The quest for tolerant varieties: integration of -omics techniques to understand stress in non-model crops
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Carpentier, S.C.; Kissel, E.; Janial, M.; Rouard, M.; Zorrilla, J.; Swennen, R. (2016) The quest for tolerant varieties: integration of -omics techniques to understand stress in non-model crops [Abstract] XXIV Plant and Animal Genome Conference. San Diego, CA (USA) 9-13 Jan 2016.
Permanent link to cite or share this item: http://hdl.handle.net/10568/78751
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Millions of people depend on rain fed crop systems that are very prone to fluctuating water availability. In-depth knowledge on the plant’s stress response is therefore of utmost importance. However, in many crops not much is known about the genes involved in early stress response and their link to long term stress response. In the light of crop improvement, we intend to fill this gap by linking phenotyping to different –omics techniques. As a proof of principle we will present how to use real-time transpiration data of different genotypes in this context. In addition, we will focus on the omics analysis of two genetically diverse cultivars. Our real-time transpiration studies have enabled us to bring forward a new hypothesis: drought tolerant varieties have a feedback mechanism that is closing stomata in response to a saturated photosynthesis. The advantage of this feedback mechanism might be that when photosynthesis is so efficient and saturated, stomata can partially close to change the H2O-efflux versus CO2-influx balance, leading to a higher transpiration efficiency. To characterize the phenotype we developed a real-time monitoring system and measured: water loss, the dynamic leaf surface temperature, and the stomatal conductance in 6 genotypes with a differing transpiration efficiency. Based on the phenotyping results we determined the time points for the cellular phenotyping and have data that place the feedback in context of sugar signalling. To get an insight into different tolerance mechanisms the leaf transcriptome of a tolerant and sensitive variety (37,582 genes, using RNA-Seq) was assessed after three days of stress, while the phenome (67 phenotypic variables) was assessed during 21 days. Using the phenome at day 21, we discerned 9 long term phenotypic stress responses present in both cultivars. Subsequently, the phenome was used to disentangle the highly multidimensional transcriptome data. More specifically, we uncovered the early stress genes that were most related to one of the envisioned 9 core long-term processes at the third day after stress induction. We developed a workflow to add value to phenotyping data and have ear marked a gene set that is most likely involved in the early development of some of the core stress responses at the phenome level.