Current features for new challenges in plant phenotyping

(1) Up to 1516 Arabidopsis thaliana plants can now be grown in PHENOPSIS .

In 2007, two more automats were built in two other independent growing chambers. Thus, 1516 plants can now be weighed, irrigated, and imaged automatically. Since then, a wide range of A. thaliana genotypes has been phenotyped in PHENOPSIS under different environmental conditions.
This diversity of genotypes includes: genetically modified lines (Massonnet et al., 2015), recombinant line populations (Tisné et al., 2008, 2010; Vasseur et al., 2014), accession collections (Bac-Molenaar et al., 2015, 2016), epigenetic hybrids (Dapp et al., 2015). The high-throughput phenotyping effort has been combined with quantitative genetic analyses (Tisné et al., 2008, 2010; Vasseur et al., 2014; Bac-Molenaar et al., 2015, 2016), statistical modelling (Lièvre et al., 2016), biochemical analyses (Ghandilyan et al., 2009; Bourdenx et al., 2011; Pascal et al., 2013) or transcript and protein analyses (Baerenfaller et al., 2012, 2015). All this has led to major advances in the understanding of the regulation of leaf development and plasticity in response to water stress.

For more information, read the publications :

Bac-Molenaar J.A., Granier C., Vreugdenhil D., Keurentjes J.J.B. (2016) Genome wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis. Plant, Cell & Environment. 39, 88-102.

Bac-Molenaar J.A., Vreugdenhil D., Granier C., Keurentjes J.J.B. (2015) Genome wide association mapping of growth dynamics detects time-specific and general QTLs. Journal of Experimental Botany. 66, (18) 5567-5580.

Baerenfaller K. et al., (2012) Systems-based analysis of Arabidopsis leaf growth reveals adaptation to water deficit. Molecular Systems Biology 8:606

Baerenfaller, K., Massonnet, C., Hennig, L., Russenberger, D., Sulpice, R., Walsh, S., Stitt, M., Granier, C., Gruissem, W. (2015) A long photoperiod relaxes energy management in Arabidopsis leaf six. Current Plant Biology, 2, 34-45.

Blonder B. et al., (2015)Testing models for the origin of the leaf economics spectrum with leaf and whole-plant traits in Arabidopsis thaliana. AoB Plants. 7

Bourdenx B., Bernard A., Domergue F. et al (2011) Overexpression of Arabidopsis ECERIFERUM1 promotes wax very-long-chain alkane biosynthesis and influences plant response to biotic and abiotic stresses. Plant Physiology 156, 29-45.

Dapp M. et al., (2015) Heterosis and inbreeding depression of epigenetic Arabidopsis hybrids. Nature Plants. 1, 15092.

Ghandilyan A. et al.,(2009)Genetic analysis identifies quantitative trait loci controlling rosette mineral concentrations in Arabidopsis thaliana under drought. New Phytologist 184:180-192.

Lièvre M., Granier C., Guédon Y. (2016) Identifying developmental phases in Arabidopsis thaliana rosette using integrative segmentation models. New Phytologist. doi: 10.1111/nph.13861.

Massonnet C. et al. (2011) New insights into the control of endoreduplication: endoreduplication is driven by organ growth in Arabidopsis leaves. Plant Physiology 157: 2044-2055.

Massonnet C. et al., (2015) Individual leaf area of early flowering arabidopsis genotypes is more affected by drought than late flowering ones: a multi-scale analysis in 35 genetically modified lines. American Journal of Plant Sciences. 6, 955-971.

Pascal S., Bernard A., Sorel M., Pervent M., Vile D., Haslam R.P., et al. (2013) The Arabidopsis cer26 mutant, like the cer2 mutant, is specifically affected in the very-long-chain fatty acid elongation process. Plant J. 73:733-746.

Tisné S. et al.,(2008) Combined genetic and modeling approaches reveal that epidermal cell area and number in leaves are controlled by leaf and plant developmental processes in Arabidopsis. Plant Physiology 148, 1117-1127.

Tisné S. et al.,(2010) Keep on growing under drought: genetic and developmental bases of the response of rosette area using a recombinant inbred line population. Plant Cell & Environment 33: 1875-1887.

Vasseur F. et al., (2012) A common genetic basis to the origin of the leaf economics spectrum and metabolic scaling allometry. Ecology Letters 15: 1149-1157.

Vasseur F, et al., (2014) Multivariate genetic analysis of plant responses to water deficit and high temperature revealed contrasted adaptive strategies. Journal of Experimental Botany. 65 (22), 6457-6469.

Westgeest, A. J., Dauzat, M., Simonneau, T., & Pantin, F. (2023). Leaf starch metabolism sets the phase of stomatal rhythm. The Plant Cell, 35(9), 3444-3469.

(2) Other variables than rosette area or leaf transpiration can be measured automatically or semi-automatically in PHENOPSIS.

The imaging station on the PHENOPSIS arm has been modified to accommodate additional cameras: a side camera for hyponasia measurements (Vasseur et al., 2014), a fluorescence camera to estimate photosynthetic efficiency (Bresson et al., 2014, Bresson et al., 2015) and an infrared camera to measure leaf temperature (Vasseur et al., 2014). In addition, we have developed protocols to measure growth at the cellular level (Wuyts et al., 2010).
Our results have repeatedly shown that having an automatic machine with an on-board camera to measure leaf area is not a sufficient condition to define the leaf growth phenotype of a genotype (Lièvre et al., 2013). Moreover, measuring a dynamic variable such as leaf area at one date on a large number of genotypes does not necessarily provide information on the behaviour of these genotypes or on the genetic control of leaf area (Lièvre et al., 2013; Bac-Molenaar et al., 2015, 2016). As illustrated in many of our works, we insist that taking into account environmental and temporal variations of the phenotype as well as considering the phenotype at different scales of organization allows a better characterization of phenotype-genotype relationships (Granier & Vile, 2014).

For more information, read the publications :

Bac-Molenaar J.A., Granier C., Vreugdenhil D., Keurentjes J.J.B. (2016) Genome wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis. Plant, Cell & Environment. 39, 88-102.

Bac-Molenaar J.A., Vreugdenhil D., Granier C., Keurentjes J.J.B. (2015) Genome wide association mapping of growth dynamics detects time-specific and general QTLs. Journal of Experimental Botany. 66, (18) 5567-5580.

Bresson J. et al., (2015) Quantifying spatial heterogeneity of chlorophyll fluorescence during plant growth and in response to water stress. Plant Methods. 11, 23.

Bresson J. et al., (2014) Interact to survive: Phyllobacterium brassicacearum improves Arabidopsis tolerance to severe water deficit and growth recovery. PLoS ONE 9(9): e107607.

Granier C, Vile D (2014) Phenotyping and beyond: modelling the relationships between traits. Curent Opinion in Plant Biology, 18: 96-102.

Lièvre M. et al., (2013) Phenotyping the kinematics of leaf development in flowering plants: recommendations and pitfalls. WIREs Developmental Biology, 2(6):809-821. 

Vasseur F. et al., (2014) Multivariate genetic analysis of plant responses to water deficit and high temperature revealed contrasted adaptive strategies. Journal of Experimental Botany. 65 (22) 6457-6469.

(3)    PHENOPSIS can be used to analyse the response of plants to drought but also to other stressful conditions.

The possibility of growing the plants with the same controller in 3 independent growth chambers made it possible to grow them at different temperatures, different photoperiods and to combine these situations with water stress situations (Baerenfaller et al., 2015; Vasseur et al., 2014). The combination of these environmental factors with more complex scenarios required the development of a new irrigation station. Thus it is now possible to grow plants in the same experiment with two different nutrient solutions. This was used to test the effect of different heavy metal concentrations (collaboration F. Gosti, BPMP Montpellier, France). We also had to modify the computer interface for controlling the automaton to be able to use different types of soil in the same experiment, for example with or without rhizobacteria (collaboration F. Varoquaux, LSTM Montpellier, France; Bresson et al., 2013 & 2014).

For more information, read the publications :

Baerenfaller K. et al., (2015) A long photoperiod relaxes energy management in Arabidopsis leaf six. Current Plant Biology. 2, 34-45.

Bresson J. et al., (2013). The PGPR strain Phyllobacterium brassicacearum STM196 induces a reproductive delay and physiological changes that result in improved drought tolerance in Arabidopsis. New Phytologist 200: 558–569.

Bresson J. et al. (2014) Interact to survive: Phyllobacterium brassicacearum improves Arabidopsis tolerance to severe water deficit and growth recovery. PLoS ONE 9(9): e107607.

Vasseur F. et al., (2014) Multivariate genetic analysis of plant responses to water deficit and high temperature revealed contrasted adaptive strategies. Journal of Experimental Botany. 65 (22) 6457-6469.

Vile D. et al., (2012) Arabidopsis growth under prolonged high temperature and water deficit: independent or interactive effects? Plant Cell and Environment 35(4): 702-718.

Westgeest, A. J., Dauzat, M., Simonneau, T., & Pantin, F. (2023). Leaf starch metabolism sets the phase of stomatal rhythm. The Plant Cell, 35(9), 3444-3469.

(4) Other species than Arabidopsis thaliana can be grown in PHENOPSIS

In recent years, numerous efforts have been made to transfer the knowledge obtained from model plants to cultivated plants (Blonder et al. 2015). Recent developments on PHENOPSIS go in this direction as they now allow plants to be grown in larger pots (1,2,3,8 L).  When larger pots are used in PHENOPSIS, the number of plants grown per experiment decreases, but promising results have already been obtained for oilseed rape (Dambreville et al., 2016), tomato and Brachypodium distachion. In 2023, a test experiment on wheat up to the grain stage in 3 L pots demonstrated the quality of the results compared with greenhouse or field cultivation.

For more information, read the publications :

Blonder B., Vasseur F., Violle C., Shipley B., Enquist B., Vile D. (2015) Testing models for the origin of the leaf economics spectrum with leaf and whole-plant traits in Arabidopsis thaliana. AoB Plants. 7, DOI: 10.1093/aobpla/plv049.

Dambreville, A., Griolet, M., Rolland, G., Dauzat, M., Bédiée, A., Balsera, C., Muller, B., Vile, D., Granier, C. (published online) Phenotyping oilseed rape growth-related traits and their responses to water deficit: the disturbing pot size effect. Functional Plant Biology. FP16036.