The need for Good Phenotyping Practice – Standards in Plant Phenotyping
Groundbreaking discoveries in molecular biology have allowed us a detailed characterization and understanding of complex genetic networks. However, the plant phenotype is the unit of importance in particular for practical issues such as crop production (Fiorani and Schurr 2013; Pieruschka and Poorter 2012). The phenotype is the result from the complex interrelation between genes and the environment (Kohl et al. 2010). While the development in plant molecular biology and in molecular-based breeding techniques has progressed rapidly within the last decades the understanding of the link between genotype and phenotype did not keep up with this development. Advances in phenotyping as the process of quantitative characterizing the phenotype has become the major limiting step. The gap between the knowledge about genes and phenotypes is particularly large in analyses of plant-environment interactions that are urgently needed for research and application to sustainable and resource-efficient crop production in the context of climate change and varying agricultural production conditions (Houle et al. 2010).
Quantitative information on genotype-environment relations is the key to address major challenges. In particular the relations how complex traits such as growth, performance or resource use efficiencies are associated with the environment follow a nonlinear response. Analysis of mapping populations, such as in the case of the quantitative trait loci (QTL) approach or genome-wide association (GWA) studies require phenotyping as a crucial component of the analysis. Additionally, this quantitative information needs to be obtained in a certain throughput with hundreds and more of lines using minimal invasive or non-invasive technologies which are integrated into screening protocols (Tardieu and Schurr 2009). Several platforms for phenotyping of model plants such as Arabidopsis have been established within recent years e.g. Phenopsis (Granier et al. 2006). Relatively small size of these model plants allows experiments in relatively small and controlled growth chambers. Currently more and more platforms for crops with different properties than the model plants have to be established to satisfy the needs of basic plant science and of the industry. Plants with a certain size and structural properties result in new challenges so that such plants cannot be treated under controlled growth chambers conditions but are grown semi or not controlled greenhouses. Validation experiments for establishing standard protocols for dynamic responses of Arabidopsis to environmental conditions were published (Granier et al. 2006; Massonnet et al. 2010). Large-scale studies with automated platforms to screen morphological and physiological traits of large plants are rather difficult and the interpretation requires comprehensive concept and standards for environmental monitoring, automation of trait assessment as well as the data acquisition and analysis. It is rather obvious that in some disciplines such as meteorology the standardization of the measurement of the environmental is essential for reliable weather forecasts or the estimation of future climate scenarios. But standardization in biological applications such as screening of the model organism mouse has also been recognized as an essential step and “the phenotype data must be generated using comprehensive phenotyping platforms that provide standardized methods, so that the results can be compared between laboratories and across time” (Mallon et al. 2008).
The EU funded project EPPN (European Plant Phenotyping Network) has a goal to integrate the European phenotyping activities. One of the key elements within EPPN is the establishment of common standards and good phenotyping practice. To achieve this goal EPPN is designing and performing a “reference experiment” with a certain number of the same genotypes of a monocot and a dicot which will be screened at different location. The important initial step in this experiment is the definition of standards for both environmental monitoring and trait assessment. In this experiment plant structure and function of selected genotypes will be analyzed under a range of environmental conditions defined by the diverse geographical location of the participating labs. Thus, standardization of environmental monitoring, trait assessment and data management is the key to elaborate and test methods to evaluate the responses of different genotypes to environmental conditions, by exploiting the contrasts of environmental conditions within different platforms. While in previous studies (Massonnet et al 2010) the experimental conditions were approximately constant in growth chambers, this cannot be maintained under greenhouse conditions at different locations. This requires a high level of standardization of environmental and phenotypic measurements. This experiment provides thus an important step towards standardization of phenotyping experiments which goes beyond the interests of the EPPN participants but addresses plant phenotyping community.
On this web platform we provide an initial set of protocols based on the EPPN "reference experiment" for the plant phenotyping community. Additionally, literature that addresses this issue is also available. Based on the expertise of the EPPN consortium, the set of protocols and literature references will be continuously extended.
Fiorani F, Schurr U (2012) Future Scenarios for Plant Phenotyping. Annual Review of Plant Biology 64, 1-17.
Granier C, Aguirrezabal L, Chenu K, Cookson SJ, Dauzat M, Hamard P, Thioux JJ, Rolland G, Bouchier-Combaud S, Lebaudy A, Muller B, Simonneau T, Tardieu F (2006) PHENOPSIS, an automated platform for reproducible phenotyping of plant responses to soil water deficit in Arabidopsis thaliana permitted the identification of an accession with low sensitivity to soil water deficit. New Phytologist 169, 623-635.
Houle D, Govindaraju DR, Omholt S (2010) Phenomics: the next challenge. Nature Reviews Genetics 11, 855-866.
Kohl P, Crampin EJ, Quinn TA, Noble D (2010) Systems Biology: An Approach. Clinical Pharmacology & Therapeutics 88, 25-33.
Mallon AM, Blake A, Hancock JM (2008) EuroPhenome and EMPReSS: online mouse phenotyping resource. Nucleic Acids Research 36, D715-D718.
Massonnet C, Vile D, Fabre J, Hannah MA, Caldana C, Lisec J, Beemster GTS, Meyer RC, Messerli G, Gronlund JT, Perkovic J, Wigmore E, May S, Bevan MW, Meyer C, Rubio-Di¡az S, Weigel D, Micol JL, Buchanan-Wollaston V, Fiorani F, Walsh S, Rinn B, Gruissem W, Hilson P, Hennig L, Willmitzer L, Granier C (2010) Probing the Reproducibility of Leaf Growth and Molecular Phenotypes: A Comparison of Three Arabidopsis Accessions Cultivated in Ten Laboratories. Plant Physiology 152, 2142-2157.
Pieruschka R, Poorter H (2012) Phenotyping plants: genes, phenes and machines. Functional Plant Biology 39, 813-820.
Poorter H, Buhler J, van Dusschoten D, Climent J, Postma JA (2012a) Pot size matters: a meta-analysis of the effects of rooting volume on plant growth. Functional Plant Biology.
Poorter H, Fiorani F, Stitt M, Schurr U, Finck A, Gibon Y, Usadel B, Munns R, Atkin OK, Tardieu F, Pons TL (2012b) The art of growing plants for experimental purposes: a practical guide for the plant biologist. Functional Plant Biology.
Tardieu F (2013) Plant response to environmental conditions: assessing potential production, water demand, and negative effects of water deficit. Frontiers in Physiology 4, 17.
Tardieu F, Schurr U (2009) "White paper" on plant phenotyping. http://www.plantphenomics.com/phenotyping2009.