Exploring chemical 'de-priming' and quantitative genetics to improve growth and yield of soybean under abiotic stress.

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One of the first changes in plants exposed to environmental stress is an increase of reactive oxygen species (ROS). During evolution, plants have 'learned' to interpret increased ROS as an early warning signal, and to use it as a trigger to induce physiological and biochemical responses that improve their chances of survival. Plant scientists are trying to understand the molecular components of stress signaling pathways and to exploit this information to develop strategies that can improve the stress tolerance of crops in the field. This is particularly important in India where the agricultural production of nutritious crops such as soybean is limited by environmental and climatic challenges arising from soil salinity, drought, water-logging and/or high temperature.'Chemical priming' has been proposed as a strategy to enhance the natural stress responses of a plant, for example through pre-treatment with low doses of ROS or ROS-producing agents. Indeed, faster or stronger induction of stress responses and improved plant stress tolerance has been reported for ROS-primed plants. However, our previous research in India has shown that the opposite approach - preventing early stress signaling by applying low concentrations of ROS-scavenging agents such as thiourea (TU) - also improves stress tolerance. The solution to this conundrum is likely to reside in the exact environmental condition ('stress scenario') under which tolerance is tested. To ensure survival, plants tend to prepare for the worst-case scenario. One would therefore expect that enhancing the natural plant responses through priming increases survival under severe long-term stress. However, in an agricultural setting some of the natural responses may be unnecessary and unwanted by the farmer. For example, production of stress-protective metabolites is energetically costly and can delay growth and development of the crop. Furthermore, some responses induced by one stress factor may exacerbate problems generated by another stress factor, e.g. closing stomata saves water under salt/drought stress but disables leaf cooling which is essential for combatting heat stress. Thus, if severe long-term stress does not occur, or is prevented through ad-hoc agricultural measures, crop varieties that ignore early stress signals ('happy-go-lucky' plants) could be better suited to farming in India than stress-sensitive ('panicky') varieties that induce strong stress responses. The aim of scenario-driven strategies would be to narrow the margin between actual and possible yield in a given stress situation.Following this line of argumentation we propose here a research programme that explores the benefits of both chemical and genetic de-priming for soybean production in Indian agriculture. Based on detailed physiological assays in the laboratory and yield data from field experiments we will establish a dose-effect curve of TU-treatments and determine the specific stress scenarios in which this approach improves soybean performance. The optimised TU formulation can immediately be applied in the field. In the longer term, TU application should be replaced by new custom varieties that are hard-wired to ignore early stress signals. To facilitate the development of 'happy-go-lucky' varieties we will therefore also investigate through RNA-sequencing the molecular processes that are targeted by TU, and carry out a genome-wide association study (GWAS) under single and combined salt/TU treatment. GWAS is possible with soybean because a large panel of accessions with re-sequenced genomes is already available. Correlating phenotypic data (root system architecture, biomass, yield) across these accessions with the genomic data will allow us to identify the genetic loci that underpin TU-modulation of stress responses. The information will enable the development of scenario-based custom varieties with improved stress tolerance through marker-assisted breeding or gene editing technology.