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Obesity is a risk factor for several major cancers. Associations of weight change in middle adulthood with cancer risk, however, are less clear. We examined the association of change in weight and body mass index (BMI) category during middle adulthood with 42 cancers, using multivariable Cox proportional hazards models in the European Prospective Investigation into Cancer and Nutrition cohort. Of 241 323 participants (31% men), 20% lost and 32% gained weight (>0.4 to 5.0 kg/year) during 6.9 years (average). During 8.0 years of follow-up after the second weight assessment, 20 960 incident cancers were ascertained. Independent of baseline BMI, weight gain (per one kg/year increment) was positively associated with cancer of the corpus uteri (hazard ratio [HR] = 1.14; 95% confidence interval: 1.05-1.23). Compared to stable weight (+/- 0.4 kg/year), weight gain (>0.4 to 5.0 kg/year) was positively associated with cancers of the gallbladder and bile ducts (HR = 1.41; 1.01-1.96), postmenopausal breast (HR = 1.08; 1.00-1.16) and thyroid (HR = 1.40; 1.04-1.90). Compared to maintaining normal weight, maintaining overweight or obese BMI (World Health Organisation categories) was positively associated with most obesity-related cancers. Compared to maintaining the baseline BMI category, weight gain to a higher BMI category was positively associated with cancers of the postmenopausal breast (HR = 1.19; 1.06-1.33), ovary (HR = 1.40; 1.04-1.91), corpus uteri (HR = 1.42; 1.06-1.91), kidney (HR = 1.80; 1.20-2.68) and pancreas in men (HR = 1.81; 1.11-2.95). Losing weight to a lower BMI category, however, was inversely associated with cancers of the corpus uteri (HR = 0.40; 0.23-0.69) and colon (HR = 0.69; 0.52-0.92). Our findings support avoiding weight gain and encouraging weight loss in middle adulthood.
The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM) is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing) to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1) gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF) and transcription regulator (TR) genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment) method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO2 response regulator 1) and Lcr2 (Low-CO2 response regulator 2), may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome. Our work can serve as a basis for future functional studies of transcriptional regulator genes and genomic regulatory elements in Chlamydomonas.
Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions.
Molecular phenotyping technologies (e.g., transcriptomics, proteomics, and metabolomics) offer the possibility to simultaneously obtain multivariate time series (MTS) data from different levels of information processing and metabolic conversions in biological systems. As a result, MTS data capture the dynamics of biochemical processes and components whose couplings may involve different scales and exhibit temporal changes. Therefore, it is important to develop methods for determining the time segments in MTS data, which may correspond to critical biochemical events reflected in the coupling of the system's components. Here we provide a novel network-based formalization of the MTS segmentation problem based on temporal dependencies and the covariance structure of the data. We demonstrate that the problem of partitioning MTS data into k segments to maximize a distance function, operating on polynomially computable network properties, often used in analysis of biological network, can be efficiently solved. To enable biological interpretation, we also propose a breakpoint-penalty (BP-penalty) formulation for determining MTS segmentation which combines a distance function with the number/length of segments. Our empirical analyses of synthetic benchmark data as well as time-resolved transcriptomics data from the metabolic and cell cycles of Saccharomyces cerevisiae demonstrate that the proposed method accurately infers the phases in the temporal compartmentalization of biological processes. In addition, through comparison on the same data sets, we show that the results from the proposed formalization of the MTS segmentation problem match biological knowledge and provide more rigorous statistical support in comparison to the contending state-of-the-art methods.
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.
The levels of cellular organization, from gene transcription to translation to protein-protein interaction and metabolism, operate via tightly regulated mutual interactions, facilitating organismal adaptability and various stress responses. Characterizing the mutual interactions between genes, transcription factors, and proteins involved in signaling, termed crosstalk, is therefore crucial for understanding and controlling cells' functionality. We aim at using high-throughput transcriptomics data to discover previously unknown links between signaling networks. We propose and analyze a novel method for crosstalk identification which relies on transcriptomics data and overcomes the lack of complete information for signaling pathways in Arabidopsis thaliana. Our method first employs a network-based transformation of the results from the statistical analysis of differential gene expression in given groups of experiments under different signal-inducing conditions. The stationary distribution of a random walk (similar to the PageRank algorithm) on the constructed network is then used to determine the putative transcripts interrelating different signaling pathways. With the help of the proposed method, we analyze a transcriptomics data set including experiments from four different stresses/signals: nitrate, sulfur, iron, and hormones. We identified promising gene candidates, downstream of the transcription factors (TFs), associated to signaling crosstalk, which were validated through literature mining. In addition, we conduct a comparative analysis with the only other available method in this field which used a biclustering-based approach. Surprisingly, the biclustering-based approach fails to robustly identify any candidate genes involved in the crosstalk of the analyzed signals. We demonstrate that our proposed method is more robust in identifying gene candidates involved downstream of the signaling crosstalk for species for which large transcriptomics data sets, normalized with the same techniques, are available. Moreover, unlike approaches based on biclustering, our approach does not rely on any hidden parameters.
Pre-exposing (priming) plants to mild, non-lethal elevated temperature improves their tolerance to a later higher-temperature stress (triggering stimulus), which is of great ecological importance. 'Thermomemory' is maintaining this tolerance for an extended period of time. NAM/ATAF1/2/ CUC2 (NAC) proteins are plant-specific transcription factors (TFs) that modulate responses to abiotic stresses, including heat stress (HS). Here, we investigated the potential role of NACs for thermomemory. We determined the expression of 104 Ara bidopsis NAC genes after priming and triggering heat stimuli, and found ATAF1 expression is strongly induced right after priming and declines below control levels thereafter during thermorecovery. Knockout mutants of ATAF1 show better thermomemory than wild type, revealing a negative regulatory role. Differential expression analyses of RNA-seq data from ATAF1 overexpressor, ataf1 mutant and wild-type plants after heat priming revealed five genes that might be priming-associated direct targets of ATAF1: AT2G31260 (ATG9), AT2G41640 (GT61), AT3G44990 (XTH31), AT4G27720 and AT3G23540. Based on co-expression analyses applied to the aforementioned RNA-seq profiles, we identified ANAC055 to be transcriptionally co-regulated with ATAF1. Like atafl, anac055 mutants show improved thermomemory, revealing a potential co-control of both NACTFs over thermomemory. Our data reveals a core importance of two NAC transcription factors, ATAF1 and ANAC055, for thermomemory.
In flowering plants, sugars act as carbon sources providing energy for developing embryos and seeds. Although most studies focus on carbon metabolism in whole seeds, knowledge about how particular sugars contribute to the developmental transitions during embryogenesis is scarce. To develop a quantitative understanding of how carbon composition changes during embryo development, and to determine how sugar status contributes to final seed or embryo size, we performed metabolic profiling of hand-dissected embryos at late torpedo and mature stages, and dormant seeds, in two Arabidopsis thaliana accessions with medium [Columbia-0 (Col-0)] and large [Burren-0 (Bur-0)] seed sizes, respectively. Our results show that, in both accessions, metabolite profiles of embryos largely differ from those of dormant seeds. We found that developmental transitions from torpedo to mature embryos, and further to dormant seeds, are associated with major metabolic switches in carbon reserve accumulation. While glucose, sucrose, and starch predominantly accumulated during seed dormancy, fructose levels were strongly elevated in mature embryos. Interestingly, Bur-0 seeds contain larger mature embryos than Col-0 seeds. Fructose and starch were accumulated to significantly higher levels in mature Bur-0 than Col-0 embryos, suggesting that they contribute to the enlarged mature Bur-0 embryos. Furthermore, we found that Bur-0 embryos accumulated a higher level of sucrose compared to hexose sugars and that changes in sucrose metabolism are mediated by sucrose synthase (SUS), with SUS genes acting non-redundantly, and in a tissue-specific manner to utilize sucrose during late embryogenesis.
Moderate and temporary heat stresses prime plants to tolerate, and survive, a subsequent severe heat stress. Such acquired thermotolerance can be maintained for several days under normal growth conditions, and can create a heat stress memory. We recently demonstrated that plastid-localized small heat shock protein 21 ( HSP21) is a key component of heat stress memory in Arabidopsis thaliana. A sustained high abundance of HSP21 during the heat stress recovery phase extends heat stress memory. The level of HSP21 is negatively controlled by plastid-localized metalloprotease FtsH6 during heat stress recovery. Here, we demonstrate that autophagy, a cellular recycling mechanism, exerts additional control over HSP21 degradation. Genetic and chemical disruption of both metalloprotease activity and autophagy trigger superior HSP21 accumulation, thereby improving memory. Furthermore, we provide evidence that autophagy cargo receptor ATG8-INTERACTING PROTEIN1 (ATI1) is associated with heat stress memory. ATI1 bodies co-localize with both autophagosomes and HSP21, and their abundance and transport to the vacuole increase during heat stress recovery. Together, our results provide new insights into the module for control of the regulation of heat stress memory, in which two distinct protein degradation pathways act in concert to degrade HSP21, thereby enabling cells to recover from the heat stress effect at the cost of reducing the heat stress memory.
We investigated the systems response of metabolism and growth after an increase in irradiance in the nonsaturating range in the algal model Chlamydomonas reinhardtii. In a three-step process, photosynthesis and the levels of metabolites increased immediately, growth increased after 10 to 15 min, and transcript and protein abundance responded by 40 and 120 to 240 min, respectively. In the first phase, starch and metabolites provided a transient buffer for carbon until growth increased. This uncouples photosynthesis from growth in a fluctuating light environment. In the first and second phases, rising metabolite levels and increased polysome loading drove an increase in fluxes. Most Calvin-Benson cycle (CBC) enzymes were substrate-limited in vivo, and strikingly, many were present at higher concentrations than their substrates, explaining how rising metabolite levels stimulate CBC flux. Rubisco, fructose-1,6-biosphosphatase, and seduheptulose-1,7-bisphosphatase were close to substrate saturation in vivo, and flux was increased by posttranslational activation. In the third phase, changes in abundance of particular proteins, including increases in plastidial ATP synthase and some CBC enzymes, relieved potential bottlenecks and readjusted protein allocation between different processes. Despite reasonable overall agreement between changes in transcript and protein abundance (R-2 = 0.24), many proteins, including those in photosynthesis, changed independently of transcript abundance.
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.
Abiotic stresses, such as salinity, cause global yield loss of all major crop plants. Factors and mechanisms that can aid in plant breeding for salt stress tolerance are therefore of great importance for food and feed production. Here, we identified a MYB-like transcription factor, Salt-Related MYB1 (SRM1), that negatively affects Arabidopsis (Arabidopsis thaliana) seed germination under saline conditions by regulating the levels of the stress hormone abscisic acid (ABA). Accordingly, several ABA biosynthesis and signaling genes act directly downstream of SRM1, including SALT TOLERANT1/NINE-CIS-EPOXYCAROTENOID DIOXYGENASE3, RESPONSIVE TO DESICCATION26, and Arabidopsis NAC DOMAIN CONTAINING PROTEIN19. Furthermore, SRM1 impacts vegetative growth and leaf shape. We show that SRM1 is an important transcriptional regulator that directly targets ABA biosynthesis and signaling-related genes and therefore may be regarded as an important regulator of ABA-mediated salt stress tolerance.
The desiccation-tolerant plant Haberlea rhodopensis can withstand months of darkness without any visible senescence. Here, we investigated the molecular mechanisms of this adaptation to prolonged (30 d) darkness and subsequent return to light. H. rhodopensis plants remained green and viable throughout the dark treatment. Transcriptomic analysis revealed that darkness regulated several transcription factor (TF) genes. Stress-and autophagy-related TFs such as ERF8, HSFA2b, RD26, TGA1, and WRKY33 were up-regulated, while chloroplast-and flowering-related TFs such as ATH1, COL2, COL4, RL1, and PTAC7 were repressed. PHYTOCHROME INTERACTING FACTOR4, a negative regulator of photomorphogenesis and promoter of senescence, also was down-regulated. In response to darkness, most of the photosynthesis-and photorespiratory-related genes were strongly down-regulated, while genes related to autophagy were up-regulated. This occurred concomitant with the induction of SUCROSE NON-FERMENTING1-RELATED PROTEIN KINASES (SnRK1) signaling pathway genes, which regulate responses to stress-induced starvation and autophagy. Most of the genes associated with chlorophyll catabolism, which are induced by darkness in dark-senescing species, were either unregulated (PHEOPHORBIDE A OXYGENASE, PAO; RED CHLOROPHYLL CATABOLITE REDUCTASE, RCCR) or repressed (STAY GREEN-LIKE, PHEOPHYTINASE, and NON-YELLOW COLORING1). Metabolite profiling revealed increases in the levels of many amino acids in darkness, suggesting increased protein degradation. In darkness, levels of the chloroplastic lipids digalactosyldiacylglycerol, monogalactosyldiacylglycerol, phosphatidylglycerol, and sulfoquinovosyldiacylglycerol decreased, while those of storage triacylglycerols increased, suggesting degradation of chloroplast membrane lipids and their conversion to triacylglycerols for use as energy and carbon sources. Collectively, these data show a coordinated response to darkness, including repression of photosynthetic, photorespiratory, flowering, and chlorophyll catabolic genes, induction of autophagy and SnRK1 pathways, and metabolic reconfigurations that enable survival under prolonged darkness.
Leaf senescence is an essential physiological process in plants that supports the recycling of nitrogen and other nutrients to support the growth of developing organs, including young leaves, seeds, and fruits. Thus, the regulation of senescence is crucial for evolutionary success in wild populations and for increasing yield in crops. Here, we describe the influence of a NAC transcription factor, SlNAP2 (Solanum lycopersicum NAC-like, activated by Apetala3/Pistillata), that controls both leaf senescence and fruit yield in tomato (S. lycopersicum). SlNAP2 expression increases during age-dependent and dark-induced leaf senescence. We demonstrate that SlNAP2 activates SlSAG113 (S. lycopersicum SENESCENCE-ASSOCIATED GENE113), a homolog of Arabidopsis (Arabidopsis thaliana) SAG113, chlorophyll degradation genes such as SlSGR1 (S. lycopersicum senescence-inducible chloroplast stay-green protein 1) and SlPAO (S. lycopersicum pheide a oxygenase), and other downstream targets by directly binding to their promoters, thereby promoting leaf senescence. Furthermore, SlNAP2 directly controls the expression of genes important for abscisic acid (ABA) biosynthesis, S. lycopersicum 9-cis-epoxycarotenoid dioxygenase 1 (SlNCED1); transport, S. lycopersicum ABC transporter G family member 40 (SlABCG40); and degradation, S. lycopersicum ABA 8'-hydroxylase (SlCYP707A2), indicating that SlNAP2 has a complex role in establishing ABA homeostasis during leaf senescence. Inhibiting SlNAP2 expression in transgenic tomato plants impedes leaf senescence but enhances fruit yield and sugar content likely due to prolonged leaf photosynthesis in aging tomato plants. Our data indicate that SlNAP2 has a central role in controlling leaf senescence and fruit yield in tomato.
Resurrection species are a group of land plants that can tolerate extreme desiccation of their vegetative tissues during harsh drought stress, and still quickly often within hours regain normal physiological and metabolic functions following rehydration. At the molecular level, this desiccation tolerance is attributed to basal cellular mechanisms including the constitutive expression of stress-associated genes and high levels of protective metabolites present already in the absence of stress, as well as to transcriptome and metabolome reconfigurations rapidly occurring during the initial phases of drought stress. Parts of this response are conferred by unique metabolites, including a diverse array of sugars, phenolic compounds, and polyols, some of which accumulate to high concentrations within the plant cell. In addition to drought stress, these metabolites are proposed to contribute to the protection against other abiotic stresses and to an increased oxidative stress tolerance. Recently, extracts of resurrection species and particular secondary metabolites therein were reported to display biological activities of importance to medicine, with e.g. antibacterial, anticancer, antifungal, and antiviral activities, rendering them possible candidates for the development of novel drug substances as well as for cosmetics. Herein, we provide an overview of the metabolite composition of resurrection species, summarize the latest reports related to the use of natural products from resurrection plants, and outline their potential for medical applications. (C) 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).
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.
For the first time, synchrotron X-ray refraction radiography (SXRR) has been paired with in-situ heat treatment to monitor microstructure and porosity evolution as a function of temperature.
The investigated material was a laser powder bed fusion (LPBF) manufactured AlSi10Mg, where the initial eutectic Si network is known to disintegrate and spherodize into larger particles with increasing temperature.
Such alloy is also prone to ther-mally induced porosity (TIP).
We show that SXRR allows detecting the changes in the Si-phase morphology upon heating, while this is currently possible only using scanning electron microscopy. SXRR also allows observing the growth of pores, usually studied via X-ray computed tomography, but on much smaller fields-of-view.
Our results show the great potential of in-situ SXRR as a tool to gain in-depth knowledge of the susceptibility of any material to thermally induced damage and/or microstructure evolution over statistically relevant volumes.
Molecular mechanisms of desiccation tolerance in the resurrection glacial relic Haberlea rhodopensis
(2013)
Haberlea rhodopensis is a resurrection plant with remarkable tolerance to desiccation. Haberlea exposed to drought stress, desiccation, and subsequent rehydration showed no signs of damage or severe oxidative stress compared to untreated control plants. Transcriptome analysis by next-generation sequencing revealed a drought-induced reprogramming, which redirected resources from growth towards cell protection. Repression of photosynthetic and growth-related genes during water deficiency was concomitant with induction of transcription factors (members of the NAC, NF-YA, MADS box, HSF, GRAS, and WRKY families) presumably acting as master switches of the genetic reprogramming, as well as with an upregulation of genes related to sugar metabolism, signaling, and genes encoding early light-inducible (ELIP), late embryogenesis abundant (LEA), and heat shock (HSP) proteins. At the same time, genes encoding other LEA, HSP, and stress protective proteins were constitutively expressed at high levels even in unstressed controls. Genes normally involved in tolerance to salinity, chilling, and pathogens were also highly induced, suggesting a possible cross-tolerance against a number of abiotic and biotic stress factors. A notable percentage of the genes highly regulated in dehydration and subsequent rehydration were novel, with no sequence homology to genes from other plant genomes. Additionally, an extensive antioxidant gene network was identified with several gene families possessing a greater number of antioxidant genes than most other species with sequenced genomes. Two of the transcripts most abundant during all conditions encoded catalases and five more catalases were induced in water-deficient samples. Using the pharmacological inhibitor 3-aminotriazole (AT) to compromise catalase activity resulted in increased sensitivity to desiccation. Metabolome analysis by GC or LC-MS revealed accumulation of sucrose, verbascose, spermidine, and gamma-aminobutyric acid during drought, as well as particular secondary metabolites accumulating during rehydration. This observation, together with the complex antioxidant system and the constitutive expression of stress protective genes suggests that both constitutive and inducible mechanisms contribute to the extreme desiccation tolerance of H. rhodopensis.
Quinoa (Chenopodium quinoa Willd.) is an herbaceous annual crop of the amaranth family (Amaranthaceae). It is increasingly cultivated for its nutritious grains, which are rich in protein and essential amino acids, lipids, and minerals. Quinoa exhibits a high tolerance towards various abiotic stresses including drought and salinity, which supports its agricultural cultivation under climate change conditions. The use of quinoa grains is compromised by anti-nutritional saponins, a terpenoid class of secondary metabolites deposited in the seed coat; their removal before consumption requires extensive washing, an economically and environmentally unfavorable process; or their accumulation can be reduced through breeding. In this study, we analyzed the seed metabolomes, including amino acids, fatty acids, and saponins, from 471 quinoa cultivars, including two related species, by liquid chromatography - mass spectrometry. Additionally, we determined a large number of agronomic traits including biomass, flowering time, and seed yield. The results revealed considerable diversity between genotypes and provide a knowledge base for future breeding or genome editing of quinoa.
The desiccation-tolerant plant Haberlea rhodopensis can withstand months of darkness without any visible senescence. Here, we investigated the molecular mechanisms of this adaptation to prolonged (30 d) darkness and subsequent return to light. H. rhodopensis plants remained green and viable throughout the dark treatment. Transcriptomic analysis revealed that darkness regulated several transcription factor (TF) genes. Stress-and autophagy-related TFs such as ERF8, HSFA2b, RD26, TGA1, and WRKY33 were up-regulated, while chloroplast-and flowering-related TFs such as ATH1, COL2, COL4, RL1, and PTAC7 were repressed. PHYTOCHROME INTERACTING FACTOR4, a negative regulator of photomorphogenesis and promoter of senescence, also was down-regulated. In response to darkness, most of the photosynthesis-and photorespiratory-related genes were strongly down-regulated, while genes related to autophagy were up-regulated. This occurred concomitant with the induction of SUCROSE NON-FERMENTING1-RELATED PROTEIN KINASES (SnRK1) signaling pathway genes, which regulate responses to stress-induced starvation and autophagy. Most of the genes associated with chlorophyll catabolism, which are induced by darkness in dark-senescing species, were either unregulated (PHEOPHORBIDE A OXYGENASE, PAO; RED CHLOROPHYLL CATABOLITE REDUCTASE, RCCR) or repressed (STAY GREEN-LIKE, PHEOPHYTINASE, and NON-YELLOW COLORING1). Metabolite profiling revealed increases in the levels of many amino acids in darkness, suggesting increased protein degradation. In darkness, levels of the chloroplastic lipids digalactosyldiacylglycerol, monogalactosyldiacylglycerol, phosphatidylglycerol, and sulfoquinovosyldiacylglycerol decreased, while those of storage triacylglycerols increased, suggesting degradation of chloroplast membrane lipids and their conversion to triacylglycerols for use as energy and carbon sources. Collectively, these data show a coordinated response to darkness, including repression of photosynthetic, photorespiratory, flowering, and chlorophyll catabolic genes, induction of autophagy and SnRK1 pathways, and metabolic reconfigurations that enable survival under prolonged darkness.