Gramene: a growing plant comparative genomics resource

Wild and cultivated allele effects on rice phenotypic traits in reciprocal backcross populations between Oryza rufipogon and two cultivars, O. sativa Nipponbare and IR36

A total of four populations of reciprocal backcross recombinant inbred lines were produced from a cross between a wild accession of Oryza rufipogon W630 and two major cultivars, O. sativa Japonica Nipponbare and Indica IR36. Using these populations, quantitative trait locus (QTL) analysis for eight morphological traits (culm length, panicle length, days to heading, panicle shape, pericarp color, hull color, seed shattering and seed awning) was carried out, and the putative QTL regions were compared among the populations. The QTLs with strong allele effects were commonly detected for culm length, panicle shape, pericarp color and hull color in all four populations, and their peak locations were close to the major genes of sd1, Spr3, Rc and Bh4, respectively. For panicle length and days to heading, some QTL regions overlapped between two or three populations. In the case of seed shattering and seed awning, strong wild allele effects at major loci were observed only in the populations with cultivated backgrounds. Since the wild and cultivated alleles have never been evaluated in the reciprocal genetic backgrounds, the present results provide new information on gene effects in breeding and domestication studies.

Antioxidant Green Factories: Toward Sustainable Production of Vitamin E in Plant In Vitro Cultures

Vitamin E is a dietary supplement synthesized only by photosynthetic organisms and, hence, is an essential vitamin for human well-being. Because of the ever-increasing demand for natural vitamin E and limitations in existing synthesis modes, attempts to improve its yield using plant in vitro cultures have gained traction in recent years. With inflating industrial production costs, integrative approaches to conventional bioprocess optimization is the need of the hour for multifold vitamin E productivity enhancement. In this review, we briefly discuss the structure, isomers, and important metabolic routes of biosynthesis for vitamin E in plants. We then emphasize its vital role in human health and its industrial applications and highlight the market demand and supply. We illustrate the advantages of in vitro plant cell/tissue culture cultivation as an alternative to current commercial production platforms for natural vitamin E. We touch upon the conventional vitamin E metabolic pathway engineering strategies, such as single/multigene overexpression and chloroplast engineering. We highlight the recent progress in plant systems biology to rationally identify metabolic bottlenecks and knockout targets in the vitamin E biosynthetic pathway. We then discuss bioprocess optimization strategies for sustainable vitamin E production, including media/process optimization, precursor/elicitor addition, and scale-up to bioreactors. We culminate the review with a short discussion on kinetic modeling to predict vitamin E production in plant cell cultures and suggestions on sustainable green extraction methods of vitamin E for reduced environmental impact. This review will be of interest to a wider research fraternity, including those from industry and academia working in the field of plant cell biology, plant biotechnology, and bioprocess engineering for phytochemical enhancement.

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.

Serial-Omics and Molecular Function Study Provide Novel Insight into Cucumber Variety Improvement

Cucumbers are rich in vitamins and minerals. The cucumber has recently become one of China’s main vegetable crops. More specifically, the adjustment of the Chinese agricultural industry’s structure and rapid economic development have resulted in increases in the planting area allocated to Chinese cucumber varieties and in the number of Chinese cucumber varieties. After complete sequencing of the “Chinese long” genome, the transcriptome, proteome, and metabolome were obtained. Cucumber has a small genome and short growing cycle, and these traits are conducive to the application of molecular breeding techniques for improving fruit quality. Here, we review the developments and applications of molecular markers and genetic maps for cucumber breeding and introduce the functions of gene families from the perspective of genomics, including fruit development and quality, hormone response, resistance to abiotic stress, epitomizing the development of other omics, and relationships among functions.

Genome-wide identification of superoxide dismutase gene families and their expression patterns under low-temperature, salt and osmotic stresses in watermelon and melon

The growth and development of watermelon and melon are affected by abiotic stresses such as cold, salinity and drought. Plant superoxide dismutase (SOD) proteins exerted great effects on plant growth, development and response to abiotic stresses. However, little is known about the characteristics of watermelon and melon SOD gene families and their expression patterns under abiotic stresses. In this study, the genome-wide identification of SOD genes and their expression patterns under abiotic stresses has been done in watermelon and melon. Seven SODs were identified in watermelon and melon, respectively. Chromosome location indicated that the SODs were dispersedly distributed on 4-6 chromosomes. Almost all the SOD proteins contained 300 amino acids or less and the intron numbers of SODs ranged from 5 to 7. On the basis of phylogenetic analysis, the SODs were classified into six sub-groups which was also verified by similar motif composition, gene structure and sub-cellular location. Gene ontology analysis displayed that many SOD proteins participated in binding, catalytic, antioxidant activity and stimulus-response. Cis-regulatory elements related to stresses and hormones were found in the promoters of the SODs. Based on the quantitative real-time PCR, most of CmSOD and ClSOD genes showed obvious up-regulation under low-temperature, NaCl and PEG₆₀₀₀ treatments. The abiotic stress-responsive SOD genes were identified to improve watermelon and melon tolerance against abiotic stresses. This was a preliminary study to describe the genome-wide analysis of SOD gene family in watermelon and melon, and the results would facilitate further study of gene cloning and functional verification of SOD genes response to abiotic stresses in watermelon and melon.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02726-7.

Plant Aquaporins: Diversity, Evolution and Biotechnological Applications

The plasma membrane forms a permeable barrier that separates the cytoplasm from the external environment, defining the physical and chemical limits in each cell in all organisms. The movement of molecules and ions into and out of cells is controlled by the plasma membrane as a critical process for cell stability and survival, maintaining essential differences between the composition of the extracellular fluid and the cytosol. In this process aquaporins (AQPs) figure as important actors, comprising highly conserved membrane proteins that carry water, glycerol and other hydrophilic molecules through biomembranes, including the cell wall and membranes of cytoplasmic organelles. While mammals have 15 types of AQPs described so far (displaying 18 paralogs), a single plant species can present more than 120 isoforms, providing transport of different types of solutes. Such aquaporins may be present in the whole plant or can be associated with different tissues or situations, including biotic and especially abiotic stresses, such as drought, salinity or tolerance to soils rich in heavy metals, for instance. The present review addresses several aspects of plant aquaporins, from their structure, classification, and function, to in silico methodologies for their analysis and identification in transcriptomes and genomes. Aspects of evolution and diversification of AQPs (with a focus on plants) are approached for the first time with the aid of the LCA (Last Common Ancestor) analysis. Finally, the main practical applications involving the use of AQPs are discussed, including patents and future perspectives involving this important protein family.

Systematic discovery of novel and valuable plant gene modules by large-scale RNA-seq samples

Motivation

The complex cellular networks underlying phenotypes are formed by the interacting gene modules. Building and analyzing genome-wide and high-quality Gene Co-expression Networks (GCNs) is useful for uncovering these modules and understanding the phenotypes of an organism.

Results

Using large-scale RNA-seq samples, we constructed high coverage and confident GCNs in two monocot species rice and maize, and two eudicot species Arabidopsis and soybean, and subdivided them into co-expressed gene modules. Taking rice as an example, we discovered many interesting and valuable modules, for instance, pollen-specific modules and starch biosynthesis module. We explored the regulatory mechanism of modules and revealed synergistic effects of gene expression regulation. In addition, we discovered that the modules conserved among plants participated in basic biological processes, whereas the species-specific modules were involved in spatiotemporal-specific processes linking genotypes to phenotypes. Our study suggests gene regulatory relationships and modules relating to cellular activities and agronomic traits in several model and crop plants, and thus providing a valuable data source for plant genetics research and breeding.

Availability and implementation

The analyzed gene expression data, reconstructed GCNs, modules and detailed annotations can be freely downloaded from ftp://47.94.193.106/pub.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genome sequence of the progenitor of wheat A subgenome Triticum urartu

Triticum urartu (diploid, AA) is the progenitor of the A subgenome of tetraploid (Triticum turgidum, AABB) and hexaploid (Triticum aestivum, AABBDD) wheat^1,2. Genomic studies of T. urartu have been useful for investigating the structure, function and evolution of polyploid wheat genomes. Here we report the generation of a high-quality genome sequence of T. urartu by combining bacterial artificial chromosome (BAC)-by-BAC sequencing, single molecule real-time whole-genome shotgun sequencing ³ , linked reads and optical mapping^4,5. We assembled seven chromosome-scale pseudomolecules and identified protein-coding genes, and we suggest a model for the evolution of T. urartu chromosomes. Comparative analyses with genomes of other grasses showed gene loss and amplification in the numbers of transposable elements in the T. urartu genome. Population genomics analysis of 147 T. urartu accessions from across the Fertile Crescent showed clustering of three groups, with differences in altitude and biostress, such as powdery mildew disease. The T. urartu genome assembly provides a valuable resource for studying genetic variation in wheat and related grasses, and promises to facilitate the discovery of genes that could be useful for wheat improvement.

Genome sequence of the progenitor of wheat A subgenome Triticum urartu

Triticum urartu (diploid, AA) is the progenitor of the A subgenome of tetraploid (Triticum turgidum, AABB) and hexaploid (Triticum aestivum, AABBDD) wheat^1,2. Genomic studies of T. urartu have been useful for investigating the structure, function and evolution of polyploid wheat genomes. Here we report the generation of a high-quality genome sequence of T. urartu by combining bacterial artificial chromosome (BAC)-by-BAC sequencing, single molecule real-time whole-genome shotgun sequencing³, linked reads and optical mapping^4,5. We assembled seven chromosome-scale pseudomolecules and identified protein-coding genes, and we suggest a model for the evolution of T. urartu chromosomes. Comparative analyses with genomes of other grasses showed gene loss and amplification in the numbers of transposable elements in the T. urartu genome. Population genomics analysis of 147 T. urartu accessions from across the Fertile Crescent showed clustering of three groups, with differences in altitude and biostress, such as powdery mildew disease. The T. urartu genome assembly provides a valuable resource for studying genetic variation in wheat and related grasses, and promises to facilitate the discovery of genes that could be useful for wheat improvement.

The genome sequence of Triticum urartu, the progenitor of the A subgenome of hexaploid wheat, provides insight into genome duplication during grass evolution.

A comparative synteny analysis tool for target-gene SNP marker discovery: connecting genomics data to breeding in Solanaceae

It is necessary for molecular breeders to overcome the difficulties in applying abundant genomic information to crop breeding. Candidate orthologs would be discovered more efficiently in less-studied crops if the information gained from studies of related crops were used. We developed a comparative analysis tool and web-based genome viewer to identify orthologous genes based synteny as well as sequence similarity between tomato, pepper and potato. The tool has a step-by-step interface with multiple viewing levels to support the easy and accurate exploration of functional orthologs. Furthermore, it provides access to single nucleotide-polymorphism markers from the massive genetic resource pool in order to accelerate the development of molecular markers for candidate orthologs in the Solanaceae. This tool provides a bridge between genome data and breeding by supporting effective marker development, data utilization and communication.

Database URL: http://tgsol.seeders.co.kr/scomp/

Identification of MicroRNA Targets of Capsicum spp. Using MiRTrans-a Trans-Omics Approach

The microRNA (miRNA) can regulate the transcripts that are involved in eukaryotic cell proliferation, differentiation, and metabolism. Especially for plants, our understanding of miRNA targets, is still limited. Early attempts of prediction on sequence alignments have been plagued by enormous false positives. It is helpful to improve target prediction specificity by incorporating the other data sources such as the dependency between miRNA and transcript expression or even cleaved transcripts by miRNA regulations, which are referred to as trans-omics data. In this paper, we developed MiRTrans (Prediction of MiRNA targets by Trans-omics data) to explore miRNA targets by incorporating miRNA sequencing, transcriptome sequencing, and degradome sequencing. MiRTrans consisted of three major steps. First, the target transcripts of miRNAs were predicted by scrutinizing their sequence characteristics and collected as an initial potential targets pool. Second, false positive targets were eliminated if the expression of miRNA and its targets were weakly correlated by lasso regression. Third, degradome sequencing was utilized to capture the miRNA targets by examining the cleaved transcripts that regulated by miRNAs. Finally, the predicted targets from the second and third step were combined by Fisher's combination test. MiRTrans was applied to identify the miRNA targets for Capsicum spp. (i.e., pepper). It can generate more functional miRNA targets than sequence-based predictions by evaluating functional enrichment. MiRTrans identified 58 miRNA-transcript pairs with high confidence from 18 miRNA families conserved in eudicots. Most of these targets were transcription factors; this lent support to the role of miRNA as key regulator in pepper. To our best knowledge, this work is the first attempt to investigate the miRNA targets of pepper, as well as their regulatory networks. Surprisingly, only a small proportion of miRNA-transcript pairs were shared between degradome sequencing and expression dependency predictions, suggesting that miRNA targets predicted by a single technology alone may be prone to report false negatives.

Systems genetics reveals key genetic elements of drought induced gene regulation in diploid potato

In plants, tolerance to drought stress is a result of numerous minor effect loci in which transcriptional regulation contributes significantly to the observed phenotypes. Under severe drought conditions, a major expression quantitative trait loci hotspot was identified on chromosome five in potato. A putative Nuclear factor y subunit C4 was identified as key candidate in the regulatory cascade in response to drought. Further investigation of the eQTL hotspots suggests a role for a putative Homeobox leucine zipper protein 12 in relation to drought in potato. Genes strongly co-expressed with Homeobox leucine zipper protein 12 were plant growth regulators responsive to water deficit stress in Arabidopsis thaliana, implying a possible conserved mechanism. Integrative analysis of genetic, genomic, phenotypic and transcriptomic data provided insights in the downstream functional components of the drought response. The abscisic acid- and environmental stress-inducible protein TAS14 was highly induced by severe drought in potato and acts as a reliable biomarker for the level of stress perceived by the plant. The systems genetics approach supported a role for multiple genes responsive to severe drought stress of Solanum tuberosum. The combination of gene regulatory networks, expression quantitative trait loci mapping and phenotypic analysis proved useful for candidate gene selection.

Exploiting semantics for searching agricultural bibliographic data

Filtering and search mechanisms which permit to identify key bibliographic references are fundamental for researchers. In this paper we propose a fully automatic and semantic method for filtering/searching bibliographic data, which allows users to look for information by specifying simple keyword queries or document queries, i.e. by simply submitting existing documents to the system. The limitations of standard techniques, based on either syntactical text search and on manually assigned descriptors, are overcome by considering the semantics intrinsically associated to the document/query terms; to this aim, we exploit different kinds of external knowledge sources (both general and specific domain dictionaries or thesauri). The proposed techniques have been developed and successfully tested for agricultural bibliographic data, which play a central role to enable researchers and policy makers to retrieve related agricultural and scientific information by using the AGROVOC thesaurus.

MGFD: the maize gene families database

Most gene families are transcription factor (TF) families, which have fundamental roles in almost all biological processes (development, growth and response to environmental factors) and have been employed to manipulate various types of metabolic, developmental and stress response pathways in plants. Maize (Zea mays) is one of the most important cereal crops in the world due its importance to human nutrition and health. Thus, identifying and annotating all the gene families in maize is an important primary step in defining their functions and understanding their roles in the regulation of diverse biological processes. In this study, we identified 96 predicted maize gene families and systematically characterized all 5826 of the genes in those families. We have also developed a comprehensive database of maize gene families (the MGFD). To further explore the functions of these gene families, we extensively annotated the genes, including such basic information as protein sequence features, gene structure, Gene Ontology classifications, phylogenetic relationships and expression profiles. The MGFD has a user-friendly web interface with multiple browse and search functions, as well as data downloading. The MGFD is freely available to users at http://mgfd.ahau.edu.cn/.

Database URL: http://mgfd.ahau.edu.cn/

Determining Phenological Patterns Associated with the Onset of Senescence in a Wheat MAGIC Mapping Population

The appropriate timing of developmental transitions is critical for adapting many crops to their local climatic conditions. Therefore, understanding the genetic basis of different aspects of phenology could be useful in highlighting mechanisms underpinning adaptation, with implications in breeding for climate change. For bread wheat (Triticum aestivum), the transition from vegetative to reproductive growth, the start and rate of leaf senescence and the relative timing of different stages of flowering and grain filling all contribute to plant performance. In this study we screened under Smart house conditions a large, multi-founder "NIAB elite MAGIC" wheat population, to evaluate the genetic elements that influence the timing of developmental stages in European elite varieties. This panel of recombinant inbred lines was derived from eight parents that are or recently have been grown commercially in the UK and Northern Europe. We undertook a detailed temporal phenotypic analysis under Smart house conditions of the population and its parents, to try to identify known or novel Quantitative Trait Loci associated with variation in the timing of key phenological stages in senescence. This analysis resulted in the detection of QTL interactions with novel traits such the time between "half of ear emergence above flag leaf ligule" and the onset of senescence at the flag leaf as well as traits associated with plant morphology such as stem height. In addition, strong correlations between several traits and the onset of senescence of the flag leaf were identified. This work establishes the value of systematically phenotyping genetically unstructured populations to reveal the genetic architecture underlying morphological variation in commercial wheat.

Genome-Wide Identification and Analysis of the VQ Motif-Containing Protein Family in Chinese Cabbage (Brassica rapa L. ssp. Pekinensis)

Previous studies have showed that the VQ motif–containing proteins in Arabidopsis thaliana and Oryza sativa play an important role in plant growth, development, and stress responses. However, little is known about the functions of the VQ genes in Brassica rapa (Chinese cabbage). In this study, we performed genome-wide identification, characterization, and expression analysis of the VQ genes in Chinese cabbage, especially under adverse environment. We identified 57 VQ genes and classified them into seven subgroups (I–VII), which were dispersedly distributed on chromosomes 1 to 10. The expansion of these genes mainly contributed to segmental and tandem duplication. Fifty-four VQ genes contained no introns and 50 VQ proteins were less than 300 amino acids in length. Quantitative real-time PCR showed that the VQ genes were differentially expressed in various tissues and during different abiotic stresses and plant hormone treatments. This study provides a comprehensive overview of Chinese cabbage VQ genes and will benefit the molecular breeding for resistance to stresses and disease, as well as further studies on the biological functions of the VQ proteins.

Core Promoter Plasticity Between Maize Tissues and Genotypes Contrasts with Predominance of Sharp Transcription Initiation Sites

Core promoters are crucial for gene regulation, providing blueprints for the assembly of transcriptional machinery at transcription start sites (TSSs). Empirically, TSSs define the coordinates of core promoters and other regulatory sequences. Thus, experimental TSS identification provides an essential step in the characterization of promoters and their features. Here, we describe the application of CAGE (cap analysis of gene expression) to identify genome-wide TSSs used in root and shoot tissues of two maize (Zea mays) inbred lines (B73 and Mo17). Our studies indicate that most TSS clusters are sharp in maize, similar to mice, but distinct from Arabidopsis thaliana, Drosophila melanogaster, or zebra fish, in which a majority of genes have broad-shaped TSS clusters. We established that ∼38% of maize promoters are characterized by a broader TATA-motif consensus, and this motif is significantly enriched in genes with sharp TSSs. A noteworthy plasticity in TSS usage between tissues and inbreds was uncovered, with ∼1500 genes showing significantly different dominant TSSs, sometimes affecting protein sequence by providing alternate translation initiation codons. We experimentally characterized instances in which this differential TSS utilization results in protein isoforms with additional domains or targeted to distinct subcellular compartments. These results provide important insights into TSS selection and gene expression in an agronomically important crop.

Genomic prediction of seedling root length in maize (Zea mays L.)

Genotypes with extreme phenotypes are valuable for studying 'difficult' quantitative traits. Genomic prediction (GP) might allow the identification of such extremes by phenotyping a training population of limited size and predicting genotypes with extreme phenotypes in large sequences of germplasm collections. We tested this approach employing seedling root traits in maize and the extensively genotyped Ames Panel. A training population made up of 384 inbred lines from the Ames Panel was phenotyped by extracting root traits from images using the software program aria. A ridge regression best linear unbiased prediction strategy was used to train a GP model. Genomic estimated breeding values for the trait 'total root length' (TRL) were predicted for 2431 inbred lines, which had previously been genotyped by sequencing. Selections were made for 100 extreme TRL lines and those with the predicted longest or shortest TRL were validated for TRL and other root traits. The two predicted extreme groups with regard to TRL were significantly different (P = 0.0001). The difference in predicted means for TRL between groups was 145.1 cm and 118.7 cm for observed means, which were significantly different (P = 0.001). The accuracy of predicting the rank between 1 and 200 of the validation population based on TRL (longest to shortest) was determined using a Spearman correlation to be ρ = 0.55. Taken together, our results support the idea that GP may be a useful approach for identifying the most informative genotypes in sequenced germplasm collections to facilitate experiments for quantitative inherited traits.

Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future

"Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information. Although, in general, the notion of capturing complex ideas using images is very appealing, would 1000 words be enough to describe the unknown in a research field such as the life sciences? Life sciences is one of the biggest generators of enormous datasets, mainly as a result of recent and rapid technological advances; their complexity can make these datasets incomprehensible without effective visualization methods. Here we discuss the past, present and future of genomic and systems biology visualization. We briefly comment on many visualization and analysis tools and the purposes that they serve. We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.

Heterosis in early maize ear inflorescence development: a genome-wide transcription analysis for two maize inbred lines and their hybrid

Heterosis, or hybrid vigor, contributes to superior agronomic performance of hybrids compared to their inbred parents. Despite its importance, little is known about the genetic and molecular basis of heterosis. Early maize ear inflorescences formation affects grain yield, and are thus an excellent model for molecular mechanisms involved in heterosis. To determine the parental contributions and their regulation during maize ear-development-genesis, we analyzed genome-wide digital gene expression profiles in two maize elite inbred lines (B73 and Mo17) and their F₁ hybrid using deep sequencing technology. Our analysis revealed 17,128 genes expressed in these three genotypes and 22,789 genes expressed collectively in the present study. Approximately 38% of the genes were differentially expressed in early maize ear inflorescences from heterotic cross, including many transcription factor genes and some presence/absence variations (PAVs) genes, and exhibited multiple modes of gene action. These different genes showing differential expression patterns were mainly enriched in five cellular component categories (organelle, cell, cell part, organelle part and macromolecular complex), five molecular function categories (structural molecule activity, binding, transporter activity, nucleic acid binding transcription factor activity and catalytic activity), and eight biological process categories (cellular process, metabolic process, biological regulation, regulation of biological process, establishment of localization, cellular component organization or biogenesis, response to stimulus and localization). Additionally, a significant number of genes were expressed in only one inbred line or absent in both inbred lines. Comparison of the differences of modes of gene action between previous studies and the present study revealed only a small number of different genes had the same modes of gene action in both maize seedlings and ear inflorescences. This might be an indication that in different tissues or developmental stages, different global expression patterns prevail, which might nevertheless be related to heterosis. Our results support the hypotheses that multiple molecular mechanisms (dominance and overdominance modes) contribute to heterosis.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases

The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible database describing metabolic pathways and enzymes from all domains of life. MetaCyc pathways are experimentally determined, mostly small-molecule metabolic pathways and are curated from the primary scientific literature. MetaCyc contains >2100 pathways derived from >37 000 publications, and is the largest curated collection of metabolic pathways currently available. BioCyc (BioCyc.org) is a collection of >3000 organism-specific Pathway/Genome Databases (PGDBs), each containing the full genome and predicted metabolic network of one organism, including metabolites, enzymes, reactions, metabolic pathways, predicted operons, transport systems and pathway-hole fillers. Additions to BioCyc over the past 2 years include YeastCyc, a PGDB for Saccharomyces cerevisiae, and 891 new genomes from the Human Microbiome Project. The BioCyc Web site offers a variety of tools for querying and analysis of PGDBs, including Omics Viewers and tools for comparative analysis. New developments include atom mappings in reactions, a new representation of glycan degradation pathways, improved compound structure display, better coverage of enzyme kinetic data, enhancements of the Web Groups functionality, improvements to the Omics viewers, a new representation of the Enzyme Commission system and, for the desktop version of the software, the ability to save display states.

Spatio-temporal transcript profiling of rice roots and shoots in response to phosphate starvation and recovery

Using rice (Oryza sativa) as a model crop species, we performed an in-depth temporal transcriptome analysis, covering the early and late stages of Pi deprivation as well as Pi recovery in roots and shoots, using next-generation sequencing. Analyses of 126 paired-end RNA sequencing libraries, spanning nine time points, provided a comprehensive overview of the dynamic responses of rice to Pi stress. Differentially expressed genes were grouped into eight sets based on their responses to Pi starvation and recovery, enabling the complex signaling pathways involved in Pi homeostasis to be untangled. A reference annotation-based transcript assembly was also generated, identifying 438 unannotated loci that were differentially expressed under Pi starvation. Several genes also showed induction of unannotated splice isoforms under Pi starvation. Among these, PHOSPHATE2 (PHO2), a key regulator of Pi homeostasis, displayed a Pi starvation-induced isoform, which was associated with increased translation activity. In addition, microRNA (miRNA) expression profiles after long-term Pi starvation in roots and shoots were assessed, identifying 20 miRNA families that were not previously associated with Pi starvation, such as miR6250. In this article, we present a comprehensive spatio-temporal transcriptome analysis of plant responses to Pi stress, revealing a large number of potential key regulators of Pi homeostasis in plants.

Controlled vocabularies for plant anatomical parts optimized for use in data analysis tools and for cross-species studies

BACKGROUND

It is generally accepted that controlled vocabularies are necessary to systematically integrate data from various sources. During the last decade, several plant ontologies have been developed, some of which are community specific or were developed for a particular purpose. In most cases, the practical application of these ontologies has been limited to systematically storing experimental data. Due to technical constraints, complex data structures and term redundancies, it has been difficult to apply them directly into analysis tools.

RESULTS

Here, we describe a simplified and cross-species compatible set of controlled vocabularies for plant anatomy, focussing mainly on monocotypledonous and dicotyledonous crop and model plants. Their content was designed primarily for their direct use in graphical visualization tools. Specifically, we created annotation vocabularies that can be understood by non-specialists, are minimally redundant, simply structured, have low tree depth, and we tested them practically in the frame of Genevestigator.

CONCLUSIONS

The application of the proposed ontologies enabled the aggregation of data from hundreds of experiments to visualize gene expression across tissue types. It also facilitated the comparison of expression across species. The described controlled vocabularies are maintained by a dedicated curation team and are available upon request.

A global view of transcriptome dynamics during flower development in chickpea by deep sequencing

Measurement of gene expression can provide important clues about gene function and molecular basis of developmental processes. Here, we have analysed the chickpea transcriptome in vegetative and flower tissues by exploiting the potential of high-throughput sequencing to measure gene expression. We mapped more than 295 million reads to quantify the transcript abundance during flower development. We detected the expression of more than 90% genes in at least one tissue analysed. We found quite a large number of genes were differentially expressed during flower development as compared to vegetative tissues. Further, we identified several genes expressed in a stage-specific manner. Various transcription factor families and metabolic pathways involved in flower development were elucidated. The members of MADS-box family were most represented among the transcription factor genes up-regulated during various stages of flower development. The abundant expression of several well-known genes implicated in flower development in chickpea flower development stages confirmed our results. In addition, we detected the expression specificities of lineage-specific genes during flower development. The expression data presented in this study is the most comprehensive dataset available for chickpea as of now and will serve as resource for unraveling the functions of many specific genes involved in flower development in chickpea and other legumes.

Reannotation and extended community resources for the genome of the non-seed plant Physcomitrella patens provide insights into the evolution of plant gene structures and functions

Background

The moss Physcomitrella patens as a model species provides an important reference for early-diverging lineages of plants and the release of the genome in 2008 opened the doors to genome-wide studies. The usability of a reference genome greatly depends on the quality of the annotation and the availability of centralized community resources. Therefore, in the light of accumulating evidence for missing genes, fragmentary gene structures, false annotations and a low rate of functional annotations on the original release, we decided to improve the moss genome annotation.

Results

Here, we report the complete moss genome re-annotation (designated V1.6) incorporating the increased transcript availability from a multitude of developmental stages and tissue types. We demonstrate the utility of the improved P. patens genome annotation for comparative genomics and new extensions to the cosmoss.org resource as a central repository for this plant “flagship” genome. The structural annotation of 32,275 protein-coding genes results in 8387 additional loci including 1456 loci with known protein domains or homologs in Plantae. This is the first release to include information on transcript isoforms, suggesting alternative splicing events for at least 10.8% of the loci. Furthermore, this release now also provides information on non-protein-coding loci. Functional annotations were improved regarding quality and coverage, resulting in 58% annotated loci (previously: 41%) that comprise also 7200 additional loci with GO annotations. Access and manual curation of the functional and structural genome annotation is provided via the http://www.cosmoss.org model organism database.

Conclusions

Comparative analysis of gene structure evolution along the green plant lineage provides novel insights, such as a comparatively high number of loci with 5’-UTR introns in the moss. Comparative analysis of functional annotations reveals expansions of moss house-keeping and metabolic genes and further possibly adaptive, lineage-specific expansions and gains including at least 13% orphan genes.

Silicon era of carbon-based life: application of genomics and bioinformatics in crop stress research

Abiotic and biotic stresses lead to massive reprogramming of different life processes and are the major limiting factors hampering crop productivity. Omics-based research platforms allow for a holistic and comprehensive survey on crop stress responses and hence may bring forth better crop improvement strategies. Since high-throughput approaches generate considerable amounts of data, bioinformatics tools will play an essential role in storing, retrieving, sharing, processing, and analyzing them. Genomic and functional genomic studies in crops still lag far behind similar studies in humans and other animals. In this review, we summarize some useful genomics and bioinformatics resources available to crop scientists. In addition, we also discuss the major challenges and advancements in the "-omics" studies, with an emphasis on their possible impacts on crop stress research and crop improvement.

The potential of C4 grasses for cellulosic biofuel production

With the advent of biorefinery technologies enabling plant biomass to be processed into biofuel, many researchers set out to study and improve candidate biomass crops. Many of these candidates are C4 grasses, characterized by a high productivity and resource use efficiency. In this review the potential of five C4 grasses as lignocellulosic feedstock for biofuel production is discussed. These include three important field crops-maize, sugarcane and sorghum-and two undomesticated perennial energy grasses-miscanthus and switchgrass. Although all these grasses are high yielding, they produce different products. While miscanthus and switchgrass are exploited exclusively for lignocellulosic biomass, maize, sorghum, and sugarcane are dual-purpose crops. It is unlikely that all the prerequisites for the sustainable and economic production of biomass for a global cellulosic biofuel industry will be fulfilled by a single crop. High and stable yields of lignocellulose are required in diverse environments worldwide, to sustain a year-round production of biofuel. A high resource use efficiency is indispensable to allow cultivation with minimal inputs of nutrients and water and the exploitation of marginal soils for biomass production. Finally, the lignocellulose composition of the feedstock should be optimized to allow its efficient conversion into biofuel and other by-products. Breeding for these objectives should encompass diverse crops, to meet the demands of local biorefineries and provide adaptability to different environments. Collectively, these C4 grasses are likely to play a central role in the supply of lignocellulose for the cellulosic ethanol industry. Moreover, as these species are evolutionary closely related, advances in each of these crops will expedite improvements in the other crops. This review aims to provide an overview of their potential, prospects and research needs as lignocellulose feedstocks for the commercial production of biofuel.

Genome-wide identification and analysis of the B3 superfamily of transcription factors in Brassicaceae and major crop plants

The plant-specific B3 superfamily of transcription factors has diverse functions in plant growth and development. Using a genome-wide domain analysis, we identified 92, 187, 58, 90, 81, 55, and 77 B3 transcription factor genes in the sequenced genome of Arabidopsis, Brassica rapa, castor bean (Ricinus communis), cocoa (Theobroma cacao), soybean (Glycine max), maize (Zea mays), and rice (Oryza sativa), respectively. The B3 superfamily has substantially expanded during the evolution in eudicots particularly in Brassicaceae, as compared to monocots in the analysis. We observed domain duplication in some of these B3 proteins, forming more complex domain architectures than currently understood. We found that the length of B3 domains exhibits a large variation, which may affect their exact number of α-helices and β-sheets in the core structure of B3 domains, and possibly have functional implications. Analysis of the public microarray data indicated that most of the B3 gene pairs encoding Arabidopsis-rice orthologs are preferentially expressed in different tissues, suggesting their different roles in these two species. Using ESTs in crops, we identified many B3 genes preferentially expressed in reproductive tissues. In a sequence-based quantitative trait loci analysis in rice and maize, we have found many B3 genes associated with traits such as grain yield, seed weight and number, and protein content. Our results provide a framework for future studies into the function of B3 genes in different phases of plant development, especially the ones related to traits in major crops.

PlantGSEA: a gene set enrichment analysis toolkit for plant community

Gene Set Enrichment Analysis (GSEA) is a powerful method for interpreting biological meaning of a list of genes by computing the overlaps with various previously defined gene sets. As one of the most widely used annotations for defining gene sets, Gene Ontology (GO) system has been used in many enrichment analysis tools. EasyGO and agriGO, two GO enrichment analysis toolkits developed by our laboratory, have gained extensive usage and citations since their releases because of their effective performance and consistent maintenance. Responding to the increasing demands of more comprehensive analysis from the users, we developed a web server as an important component of our bioinformatics analysis toolkit, named PlantGSEA, which is based on GSEA method and mainly focuses on plant organisms. In PlantGSEA, 20 290 defined gene sets deriving from different resources were collected and used for GSEA analysis. The PlantGSEA currently supports gene locus IDs and Affymatrix microarray probe set IDs from four plant model species (Arabidopsis thaliana, Oryza sativa, Zea mays and Gossypium raimondii). The PlantGSEA is an efficient and user-friendly web server, and now it is publicly accessible at http://structuralbiology.cau.edu.cn/PlantGSEA.

Clever generation of rich SPARQL queries from annotated relational schema: application to Semantic Web Service creation for biological databases

Background

In recent years, a large amount of “-omics” data have been produced. However, these data are stored in many different species-specific databases that are managed by different institutes and laboratories. Biologists often need to find and assemble data from disparate sources to perform certain analyses. Searching for these data and assembling them is a time-consuming task. The Semantic Web helps to facilitate interoperability across databases. A common approach involves the development of wrapper systems that map a relational database schema onto existing domain ontologies. However, few attempts have been made to automate the creation of such wrappers.

Results

We developed a framework, named BioSemantic, for the creation of Semantic Web Services that are applicable to relational biological databases. This framework makes use of both Semantic Web and Web Services technologies and can be divided into two main parts: (i) the generation and semi-automatic annotation of an RDF view; and (ii) the automatic generation of SPARQL queries and their integration into Semantic Web Services backbones. We have used our framework to integrate genomic data from different plant databases.

Conclusions

BioSemantic is a framework that was designed to speed integration of relational databases. We present how it can be used to speed the development of Semantic Web Services for existing relational biological databases. Currently, it creates and annotates RDF views that enable the automatic generation of SPARQL queries. Web Services are also created and deployed automatically, and the semantic annotations of our Web Services are added automatically using SAWSDL attributes. BioSemantic is downloadable at http://southgreen.cirad.fr/?q=content/Biosemantic.

The plant ontology as a tool for comparative plant anatomy and genomic analyses

The Plant Ontology (PO; http://www.plantontology.org/) is a publicly available, collaborative effort to develop and maintain a controlled, structured vocabulary ('ontology') of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded to include all green plants. The PO was the first multispecies anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontologies that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. As of Release #18 (July 2012), there are about 2.2 million annotations linking PO terms to >110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and quantitative trait loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs.

Current challenges in de novo plant genome sequencing and assembly

Genome sequencing is now affordable, but assembling plant genomes de novo remains challenging. We assess the state of the art of assembly and review the best practices for the community.

Current challenges in de novo plant genome sequencing and assembly

Genome sequencing is now affordable, but assembling plant genomes de novo remains challenging. We assess the state of the art of assembly and review the best practices for the community.

Cis-regulatory signatures of orthologous stress-associated bZIP transcription factors from rice, sorghum and Arabidopsis based on phylogenetic footprints

Background

The potential contribution of upstream sequence variation to the unique features of orthologous genes is just beginning to be unraveled. A core subset of stress-associated bZIP transcription factors from rice (Oryza sativa) formed ten clusters of orthologous groups (COG) with genes from the monocot sorghum (Sorghum bicolor) and dicot Arabidopsis (Arabidopsis thaliana). The total cis-regulatory information content of each stress-associated COG was examined by phylogenetic footprinting to reveal ortholog-specific, lineage-specific and species-specific conservation patterns.

Results

The most apparent pattern observed was the occurrence of spatially conserved ‘core modules’ among the COGs but not among paralogs. These core modules are comprised of various combinations of two to four putative transcription factor binding site (TFBS) classes associated with either developmental or stress-related functions. Outside the core modules are specific stress (ABA, oxidative, abiotic, biotic) or organ-associated signals, which may be functioning as ‘regulatory fine-tuners’ and further define lineage-specific and species-specific cis-regulatory signatures. Orthologous monocot and dicot promoters have distinct TFBS classes involved in disease and oxidative-regulated expression, while the orthologous rice and sorghum promoters have distinct combinations of root-specific signals, a pattern that is not particularly conserved in Arabidopsis.

Conclusions

Patterns of cis-regulatory conservation imply that each ortholog has distinct signatures, further suggesting that they are potentially unique in a regulatory context despite the presumed conservation of broad biological function during speciation. Based on the observed patterns of conservation, we postulate that core modules are likely primary determinants of basal developmental programming, which may be integrated with and further elaborated by additional intrinsic or extrinsic signals in conjunction with lineage-specific or species-specific regulatory fine-tuners. This synergy may be critical for finer-scale spatio-temporal regulation, hence unique expression profiles of homologous transcription factors from different species with distinct zones of ecological adaptation such as rice, sorghum and Arabidopsis. The patterns revealed from these comparisons set the stage for further empirical validation by functional genomics.

BAR expressolog identification: expression profile similarity ranking of homologous genes in plant species

Large numbers of sequences are now readily available for many plant species, allowing easy identification of homologous genes. However, orthologous gene identification across multiple species is made difficult by evolutionary events such as whole-genome or segmental duplications. Several developmental atlases of gene expression have been produced in the past couple of years, and it may be possible to use these transcript abundance data to refine ortholog predictions. In this study, clusters of homologous genes between seven plant species - Arabidopsis, soybean, Medicago truncatula, poplar, barley, maize and rice - were identified. Following this, a pipeline to rank homologs within gene clusters by both sequence and expression profile similarity was devised by determining equivalent tissues between species, with the best expression profile match being termed the 'expressolog'. Five electronic fluorescent pictograph (eFP) browsers were produced as part of this effort, to aid in visualization of gene expression data and to complement existing eFP browsers at the Bio-Array Resource (BAR). Within the eFP browser framework, these expression profile similarity rankings were incorporated into an Expressolog Tree Viewer to allow cross-species homolog browsing by both sequence and expression pattern similarity. Global analyses showed that orthologs with the highest sequence similarity do not necessarily exhibit the highest expression pattern similarity. Other orthologs may show different expression patterns, indicating that such genes may require re-annotation or more specific annotation. Ultimately, it is envisaged that this pipeline will aid in improvement of the functional annotation of genes and translational plant research.

Linking microarray data to QTLs highlights new genes related to Al tolerance in maize

The presence of aluminum (Al) is one of the main factors limiting crop yield in Brazil and worldwide. Plant responses to Al are complex, and the use of techniques such as microarrays can facilitate their comprehension. In a previous work, we evaluated the transcriptome of two maize lines, Cat100-6 and S1587-17, after growing the plants for 1 or 3 days in acid soil (pH 4.1) or alkaline soil with Ca(OH)₂ (pH 5.5), and we identified genes that likely contribute to Al tolerance. The mapping of these genes to the chromosomes allowed the identification of the genes that are localized in maize QTLs previously reported in the literature as associated with the tolerant phenotype. We were able to map genes encoding proteins possibly involved with acid soil tolerance, such as the ones encoding an RNA binding protein, a protease inhibitor, replication factors, xyloglucan endotransglycosylase and cyclins, inside QTLs known to be important for the Al-tolerant phenotype.

AlliumMap-A comparative genomics resource for cultivated Allium vegetables

Background

Vegetables of the genus Allium are widely consumed but remain poorly understood genetically. Genetic mapping has been conducted in intraspecific crosses of onion (Allium cepa L.), A. fistulosum and interspecific crosses between A. roylei and these two species, but it has not been possible to access genetic maps and underlying data from these studies easily.

Description

An online comparative genomics database, AlliumMap, has been developed based on the GMOD CMap tool at http://alliumgenetics.org. It has been populated with curated data linking genetic maps with underlying markers and sequence data from multiple studies. It includes data from multiple onion mapping populations as well as the most closely related species A. roylei and A. fistulosum. Further onion EST-derived markers were evaluated in the A. cepa x A. roylei interspecific population, enabling merging of the AFLP-based maps. In addition, data concerning markers assigned in multiple studies to the Allium physical map using A. cepa-A. fistulosum alien monosomic addition lines have been compiled. The compiled data reveal extensive synteny between onion and A. fistulosum.

Conclusions

The database provides the first online resource providing genetic map and marker data from multiple Allium species and populations. The additional markers placed on the interspecific Allium map confirm the value of A. roylei as a valuable bridge between the genetics of onion and A. fistulosum and as a means to conduct efficient mapping of expressed sequence markers in Allium. The data presented suggest that comparative approaches will be valuable for genetic and genomic studies of onion and A. fistulosum. This online resource will provide a valuable means to integrate genetic and sequence-based explorations of Allium genomes.

Dissection of genotype-phenotype associations in rice grains using metabolome quantitative trait loci analysis

A comprehensive and large-scale metabolome quantitative trait loci (mQTL) analysis was performed to investigate the genetic backgrounds associated with metabolic phenotypes in rice grains. The metabolome dataset consisted of 759 metabolite signals obtained from the grains of 85 lines of rice (Oryza sativa, Sasanishiki × Habataki back-crossed inbred lines). Metabolome analysis was performed using four mass spectrometry pipelines to enhance detection of different classes of metabolites. This mQTL analysis of a wide range of metabolites highlighted an uneven distribution of 802 mQTLs on the rice genome, as well as different modes of metabolic trait (m-trait) control among various types of metabolites. The levels of most metabolites within rice grains were highly sensitive to environmental factors, but only weakly associated with mQTLs. Coordinated control was observed for several groups of metabolites, such as amino acids linked to the mQTL hotspot on chromosome 3. For flavonoids, m-trait variation among the experimental lines was tightly governed by genetic factors that alter the glycosylation of flavones. Many loci affecting levels of metabolites were detected by QTL analysis, and plausible gene candidates were evaluated by in silico analysis. Several mQTLs profoundly influenced metabolite levels, providing insight into the control of rice metabolism. The genomic region and genes potentially responsible for the biosynthesis of apigenin-6,8-di-C-α-l-arabinoside are presented as an example of a critical mQTL identified by the analysis.

Alteration of gene expression profile in maize infected with a double-stranded RNA fijivirus associated with symptom development

Maize rough dwarf disease caused by Rice black-streaked dwarf virus (RBSDV) is a major viral disease in China. It has been suggested that the viral infection of plants might cause distinct disease symptoms through the inhibition or activation of host gene transcription. We scanned the gene expression profile of RBSDV-infected maize through oligomer-based microarrays to reveal possible expression changes associated with symptom development. Our results demonstrate that various resistance-related maize genes and cell wall- and development-related genes, such as those for cellulose synthesis, are among the genes whose expression is dramatically altered. These results could aid in research into new strategies to protect cereal crops against viruses, and reveal the molecular mechanisms of development of specific symptoms in rough dwarf-related diseases.

Metabolomics in agriculture

Metabolome refers to the complete set of metabolites synthesized through a series of multiple enzymatic steps from various biochemical pathways processing the information encrypted in the plant genome. Knowledge about synthesis and regulation of various plant metabolic substances has improved substantially with availability of Omics data originating from sequencing of plant genomes. Metabolic profiling of crops is increasingly becoming popular in assessing plant phenotypes and genetic diversity. Metabolic compositional changes vividly reflect the changes occurring during plant growth, development, and in response to stress. Hence, study of plant metabolic pathways, the interconnections between them in context of systems biology is increasingly becoming popular in identification of candidate genes. The present article reviews recent developments in analysis of plant metabolomics, available bioinformatics techniques and databases employed for comparative pathway analysis, metabolic QTLs, and their application in plants.

Designing a transcriptome next-generation sequencing project for a nonmodel plant species

The application of next-generation sequencing (NGS) to transcriptomics, commonly called RNA-seq, allows the nearly complete characterization of transcriptomic events occurring in a specific tissue. It has proven particularly useful in nonmodel species, which often lack the resources available for sequenced organisms. Mainly, RNA-seq does not require a reference genome to gain useful transcriptomic information. In this review, the application of RNA-seq to nonmodel plant species will be addressed. Important experimental considerations from presequencing issues to postsequencing analysis, including sample and platform selection, and useful bioinformatics tools for assembly and data analysis, are covered. Methods of assembling RNA-seq data and analyses commonly performed with RNA-seq data, including single nucleotide polymorphism detection and analysis of differential expression, are explored. In addition, studies that have used RNA-seq to elucidate nonmodel plant transcriptomics are highlighted.

The Biofuel Feedstock Genomics Resource: a web-based portal and database to enable functional genomics of plant biofuel feedstock species

Major feedstock sources for future biofuel production are likely to be high biomass producing plant species such as poplar, pine, switchgrass, sorghum and maize. One active area of research in these species is genome-enabled improvement of lignocellulosic biofuel feedstock quality and yield. To facilitate genomic-based investigations in these species, we developed the Biofuel Feedstock Genomic Resource (BFGR), a database and web-portal that provides high-quality, uniform and integrated functional annotation of gene and transcript assembly sequences from species of interest to lignocellulosic biofuel feedstock researchers. The BFGR includes sequence data from 54 species and permits researchers to view, analyze and obtain annotation at the gene, transcript, protein and genome level. Annotation of biochemical pathways permits the identification of key genes and transcripts central to the improvement of lignocellulosic properties in these species. The integrated nature of the BFGR in terms of annotation methods, orthologous/paralogous relationships and linkage to seven species with complete genome sequences allows comparative analyses for biofuel feedstock species with limited sequence resources.

Database URL:http://bfgr.plantbiology.msu.edu

Phytozome: a comparative platform for green plant genomics

The number of sequenced plant genomes and associated genomic resources is growing rapidly with the advent of both an increased focus on plant genomics from funding agencies, and the application of inexpensive next generation sequencing. To interact with this increasing body of data, we have developed Phytozome (http://www.phytozome.net), a comparative hub for plant genome and gene family data and analysis. Phytozome provides a view of the evolutionary history of every plant gene at the level of sequence, gene structure, gene family and genome organization, while at the same time providing access to the sequences and functional annotations of a growing number (currently 25) of complete plant genomes, including all the land plants and selected algae sequenced at the Joint Genome Institute, as well as selected species sequenced elsewhere. Through a comprehensive plant genome database and web portal, these data and analyses are available to the broader plant science research community, providing powerful comparative genomics tools that help to link model systems with other plants of economic and ecological importance.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

The MetaCyc database (http://metacyc.org/) provides a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. MetaCyc contains more than 1800 pathways derived from more than 30 000 publications, and is the largest curated collection of metabolic pathways currently available. Most reactions in MetaCyc pathways are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes and literature citations. BioCyc (http://biocyc.org/) is a collection of more than 1700 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference database, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs contain additional features, including predicted operons, transport systems and pathway-hole fillers. The BioCyc website and Pathway Tools software offer many tools for querying and analysis of PGDBs, including Omics Viewers and comparative analysis. New developments include a zoomable web interface for diagrams; flux-balance analysis model generation from PGDBs; web services; and a new tool called Web Groups.

Next generation functional proteomics in non-model plants: A survey on techniques and applications for the analysis of protein complexes and post-translational modifications

The congruent development of computational technology, bioinformatics and analytical instrumentation makes proteomics ready for the next leap. Present-day state of the art proteomics grew from a descriptive method towards a full stake holder in systems biology. High throughput and genome wide studies are now made at the functional level. These include quantitative aspects, functional aspects with respect to protein interactions as well as post translational modifications and advanced computational methods that aid in predicting protein function and mapping these functionalities across the species border. In this review an overview is given of the current status of these aspects in plant studies with special attention to non-genomic model plants.

A survey of metabolic databases emphasizing the MetaCyc family

Thanks to the confluence of genome sequencing and bioinformatics, the number of metabolic databases has expanded from a handful in the mid-1990s to several thousand today. These databases lie within distinct families that have common ancestry and common attributes. The main families are the MetaCyc, KEGG, Reactome, Model SEED, and BiGG families. We survey these database families, as well as important individual metabolic databases, including multiple human metabolic databases. The MetaCyc family is described in particular detail. It contains well over 1,000 databases, including highly curated databases for Escherichia coli, Saccharomyces cerevisiae, Mus musculus, and Arabidopsis thaliana. These databases are available through a number of web sites that offer a range of software tools for querying and visualizing metabolic networks. These web sites also provide multiple tools for analysis of gene expression and metabolomics data, including visualization of those datasets on metabolic network diagrams and over-representation analysis of gene sets and metabolite sets.

Rice-Map: a new-generation rice genome browser

Background

The concurrent release of rice genome sequences for two subspecies (Oryza sativa L. ssp. japonica and Oryza sativa L. ssp. indica) facilitates rice studies at the whole genome level. Since the advent of high-throughput analysis, huge amounts of functional genomics data have been delivered rapidly, making an integrated online genome browser indispensable for scientists to visualize and analyze these data. Based on next-generation web technologies and high-throughput experimental data, we have developed Rice-Map, a novel genome browser for researchers to navigate, analyze and annotate rice genome interactively.

Description

More than one hundred annotation tracks (81 for japonica and 82 for indica) have been compiled and loaded into Rice-Map. These pre-computed annotations cover gene models, transcript evidences, expression profiling, epigenetic modifications, inter-species and intra-species homologies, genetic markers and other genomic features. In addition to these pre-computed tracks, registered users can interactively add comments and research notes to Rice-Map as User-Defined Annotation entries. By smoothly scrolling, dragging and zooming, users can browse various genomic features simultaneously at multiple scales. On-the-fly analysis for selected entries could be performed through dedicated bioinformatic analysis platforms such as WebLab and Galaxy. Furthermore, a BioMart-powered data warehouse "Rice Mart" is offered for advanced users to fetch bulk datasets based on complex criteria.

Conclusions

Rice-Map delivers abundant up-to-date japonica and indica annotations, providing a valuable resource for both computational and bench biologists. Rice-Map is publicly accessible at http://www.ricemap.org/, with all data available for free downloading.

Exploration of plant genomes in the FLAGdb++ environment

BACKGROUND

In the contexts of genomics, post-genomics and systems biology approaches, data integration presents a major concern. Databases provide crucial solutions: they store, organize and allow information to be queried, they enhance the visibility of newly produced data by comparing them with previously published results, and facilitate the exploration and development of both existing hypotheses and new ideas.

RESULTS

The FLAGdb++ information system was developed with the aim of using whole plant genomes as physical references in order to gather and merge available genomic data from in silico or experimental approaches. Available through a JAVA application, original interfaces and tools assist the functional study of plant genes by considering them in their specific context: chromosome, gene family, orthology group, co-expression cluster and functional network. FLAGdb++ is mainly dedicated to the exploration of large gene groups in order to decipher functional connections, to highlight shared or specific structural or functional features, and to facilitate translational tasks between plant species (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa and Vitis vinifera).

CONCLUSION

Combining original data with the output of experts and graphical displays that differ from classical plant genome browsers, FLAGdb++ presents a powerful complementary tool for exploring plant genomes and exploiting structural and functional resources, without the need for computer programming knowledge. First launched in 2002, a 15th version of FLAGdb++ is now available and comprises four model plant genomes and over eight million genomic features.