@article{BalazadehKwasniewskiCaldanaetal.2011, author = {Balazadeh, Salma and Kwasniewski, Miroslaw and Caldana, Camila and Mehrnia, Mohammad and Zanor, Maria Ines and Xue, Gang-Ping and M{\"u}ller-R{\"o}ber, Bernd}, title = {ORS1, an H2O2-Responsive NAC Transcription Factor, Controls Senescence in Arabidopsis thaliana}, series = {Molecular plant}, volume = {4}, journal = {Molecular plant}, number = {2}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {1674-2052}, doi = {10.1093/mp/ssq080}, pages = {346 -- 360}, year = {2011}, abstract = {We report here that ORS1, a previously uncharacterized member of the NAC transcription factor family, controls leaf senescence in Arabidopsis thaliana. Overexpression of ORS1 accelerates senescence in transgenic plants, whereas its inhibition delays it. Genes acting downstream of ORS1 were identified by global expression analysis using transgenic plants producing dexamethasone-inducible ORS1-GR fusion protein. Of the 42 up-regulated genes, 30 (similar to 70\%) were previously shown to be up-regulated during age-dependent senescence. We also observed that 32 (similar to 76\%) of the ORS1-dependent genes were induced by long-term (4 d), but not short-term (6 h) salinity stress (150 mM NaCl). Furthermore, expression of 16 and 24 genes, respectively, was induced after 1 and 5 h of treatment with hydrogen peroxide (H2O2), a reactive oxygen species known to accumulate during salinity stress. ORS1 itself was found to be rapidly and strongly induced by H2O2 treatment in both leaves and roots. Using in vitro binding site selection, we determined the preferred binding motif of ORS1 and found it to be present in half of the ORS1-dependent genes. ORS1 is a paralog of ORE1/ANAC092/AtNAC2, a previously reported regulator of leaf senescence. Phylogenetic footprinting revealed evolutionary conservation of the ORS1 and ORE1 promoter sequences in different Brassicaceae species, indicating strong positive selection acting on both genes. We conclude that ORS1, similarly to ORE1, triggers expression of senescence-associated genes through a regulatory network that may involve cross-talk with salt- and H2O2-dependent signaling pathways.}, language = {en} } @article{RohrmannTohgeAlbaetal.2011, author = {Rohrmann, Johannes and Tohge, Takayuki and Alba, Rob and Osorio, Sonia and Caldana, Camila and McQuinn, Ryan and Arvidsson, Samuel Janne and van der Merwe, Margaretha J. and Riano-Pachon, Diego Mauricio and M{\"u}ller-R{\"o}ber, Bernd and Fei, Zhangjun and Nesi, Adriano Nunes and Giovannoni, James J. and Fernie, Alisdair R.}, title = {Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development}, series = {The plant journal}, volume = {68}, journal = {The plant journal}, number = {6}, publisher = {Wiley-Blackwell}, address = {Malden}, issn = {0960-7412}, doi = {10.1111/j.1365-313X.2011.04750.x}, pages = {999 -- 1013}, year = {2011}, abstract = {Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes.}, language = {en} }