Genome-wide association studies identify loci controlling specialized seed metabolites in Arabidopsis.

Plants synthesize specialized metabolites to facilitate environmental and ecological interactions. During evolution, plants diversified in their potential to synthesize these metabolites. Quantitative differences in metabolite levels of natural Arabidopsis (Arabidopsis thaliana) accessions can be employed to unravel the genetic basis for metabolic traits using genome-wide association studies (GWAS). Here, we performed metabolic GWAS on seeds of a panel of 315 A. thaliana natural accessions, including the reference genotypes C24 and Col-0, for polar and semi-polar seed metabolites using untargeted ultra-performance liquid chromatography-mass spectrometry. As a complementary approach, we performed quantitative trait locus (QTL) mapping of near-isogenic introgression lines between C24 and Col-0 for specific seed specialized metabolites. Besides common QTL between seeds and leaves, GWAS revealed seed-specific QTL for specialized metabolites, indicating differences in the genetic architecture of seeds and leaves. In seeds, aliphatic methylsulfinylalkyl and methylthioalkyl glucosinolates associated with the ALKENYL HYDROXYALKYL PRODUCING loci (GS-ALK and GS-OHP) on chromosome 4 containing alkenyl hydroxyalkyl producing 2 (AOP2) and 3 (AOP3) or with the GS-ELONG locus on chromosome 5 containing methylthioalkyl malate synthase (MAM1) and MAM3. We detected two unknown sulfur-containing compounds that were also mapped to these loci. In GWAS, some of the annotated flavonoids (kaempferol 3-O-rhamnoside-7-O-rhamnoside, quercetin 3-O-rhamnoside-7-O-rhamnoside) were mapped to transparent testa 7 (AT5G07990), encoding a cytochrome P450 75B1 monooxygenase. Three additional mass signals corresponding to quercetin-containing flavonols were mapped to UGT78D2 (AT5G17050). The association of the loci and associating metabolic features were functionally verified in knockdown mutant lines. By performing GWAS and QTL mapping, we were able to leverage variation of natural populations and parental lines to study seed specialized metabolism. The GWAS data set generated here is a high-quality resource that can be investigated in further studies.

Chloroplast translational regulation uncovers nonessential photosynthesis genes as key players in plant cold acclimation.

Plants evolved efficient multifaceted acclimation strategies to cope with low temperatures. Chloroplasts respond to temperature stimuli and participate in temperature sensing and acclimation. However, very little is known about the involvement of chloroplast genes and their expression in plant chilling tolerance. Here we systematically investigated cold acclimation in tobacco seedlings over 2 days of exposure to low temperatures by examining responses in chloroplast genome copy number, transcript accumulation and translation, photosynthesis, cell physiology, and metabolism. Our time-resolved genome-wide investigation of chloroplast gene expression revealed substantial cold-induced translational regulation at both the initiation and elongation levels, in the virtual absence of changes at the transcript level. These cold-triggered dynamics in chloroplast translation are widely distinct from previously described high light-induced effects. Analysis of the gene set responding significantly to the cold stimulus suggested nonessential plastid-encoded subunits of photosynthetic protein complexes as novel players in plant cold acclimation. Functional characterization of one of these cold-responsive chloroplast genes by reverse genetics demonstrated that the encoded protein, the small cytochrome b6f complex subunit PetL, crucially contributes to photosynthetic cold acclimation. Together, our results uncover an important, previously underappreciated role of chloroplast translational regulation in plant cold acclimation.

Ultra-high-performance liquid chromatography high-resolution mass spectrometry variants for metabolomics research.

Ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) variants currently represent the best tools to tackle the challenges of complexity and lack of comprehensive coverage of the metabolome. UHPLC offers flexible and efficient separation coupled with high-sensitivity detection via HRMS, allowing for the detection and identification of a broad range of metabolites. Here we discuss current common strategies for UHPLC-HRMS-based metabolomics, with a focus on expanding metabolome coverage.

A phased genome based on single sperm sequencing reveals crossover pattern and complex relatedness in tea plants.

For diploid organisms that are highly heterozygous, a phased haploid genome can greatly aid in functional genomic, population genetic and breeding studies. Based on the genome sequencing of 135 single sperm cells of the elite tea cultivar 'Fudingdabai', we herein phased the genome of Camellia sinensis, one of the most popular beverage crops worldwide. High-resolution genetic and recombination maps of Fudingdabai were constructed, which revealed that crossover (CO) positions were frequently located in the 5' and 3' ends of annotated genes, while CO distributions across the genome were random. The low CO frequency in tea can be explained by strong CO interference, and CO simulation revealed the proportion of interference insensitive CO ranged from 5.2% to 11.7%. We furthermore developed a method to infer the relatedness between tea accessions and detected complex kinship and genetic signatures of 106 tea accessions. Among them, 59 accessions were closely related with Fudingdabai and 31 of them were first-degree relatives. We additionally identified genes displaying allele specific expression patterns between the two haplotypes of Fudingdabai and genes displaying significantly differential expression levels between Fudingdabai and other haplotypes. These results lay the foundation for further investigation of genetic and epigenetic factors underpinning the regulation of gene expression and provide insights into the evolution of tea plants as well as a valuable genetic resource for future breeding efforts.

Multi-tissue integration of transcriptomic and specialized metabolite profiling provides tools for assessing the common bean (Phaseolus vulgaris) metabolome.

Common bean (Phaseolus vulgaris L.) is an important legume species with a rich natural diversity of landraces that originated from the wild forms following multiple independent domestication events. After the publication of its genome, several resources for this relevant crop have been made available. A comprehensive characterization of specialized metabolism in P. vulgaris, however, is still lacking. In this study, we used a metabolomics approach based on liquid chromatography-mass spectrometry to dissect the chemical composition at a tissue-specific level in several accessions of common bean belonging to different gene pools. Using a combination of literature search, mass spectral interpretation, 13 C-labeling, and correlation analyses, we were able to assign chemical classes and/or putative structures for approximately 39% of all measured metabolites. Additionally, we integrated this information with transcriptomics data and phylogenetic inference from multiple legume species to reconstruct the possible metabolic pathways and identify sets of candidate genes involved in the biosynthesis of specialized metabolites. A particular focus was given to flavonoids, triterpenoid saponins and hydroxycinnamates, as they represent metabolites involved in important ecological interactions and they are also associated with several health-promoting benefits when integrated into the human diet. The data are presented here in the form of an accessible resource that we hope will set grounds for further studies on specialized metabolism in legumes.

Canalization of Tomato Fruit Metabolism.

To explore the genetic robustness (canalization) of metabolism, we examined the levels of fruit metabolites in multiple harvests of a tomato introgression line (IL) population. The IL partitions the whole genome of the wild species Solanum pennellii in the background of the cultivated tomato (Solanum lycopersicum). We identified several metabolite quantitative trait loci that reduce variability for both primary and secondary metabolites, which we named canalization metabolite quantitative trait loci (cmQTL). We validated nine cmQTL using an independent population of backcross inbred lines, derived from the same parents, which allows increased resolution in mapping the QTL previously identified in the ILs. These cmQTL showed little overlap with QTL for the metabolite levels themselves. Moreover, the intervals they mapped to harbored few metabolism-associated genes, suggesting that the canalization of metabolism is largely controlled by regulatory genes.

The arginine decarboxylase gene ADC1, associated to the putrescine pathway, plays an important role in potato cold-acclimated freezing tolerance as revealed by transcriptome and metabolome analyses.

Low temperature severely influences potato production as the cultivated potato (Solanum tuberosum) is frost sensitive, however the mechanism underlying the freezing tolerance of the potato is largely unknown. In the present research, we studied the transcriptome and metabolome of the freezing-tolerant wild species Solanum acaule (Aca) and freezing-sensitive cultivated S. tuberosum (Tub) to identify the main pathways and important factors related to freezing tolerance. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation indicated that polyamine and amino acid metabolic pathways were specifically upregulated in Aca under cold treatment. The transcriptome changes detected in Aca were accompanied by the specific accumulation of putrescine, saccharides, amino acids and other metabolites. The combination of transcriptome and metabolome analyses revealed that putrescine exhibited an accumulative pattern in accordance with the expression of the arginine decarboxylase gene ADC1. The primary role of putrescine was further confirmed by analyzing all three polyamines (putrescine, spermidine, and spermine) and the genes encoding the corresponding enzymes in two sets of potato genotypes with distinct freezing tolerance, implying that only putrescine and ADC1 were uniquely enhanced by cold in the freezing-tolerant genotypes. The function of putrescine was further analyzed by its exogenous application and the overexpression of SaADC1 in S. tuberosum cv. E3, indicating its important role(s) in cold-acclimated freezing tolerance, which was accompanied with the activation of C-repeat binding factor genes (CBFs). The present research has identified that the ADC1-associated putrescine pathway plays an important role in cold-acclimated freezing tolerance of potato, probably by enhancing the expression of CBF genes.

Cucumber ovaries inhibited by dominant fruit express a dynamic developmental program, distinct from either senescence-determined or fruit-setting ovaries.

Cucurbits represent an attractive model to explore the dynamics of fruit set, whose regulation is not fully understood, despite its importance for yield determination. A fertilized ovary must integrate signals from distant plant parts and 'decide' whether to set fruit, or remain inhibited and later senesce. Here, we set out to characterize first-fruit inhibition (FFI), that is, the inhibitory effect of the first fruit on subsequent development of younger ovaries during pollination-induced and parthenocarpic fruit set. After the first fertilized ovaries set fruit, younger fertilized ovaries remained in a temporary state of inhibition. Such ovaries preserved their size and green color, and if the older fruit were removed within a 1-week reversibility window, they set fruit. The FFI effect was documented in both fertilized and parthenocarpic ovaries. We compared the gene expression profiles of pollinated ovaries (committed to set fruit) with respect to those affected by FFI, and to non-pollinated ovaries (undergoing senescence). The three fates of the ovaries were characterized by wide changes in gene expression, with several specific transcripts being up- or down-regulated in response to pollination, and to the presence of inhibitory fruit. Metabolic profiling was undertaken and integrated with the transcriptomic data in order to characterize early physiological changes that occur in post-anthesis ovaries in parthenocarpic and non-parthenocarpic genotypes. The combined results are discussed with respect to current models of fruit set and specifically with regard to FFI. Moreover, these metabolome and transcriptome data provide a valuable resource for studying ovary development and fruit set.

The Extra-Pathway Interactome of the TCA Cycle: Expected and Unexpected Metabolic Interactions.

The plant tricarboxylic acid (TCA) cycle provides essential precursors for respiration, amino acid biosynthesis, and general nitrogen metabolism; moreover, it is closely involved in biotic stress responses and cellular redox homeostasis. To further understand the in vivo function of the TCA cycle enzymes, we combined affinity purification with proteomics to generate a comprehensive extra-pathway protein-protein interaction network of the plant TCA cycle. We identified 125 extra-pathway interactions in Arabidopsis (Arabidopsis thaliana) mostly related to the mitochondrial electron transport complex/ATP synthesis and amino acid metabolism but also to proteins associated with redox stress. We chose three high-scoring and two low-scoring interactions for complementary bimolecular fluorescence complementation and yeast two-hybrid assays, which highlighted the reliability of our approach, supported the intimate involvement of TCA cycle enzymes within many biological processes, and reflected metabolic changes reported previously for the corresponding mutant lines. To analyze the function of a subset of these interactions, we selected two mutants of mitochondrial glutaredoxin S15 and Amidase, which have not yet been analyzed with respect to their TCA cycle function, and performed metabolite profiling and flux analysis. Consistent with their interactions identified in this study, TCA cycle metabolites and the relative TCA flux of the two mutants were altered significantly.

Identification and mode of inheritance of quantitative trait loci for secondary metabolite abundance in tomato.

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.

The Integration of Metabolomics and Next-Generation Sequencing Data to Elucidate the Pathways of Natural Product Metabolism in Medicinal Plants.

Plants have always been used as medicines since ancient times to treat diseases. The knowledge around the active components of herbal preparations has remained nevertheless fragmentary: the biosynthetic pathways of many secondary metabolites of pharmacological importance have been clarified only in a few species, while the chemodiversity present in many medicinal plants has remained largely unexplored. Despite the advancements of synthetic biology for production of medicinal compounds in heterologous hosts, the native plant species are often the most reliable and economic source for their production. It thus becomes fundamental to investigate the metabolic composition of medicinal plants to characterize their natural metabolic diversity and to define the biosynthetic routes in planta of important compounds to develop strategies to further increase their content. We present here a number of case studies for selected classes of secondary metabolites and we review their health benefits and the historical developments in their structural elucidation and characterization of biosynthetic genes. We cover the cases of benzoisoquinoline and monoterpenoid indole alkaloids, cannabinoids, caffeine, ginsenosides, withanolides, artemisinin, and taxol; we show how the "early" biochemical or the more recent integrative approaches-based on omics-analyses-have helped to elucidate their metabolic pathways and cellular compartmentation. We also summarize how the knowledge generated about their biosynthesis has been used to develop metabolic engineering strategies in heterologous and native hosts. We conclude that following the advent of novel, high-throughput and cost-effective analytical technologies, the secondary metabolism of medicinal plants can now be examined under the lens of systems biology.

Evolutionary Metabolomics Reveals Domestication-Associated Changes in Tetraploid Wheat Kernels.

Domestication and breeding have influenced the genetic structure of plant populations due to selection for adaptation from natural habitats to agro-ecosystems. Here, we investigate the effects of selection on the contents of 51 primary kernel metabolites and their relationships in three Triticum turgidum L. subspecies (i.e., wild emmer, emmer, durum wheat) that represent the major steps of tetraploid wheat domestication. We present a methodological pipeline to identify the signature of selection for molecular phenotypic traits (e.g., metabolites and transcripts). Following the approach, we show that a reduction in unsaturated fatty acids was associated with selection during domestication of emmer (primary domestication). We also show that changes in the amino acid content due to selection mark the domestication of durum wheat (secondary domestication). These effects were found to be partially independent of the associations that unsaturated fatty acids and amino acids have with other domestication-related kernel traits. Changes in contents of metabolites were also highlighted by alterations in the metabolic correlation networks, indicating wide metabolic restructuring due to domestication. Finally, evidence is provided that wild and exotic germplasm can have a relevant role for improvement of wheat quality and nutritional traits.

Combined correlation-based network and mQTL analyses efficiently identified loci for branched-chain amino acid, serine to threonine, and proline metabolism in tomato seeds.

Correlation-based network analysis (CNA) of the metabolic profiles of seeds of a tomato introgression line mapping population revealed a clique of proteinogenic amino acids: Gly, Ile, Pro, Ser, Thr, and Val. Correlations between profiles of these amino acids exhibited a statistically significant average correlation coefficient of 0.84 as compared with an average correlation coefficient of 0.39 over the 16 119 other metabolite cliques containing six metabolites. In silico removal of cliques was used to quantify their importance in determining seminal network properties, highlighting the strong effects of the amino acid clique. Quantitative trait locus analysis revealed co-localization for the six amino acids on chromosome 2, 4 and 10. Sequence analysis identified a unique set of 10 genes on chromosome 2 only, which were associated with amino acid metabolism and specifically the metabolism of Ser-Gly and their conversion into branched-chain amino acids. Metabolite profiling of a set of sublines, with introgressions on chromosome 2, identified a significant change in the abundance of the six amino acids in comparison with M82. Expression analysis of candidate genes affecting Ser metabolism matched the observation from the metabolite data, suggesting a coordinated behavior of the level of these amino acids at the genetic level. Analysis of transcription factor binding sites in the promoter regions of the identified genes suggested combinatorial response to light and the circadian clock.

Integrative Approaches to Enhance Understanding of Plant Metabolic Pathway Structure and Regulation.

Huge insight into molecular mechanisms and biological network coordination have been achieved following the application of various profiling technologies. Our knowledge of how the different molecular entities of the cell interact with one another suggests that, nevertheless, integration of data from different techniques could drive a more comprehensive understanding of the data emanating from different techniques. Here, we provide an overview of how such data integration is being used to aid the understanding of metabolic pathway structure and regulation. We choose to focus on the pairwise integration of large-scale metabolite data with that of the transcriptomic, proteomics, whole-genome sequence, growth- and yield-associated phenotypes, and archival functional genomic data sets. In doing so, we attempt to provide an update on approaches that integrate data obtained at different levels to reach a better understanding of either single gene function or metabolic pathway structure and regulation within the context of a broader biological process.

Exploring natural variation of photosynthetic, primary metabolism and growth parameters in a large panel of Capsicum chinense accessions.

MAIN CONCLUSION: Collectively, the results presented improve upon the utility of an important genetic resource and attest to a complex genetic basis for differences in both leaf metabolism and fruit morphology between natural populations. Diversity of accessions within the same species provides an alternative method to identify physiological and metabolic traits that have large effects on growth regulation, biomass and fruit production. Here, we investigated physiological and metabolic traits as well as parameters related to plant growth and fruit production of 49 phenotypically diverse pepper accessions of Capsicum chinense grown ex situ under controlled conditions. Although single-trait analysis identified up to seven distinct groups of accessions, working with the whole data set by multivariate analyses allowed the separation of the 49 accessions in three clusters. Using all 23 measured parameters and data from the geographic origin for these accessions, positive correlations between the combined phenotypes and geographic origin were observed, supporting a robust pattern of isolation-by-distance. In addition, we found that fruit set was positively correlated with photosynthesis-related parameters, which, however, do not explain alone the differences in accession susceptibility to fruit abortion. Our results demonstrated that, although the accessions belong to the same species, they exhibit considerable natural intraspecific variation with respect to physiological and metabolic parameters, presenting diverse adaptation mechanisms and being a highly interesting source of information for plant breeders. This study also represents the first study combining photosynthetic, primary metabolism and growth parameters for Capsicum to date.

Variability of metabolite levels is linked to differential metabolic pathways in Arabidopsis's responses to abiotic stresses.

Constraint-based approaches have been used for integrating data in large-scale metabolic networks to obtain insights into metabolism of various organisms. Due to the underlying steady-state assumption, these approaches are usually not suited for making predictions about metabolite levels. Here, we ask whether we can make inferences about the variability of metabolite levels from a constraint-based analysis based on the integration of transcriptomics data. To this end, we analyze time-resolved transcriptomics and metabolomics data from Arabidopsis thaliana under a set of eight different light and temperature conditions. In a previous study, the gene expression data have already been integrated in a genome-scale metabolic network to predict pathways, termed modulators and sustainers, which are differentially regulated with respect to a biochemically meaningful data-driven null model. Here, we present a follow-up analysis which bridges the gap between flux- and metabolite-centric methods. One of our main findings demonstrates that under certain environmental conditions, the levels of metabolites acting as substrates in modulators or sustainers show significantly lower temporal variations with respect to the remaining measured metabolites. This observation is discussed within the context of a systems-view of plasticity and robustness of metabolite contents and pathway fluxes. Our study paves the way for investigating the existence of similar principles in other species for which both genome-scale networks and high-throughput metabolomics data of high quality are becoming increasingly available.

The essential role of sugar metabolism in the acclimation response of Arabidopsis thaliana to high light intensities.

Retrograde signals from chloroplasts are thought to control the expression of nuclear genes associated with plastidial processes such as acclimation to varying light conditions. Arabidopsis mutants altered in the day and night path of photoassimilate export from the chloroplasts served as tools to study the involvement of carbohydrates in high light (HL) acclimation. A double mutant impaired in the triose phosphate/phosphate translocator (TPT) and ADP-glucose pyrophosphorylase (AGPase) (adg1-1/tpt-2) exhibits a HL-dependent depletion in endogenous carbohydrates combined with a severe growth and photosynthesis phenotype. The acclimation response of mutant and wild-type plants has been assessed in time series after transfer from low light (LL) to HL by analysing photosynthetic performance, carbohydrates, MgProtoIX (a chlorophyll precursor), and the ascorbate/glutathione redox system, combined with microarray-based transcriptomic and GC-MS-based metabolomic approaches. The data indicate that the accumulation of soluble carbohydrates (predominantly glucose) acts as a short-term response to HL exposure in both mutant and wild-type plants. Only if carbohydrates are depleted in the long term (e.g. after 2 d) is the acclimation response impaired, as observed in the adg1-1/tpt-2 double mutant. Furthermore, meta-analyses conducted with in-house and publicly available microarray data suggest that, in the long term, reactive oxygen species such as H2O2 can replace carbohydrates as signals. Moreover, a cross-talk exists between genes associated with the regulation of starch and lipid metabolism. The involvement of genes responding to phytohormones in HL acclimation appears to be less likely. Various candidate genes involved in retrograde control of nuclear gene expression emerged from the analyses of global gene expression.

BAHD Company: The Ever-Expanding Roles of the BAHD Acyltransferase Gene Family in Plants.

Plants' ability to chemically modify core structures of specialized metabolites is the main reason why the plant kingdom contains such a wide and rich array of diverse compounds. One of the most important types of chemical modifications of small molecules is the addition of an acyl moiety to produce esters and amides. Large-scale phylogenomics analyses have shown that the enzymes that perform acyl transfer reactions on the myriad small molecules synthesized by plants belong to only a few gene families. This review is focused on describing the biochemistry, evolutionary origins, and chemical ecology implications of one of these families-the BAHD acyltransferases. The growth of advanced metabolomic studies coupled with next-generation sequencing of diverse plant species has confirmed that the BAHD family plays critical roles in modifying nearly all known classes of specialized metabolites. The current and future outlook for research on BAHDs includes expanding their roles in synthetic biology and metabolic engineering.

Synthetic biology identifies the minimal gene set required for paclitaxel biosynthesis in a plant chassis.

The diterpenoid paclitaxel (Taxol) is a chemotherapy medication widely used as a first-line treatment against several types of solid cancers. The supply of paclitaxel from natural sources is limited. However, missing knowledge about the genes involved in several specific metabolic steps of paclitaxel biosynthesis has rendered it difficult to engineer the full pathway. In this study, we used a combination of transcriptomics, cell biology, metabolomics, and pathway reconstitution to identify the complete gene set required for the heterologous production of paclitaxel. We identified the missing steps from the current model of paclitaxel biosynthesis and confirmed the activity of most of the missing enzymes via heterologous expression in Nicotiana benthamiana. Notably, we identified a new C4ß-C20 epoxidase that could overcome the first bottleneck of metabolic engineering. We used both previously characterized and newly identified oxomutases/epoxidases, taxane 1ß-hydroxylase, taxane 9α-hydroxylase, taxane 9α-dioxygenase, and phenylalanine-CoA ligase, to successfully biosynthesize the key intermediate baccatin III and to convert baccatin III into paclitaxel in N. benthamiana. In combination, these approaches establish a metabolic route to taxoid biosynthesis and provide insights into the unique chemistry that plants use to generate complex bioactive metabolites.

Preparation and Curation of Omics Data for Genome-Wide Association Studies.

With the development of large-scale molecular phenotyping platforms, genome-wide association studies have greatly developed, being no longer limited to the analysis of classical agronomic traits, such as yield or flowering time, but also embracing the dissection of the genetic basis of molecular traits. Data generated by omics platforms, however, pose some technical and statistical challenges to the classical methodology and assumptions of an association study. Although genotyping data are subject to strict filtering procedures, and several advanced statistical approaches are now available to adjust for population structure, less attention has been instead devoted to the preparation of omics data prior to GWAS. In the present chapter, we briefly present the methods to acquire profiling data from transcripts, proteins, and small molecules, and discuss the tools and possibilities to clean, normalize, and remove the unwanted variation from large datasets of molecular phenotypic traits prior to their use in GWAS.