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Background: Leaf senescence is a complex process, controlled by multiple genetic and environmental variables. In sunflower, leaf senescence is triggered abruptly following anthesis thereby limiting the capacity of plants to keep their green leaf area during grain filling, which subsequently has a strong impact on crop yield. Recently, we performed a selection of contrasting sunflower inbred lines for the progress of leaf senescence through a physiological, cytological and molecular approach. Here we present a large scale transcriptomic analysis using RNA-seq and its integration with metabolic profiles for two contrasting sunflower inbred lines, R453 and B481-6 (early and delayed senescence respectively), with the aim of identifying metabolic pathways associated to leaf senescence., Results: Gene expression profiles revealed a higher number of differentially expressed genes, as well as, higher expression levels in R453, providing evidence for early activation of the senescence program in this line. Metabolic pathways associated with sugars and nutrient recycling were differentially regulated between the lines. Additionally, we identified transcription factors acting as hubs in the co-expression networks; some previously reported as senescence-associated genes in model species but many are novel candidate genes., Conclusions: Understanding the onset and the progress of the senescence process in crops and the identification of these new candidate genes will likely prove highly useful for different management strategies to mitigate the impact of senescence on crop yield. Functional characterization of candidate genes will help to develop molecular tools for biotechnological applications in breeding crop yield.

Orthodox seeds are living organisms that survive anhydrobiosis and may display dormancy, an inability to germinate at harvest. Seed germination potential can be acquired during a prolonged period of dry storage called after-ripening. The aim of this work was to determine if gene transcription is an underlying regulatory mechanism for dormancy alleviation during after-ripening. To identify changes in gene transcription strictly associated with the acquisition of germination potential but not with storage, we used seed storage at low relative humidity that maintains dormancy as control. Transcriptome profiling was performed using DNA microarray to compare change in gene transcript abundance between dormant (D), after-ripened non-dormant (ND) and after-ripened dormant seeds (control, C). Quantitative real-time polymerase chain reaction (qPCR) was used to confirm gene expression. Comparison between D and ND showed the differential expression of 115 probesets at cut-off values of two-fold change (p<0.05). Comparisons between both D and C with ND in transcript abundance showed that only 13 transcripts, among 115, could be specific to dormancy alleviation. qPCR confirms the expression pattern of these transcripts but without significant variation between conditions. Here we show that sunflower seed dormancy alleviation in the dry state is not related to regulated changes in gene expression.

Plant or soil water status is required in many scientific fields to understand plant responses to drought. Because the transcriptomic response to abiotic conditions, such as water deficit, reflects plant water status, genomic tools could be used to develop a new type of molecular biomarker. Using the sunflower (Helianthus annuus L.) as a model species to study the transcriptomic response to water deficit both in greenhouse and field conditions, we specifically identified three genes that showed an expression pattern highly correlated to plant water status as estimated by the pre-dawn leaf water potential, fraction of transpirable soil water, soil water content or fraction of total soil water in controlled conditions. We developed a generalized linear model to estimate these classical water status indicators from the expression levels of the three selected genes under controlled conditions. This estimation was independent of the four tested genotypes and the stage (pre- or post-flowering) of the plant. We further validated this gene expression biomarker under field conditions for four genotypes in three different trials, over a large range of water status, and we were able to correct their expression values for a large diurnal sampling period., (© 2013 John Wiley & Sons Ltd.)