an ecophysiological model combined with a QTL approach. , 2005, Journal of experimental botany.

[67]  G. Coupland,et al.  The quest for florigen: a review of recent progress. , 2006, Journal of experimental botany.

[68]  M. J. Kropff,et al.  AFLP mapping of quantitative trait loci for yield-determining physiological characters in spring barley , 1999, Theoretical and Applied Genetics.

[69]  Stephen M. Welch,et al.  A Genetic Neural Network Model of Flowering Time Control in Arabidopsis thaliana , 2003 .

[70]  S. Kay,et al.  Photoperiodic control of flowering: not only by coincidence. , 2006, Trends in plant science.

[71]  Ulrich Schurr,et al.  The Effects of Elevated CO2 Concentration on Soybean Gene Expression. An Analysis of Growing and Mature Leaves1[W][OA] , 2006, Plant Physiology.

[72]  Takeshi Horie,et al.  Leaf Nitrogen, Photosynthesis, and Crop Radiation Use Efficiency: A Review , 1989 .

[73]  Xinyou Yin,et al.  Crop Systems Dynamics: An Ecophysiological Simulation Model for Genotype-By-Environment Interactions , 2005 .

[74]  M. Yano,et al.  Genetic control of flowering time in rice, a short-day plant. , 2001, Plant physiology.

[75]  R. A. Fischer,et al.  PAPER PRESENTED AT INTERNATIONAL WORKSHOP ON INCREASING WHEAT YIELD POTENTIAL, CIMMYT, OBREGON, MEXICO, 20–24 MARCH 2006 Understanding the physiological basis of yield potential in wheat , 2007, The Journal of Agricultural Science.

[76]  Shoichi Matsuo,et al.  Hd3a Protein Is a Mobile Flowering Signal in Rice , 2007, Science.

[77]  L. Bertalanffy.  Modern Theories of Development: an Introduction to Theoretical Biology , 2014, Nature.

[78]  F. Woodward,et al.  Potential impacts of global elevated CO(2) concentrations on plants. , 2002, Current opinion in plant biology.

[79]  R. Bernardo.  What If We Knew All the Genes for a Quantitative Trait in Hybrid Crops , 2001 .

[80]  K. Cassman.  Ecological intensification of cereal production systems: yield potential, soil quality, and precision agriculture. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[81]  C. Field,et al.  Allocating leaf nitrogen for the maximization of carbon gain: Leaf age as a control on the allocation program , 1983, Oecologia.

[82]  H. H. Laar,et al.  Comprar Scale and Complexity in Plant Systems Research · Gene-Plant-Crop Relations | Spiertz, J.H.J. | 9781402059049 | Springer , 2007 .

[83]  G. Farquhar,et al.  Some relationships between the biochemistry of photosynthesis and the gas exchange of leaves , 1981, Planta.

[84]  Wei Huang,et al.  A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase , 2007, Nature Genetics.

[85]  M. Blair,et al.  The molecularization of public sector crop breeding: progress, problems, and prospects , 2007 .

[86]  D. Lawlor.  Carbon and nitrogen assimilation in relation to yield: mechanisms are the key to understanding production systems. , 2002, Journal of experimental botany.