A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

Comprehensive transcriptomic meta-analysis unveils new responsive genes to methyl jasmonate and ethylene in Catharanthusroseus

In Catharanthus roseus, vital plant hormones, namely methyl jasmonate (MeJA) and ethylene, serve as abiotic triggers, playing a crucial role in stimulating the production of specific secondary compounds with anticancer properties. Understanding how plants react to various stresses, stimuli, and the pathways involved in biosynthesis holds significant promise. The application of stressors like ethylene and MeJA induces the plant's defense mechanisms, leading to increased secondary metabolite production. To delve into the essential transcriptomic processes linked to hormonal responses, this study employed an integrated approach combining RNA-Seq data meta-analysis and system biology methodologies. Furthermore, the validity of the meta-analysis findings was confirmed using RT-qPCR. Within the meta-analysis, 903 genes exhibited differential expression (DEGs) when comparing normal conditions to those of the treatment. Subsequent analysis, encompassing gene ontology, KEGG, TF, and motifs, revealed that these DEGs were actively engaged in multiple biological processes, particularly in responding to various stresses and stimuli. Additionally, these genes were notably enriched in diverse biosynthetic pathways, including those related to TIAs, housing valuable medicinal compounds found in this plant. Furthermore, by conducting co-expression network analysis, we identified hub genes within modules associated with stress response and the production of TIAs. Most genes linked to the biosynthesis pathway of TIAs clustered within three specific modules. Noteworthy hub genes, including Helicase ATP-binding domain, hbdA, and ALP1 genes within the blue, turquoise, and green module networks, are presumed to play a role in the TIAs pathway. These identified candidate genes hold potential for forthcoming genetic and metabolic engineering initiatives aimed at augmenting the production of secondary metabolites and medicinal compounds within C. roseus.

Plant Reactome Knowledgebase: empowering plant pathway exploration and OMICS data analysis

Plant Reactome (https://plantreactome.gramene.org) is a freely accessible, comprehensive plant pathway knowledgebase. It provides curated reference pathways from rice (Oryza sativa) and gene-orthology-based pathway projections to 129 additional species, spanning single-cell photoautotrophs, non-vascular plants, and higher plants, thus encompassing a wide-ranging taxonomic diversity. Currently, Plant Reactome houses a collection of 339 reference pathways, covering metabolic and transport pathways, hormone signaling, genetic regulations of developmental processes, and intricate transcriptional networks that orchestrate a plant's response to abiotic and biotic stimuli. Beyond being a mere repository, Plant Reactome serves as a dynamic data discovery platform. Users can analyze and visualize omics data, such as gene expression, gene-gene interaction, proteome, and metabolome data, all within the rich context of plant pathways. Plant Reactome is dedicated to fostering data interoperability, upholding global data standards, and embracing the tenets of the Findable, Accessible, Interoperable and Re-usable (FAIR) data policy.

Tryptophan metabolites and gut microbiota play an important role in pediatric migraine diagnosis

BACKGROUND

The pathogenesis of pediatric migraine remains unclear and presents challenges in diagnosis. Recently, growing evidence has indicated that the gut microbiota can exert modulatory functions at the gut-brain axis by directly or indirectly regulating tryptophan metabolism. Consequently, we aimed to elucidate the potential association among gut microbiota, tryptophan metabolism, and pediatric migraine while also identifying diagnostic biomarkers for pediatric migraine.

METHODS

The gut microbiota composition of 33 migraine children and 42 healthy children, aged less than ten years, from the GMrepo database, was analyzed using the Shannon index, Simpson index, principal coordinates analysis, and Wilcoxon rank-sum test. Microbial diagnostic biomarkers were identified using linear discriminant analysis effect size, ridge regression, and random forest. Plasma concentrations of tryptophan metabolites investigated by enzyme-linked immunosorbent assay were compared between 51 migraine children and 120 healthy children, aged less than eighteen years, using t tests and analysis of variance. The receiver operating characteristic curve was performed to evaluate the diagnostic value of microbial and metabolite biomarkers in pediatric migraine.

RESULTS

Differences in the composition of gut microbiota, notably the genera that regulate tryptophan metabolism, were observed in pediatric migraine children. Further investigations revealed a significant decrease in plasma kynurenic acid levels (p < 0.001) among migraine children, along with a significant increase in serotonin (p < 0.05) and quinolinic acid (p < 0.001). Subsequently, we established the normal reference intervals for plasma concentrations of tryptophan metabolites in children. More importantly, the ratio of kynurenic acid to quinolinic acid (AUC: 0.871, sensitivity: 86.3%, specificity: 83.3%) exhibited excellent diagnostic efficacy for pediatric migraine.

CONCLUSION

Our study suggests that the gut microbiota may play an important role in the development of pediatric migraine by regulating tryptophan metabolism. We believe that microbial and metabolite biomarkers are sensitive diagnostic tests for pediatric migraine.

TRIAL REGISTRATION

The study was registered at ClinicalTrials.gov (NCT05969990).

Dynamic nitrogen reallocation in rice plants upon insect herbivory by a generalist lepidopteran pest Spodoptera litura (Fabricius)

Nitrogen (N) is a limited nutrient for both plants and herbivores. How plants reallocate N upon herbivore attack is vital for plant tolerance to herbivores. Here we investigated N reallocation in rice during a 2-day herbivore attack by a generalist herbivore Spodoptera litura and 2 days after herbivore removal. Labeled 15 N was translocated during insect attack from feeding-damaged leaves to roots, particularly to young roots. The amounts of chlorophyll and Rubisco were significantly reduced in the attacked leaves. Both free amino acids and nitrate accumulated in the damaged leaves and young roots, while ammonium content was decreased. Activities of nitrate reductase and glutamine synthetase were enhanced in feeding-damaged leaves but inhibited in young roots. The expression of amino acid transporters OsAAP6, OsAAT15, and jasmonate-responsive genes OsAOS, OsMAPK3, OsMAPK6 was induced in the damaged leaves. However, 2 days after herbivore removal, N uptake was increased and herbivory-induced 15 N transfer to roots was partially reverted back to the damaged leaves, resulting in N levels in the previously damaged leaves were even higher than that in control leaves. Collectively, our results indicate a dynamic N reallocation in rice responses to insect herbivory.

Reference genome of the nutrition-rich orphan crop chia (Salvia hispanica) and its implications for future breeding

Chia (Salvia hispanica L.) is one of the most popular nutrition-rich foods and pseudocereal crops of the family Lamiaceae. Chia seeds are a rich source of proteins, polyunsaturated fatty acids (PUFAs), dietary fibers, and antioxidants. In this study, we present the assembly of the chia reference genome, which spans 303.6 Mb and encodes 48,090 annotated protein-coding genes. Our analysis revealed that ~42% of the chia genome harbors repetitive content, and identified ~3 million single nucleotide polymorphisms (SNPs) and 15,380 simple sequence repeat (SSR) marker sites. By investigating the chia transcriptome, we discovered that ~44% of the genes undergo alternative splicing with a higher frequency of intron retention events. Additionally, we identified chia genes associated with important nutrient content and quality traits, such as the biosynthesis of PUFAs and seed mucilage fiber (dietary fiber) polysaccharides. Notably, this is the first report of in-silico annotation of a plant genome for protein-derived small bioactive peptides (biopeptides) associated with improving human health. To facilitate further research and translational applications of this valuable orphan crop, we have developed the Salvia genomics database (SalviaGDB), accessible at https://salviagdb.org.

Integrating omics databases for enhanced crop breeding

Crop plant breeding involves selecting and developing new plant varieties with desirable traits such as increased yield, improved disease resistance, and enhanced nutritional value. With the development of high-throughput technologies, such as genomics, transcriptomics, and metabolomics, crop breeding has entered a new era. However, to effectively use these technologies, integration of multi-omics data from different databases is required. Integration of omics data provides a comprehensive understanding of the biological processes underlying plant traits and their interactions. This review highlights the importance of integrating omics databases in crop plant breeding, discusses available omics data and databases, describes integration challenges, and highlights recent developments and potential benefits. Taken together, the integration of omics databases is a critical step towards enhancing crop plant breeding and improving global food security.

Hormonal Interplay Leading to Black Knot Disease Establishment and Progression in Plums

Black Knot (BK) is a deadly disease of European (Prunus domestics) and Japanese (Prunus salicina) plums caused by the hemibiotrophic fungus Apiosporina morbosa. After infection, the appearance of warty black knots indicates a phytohormonal imbalance in infected tissues. Based on this hypothesis, we quantified phytohormones such as indole-3-acetic acid, tryptophan, indoleamines (N-acetylserotonin, serotonin, and melatonin), and cytokinins (zeatin, 6-benzyladenine, and 2-isopentenyladenine) in temporally collected tissues of susceptible and resistant genotypes belonging to European and Japanese plums during of BK progression. The results suggested auxin-cytokinins interplay driven by A. morbosa appears to be vital in disease progression by hampering the plant defense system. Taken together, our results indicate the possibility of using the phytohormone profile as a biomarker for BK resistance in plums.

Chlorophyll fluorescence-based high-throughput phenotyping facilitates the genetic dissection of photosynthetic heat tolerance in African (Oryza glaberrima) and Asian (Oryza sativa) rice

Rising temperatures and extreme heat events threaten rice production. Half of the global population relies on rice for basic nutrition, and therefore developing heat-tolerant rice is essential. During vegetative development, reduced photosynthetic rates can limit growth and the capacity to store soluble carbohydrates. The photosystem II (PSII) complex is a particularly heat-labile component of photosynthesis. We have developed a high-throughput chlorophyll fluorescence-based screen for photosynthetic heat tolerance capable of screening hundreds of plants daily. Through measuring the response of maximum PSII efficiency to increasing temperature, this platform generates data for modelling the PSII-temperature relationship in large populations in a small amount of time. Coefficients from these models (photosynthetic heat tolerance traits) demonstrated high heritabilities across African (Oryza glaberrima) and Asian (Oryza sativa, Bengal Assam Aus Panel) rice diversity sets, highlighting valuable genetic variation accessible for breeding. Genome-wide association studies were performed across both species for these traits, representing the first documented attempt to characterize the genetic basis of photosynthetic heat tolerance in any species to date. A total of 133 candidate genes were highlighted. These were significantly enriched with genes whose predicted roles suggested influence on PSII activity and the response to stress. We discuss the most promising candidates for improving photosynthetic heat tolerance in rice.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.

Characterizing serotonin biosynthesis in Setaria viridis leaves and its effect on aphids

A combined transcriptomic and metabolic analysis of Setaria viridis leaves responding to aphid infestation was used to identify genes related to serotonin biosynthesis. Setaria viridis (green foxtail), a short life-cycle C4 plant in the Poaceae family, is the wild ancestor of Setaria italica (foxtail millet), a resilient crop that provides good yields in dry and marginal land. Although S. viridis has been studied extensively in the last decade, the molecular mechanisms of insect resistance in this species remain under-investigated. To address this issue, we performed a metabolic analysis of S. viridis and discovered that these plants accumulate the tryptophan-derived compounds tryptamine and serotonin. To elucidate the defensive functions of serotonin, Rhophalosiphum padi (bird cherry-oat aphids) were exposed to this compound, either by exogenous application to the plant medium or with artificial diet bioassays. In both cases, exposure to serotonin increased aphid mortality. To identify genes that are involved in serotonin biosynthesis, we conducted a transcriptome analysis and identified several predicted S. viridis tryptophan decarboxylase (TDC) and tryptamine 5-hydroxylase (T5H) genes. Two candidate genes were ectopically expressed in Nicotiana tabacum, where SvTDC1 (Sevir.6G066200) had tryptophan decarboxylase activity, and SvT5H1 (Sevir.8G219600) had tryptamine hydroxylase activity. Moreover, the function of the SvTDC1 gene was validated using virus-induced gene silencing in S. italica, which caused a reduction in serotonin levels. This study provides the first evidence of serotonin biosynthesis in Setaria leaves. The biosynthesis of serotonin may play an important role in defense responses and could prove to be useful for developing more pest-tolerant Setaria italica cultivars.

Exploring Genomic Variations in Nematode-Resistant Mutant Rice Lines

Rice (Oryza sativa) production is seriously affected by the root-knot nematode Meloidogyne graminicola, which has emerged as a menace in upland and irrigated rice cultivation systems. Previously, activation tagging in rice was utilized to identify candidate gene(s) conferring resistance against M. graminicola. T-DNA insertional mutants were developed in a rice landrace (acc. JBT 36/14), and four mutant lines showed nematode resistance. Whole-genome sequencing of JBT 36/14 was done along with the four nematode resistance mutant lines to identify the structural genetic variations that might be contributing to M. graminicola resistance. Sequencing on Illumina NovaSeq 6000 platform identified 482,234 genetic variations in JBT 36/14 including 448,989 SNPs and 33,245 InDels compared to reference indica genome. In addition, 293,238-553,648 unique SNPs and 32,395-65,572 unique InDels were found in the four mutant lines compared to their JBT 36/14 background, of which 93,224 SNPs and 8,170 InDels were common between all the mutant lines. Functional annotation of genes containing these structural variations showed that the majority of them were involved in metabolism and growth. Trait analysis revealed that most of these genes were involved in morphological traits, physiological traits and stress resistance. Additionally, several families of transcription factors, such as FAR1, bHLH, and NAC, and putative susceptibility (S) genes, showed the presence of SNPs and InDels. Our results indicate that subject to further genetic validations, these structural genetic variations may be involved in conferring nematode resistance to the rice mutant lines.

PlantPathMarks (PPMdb): an interactive hub for pathways-based markers in plant genomes

Over the past decade, the problem of finding an efficient gene-targeting marker set or signature for plant trait characterization has remained challenging. Many databases focusing on pathway mining have been released with one major deficiency, as they lack to develop marker sets that target only genes controlling a specific pathway or certain biological process. Herein, we present the PlantPathMarks database (PPMdb) as a comprehensive, web-based, user-friendly, and interactive hub for pathway-based markers in plant genomes. Based on our newly developed pathway gene set mining approach, two novel pathway-based marker systems called pathway gene-targeted markers (PGTMs) and pathway microsatellite-targeted markers (PMTMs) were developed as a novel class of annotation-based markers. In the PPMdb database, 2,690,742 pathway-based markers reflecting 9,894 marker panels were developed across 82 plant genomes. The markers include 691,555 PGTMs and 1,999,187 PMTMs. Across these genomes, 165,378 enzyme-coding genes were mapped against 126 KEGG reference pathway maps. PPMdb is furnished with three interactive visualization tools (Map Browse, JBrowse and Species Comparison) to visualize, map, and compare the developed markers over their KEGG reference pathway maps. All the stored marker panels can be freely downloaded. PPMdb promises to create a radical shift in the paradigm of the area of molecular marker research. The use of PPMdb as a mega-tool represents an impediment for non-bioinformatician plant scientists and breeders. PPMdb is freely available at http://ppmdb.easyomics.org.

The Wild Rice Locus CTS-12 Mediates ABA-Dependent Stomatal Opening Modulation to Limit Water Loss Under Severe Chilling Stress

A near-isogenic line (NIL) DC90 which was generated by introgressing a wild rice (Oryza rufipogon Griff.) locus CTS-12 into the 9311(Oryza sativa L. ssp. indica) background confers chilling tolerance phenotype. Here, our pilot trials showed that chilling tolerance was positively correlated with abscisic acid (ABA) biosynthesis. To understand how CTS-12 mediated the ABA-dependent multi-levels of regulation, the integration of transcriptomic and metabolomic profiling using the two-way orthogonal projections to latent structures (O2PLS) and discriminant analysis (OPLS-DA) modeling was performed to investigate the mechanisms underlying chilling tolerance. Our results revealed that metabolic shifts, including the activation of stachyose biosynthesis, amino acid metabolism pathways, phenylpropanoid/flavonoid biosynthesis, ABA biosynthesis, and perturbation of glycolysis, occurred under chilling treatment; in the recovery period, glutamate-related pathways, β-alanine biosynthesis and degradation, and serotonin biosynthesis pathways were differentiated between 9311 and DC90. Particularly, the differentially accumulated metabolites (DAMs) and differentially expressed genes (DEGs), including galactinol, β-alanine, glutamate, naringenin, serotonin, ABA, and LOC_Os03g44380 (9-cis-epoxycarotenoid dioxygenase 3, OsNCED3), might be involved in the chilling tolerance variation of 9311 and DC90. CRISPR/Cas9-edited OsNCED3 resulted in chilling sensitive of japonica rice ZH11, demonstrating the involvement of ABA pathway in chilling stress response. In addition, chilling tolerance of rice was associated with the balance of water uptake and loss that was modulated by stomatal movement under chilling stress. Therefore, we speculated that the CTS-12-mediated ABA signaling pathway leads to transcriptional regulation of chilling-responsive genes and, in turn, triggers metabolic shifts to coordinately regulate the stomatal movement of guard cells. The results of this study improve our understanding of the multilevel regulation of wild rice in response to chilling stress.

Effects of Water Deficit and Heat Stress on Nicotiana langsdorffii Metabolomic Pattern Modified by Insertion of rolD Gene from Agrobacterium rhizogenes

Abiotic stresses are major factors that negatively affect plant growth and productivity. Plants have developed complex strategies to ensure their survival and reproduction under adverse conditions, activating mechanisms that involve changes at different metabolic levels. In order to select stress-resistant species, research has focused on molecular studies and genetic engineering, showing promising results. In this work, the insertion of the rolD gene from Agrobacterium rhizogenes into Nicotiana langsdorffii plants is investigated, in order to assess the potential of this genetic modification towards mitigating water and heat stresses. Different approaches were combined: a high-throughput metabolomics and ionomics study was performed, together with the determination of important plant phytohormones. The aim was to identify the influence of abiotic stresses on plants and to highlight the effects of the rolD genetic modification on plant stress response. The most relevant compounds for each kind of stress were identified, belonging mainly to the classes of lipids, acyl sugars, glycosides, and amino acid derivatives. Water stress (WS) determined a decrease of elements and secondary metabolites, while amino acids and their derivatives increased, proving to be key molecules in this type of stress. RolD plants exposed to high temperature stress (HS) presented higher dry weight levels than controls, as well as increased amounts of K and adenosine and lower levels of damage-associated metabolites, suggesting the increased resistance of rolD-modified plants toward HS.

Plant Reactome: a knowledgebase and resource for comparative pathway analysis

Plant Reactome (https://plantreactome.gramene.org) is an open-source, comparative plant pathway knowledgebase of the Gramene project. It uses Oryza sativa (rice) as a reference species for manual curation of pathways and extends pathway knowledge to another 82 plant species via gene-orthology projection using the Reactome data model and framework. It currently hosts 298 reference pathways, including metabolic and transport pathways, transcriptional networks, hormone signaling pathways, and plant developmental processes. In addition to browsing plant pathways, users can upload and analyze their omics data, such as the gene-expression data, and overlay curated or experimental gene-gene interaction data to extend pathway knowledge. The curation team actively engages researchers and students on gene and pathway curation by offering workshops and online tutorials. The Plant Reactome supports, implements and collaborates with the wider community to make data and tools related to genes, genomes, and pathways Findable, Accessible, Interoperable and Re-usable (FAIR).

Adaptation of the metabolomics profile of rice after Pyricularia oryzae infection

Pyricularia oryzae (P. oryzae), one of the most devastating fungal pathogens, is the cause of blast disease in rice. Infection with a blast fungus induces biological responses in the host plant that lead to its survival through the termination or suppression of pathogen growth, and metabolite compounds play vital roles in plant interactions with a wide variety of other organisms. Numerous studies have indicated that rice has a multi-layered plant immune system that includes pre-developed (e.g., cell wall and phytoanticipins), constitutive and inducible (phytoalexins) defence barriers against stresses. Significant progress towards understanding the basis of the molecular mechanisms underlying the defence responses of rice to P. oryzae has been achieved. Nonetheless, even though the important metabolites in the responses of rice to pathogens have been identified, their exact mechanisms and their contributions to plant immunity against blast fungi have not been elucidated. The purpose of this review is to summarize and discuss recent advances towards the understanding of the integrated metabolite variations in rice after P. oryzae invasion.

Gramene 2018: unifying comparative genomics and pathway resources for plant research

Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces.

Functional Identification of Corynespora cassiicola-Responsive miRNAs and Their Targets in Cucumber

Target leaf spot (TLS), which is caused by Corynespora cassiicola (C. cassiicola), is one of the most important diseases in cucumber (Cucumis sativus L.). Our previous research identified several C. cassiicola-responsive miRNAs in cucumber by high-throughput sequencing, including two known miRNAs and two novel miRNAs. The target genes of these miRNAs were related to secondary metabolism. In this study, we verified the interaction between these miRNAs and target genes by histochemical staining and fluorescence quantitative assays of GUS. We transiently expressed the candidate miRNAs and target genes in cucumber cotyledons to investigate the resistance to C. cassiicola. Transient expression of miR164d, miR396b, Novel-miR1, and Novel-miR7 in cucumber resulted in decreased resistance to C. cassiicola, while transient expression of NAC (inhibited by miR164d), APE (inhibited by miR396b), 4CL (inhibited by Novel-miR1), and PAL (inhibited by Novel-miR7) led to enhanced resistance to C. cassiicola. In addition, overexpression of 4CL and PAL downregulated lignin synthesis, and overexpression of Novel-miR1 and Novel-miR7 also downregulated lignin synthesis, indicating that the regulation of 4CL and PAL by Novel-miR1 and Novel-miR7 could affect lignin content. The tobacco rattle virus (TRV) induced short tandem target mimic (STTM)-miRNA silencing vector was successfully constructed, and target miRNAs were successfully silenced. The identification of disease resistance and lignin content showed that silencing candidate miRNAs could improve cucumber resistance to C. cassiicola.

Whole Genome Sequencing and Comparative Genomic Analysis Reveal Allelic Variations Unique to a Purple Colored Rice Landrace (Oryza sativa ssp. indica cv. Purpleputtu)

Purpleputtu (Oryza sativa ssp. indica cv. Purpleputtu) is a unique rice landrace from southern India that exhibits predominantly purple color. This study reports the underlying genetic complexity of the trait, associated domestication and de-domestication processes during its coevolution with present day cultivars. Along-with genome level allelic variations in the entire gene repertoire associated with the purple, red coloration of grain and other plant parts. Comparative genomic analysis using 'a panel of 108 rice lines' revealed a total of 3,200,951 variants including 67,774 unique variations in Purpleputtu (PP) genome. Multiple sequence alignment uncovered a 14 bp deletion in Rc (Red colored, a transcription factor of bHLH class) locus of PP, a key regulatory gene of anthocyanin biosynthetic pathway. Interestingly, this deletion in Rc gene is a characteristic feature of the present-day white pericarped rice cultivars. Phylogenetic analysis of Rc locus revealed a distinct clade showing proximity to the progenitor species Oryza rufipogon and O. nivara. In addition, PP genome exhibits a well conserved 4.5 Mbp region on chromosome 5 that harbors several loci associated with domestication of rice. Further, PP showed 1,387 unique when SNPs compared to 3,023 lines of rice (SNP-Seek database). The results indicate that PP genome is rich in allelic diversity and can serve as an excellent resource for rice breeding for a variety of agronomically important traits such as disease resistance, enhanced nutritional values, stress tolerance, and protection from harmful UV-B rays.

Involving community in genes and pathway curation

Biocuration plays a crucial role in building databases and complex systems-level platforms required for processing, annotating and analyzing ‘Big Data’ in biology. However, biocuration efforts cannot keep pace with a dramatic increase in the production of omics data; this presents one of the bottlenecks in genomics. In two pathway curation jamborees, Plant Reactome curators tested strategies for introducing researchers to pathway curation tools, harnessing biologists’ expertise in curating plant pathways and developing a network of community biocurators. We summarize the strategy, workflow and outcomes of these exercises, and discuss the role of community biocuration in advancing databases and genomic resources.

Novel perspectives on the molecular crosstalk mechanisms of serotonin and melatonin in plants

Current review focuses on the significant role of serotonin and melatonin in various molecular crosstalk mechanisms in plants. In this context phytohormones (like auxin, gibberellins, ethylene or abscisic acid), plant growth regulators, and associated biomolecules like reactive oxygen species, nitric oxide, brassinosteroids and hydrogen sulphide have been discussed in a wider context. Long distance signaling responses of serotonin in association with auxin, jasmonic acid, salicylic acid and ABA have been critically reviewed. Auxin-serotonin crosstalk in relation to PIN protein functioning and root growth regulation appears to be a major advancement in the context of phytoserotonin signaling in plants. Auxin and serotonin share structural similarities which bring possibilities of auxin receptors being surrogated for serotonin transport in plants. The modulation of root apex architecture is highly regulative in terms of serotonin-jasmonic acid crosstalk. Reactive oxygen species (ROS) appears to be a primary mediator of serotonin mediated root growth response. Serotonin induced signaling therefore involve ROS, auxin, JA and ethylene action. Although there exists handful of critical reviews on the role of phytomelatonin in plants, recent advancements on its regulatory role in modulating plant hormones, ROS scavenging enzymes, ROS/RNS and glutathione levels need attention. Melatonin signaling associated with nitrogen metabolism and nitrosative stress are recent developments in plants. Interesting relationship between nitric oxide and melatonin has been established in relation with biotic and abiotic stress tolerance in plants. Developments in hydrogen sulphide-melatonin signaling in plants are still at its nascent stage but exhibits promising scopes for future.

The Tryptophan decarboxylase 1 Gene From Aegilops variabilis No.1 Regulate the Resistance Against Cereal Cyst Nematode by Altering the Downstream Secondary Metabolite Contents Rather Than Auxin Synthesis

Cereal cyst nematode (CCN, Heterodera avenae) is a most important pathogen of wheat and causes tremendous yield loss annually over the world. Since the lack of resistance materials among wheat cultivars, identification and characterization of the resistance-related genes from the relatives of wheat is a necessary and efficient way. As a close relative of wheat with high resistance against CCN, Aegilops variabilis No.1 is believed to be a valuable source for wheat breeding against this devastating disease. However so far, very few resistance-associated genes have been characterized from this species. In this study, we present that the tryptophan decarboxylase genes from Ae. variabilis No.1 (AeVTDC1 and AeVTDC2) were both induced by CCN juveniles at the early stage of resistance response (30 h post-inoculation), with AeVTDC1 more sensitive to CCN infection than AeVTDC2. Silencing of AeVTDC1 led to compromised immunity to CCN with more CCN intrusion into roots; while overexpression AeVTDC1 in Nicotiana tabacum dramatically enhanced the resistance of plants by reducing the knots formed on roots. Metabolism analysis showed that the contents of secondary metabolites with activity of resistance to varied pathogens correlated with the expression level of AeVTDC1 in both Ae. variabilis No.1 and the transgenic tobacco plants. In addition, the content of IAA was not affected by either silencing or overexpressing of AeVTDC1. Hence, our research provided AeVTDC1 a valuable target that mediates resistance to CCN and root knot nematode (RKN, Meloidogyne naasi) without influencing the auxin biosynthesis.

Genome-wide characterization of Phytophthora infestans metabolism: a systems biology approach

Genome-scale metabolic models (GEMs) provide a functional view of the complex network of biochemical reactions in the living cell. Initially mainly applied to reconstruct the metabolism of model organisms, the availability of increasingly sophisticated reconstruction methods and more extensive biochemical databases now make it possible to reconstruct GEMs for less well-characterized organisms, and have the potential to unravel the metabolism in pathogen-host systems. Here, we present a GEM for the oomycete plant pathogen Phytophthora infestans as a first step towards an integrative model with its host. We predict the biochemical reactions in different cellular compartments and investigate the gene-protein-reaction associations in this model to obtain an impression of the biochemical capabilities of P. infestans. Furthermore, we generate life stage-specific models to place the transcriptomic changes of the genes encoding metabolic enzymes into a functional context. In sporangia and zoospores, there is an overall down-regulation, most strikingly reflected in the fatty acid biosynthesis pathway. To investigate the robustness of the GEM, we simulate gene deletions to predict which enzymes are essential for in vitro growth. This model is an essential first step towards an understanding of P. infestans and its interactions with plants as a system, which will help to formulate new hypotheses on infection mechanisms and disease prevention.

Transcriptome and miRNA analyses of the response to Corynespora cassiicola in cucumber

Cucumber (Cucumis sativus L.) target leaf spot (TLS), which is caused by the fungus Corynespora cassiicola (C. cassiicola), seriously endangers the production of cucumber. In this assay, we performed comprehensive sequencing of the transcriptome and microRNAs (miRNAs) of a resistant cucumber (Jinyou 38) during C. cassiicola inoculation using the Illumina NextSeq 500 platform. The possible genes related to the response to C. cassiicola were associated with plant hormones, transcription factors, primary metabolism, Ca²⁺ signaling pathways, secondary metabolism and defense genes. In total, 150 target genes of these differentially expressed miRNAs were predicted by the bioinformatic analysis. By analyzing the function of the target genes, several candidate miRNAs that may be related to the response to C. cassiicola stress were selected. We also predicted 7 novel miRNAs and predicted their target genes. Moreover, the expression patterns of the candidate genes and miRNAs were tested by quantitative real-time RT-PCR. According to the analysis, genes and miRNAs associated with secondary metabolism, particularly the phenylpropanoid biosynthesis pathway, may play a major role in the resistance to C. cassiicola stress in cucumber. These results offer a foundation for future studies exploring the mechanism and key genes of resistance to cucumber TLS.

SolCyc: a database hub at the Sol Genomics Network (SGN) for the manual curation of metabolic networks in Solanum and Nicotiana specific databases

Database URL

https://solgenomics.net/tools/solcyc/.

Effects of acute salt stress on modulation of gene expression in a Malaysian salt-tolerant indigenous rice variety, Bajong

The small genome size of rice relative to wheat and barley, together with its salt sensitivity, make it an ideal candidate for studies of salt stress response. Transcriptomics has emerged as a powerful technique to study salinity responses in many crop species. By identifying a large number of differentially expressed genes (DEGs) simultaneously after the stress induction, it can provide crucial insight into the immediate responses towards the stressor. In this study, a Malaysian salt-tolerant indigenous rice variety named Bajong and one commercial rice variety named MR219 were investigated for their performance in plant growth and ion accumulation properties after salt stress treatment. Bajong was further investigated for the changes in leaf's transcriptome after 6 h of stress treatment using 100 mM NaCl. Based on the results obtained, Bajong is found to be significantly more salt tolerant than MR219, showing better growth and a lower sodium ion accumulation after the stress treatment. Additionally, Bajong was analysed by transcriptomic sequencing, generating a total of 130 millions reads. The reads were assembled into de novo transcriptome and each transcript was annotated using several pre-existing databases. The transcriptomes of control and salt-stressed samples were then compared, leading to the discovery of 4096 DEGs. Based on the functional annotation results obtained, the enrichment factor of each functional group in DEGs was calculated in relation to the total reads obtained. It was found that the group with the highest gene modulation was involved in the secondary metabolite biosynthesis of plants, with approximately 2.5% increase in relation to the total reads obtained. This suggests an extensive transcriptional reprogramming of the secondary metabolic pathways after stress induction, which could be directly responsible for the salt tolerance capability of Bajong.

The buffering capacity of stems: genetic architecture of nonstructural carbohydrates in cultivated Asian rice, Oryza sativa

Harnessing stem carbohydrate dynamics in grasses offers an opportunity to help meet future demands for plant-based food, fiber and fuel production, but requires a greater understanding of the genetic controls that govern the synthesis, interconversion and transport of such energy reserves. We map out a blueprint of the genetic architecture of rice (Oryza sativa) stem nonstructural carbohydrates (NSC) at two critical developmental time-points using a subpopulation-specific genome-wide association approach on two diverse germplasm panels followed by quantitative trait loci (QTL) mapping in a biparental population. Overall, 26 QTL are identified; three are detected in multiple panels and are associated with starch-at-maturity, sucrose-at-maturity and NSC-at-heading. They tag OsHXK6 (rice hexokinase), ISA2 (rice isoamylase) and a tandem array of sugar transporters. This study provides the foundation for more in-depth molecular investigation to validate candidate genes underlying rice stem NSC and informs future comparative studies in other agronomically vital grass species.

Transcriptome Analyses of Two Citrus Cultivars (Shiranuhi and Huangguogan) in Seedling Etiolation

Citrus species are among the most important fruit crops. However, gene regulation and signaling pathways related to etiolation in this crop remain unknown. Using Illumina sequencing technology, modification of global gene expression in two hybrid citrus cultivars—Huangguogan and Shiranuhi, respectively—were investigated. More than 834.16 million clean reads and 125.12 Gb of RNA-seq data were obtained, more than 91.37% reads had a quality score of Q30. 124,952 unigenes were finally generated with a mean length of 1,189 bp. 79.15%, 84.35%, 33.62%, 63.12%, 57.67%, 57.99% and 37.06% of these unigenes had been annotated in NR, NT, KO, SwissProt, PFAM, GO and KOG databases, respectively. Further, we identified 604 differentially expressed genes in multicoloured and etiolated seedlings of Shiranuhi, including 180 up-regulated genes and 424 down-regulated genes. While in Huangguogan, we found 1,035 DEGs, 271 of which were increasing and the others were decreasing. 7 DEGs were commonly up-regulated, and 59 DEGs down-regulated in multicoloured and etiolated seedlings of these two cultivars, suggesting that some genes play fundamental roles in two hybrid citrus seedlings during etiolation. Our study is the first to provide the transcriptome sequence resource for seedlings etiolation of Shiranuhi and Huangguogan.

Genome-Wide Prediction of Metabolic Enzymes, Pathways, and Gene Clusters in Plants

Plant metabolism underpins many traits of ecological and agronomic importance. Plants produce numerous compounds to cope with their environments but the biosynthetic pathways for most of these compounds have not yet been elucidated. To engineer and improve metabolic traits, we need comprehensive and accurate knowledge of the organization and regulation of plant metabolism at the genome scale. Here, we present a computational pipeline to identify metabolic enzymes, pathways, and gene clusters from a sequenced genome. Using this pipeline, we generated metabolic pathway databases for 22 species and identified metabolic gene clusters from 18 species. This unified resource can be used to conduct a wide array of comparative studies of plant metabolism. Using the resource, we discovered a widespread occurrence of metabolic gene clusters in plants: 11,969 clusters from 18 species. The prevalence of metabolic gene clusters offers an intriguing possibility of an untapped source for uncovering new metabolite biosynthesis pathways. For example, more than 1,700 clusters contain enzymes that could generate a specialized metabolite scaffold (signature enzymes) and enzymes that modify the scaffold (tailoring enzymes). In four species with sufficient gene expression data, we identified 43 highly coexpressed clusters that contain signature and tailoring enzymes, of which eight were characterized previously to be functional pathways. Finally, we identified patterns of genome organization that implicate local gene duplication and, to a lesser extent, single gene transposition as having played roles in the evolution of plant metabolic gene clusters.

Variant Effect Prediction Analysis Using Resources Available at Gramene Database

The goal of Gramene database ( www.gramene.org ) is to empower the plant research community in conducting comparative genomics studies across model plants and crops by employing a phylogenetic framework and orthology-based projections. Gramene database (release #49) provides resources for comparative plant genomics including well-annotated plant genomes (39 complete reference genomes and six partial genomes), genetic or structural variation data for 14 plant species, pathways for 58 plant species, and gene expression data for 14 species including Arabidopsis, rice, maize, soybean, wheat, etc. (fetched from EBI-EMBL Gene Expression Atlas database). Gramene also facilitates visualization and analysis of user-defined data in the context of species-specific Genome Browsers or pathways. This chapter describes basic navigation for Gramene users and illustrates how they can use the genome section to analyze the gene expression and nucleotide variation data generated in their labs. This includes (1) upload and display of genomic data onto a Genome Browser track, (2) analysis of variation data using online Variant Effect Predictor (VEP) tool for smaller data sets, and (3) the use of the stand-alone Perl scripts and command line protocols for variant effect prediction on larger data sets.

Pathway Analysis and Omics Data Visualization Using Pathway Genome Databases: FragariaCyc, a Case Study

The species-specific plant Pathway Genome Databases (PGDBs) based on the BioCyc platform provide a conceptual model of the cellular metabolic network of an organism. Such frameworks allow analysis of the genome-scale expression data to understand changes in the overall metabolisms of an organism (or organs, tissues, and cells) in response to various extrinsic (e.g. developmental and differentiation) and/or extrinsic signals (e.g. pathogens and abiotic stresses) from the surrounding environment. Using FragariaCyc, a pathway database for the diploid strawberry Fragaria vesca, we show (1) the basic navigation across a PGDB; (2) a case study of pathway comparison across plant species; and (3) an example of RNA-Seq data analysis using Omics Viewer tool. The protocols described here generally apply to other Pathway Tools-based PGDBs.

Functional classification of rice flanking sequence tagged genes using MapMan terms and global understanding on metabolic and regulatory pathways affected by dxr mutant having defects in light response

BACKGROUND

Rice is one of the most important food crops for humans. To improve the agronomical traits of rice, the functions of more than 1,000 rice genes have been recently characterized and summarized. The completed, map-based sequence of the rice genome has significantly accelerated the functional characterization of rice genes, but progress remains limited in assigning functions to all predicted non-transposable element (non-TE) genes, estimated to number 37,000-41,000.

RESULTS

The International Rice Functional Genomics Consortium (IRFGC) has generated a huge number of gene-indexed mutants by using mutagens such as T-DNA, Tos17 and Ds/dSpm. These mutants have been identified by 246,566 flanking sequence tags (FSTs) and cover 65 % (25,275 of 38,869) of the non-TE genes in rice, while the mutation ratio of TE genes is 25.7 %. In addition, almost 80 % of highly expressed non-TE genes have insertion mutations, indicating that highly expressed genes in rice chromosomes are more likely to have mutations by mutagens such as T-DNA, Ds, dSpm and Tos17. The functions of around 2.5 % of rice genes have been characterized, and studies have mainly focused on transcriptional and post-transcriptional regulation. Slow progress in characterizing the function of rice genes is mainly due to a lack of clues to guide functional studies or functional redundancy. These limitations can be partially solved by a well-categorized functional classification of FST genes. To create this classification, we used the diverse overviews installed in the MapMan toolkit. Gene Ontology (GO) assignment to FST genes supplemented the limitation of MapMan overviews.

CONCLUSION

The functions of 863 of 1,022 known genes can be evaluated by current FST lines, indicating that FST genes are useful resources for functional genomic studies. We assigned 16,169 out of 29,624 FST genes to 34 MapMan classes, including major three categories such as DNA, RNA and protein. To demonstrate the MapMan application on FST genes, transcriptome analysis was done from a rice mutant of 1-deoxy-D-xylulose 5-phosphate reductoisomerase (DXR) gene with FST. Mapping of 756 down-regulated genes in dxr mutants and their annotation in terms of various MapMan overviews revealed candidate genes downstream of DXR-mediating light signaling pathway in diverse functional classes such as the methyl-D-erythritol 4-phosphatepathway (MEP) pathway overview, photosynthesis, secondary metabolism and regulatory overview. This report provides a useful guide for systematic phenomics and further applications to enhance the key agronomic traits of rice.

Robust phenotyping strategies for evaluation of stem non-structural carbohydrates (NSC) in rice

Rice plants (Oryza sativa) accumulate excess photoassimilates in the form of non-structural carbohydrates (NSCs) in their stems prior to heading that can later be mobilized to supplement photosynthate production during grain-filling. Despite longstanding interest in stem NSC for rice improvement, the dynamics of NSC accumulation, remobilization, and re-accumulation that have genetic potential for optimization have not been systematically investigated. Here we conducted three pilot experiments to lay the groundwork for large-scale diversity studies on rice stem NSC. We assessed the relationship of stem NSC components with 21 agronomic traits in large-scale, tropical yield trials using 33 breeder-nominated lines, established an appropriate experimental design for future genetic studies using a Bayesian framework to sample sub-datasets from highly replicated greenhouse data using 36 genetically diverse genotypes, and used 434 phenotypically divergent rice stem samples to develop two partial least-squares (PLS) models using near-infrared (NIR) spectra for accurate, rapid prediction of rice stem starch, sucrose, and total non-structural carbohydrates. We find evidence that stem reserves are most critical for short-duration varieties and suggest that pre-heading stem NSC is worthy of further experimentation for breeding early maturing rice.

Plant Reactome: a resource for plant pathways and comparative analysis

Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX.

Differentiation and description of aromatic short grain rice landraces of eastern Indian state of Odisha based on qualitative phenotypic descriptors

Background

Speciality rice, in general, and aromatic rice in particular, possess enormous market potential for enhancing farm profits. However, systematic characterization of the diversity present in this natural wealth is a major pre requisite for using it in the breeding programs. This study reports qualitative phenotypic trait based characterization of 126 short grain aromatic rice genotypes, collected from different areas of the state of Odisha, India.

Results

Out of the 24 descriptors employed, highest variability (8 different types) was observed for lemma-palea colour with a genetic diversity index (He) of 0.696. The principal component analysis reveals that the tip colour of lemma, colour of awn and colour of stigma, cumulatively explain 74 % of the total variation. The Population STRUCTURE analysis classified the population into two subpopulations which were subdivided further into four distinct groups. The western and southern districts of Odisha are endowed with maximum diversity in comparison to eastern and northern districts and at district level comparisons, Koraput and Puri districts are rich with a genetic diversity values of 0.324 and 0.303 respectively. With this set of morphological qualitative traits, based on ‘phenoprinting’, a newly proposed bar coding system, unique fingerprints of each genotype can be effectively generated that can help in easy identification of these genotypes.

Conclusion

Though aromatic rices represent a tiny fraction of the total rice germplasm, a small collection of 126 land races did exhibit rich diversity for all the qualitative traits. For lemma-palea colour, eight different types were detected while for tip colour of lemma, six different types were recorded, suggesting the presence of rich variability in short grain aromatic rices that are conserved in this region. The proposed ‘phenoprinting’ can be an effective descriptor with the unique finger prints generated for each genotype and coupled with molecular (DNA) finger printing, we can discriminate and identify each and every aromatic short grain rice genotype. The proposed system not only help in conservation but also can confer IPR protection to these specialty rices.

Electronic supplementary material

The online version of this article (doi:10.1186/s12898-016-0086-8) contains supplementary material, which is available to authorized users.

Circadian regulation of hormone signaling and plant physiology

The survival and reproduction of plants depend on their ability to cope with a wide range of daily and seasonal environmental fluctuations during their life cycle. Phytohormones are plant growth regulators that are involved in almost every aspect of growth and development as well as plant adaptation to myriad abiotic and biotic conditions. The circadian clock, an endogenous and cell-autonomous biological timekeeper that produces rhythmic outputs with close to 24-h rhythms, provides an adaptive advantage by synchronizing plant physiological and metabolic processes to the external environment. The circadian clock regulates phytohormone biosynthesis and signaling pathways to generate daily rhythms in hormone activity that fine-tune a range of plant processes, enhancing adaptation to local conditions. This review explores our current understanding of the interplay between the circadian clock and hormone signaling pathways.

Genome-scale reconstruction of the metabolic network in Pseudomonas stutzeri A1501

Pseudomonas stutzeri A1501 is an endophytic bacterium capable of nitrogen fixation. This strain has been isolated from the rice rhizosphere and provides the plant with fixed nitrogen and phytohormones. These interesting features encouraged us to study the metabolism of this microorganism at the systems-level. In this work, we present the first genome-scale metabolic model (iPB890) for P. stutzeri, involving 890 genes, 1135 reactions, and 813 metabolites. A combination of automatic and manual approaches was used in the reconstruction process. Briefly, using the metabolic networks of Pseudomonas aeruginosa and Pseudomonas putida as templates, a draft metabolic network of P. stutzeri was reconstructed. Then, the draft network was driven through an iterative and curative process of gap filling. In the next step, the model was evaluated using different experimental data such as specific growth rate, Biolog substrate utilization data and other experimental observations. In most of the evaluation cases, the model was successful in correctly predicting the cellular phenotypes. Thus, we posit that the iPB890 model serves as a suitable platform to explore the metabolism of P. stutzeri.

PPIM: A Protein-Protein Interaction Database for Maize

Maize (Zea mays) is one of the most important crops worldwide. To understand the biological processes underlying various traits of the crop (e.g. yield and response to stress), a detailed protein-protein interaction (PPI) network is highly demanded. Unfortunately, there are very few such PPIs available in the literature. Therefore, in this work, we present the Protein-Protein Interaction Database for Maize (PPIM), which covers 2,762,560 interactions among 14,000 proteins. The PPIM contains not only accurately predicted PPIs but also those molecular interactions collected from the literature. The database is freely available at http://comp-sysbio.org/ppim with a user-friendly powerful interface. We believe that the PPIM resource can help biologists better understand the maize crop.

Gramene: A Resource for Comparative Analysis of Plants Genomes and Pathways

Gramene is an integrated informatics resource for accessing, visualizing, and comparing plant genomes and biological pathways. Originally targeting grasses, Gramene has grown to host annotations for economically important and research model crops, including wheat, potato, tomato, banana, grape, poplar, and Chlamydomonas. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. This chapter outlines system requirements for end users and database hosting, data types and basic navigation within Gramene, and provides examples of how to (1) view a phylogenetic tree for a family of transcription factors, (2) explore genetic variation in the orthologues of a gene with a known trait association, and (3) upload, visualize, and privately share end user data into a new genome browser track.Moreover, this is the first publication describing Gramene's new web interface-intended to provide a simplified portal to the most complete and up-to-date set of plant genome and pathway annotations.

Modeling Rice Metabolism: From Elucidating Environmental Effects on Cellular Phenotype to Guiding Crop Improvement

Crop productivity is severely limited by various biotic and abiotic stresses. Thus, it is highly needed to understand the underlying mechanisms of environmental stress response and tolerance in plants, which could be addressed by systems biology approach. To this end, high-throughput omics profiling and in silico modeling can be considered to explore the environmental effects on phenotypic states and metabolic behaviors of rice crops at the systems level. Especially, the advent of constraint-based metabolic reconstruction and analysis paves a way to characterize the plant cellular physiology under various stresses by combining the mathematical network models with multi-omics data. Rice metabolic networks have been reconstructed since 2013 and currently six such networks are available, where five are at genome-scale. Since their publication, these models have been utilized to systematically elucidate the rice abiotic stress responses and identify agronomic traits for crop improvement. In this review, we summarize the current status of the existing rice metabolic networks and models with their applications. Furthermore, we also highlight future directions of rice modeling studies, particularly stressing how these models can be used to contextualize the affluent multi-omics data that are readily available in the public domain. Overall, we envisage a number of studies in the future, exploiting the available metabolic models to enhance the yield and quality of rice and other food crops.

FragariaCyc: A Metabolic Pathway Database for Woodland Strawberry Fragaria vesca

FragariaCyc is a strawberry-specific cellular metabolic network based on the annotated genome sequence of Fragaria vesca L. ssp. vesca, accession Hawaii 4. It was built on the Pathway-Tools platform using MetaCyc as the reference. The experimental evidences from published literature were used for supporting/editing existing entities and for the addition of new pathways, enzymes, reactions, compounds, and small molecules in the database. To date, FragariaCyc comprises 66 super-pathways, 488 unique pathways, 2348 metabolic reactions, 3507 enzymes, and 2134 compounds. In addition to searching and browsing FragariaCyc, researchers can compare pathways across various plant metabolic networks and analyze their data using Omics Viewer tool. We view FragariaCyc as a resource for the community of researchers working with strawberry and related fruit crops. It can help understanding the regulation of overall metabolism of strawberry plant during development and in response to diseases and abiotic stresses. FragariaCyc is available online at http://pathways.cgrb.oregonstate.edu.

Serotonin attenuates biotic stress and leads to lesion browning caused by a hypersensitive response to Magnaporthe oryzae penetration in rice

The hypersensitive response (HR) of plants is one of the earliest responses to prevent pathogen invasion. A brown dot lesion on a leaf is visual evidence of the HR against the blast fungus Magnaporthe oryzae in rice, but tracking the browning process has been difficult. In this study, we induced the HR in rice cultivars harboring the blast resistance gene Pit by inoculation of an incompatible M. oryzae strain, which generated a unique resistance lesion with a brown ring (halo) around the brown fungal penetration site. Inoculation analysis using a plant harboring Pit but lacking an enzyme that catalyzes tryptamine to serotonin showed that high accumulation of the oxidized form of serotonin was the cause of the browning at the halo and penetration site. Our analysis of the halo browning process in the rice leaf revealed that abscisic acid enhanced biosynthesis of serotonin under light conditions, and serotonin changed to the oxidized form via hydrogen peroxide produced by light. The dramatic increase in serotonin, which has a high antioxidant activity, suppressed leaf damage outside the halo, blocked expansion of the browning area and attenuated inhibition of plant growth. These results suggest that serotonin helps to reduce biotic stress in the plant by acting as a scavenger of oxygen radicals to protect uninfected tissues from oxidative damage caused by the HR. The deposition of its oxide at the HR lesion is observed as lesion browning.

Identification of candidate network hubs involved in metabolic adjustments of rice under drought stress by integrating transcriptome data and genome-scale metabolic network

In this study, we have integrated a rice genome-scale metabolic network and the transcriptome of a drought-tolerant rice line, DK151, to identify the major transcriptional regulators involved in metabolic adjustments necessary for adaptation to drought. This was achieved by examining the differential expressions of transcription factors and metabolic genes in leaf, root and young panicle of rice plants subjected to drought stress during tillering, booting and panicle elongation stages. Critical transcription factors such as AP2/ERF, bZIP, MYB and NAC that control the important nodes in the gene regulatory pathway were identified through correlative analysis of the patterns of spatio-temporal expression and cis-element enrichment. We showed that many of the candidate transcription factors involved in metabolic adjustments were previously linked to phenotypic variation for drought tolerance. This approach represents the first attempt to integrate models of transcriptional regulation and metabolic pathways for the identification of candidate regulatory genes for targeted selection in rice breeding.

Plant Pathway Databases

Pathway databases provide information about the role of chemicals, genes, and gene products in the form of protein or RNA, their interactions leading to the formulation of metabolic, transport, regulatory, and signaling reactions. The reactions can then be tethered by the principle of inputs and outputs of one or more reaction to create pathways. This chapter provides a list of various online databases that carry information about plant pathways and provides a brief overview of how to use the pathway databases such as WikiPathways Plants Portal, MapMan and the cereal crop pathway databases like RiceCyc and MaizeCyc, that were developed using the Pathway Tools software.

Phenolic Phytoalexins in Rice: Biological Functions and Biosynthesis

Phytoalexins are inducible secondary metabolites possessing antimicrobial activity against phytopathogens. Rice produces a wide array of phytoalexins in response to pathogen attacks and environmental stresses. With few exceptions, most phytoalexins identified in rice are diterpenoid compounds. Until very recently, flavonoid sakuranetin was the only known phenolic phytoalexin in rice. However, recent studies have shown that phenylamides are involved in defense against pathogen attacks in rice. Phenylamides are amine-conjugated phenolic acids that are induced by pathogen infections and abiotic stresses including ultra violet (UV) radiation in rice. Stress-induced phenylamides, such as N-trans-cinnamoyltryptamine, N-p-coumaroylserotonin and N-cinnamoyltyramine, have been reported to possess antimicrobial activities against rice bacterial and fungal pathogens, an indication of their direct inhibitory roles against invading pathogens. This finding suggests that phenylamides act as phytoalexins in rice and belong to phenolic phytoalexins along with sakuranetin. Phenylamides also have been implicated in cell wall reinforcement for disease resistance and allelopathy of rice. Synthesis of phenolic phytoalexins is stimulated by phytopathogen attacks and abiotic challenges including UV radiation. Accumulating evidence has demonstrated that biosynthetic pathways including the shikimate, phenylpropanoid and arylmonoamine pathways are coordinately activated for phenolic phytoalexin synthesis, and related genes are induced by biotic and abiotic stresses in rice.

Omics-Based Comparative Transcriptional Profiling of Two Contrasting Rice Genotypes during Early Infestation by Small Brown Planthopper

The small brown planthopper (SBPH) is one of the destructive pests of rice. Although different biochemical pathways that are involved in rice responding to planthopper infestation have been documented, it is unclear which individual metabolic pathways are responsive to planthopper infestation. In this study, an omics-based comparative transcriptional profiling of two contrasting rice genotypes, an SBPH-resistant and an SBPH-susceptible rice line, was assessed for rice individual metabolic pathways responsive to SBPH infestation. When exposed to SBPH, 166 metabolic pathways were differentially regulated; of these, more than one-third of metabolic pathways displayed similar change patterns between these two contrasting rice genotypes; the difference of change pattern between these two contrasting rice genotypes mostly lies in biosynthetic pathways and the obvious difference of change pattern lies in energy metabolism pathways. Combining the Pathway Tools Omics Viewer with the web tool Venn, 21 and 6 metabolic pathways which potentially associated with SBPH resistance and susceptibility, respectively were identified. This study presents an omics-based comparative transcriptional profiling of SBPH-resistant and SBPH-susceptible rice plants during early infestation by SBPH, which will be very informative in studying rice-insect interaction. The results will provide insight into how rice plants respond to early infestation by SBPH from the biochemical pathways perspective.

Unraveling the Light-Specific Metabolic and Regulatory Signatures of Rice through Combined in Silico Modeling and Multiomics Analysis

Light quality is an important signaling component upon which plants orchestrate various morphological processes, including seed germination and seedling photomorphogenesis. However, it is still unclear how plants, especially food crops, sense various light qualities and modulate their cellular growth and other developmental processes. Therefore, in this work, we initially profiled the transcripts of a model crop, rice (Oryza sativa), under four different light treatments (blue, green, red, and white) as well as in the dark. Concurrently, we reconstructed a fully compartmentalized genome-scale metabolic model of rice cells, iOS2164, containing 2,164 unique genes, 2,283 reactions, and 1,999 metabolites. We then combined the model with transcriptome profiles to elucidate the light-specific transcriptional signatures of rice metabolism. Clearly, light signals mediated rice gene expressions, differentially regulating numerous metabolic pathways: photosynthesis and secondary metabolism were up-regulated in blue light, whereas reserve carbohydrates degradation was pronounced in the dark. The topological analysis of gene expression data with the rice genome-scale metabolic model further uncovered that phytohormones, such as abscisate, ethylene, gibberellin, and jasmonate, are the key biomarkers of light-mediated regulation, and subsequent analysis of the associated genes' promoter regions identified several light-specific transcription factors. Finally, the transcriptional control of rice metabolism by red and blue light signals was assessed by integrating the transcriptome and metabolome data with constraint-based modeling. The biological insights gained from this integrative systems biology approach offer several potential applications, such as improving the agronomic traits of food crops and designing light-specific synthetic gene circuits in microbial and mammalian systems.