About

Scientific context

Expansive growth of leaves or of reproductive organs such as silks are affected by water deficit before any reduction in photosynthesis or root growth. The objective of the Phenodyn platform is to perform a genetic analysis of growth and gas exchanges which vary rapidly with environmental conditions (see movie). In particular, we aim to disentangle the genetic basis of the differences in growth rate and of its responses to temperature, evaporative demand and soil water deficit. Time courses of elongation rate, transpiration and environmental conditions are dissected into more heritable traits (maximum rate and sensitivity) which are stable characteristics of genotypes, amenable to genetic analysis. Phenodyn has been used for detection of QTLs of sensitivity of leaf elongation rate to soil water deficit and evaporative demand^1,2, for physiological analyses using transgenic or introgression lines⁵, and for analysing the genetic variability of growth and of its sensitivity to environmental conditions in panels of lines with different geographical and genetic origins. Phenodyn has been tested for maize leaves ^1,2,3,5 and rice leaves ⁶ and for maize silks ⁴.

Movie (2min)

The Phenodyn platform (current throughput : 480 plants) imposes drought scenarios under fluctuating atmospheric conditions in the greenhouse or the growth chamber, and follows transpiration and expansive growth with a definition of 5-15 min over periods of 1-2 weeks. This allows identification of the genetic variability of response of growth and transpiration to environmental cues, and in a quantification of the sensitivity to abiotic stresses. The experimental set-up in the greenhouse consists in 140 balances which measure changes in soil water status and transpiration, 420 displacement transducers which continuously measure leaf elongation rate, and a set of climatic sensors. A companion set-up is placed in a growth chamber, with the same sensors for measurement of 60 plants simultaneously. Leaf or silk elongation rates are measured with rotational displacement transducers. They are transmitted to the sensor via a pulley which carries a thread attached to the leaf or silk tip and to a 20 g counterweight. Soil water content is estimated by continuously weighing columns. Differences in weight are attributed to changes in soil water content, after correction for the increase in mean plant biomass as a function of phenological stage. Soil water content is transformed into soil water potential via a water release curve corresponding to the potting compost. Air temperature, relative humidity and light are measured at plant level, with two series of sensors per block. The temperature of the meristematic zone of studied organs is measured with fine copper-constantan thermocouples. All data are averaged and stored every 5 to 15 min in the database. It was checked (i) that the procedure for estimating soil water content generates errors smaller than 3 g , i.e. an error in soil water content of about 6 10^-4g, (ii) that a counterweight of 20 g does not cause changes in elongation rate of leaf or silks of maize. Conversely, it affects leaf growth of rice on the first day after emergence.

The Phenodyn Information system

The phenotyping platform is associated to an information system for real time monitoring of experiments, post-analysis of large datasets (around 700.000 datapoints are generated in each experiment) and identification of genotypic parameters.

Information system architecture

Two computers automatically send data to a database through wifi access every 5 to 15 minutes. Manual measurements on plants (ie. phenology) are also entered in the database using CSV files. Data are stored in an MySQL 5.0 database hosted on a Linux server. Database interface is based on PHP programs or HTML pages and some R scripts to generate elaborated graphics. We also use Ajax for a better user interaction.

Web Interface for real time monitoring

The system is based on a client-server architecture. Time-courses are visualised using PHP (jpgraph library) or R scripts.

• Through the web interface, users can follow the outputs of the 500 sensors during the experiment for rapid inspection of time courses for a real-time identification of problems (e.g. sensors quality) and decision making (e.g. watering).
• A more detailed picture of the experiment is provided by export procedures using R scripts which synthesise data (e.g. climatic conditions, growth of all plants of a common genotypes, comparison between genotypes).
• Procedures for data validation (assigned by domain or expert rules and statistics testing) are under development.

References

1. Sadok W, Naudin Ph, Boussuge B, Muller B, Welcker C, Tardieu F (2007) Leaf growth rate per unit thermal time follows QTL-dependent daily patterns in hundreds of maize lines under naturally fluctuating conditions. Plant Cell and Environment 30, 135-146
2. Welcker C, Boussuge B, Benciveni C, Ribaut JM, Tardieu F. (2007) Are source and sinks strengths genetically linked in maize plants subjected to water deficit ? A QTL study of the responses of leaf growth and Anthesis-Silking Interval to water deficit. Journal of Experimental Botany, 58, 339 - 349
3. Chenu, K, Chapman SC Hammer GL, McLean G, Ben Haj Salah H, Tardieu F (2008) Short-term responses of leaf growth rate to water deficit scale up to whole-plant and crop levels: an integrated modelling approach in maize. Plant Cell and Environment 31, 378-391
4. Fuad-Hassan A, Tardieu F, Turc O (2008) Drought-induced changes in anthesis-silking interval are related to silk expansion: a spatio-temporal growth analysis in maize plants subjected to soil water deficit Plant Cell and Environment 31, 1349 - 1360
5. Parent B, Hachez C, Redondo E, Simonneau T, Chaumont F, Tardieu F (2009) Drought and ABA effects on aquaporin content translate into changes in hydraulic conductivity and leaf growth rate : a trans-scale approach. Plant Physiology, 149, 2000-2012
6. Parent B, Conejero G, Tardieu F (2009) Spatial and temporal analysis of non-steady elongation of rice leaves Plant Cell and Environment 32 1561-1572
7. Reymond M, Muller B, Leonardi A, Charcosset A, Tardieu F (2003) 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 deficit. Plant Physiology 131: 664-675

- Scientifiques : Tardieu François, Welcker Claude
- Techniciens : Berthezene Stéphane, Brichet Nicolas, Hamard Philippe, Suard Benoît
- Informaticiens: Vincent Negre,Tireau Anne, Pascal Neveu, Boussgue Benoît