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A large-scale metabolic quantitative trait loci (mQTL) analysis was performed on the well-characterized Solanum pennellii introgression lines to investigate the genomic regions associated with secondary metabolism in tomato fruit pericarp. In total, 679 mQTLs were detected across the 76 introgression lines. Heritability analyses revealed that mQTLs of secondary metabolism were less affected by environment than mQTLs of primary metabolism. Network analysis allowed us to assess the interconnectivity of primary and secondary metabolism as well as to compare and contrast their respective associations with morphological traits. Additionally, we applied a recently established real-time quantitative PCR platform to gain insight into transcriptional control mechanisms of a subset of the mQTLs, including those for hydroxycinnamates, acyl-sugar, naringenin chalcone, and a range of glycoalkaloids. Intriguingly, many of these compounds displayed a dominant-negative mode of inheritance, which is contrary to the conventional wisdom that secondary metabolite contents decreased on domestication. We additionally performed an exemplary evaluation of two candidate genes for glycolalkaloid mQTLs via the use of virus-induced gene silencing. The combined data of this study were compared with previous results on primary metabolism obtained from the same material and to other studies of natural variance of secondary metabolism.
Oxidative stress causes dramatic changes in the expression levels of many genes. The formation of a functional protein through successful mRNA translation is central to a coordinated cellular response. To what extent the response towards reactive oxygen species (ROS) is regulated at the translational level is poorly understood. Here we analysed leaf- and tissue-specific translatomes using a set of transgenic Arabidopsis thaliana lines expressing a FLAG-tagged ribosomal protein to immunopurify polysome-bound mRNAs before and after oxidative stress. We determined transcript levels of 171 ROS-responsive genes upon paraquat treatment, which causes formation of superoxide radicals, at the whole-organ level. Furthermore, the translation of mRNAs was determined for five cell types: mesophyll, bundle sheath, phloem companion, epidermal and guard cells. Mesophyll and bundle sheath cells showed the strongest response to paraquat treatment. Interestingly, several ROS-responsive transcription factors displayed cell type-specific translation patterns, while others were translated in all cell types. In part, cell type-specific translation could be explained by the length of the 5-untranslated region (5-UTR) and the presence of upstream open reading frames (uORFs). Our analysis reveals insights into the translational regulation of ROS-responsive genes, which is important to understanding cell-specific responses and functions during oxidative stress.
The study illustrates the response of different Arabidopsis thaliana leaf cells and tissues to oxidative stress at the translational level, an aspect of reactive oxygen species (ROS) biology that has been little studied in the past. Our data reveal insights into how translational regulation of ROS-responsive genes is fine-tuned at the cellular level, a phenomenon contributing to the integrated physiological response of leaves to stresses involving changes in ROS levels.
In roots of Arabidopsis (Arabidopsis thaliana), L-lactate is generated by the reduction of pyruvate via L-lactate dehydrogenase, but this enzyme does not efficiently catalyze the reverse reaction. Here, we identify the Arabidopsis glycolate oxidase (GOX) paralogs GOX1, GOX2, and GOX3 as putative L-lactate-metabolizing enzymes based on their homology to CYB2, the L-lactate cytochrome c oxidoreductase from the yeast Saccharomyces cerevisiae. We found that GOX3 uses L-lactate with a similar efficiency to glycolate; in contrast, the photorespiratory isoforms GOX1 and GOX2, which share similar enzymatic properties, use glycolate with much higher efficiencies than L-lactate. The key factor making GOX3 more efficient with L-lactate than GOX1 and GOX2 is a 5- to 10-fold lower Km for the substrate. Consequently, only GOX3 can efficiently metabolize L-lactate at low intracellular concentrations. Isotope tracer experiments as well as substrate toxicity tests using GOX3 loss-of-function and overexpressor plants indicate that L-lactate is metabolized in vivo by GOX3. Moreover, GOX3 rescues the lethal growth phenotype of a yeast strain lacking CYB2, which cannot grow on L-lactate as a sole carbon source. GOX3 is predominantly present in roots and mature to aging leaves but is largely absent from young photosynthetic leaves, indicating that it plays a role predominantly in heterotrophic rather than autotrophic tissues, at least under standard growth conditions. In roots of plants grown under normoxic conditions, loss of function of GOX3 induces metabolic rearrangements that mirror wild-type responses under hypoxia. Thus, we identified GOX3 as the enzyme that metabolizes L-lactate to pyruvate in vivo and hypothesize that it may ensure the sustainment of low levels of L-lactate after its formation under normoxia.
Plants respond to low carbon supply by massive reprogramming of the transcriptome and metabolome. We show here that the carbon starvation-induced NAC (for NO APICAL MERISTEM/ARABIDOPSIS TRANSCRIPTION ACTIVATION FACTOR/CUP-SHAPED COTYLEDON) transcription factor Arabidopsis (Arabidopsis thaliana) Transcription Activation Factor1 (ATAF1) plays an important role in this physiological process. We identified TREHALASE1, the only trehalase-encoding gene in Arabidopsis, as a direct downstream target of ATAF1. Overexpression of ATAF1 activates TREHALASE1 expression and leads to reduced trehalose-6-phosphate levels and a sugar starvation metabolome. In accordance with changes in expression of starch biosynthesis-and breakdown-related genes, starch levels are generally reduced in ATAF1 overexpressors but elevated in ataf1 knockout plants. At the global transcriptome level, genes affected by ATAF1 are broadly associated with energy and carbon starvation responses. Furthermore, transcriptional responses triggered by ATAF1 largely overlap with expression patterns observed in plants starved for carbon or energy supply. Collectively, our data highlight the existence of a positively acting feedforward loop between ATAF1 expression, which is induced by carbon starvation, and the depletion of cellular carbon/energy pools that is triggered by the transcriptional regulation of downstream gene regulatory networks by ATAF1.
High nitrogen (N) efficiency, characterized by high grain yield under N limitation, is an important agricultural trait in Brassica napus L. cultivars related to delayed senescence of older leaves during reproductive growth (a syndrome called stay-green). The aim of this study was thus to identify genes whose expression is specifically altered during N starvation-induced leaf senescence and that can be used as markers to distinguish cultivars at early stages of senescence prior to chlorophyll loss. To this end, the transcriptomes of leaves of two B. napus cultivars differing in stay-green characteristics and N efficiency were analyzed 4 days after the induction of senescence by either N starvation, leaf shading or detaching. In addition to N metabolism genes, N starvation mostly (and specifically) repressed genes related to photosynthesis, photorespiration and cell-wall structure, while genes related to mitochondrial electron transport and flavonoid biosynthesis were predominately up-regulated. A kinetic study over a period of 12 days with four B. napus cultivars differing in their stay-green characteristics confirmed the cultivar-specific regulation of six genes in agreement with their senescence behavior: the senescence regulator ANAC029, the anthocyanin synthesis-related genes ANS and DFR-like1, the ammonium transporter AMT1:4, the ureide transporter UPSS, and SPS1 involved in sucrose biosynthesis. The identified genes represent markers for the detection of cultivar-specific differences in N starvation-induced leaf senescence and can thus be employed as valuable tools in B. napus breeding. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
MYB transcription factors (TFs) are important regulators of flavonoid biosynthesis in plants. Here, we report MYB112 as a formerly unknown regulator of anthocyanin accumulation in Arabidopsis (Arabidopsis thaliana). Expression profiling after chemically induced overexpression of MYB112 identified 28 up-and 28 down-regulated genes 5 h after inducer treatment, including MYB7 and MYB32, which are both induced. In addition, upon extended induction, MYB112 also positively affects the expression of PRODUCTION OF ANTHOCYANIN PIGMENT1, a key TF of anthocyanin biosynthesis, but acts negatively toward MYB12 and MYB111, which both control flavonol biosynthesis. MYB112 binds to an 8-bp DNA fragment containing the core sequence (A/T/G)(A/C) CC(A/T)(A/G/T)(A/C)(T/C). By electrophoretic mobility shift assay and chromatin immunoprecipitation coupled to quantitative polymerase chain reaction, we show that MYB112 binds in vitro and in vivo to MYB7 and MYB32 promoters, revealing them as direct downstream target genes. We further show that MYB112 expression is up-regulated by salinity and high light stress, environmental parameters that both require the MYB112 TF for anthocyanin accumulation under these stresses. In contrast to several other MYB TFs affecting anthocyanin biosynthesis, MYB112 expression is not controlled by nitrogen limitation or an excess of carbon. Thus, MYB112 constitutes a regulator that promotes anthocyanin accumulation under abiotic stress conditions.
Growth-regulating factors (GRFs) are plant-specific transcription factors that were originally identified for their roles in stem and leaf development, but recent studies highlight them to be similarly important for other central developmental processes including flower and seed formation, root development, and the coordination of growth processes under adverse environmental conditions. The expression of several GRFs is controlled by microRNA miR396, and the GRF-miRNA396 regulatory module appears to be central to several of these processes. In addition, transcription factors upstream of GRFs and miR396 have been discovered, and gradually downstream target genes of GRFs are being unraveled. Here, we review the current knowledge of the biological functions performed by GRFs and survey available molecular data to illustrate how they exert their roles at the cellular level.
Recent analyses have demonstrated that plant metabolic networks do not differ in their structural properties and that genes involved in basic metabolic processes show smaller coexpression than genes involved in specialized metabolism. By contrast, our analysis reveals differences in the structure of plant metabolic networks and patterns of coexpression for genes in (non)specialized metabolism. Here we caution that conclusions concerning the organization of plant metabolism based on network-driven analyses strongly depend on the computational approaches used.
Time-series data from multicomponent systems capture the dynamics of the ongoing processes and reflect the interactions between the components. The progression of processes in such systems usually involves check-points and events at which the relationships between the components are altered in response to stimuli. Detecting these events together with the implicated components can help understand the temporal aspects of complex biological systems. Here we propose a regularized regression-based approach for identifying breakpoints and corresponding segments from multivariate time-series data. In combination with techniques from clustering, the approach also allows estimating the significance of the determined breakpoints as well as the key components implicated in the emergence of the breakpoints. Comparative analysis with the existing alternatives demonstrates the power of the approach to identify biologically meaningful breakpoints in diverse time-resolved transcriptomics data sets from the yeast Saccharomyces cerevisiae and the diatom Thalassiosira pseudonana.