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Plants accumulate a vast array of secondary metabolites, which constitute a natural resource for pharmaceuticals. Oldenlandia corymbosa belongs to the Rubiaceae family, and has been used in traditional medicine to treat different diseases, including cancer. However, the active metabolites of the plant, their biosynthetic pathway and mode of action in cancer are unknown. To fill these gaps, we exposed this plant to eight different stress conditions and combined different omics data capturing gene expression, metabolic profiles, and anti-cancer activity. Our results show that O. corymbosa extracts are active against breast cancer cell lines and that ursolic acid is responsible for this activity. Moreover, we assembled a high-quality genome and uncovered two genes involved in the biosynthesis of ursolic acid. Finally, we also revealed that ursolic acid causes mitotic catastrophe in cancer cells and identified three high-confidence protein binding targets by Cellular Thermal Shift Assay (CETSA) and reverse docking. Altogether, these results constitute a valuable resource to further characterize the biosynthesis of active metabolites in the Oldenlandia group, while the mode of action of ursolic acid will allow us to further develop this valuable compound. Ministry of Education (MOE) Nanyang Technological University Published version I.J. is supported by Nanyang Biologics, M.M. is supported by a NTU Start‐Up Grant and Singaporean Ministry of Education grant MOE2018‐T2‐2‐053. J.M.D (NTU‐PPF‐2019). Y.K. is supported by Natural Product Research Laboratory Biomedical Research Council of A*STAR (Agency for Science, Technology and Research) Transition Fund (H16/99/b0/004), the Singapore Institute of Food and Biotechnology Innovation core fund.

Natural products from traditional medicinal plants are valuable candidates for clinical cancer therapy. Plants from the Oldenlandia-Hedyotis complex are popular ingredients of Traditional Chinese Medicine (TCM), however a major hurdle in the plant bioprospecting process of TCM plants is that the active metabolites, their biosynthetic pathways, and mode of action are often unknown. We show that Oldenlandia corymbosa extracts are active against breast cancer cell lines. To study the genes involved in the biosynthesis of active compounds in this medicinal plant, we assembled a high-quality genome. We show that the main active compound is ursolic acid and that abiotic stresses cause changes in anti-cancer activity, metabolite composition, and gene expression of plants. To reveal the mode of action of ursolic acid, we show that cancer cells undergo mitotic catastrophe, and we identify three high-confidence protein binding targets by Cellular Thermal Shift Assay (CETSA) and reverse docking.

Natural light environments are highly variable. Flexible adjustment between light energy utilization and photoprotection is therefore of vital importance for plant performance and fitness in the field. Short-term reactions to changing light intensity are triggered inside chloroplasts and leaves within seconds to minutes, whereas long-term adjustments proceed over hours and days, integrating multiple signals. While the mechanisms of long-term acclimation to light intensity have been studied by changing constant growth light intensity during the day, responses to fluctuating growth light intensity have rarely been inspected in detail. We performed transcriptome profiling in Arabidopsis (Arabidopsis thaliana) leaves to investigate long-term gene expression responses to fluctuating light (FL). In particular, we examined whether responses differ between young and mature leaves or between morning and the end of the day. Our results highlight global reprogramming of gene expression under FL, including that of genes related to photoprotection, photosynthesis, and photorespiration and to pigment, prenylquinone, and vitamin metabolism. The FL-induced changes in gene expression varied between young and mature leaves at the same time point and between the same leaves in the morning and at the end of the day, indicating interactions of FL acclimation with leaf development stage and time of day. Only 46 genes were up- or down-regulated in both young and mature leaves at both time points. Combined analyses of gene coexpression and cis-elements pointed to a role of the circadian clock and light in coordinating the acclimatory responses of functionally related genes. Our results also suggest a possible cross talk between FL acclimation and systemic acquired resistance-like gene expression in young leaves.

Pectin is a vital component of the plant cell wall and provides the molecular glue that maintains cell-cell adhesion, among other functions. As the most complex wall polysaccharide, pectin is composed of several covalently linked domains, such as homogalacturonan (HG) and rhamnogalacturonan I (RG I). Pectin has widespread uses in the food industry and has emerging biomedical applications, but its synthesis remains poorly understood. For instance, the enzymes that catalyze RG I elongation remain unknown. Recently, a coexpression- and sequence-based MUCILAGE-RELATED (MUCI) reverse genetic screen uncovered hemicellulose biosynthetic enzymes in the Arabidopsis (Arabidopsis thaliana) seed coat. Here, we use an extension of this strategy to identify MUCI70 as the founding member of a glycosyltransferase family essential for the accumulation of seed mucilage, a gelatinous wall rich in unbranched RG I. Detailed biochemical and histological characterization of two muci70 mutants and two galacturonosyltransferase11 (gaut11) mutants identified MUCI70 and GAUT11 as required for two distinct RG I domains in seed mucilage. We demonstrate that, unlike MUCI70, GAUT11 catalyzes HG elongation in vitro and, thus, likely is required for the synthesis of an HG region important for RG I elongation. Analysis of a muci70 gaut11 double mutant confirmed that MUCI70 and GAUT11 are indispensable for the production and release of the bulk of mucilage RG I and for shaping the surface morphology of seeds. In addition, we uncover relationships between pectin and hemicelluloses and show that xylan is essential for the elongation of at least one RG I domain.

To develop novel biorefinery concepts, the use of bio-based catalysts and solvents must be aligned with the principles of green chemistry. In this context, biogenic 2,5-furandicarboxylic acid (FDCA) is a very promising yet underused molecule with high potential for application as an acid catalyst, combining feasibility and sustainability with efficient and straightforward recovery. In this study, FDCA was evaluated as a catalyst in the recently developed OrganoCat pretreatment, a biphasic lignocellulose fractionation system. The catalyst was investigated for the efficient fractionation of the three main components-lignin, cellulose and noncellulosic sugars-with particular focus on the lignin quality, on the effect on enzymatic hydrolysis of the cellulosic residue, and on the noncellulosic sugar extraction. To address recovery of FDCA from the OrganoCat system, a method was developed, leading to the recovery of >97 % of FDCA with a spectroscopic purity of >99 %, maintaining full activity in consecutive runs.

New technologies reveal the deposition and remodeling of plant cell wall polysaccharides and their impact on plant development.

Molecular plant 13(7), 1027-1046 (2020). doi:10.1016/j.molp.2020.04.004, Published by Oxford Univ. Press, Oxford

UMR BFP - Equipe Métabolisme; International audience; Protein synthesis and degradation are essential processes that regulate cell status. Because labeling in bulky organs, such as fruits, is difficult, we developed a modeling approach to study protein turnover at the global scale in developing tomato (Solanum lycopersicum) fruit. Quantitative data were collected for transcripts and proteins during fruit development. Clustering analysis showed smaller changes in protein abundance compared to mRNA abundance. Furthermore, protein and transcript abundance were poorly correlated, and the coefficient of correlation decreased during fruit development and ripening, with transcript levels decreasing more than protein levels. A mathematical model with one ordinary differential equation was used to estimate translation (kt) and degradation (kd) rate constants for almost 2,400 detected transcript-protein pairs and was satisfactorily fitted for over a thousand pairs. The model predicted median values of about 2 min for the translation of a protein, and a protein lifetime of approximately 11 days. The constants were validated and inspected for biological relevance. Proteins involved in protein synthesis had higher kt and kd values, indicating that the protein machinery is particularly flexible. Our model also predicts that protein concentration is more strongly affected by the rate of translation than that of degradation.

To investigate whether the transcriptional response to carbon (C) depletion and sucrose resupply depends on the duration and severity of the C depletion, Arabidopsis seedlings were grown in liquid culture and harvested 3, 6, 12, 24, 48 and 72 h after removing sucrose from the medium and 30 min after resupplying sucrose at each time. Expression profiling revealed early transcriptional inhibition of cell wall synthesis and remodelling of signalling, followed by induction of C recycling and photosynthesis and general inhibition of growth. The temporal sequence differed from the published response to progressive exhaustion of C during a night and extended night in vegetatively growing plants. The response to sucrose readdition was conserved across the C-depletion time course. Intriguingly, the vast majority of rapidly responding transcripts decreased rather than increased. The majority of transcripts that respond rapidly to sucrose and many transcripts that respond during C depletion also decrease after treating seedlings with the transcriptional inhibitor cordycepin A. Comparison with published responses to overexpression of otsA, AKIN10 and bZIP11 revealed that many genes that respond to C depletion, and especially sucrose resupply, respond to one or more of these C-signalling components. Thus, multiple factors contribute to C responsiveness, including many signalling components, transcriptional regulation and transcript turnover.

Recent massive growth in the production of sequencing data necessitates matching improve-ments in bioinformatics tools to effectively utilize it. Existing tools suffer from limitations in both scalability and applicability which are inherent to their underlying algorithms and data structures. We identify the key requirements for the ideal data structure for sequence analy-ses: it should be informationally lossless, locally updatable, and memory efficient; requirements which are not met by data structures underlying the major assembly strategies Overlap Layout Consensus and De Bruijn Graphs. We therefore propose a new data structure, the LOGAN graph, which is based on a memory efficient Sparse De Bruijn Graph with routing information. Innovations in storing routing information and careful implementation allow sequence datasets for Escherichia coli (4.6Mbp, 117x coverage), Arabidopsis thaliana (135Mbp, 17.5x coverage) and Solanum pennellii (1.2Gbp, 47x coverage) to be loaded into memory on a desktop computer in seconds, minutes, and hours respectively. Memory consumption is competitive with state of the art alternatives, while losslessly representing the reads in an indexed and updatable form. Both Second and Third Generation Sequencing reads are supported. Thus, the LOGAN graph is positioned to be the backbone for major breakthroughs in sequence analysis such as integrated hybrid assembly, assembly of exceptionally large and repetitive genomes, as well as assembly and representation of pan-genomes.

Recent updates in sequencing technology have made it possible to obtain Gigabases of sequence data from one single flowcell. Prior to this update, the nanopore sequencing technology was mainly used to analyze and assemble microbial samples1-3. Here, we describe the generation of a comprehensive nanopore sequencing dataset with a median fragment size of 11,979 bp for the wild tomato speciesSolanum pennelliifeaturing an estimated genome size of ca 1.0 to 1.1 Gbases. We describe its genome assembly to a contig N50 of 2.5 MB using a pipeline comprising a Canu4pre-processing and a subsequent assembly using SMARTdenovo. We show that the obtained nanopore basedde novogenome reconstruction is structurally highly similar to that of the referenceS. pennelliiLA7165genome but has a high error rate caused mostly by deletions in homopolymers. After polishing the assembly with Illumina short read data we obtained an error rate of S. pennelliigenome5. Taken together our data indicate such long read sequencing data can be used to affordably sequence and assemble Gbase sized diploid plant genomes.Raw data is available athttp://www.plabipd.de/portal/solanum-pennelliiand has been deposited as PRJEB19787.

Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.

Large-scale biology article; International audience; Updates in nanopore technology have made it possible to obtain gigabases of sequence data. Prior to this, nanopore sequencing technology was mainly used to analyze microbial samples. Here, we describe the generation of a comprehensive nanopore sequencing data set with a median read length of 11,979 bp for a self-compatible accession of the wild tomato species Solanum pennellii. We describe the assembly of its genome to a contig N50 of 2.5 MB. The assembly pipeline comprised initial read correction with Canu and assembly with SMARTdenovo. The resulting raw nanopore-based de novo genome is structurally highly similar to that of the reference S. pennellii LA716 accession but has a high error rate and was rich in homopolymer deletions. After polishing the assembly with Illumina reads, we obtained an error rate of

The methylesterification status of cell wall homogalacturonans, mediated through the action of pectin methylesterases (PMEs), influences the biophysical properties of plant cell walls such as elasticity and porosity, important parameters for cell elongation and water uptake. The completion of seed germination requires cell wall extensibility changes in both the radicle itself and in the micropylar tissues surrounding the radicle. In wild-type seeds of Arabidopsis (Arabidopsis thaliana), PME activities peaked around the time of testa rupture but declined just before the completion of germination (endosperm weakening and rupture). We overexpressed an Arabidopsis PME inhibitor to investigate PME involvement in seed germination. Seeds of the resultant lines showed a denser methylesterification status of their cell wall homogalacturonans, but there were no changes in the neutral sugar and uronic acid composition of the cell walls. As compared with wild-type seeds, the PME activities of the overexpressing lines were greatly reduced throughout germination, and the low steady-state levels neither increased nor decreased. The most striking phenotype was a significantly faster rate of germination, which was not connected to altered testa rupture morphology but to alterations of the micropylar endosperm cells, evident by environmental scanning electron microscopy. The transgenic seeds also exhibited an apparent reduced sensitivity to abscisic acid with respect to its inhibitory effects on germination. We speculate that PME activity contributes to the temporal regulation of radicle emergence in endospermic seeds by altering the mechanical properties of the cell walls and thereby the balance between the two opposing forces of radicle elongation and mechanical resistance of the endosperm.

The model organism Arabidopsis thaliana is readily used in basic research due to resource availability and relative speed of data acquisition. A major goal is to transfer acquired knowledge from Arabidopsis to crop species. However, the identification of functional equivalents of well-characterized Arabidopsis genes in other plants is a nontrivial task. It is well documented that transcriptionally coordinated genes tend to be functionally related and that such relationships may be conserved across different species and even kingdoms. To exploit such relationships, we constructed whole-genome coexpression networks for Arabidopsis and six important plant crop species. The interactive networks, clustered using the HCCA algorithm, are provided under the banner PlaNet (http://aranet.mpimp-golm.mpg.de). We implemented a comparative network algorithm that estimates similarities between network structures. Thus, the platform can be used to swiftly infer similar coexpressed network vicinities within and across species and can predict the identity of functional homologs. We exemplify this using the PSA-D and chalcone synthase-related gene networks. Finally, we assessed how ontology terms are transcriptionally connected in the seven species and provide the corresponding MapMan term coexpression networks. The data support the contention that this platform will considerably improve transfer of knowledge generated in Arabidopsis to valuable crop species.

The methylesterification status of cell wall pectins, mediated through the interplay of pectin methylesterases (PMEs) and pectin methylesterase inhibitors (PMEIs), influences the biophysical properties of plant cell walls. We found that the overexpression of a PMEI gene in Arabidopsis thaliana plants caused the stems to develop twists and loops, most strongly around points on the stem where leaves or inflorescences failed to separate from the main stem. Altered elasticity of the stem, underdevelopment of the leaf cuticle, and changes in the sugar composition of the cell walls of stems were evident in the PMEI overexpression lines. We discuss the mechanisms that potentially underlie the aberrant growth phenotypes.

Plant cell walls are essential for plant growth and development. The cell walls are traditionally divided into primary walls, which surround growing cells, and secondary walls, which provide structural support to certain cell types and promote their functions. While much information is available about the enzymes and components that contribute to the production of these two types of walls, much less is known about the transition from primary to secondary wall synthesis. To address this question, we made use of a transcription factor system in Arabidopsis (Arabidopsis thaliana) in which an overexpressed master secondary wall-inducing transcription factor, VASCULAR-RELATED NAC DOMAIN PROTEIN7, can be redirected into the nucleus by the addition of dexamethasone. We established the time frame during which primary wall synthesis changed into secondary wall production in dexamethasone-treated seedlings and measured transcript and metabolite abundance at eight time points after induction. Using cluster- and network-based analyses, we integrated the data sets to explore coordination between transcripts, metabolites, and the combination of the two across the time points. We provide the raw data as well as a range of network-based analyses. These data reveal links between hormone signaling and metabolic processes during the formation of secondary walls and provide a framework toward a deeper understanding of how primary walls transition into secondary walls.

Frontiers in Plant Science 3, 294 (2012). doi:10.3389/fpls.2012.00294, Published by Frontiers Media, Lausanne

l-Ara, an important constituent of plant cell walls, is found predominantly in the furanose rather than in the thermodynamically more stable pyranose form. Nucleotide sugar mutases have been demonstrated to interconvert UDP-l-arabinopyranose (UDP-Arap) and UDP-l-arabinofuranose (UDP-Araf) in rice (Oryza sativa). These enzymes belong to a small gene family encoding the previously named Reversibly Glycosylated Proteins (RGPs). RGPs are plant-specific cytosolic proteins that tend to associate with the endomembrane system. In Arabidopsis thaliana, the RGP protein family consists of five closely related members. We characterized all five RGPs regarding their expression pattern and subcellular localizations in transgenic Arabidopsis plants. Enzymatic activity assays of recombinant proteins expressed in Escherichia coli identified three of the Arabidopsis RGP protein family members as UDP-l-Ara mutases that catalyze the formation of UDP-Araf from UDP-Arap. Coimmunoprecipitation and subsequent liquid chromatography-electrospray ionization-tandem mass spectrometry analysis revealed a distinct interaction network between RGPs in different Arabidopsis organs. Examination of cell wall polysaccharide preparations from RGP1 and RGP2 knockout mutants showed a significant reduction in total l-Ara content (12–31%) compared with wild-type plants. Concomitant downregulation of RGP1 and RGP2 expression results in plants almost completely deficient in cell wall–derived l-Ara and exhibiting severe developmental defects.

Despite the growing volume of experimentally validated knowledge about the sub cellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the sub cellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the sub cellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mitochondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel sub cellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins. © 2011 Ryngajllo, Childs, Lohse, Giorgi, Lude, Selbig and Usadel.

International audience; Very few reports have studied the interactions between ascorbate and fruit metabolism. In order to get insights into the complex relationships between ascorbate biosynthesis/recycling and other metabolic pathways in the fruit, we undertook a fruit systems biology approach. To this end, we have produced tomato transgenic lines altered in ascorbate content and redox ratio by RNAi-targeting several key enzymes involved in ascorbate biosynthesis (2 enzymes) and recycling (2 enzymes). In the VTC (ViTamin C) Fruit project, we then generated phenotypic and genomic (transcriptome, proteome, metabolome) data from wild type and mutant tomato fruit at two stages of fruit development, and developed or implemented statistical and bioinformatic tools as a web application (named VTC Tool box) necessary to store, analyse and integrate experimental data in tomato. By using Kohonen's self-organizing maps (SOMs) to cluster the biological data, pair-wise Pearson correlation analyses and simultaneous visualization of transcript/protein and metabolites (MapMan), this approach allowed us to uncover major relationships between ascorbate and other metabolic pathways.

Transcriptional coordination, or co-expression, of genes may signify functional relatedness of the corresponding proteins. For example, several genes involved in secondary cell wall cellulose biosynthesis are co-expressed with genes engaged in the synthesis of xylan, which is a major component of the secondary cell wall. To extend these types of analyses, we investigated the co-expression relationships of all Carbohydrate-Active enZYmes (CAZy)-related genes for Arabidopsis thaliana. Thus, the intention was to transcriptionally link different cell wall-related processes to each other, and also to other biological functions. To facilitate easy manual inspection, we have displayed these interactions as networks and matrices, and created a web-based interface (http://aranet.mpimp-golm.mpg.de/corecarb) containing downloadable files for all the transcriptional associations.

Gene co-expression analysis has emerged in the past 5 years as a powerful tool for gene function prediction. In essence, co-expression analysis asks the question 'what are the genes that are co-expressed, that is, those that show similar expression profiles across many experiments, with my gene of interest?'. Genes that are highly co-expressed may be involved in the biological process or processes of the query gene. This review describes the tools that are available for performing such analyses, how each of these perform, and also discusses statistical issues including how normalization of gene expression data can influence co-expression results, calculation of co-expression scores and P values, and the influence of data sets used for co-expression analysis. Finally, examples from the literature will be presented, wherein co-expression has been used to corroborate and discover various aspects of plant biology. © 2009 Blackwell Publishing Ltd.

Indole Acetic Acid 9 (IAA9) is a negative auxin response regulator belonging to the Aux/IAA transcription factor gene family whose downregulation triggers fruit set before pollination, thus giving rise to parthenocarpy. In situ hybridization experiments revealed that a tissue-specific gradient of IAA9 expression is established during flower development, the release of which upon pollination triggers the initiation of fruit development. Comparative transcriptome and targeted metabolome analysis uncovered important features of the molecular events underlying pollination-induced and pollination-independent fruit set. Comprehensive transcriptomic profiling identified a high number of genes common to both types of fruit set, among which only a small subset are dependent on IAA9 regulation. The fine-tuning of Aux/IAA and ARF genes and the downregulation of TAG1 and TAGL6 MADS box genes are instrumental in triggering the fruit set program. Auxin and ethylene emerged as the most active signaling hormones involved in the flower-to-fruit transition. However, while these hormones affected only a small number of transcriptional events, dramatic shifts were observed at the metabolic and developmental levels. The activation of photosynthesis and sucrose metabolism-related genes is an integral regulatory component of fruit set process. The combined results allow a far greater comprehension of the regulatory and metabolic events controlling early fruit development both in the presence and absence of pollination/fertilization.

Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1-phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production.

Summary Two of the major challenges in functional genomics are to identify genes that play a key role in biological processes, and to elucidate the biological role of the large numbers of genes whose function is poorly characterized or still completely unknown. In this study, a combination of large-scale expressed sequence tag sequencing, high-throughput gene silencing and visual phenotyping was used to identify genes in which partial inhibition of expression leads to marked phenotypic changes, mostly on leaves. Three normalized tobacco (Nicotiana tabacum) cDNA libraries were prepared directly in a binary vector using different tissues of tobacco as an RNA source, randomly sequenced and clustered. The Agrobacterium–tobacco leaf disc transformation system was used to generate sets of antisense or co-suppression transgenic tobacco plants for over 20 000 randomly chosen clones, each representing an independent cluster. After transfer to the glasshouse, transgenic plants were scored visually after 10–14 days for changes in growth, leaf form and chlorosis or necrosis. Putative hits were validated by repeating the transformation. This procedure is more stringent than the analysis of knockout mutants, because it requires that even a partial decrease in expression generates a phenotype. This procedure identified 88 validated gene/phenotype relations. These included several previously characterized gene/phenotype relationships, demonstrating the validity of the approach. For about one-third, a function could be inferred, but a loss-of-function phenotype had not been described previously. Strikingly, almost one-half of the validated genes were poorly annotated, or had no known function. For 77 of these tobacco sequences, a single or small number of potential orthologues were identified in Arabidopsis. The genes for which orthologues were identified in Arabidopsis included about one-half of the genes whose function was completely unknown. Comparison with published gene/phenotype relations for Arabidopsis knockout mutants revealed surprisingly little overlap with the present study. Our results indicate that partial gene silencing identifies novel gene/phenotype relationships, which are distinct from those uncovered by knockout screens. They also show that it is possible to perform these analyses in a crop species in which full genome sequence information is lacking, and subsequently to transfer the information to a reference species in which functional studies can be performed more effectively.

An analysis of the temporal dynamics of metabolite and transcript levels, as well as enzyme activity, of 137 metabolites during diurnal cycles in Arabidopsis leaves, Background Genome-wide transcript profiling and analyses of enzyme activities from central carbon and nitrogen metabolism show that transcript levels undergo marked and rapid changes during diurnal cycles and after transfer to darkness, whereas changes in activities are smaller and delayed. In the starchless pgm mutant, where sugars are depleted every night, there are accentuated diurnal changes in transcript levels. Enzyme activities in this mutant do not show larger diurnal changes; instead, they shift towards the levels found in the wild type after several days of darkness. This indicates that enzyme activities change slowly, integrating the changes in transcript levels over several diurnal cycles. Results To generalize this conclusion, 137 metabolites were profiled using gas and liquid chromatography coupled to mass spectroscopy. The amplitudes of the diurnal changes in metabolite levels in pgm were (with the exception of sugars) similar or smaller than in the wild type. The average levels shifted towards those found after several days of darkness in the wild type. Examples include increased levels of amino acids due to protein degradation, decreased levels of fatty acids, increased tocopherol and decreased myo-inositol. Many metabolite-transcript correlations were found and the proportion of transcripts correlated with sugars increased dramatically in the starchless mutant. Conclusion Rapid diurnal changes in transcript levels are integrated over time to generate quasi-stable changes across large sectors of metabolism. This implies that correlations between metabolites and transcripts are due to regulation of gene expression by metabolites, rather than metabolites being changed as a consequence of a change in gene expression.