GabiPD: the GABI primary database--a plant integrative 'omics' database

Integrated transcriptomic and metabolomic analyses reveal key genes controlling flavonoid biosynthesis in Citrus grandis 'Tomentosa' fruits

As a well-recognized traditional Chinese medicine (TCM), immature fruits of Citrus grandis 'Tomentosa' (CGT) serve to cure chronic cough in humans. Specialized metabolites including flavonoids may have contribute to this curing effect. Knowledge about the molecular mechanisms underlying flavonoid biosynthesis in 'Tomentosa' fruits will, therefore, support the breeding of varieties with improved medicinal properties. Hence, we profiled the transcriptomes and metabolites of the fruits of two contrasting C. grandis varieties, namely 'Zheng-Mao' ('ZM') used in TCM production, and a locally cultivated pomelo, namely 'Guang-Qing' ('GQ'), at four developmental stages. A total of 39 flavonoids, including 14 flavanone/flavone, 5 isoflavonoids, 12 flavonols, and 6 anthocyanins, were identified, and 16 of which were quantitatively determined in the fruits of the two varieties. We found that 'ZM' fruits contain more flavonoids than 'GQ'. Specifically, rhoifolin levels were significantly higher in 'ZM' than in 'GQ'. We annotated 31,510 genes, including 1,387 previously unknown ones, via transcriptome sequencing of 'ZM' and 'GQ.' A total of 646 genes were found to be differentially expressed between 'ZM' and 'GQ' throughout at all four fruit developmental stages, indicating that they are robust expression markers for future breeding programs. Weighted gene co-expression network analysis identified 18 modules. Combined transcriptional and metabolic analysis revealed 25 genes related to flavonoid biosynthesis and 16 transcriptional regulators (MYBs, bHLHs, WD40) that may be involved in the flavonoids biosynthesis in C. grandis 'Tomentosa' fruits.

Identification of Novel Associations of Candidate Genes with Resistance to Late Blight in Solanum tuberosum Group Phureja

The genetic basis of quantitative disease resistance has been studied in crops for several decades as an alternative to R gene mediated resistance. The most important disease in the potato crop is late blight, caused by the oomycete Phytophthora infestans. Quantitative disease resistance (QDR), as any other quantitative trait in plants, can be genetically mapped to understand the genetic architecture. Association mapping using DNA-based markers has been implemented in many crops to dissect quantitative traits. We used an association mapping approach with candidate genes to identify the first genes associated with quantitative resistance to late blight in Solanum tuberosum Group Phureja. Twenty-nine candidate genes were selected from a set of genes that were differentially expressed during the resistance response to late blight in tetraploid European potato cultivars. The 29 genes were amplified and sequenced in 104 accessions of S. tuberosum Group Phureja from Latin America. We identified 238 SNPs in the selected genes and tested them for association with resistance to late blight. The phenotypic data were obtained under field conditions by determining the area under disease progress curve (AUDPC) in two seasons and in two locations. Two genes were associated with QDR to late blight, a potato homolog of thylakoid lumen 15 kDa protein (StTL15A) and a stem 28 kDa glycoprotein (StGP28). Key message: A first association mapping experiment was conducted in Solanum tuberosum Group Phureja germplasm, which identified among 29 candidates two genes associated with quantitative resistance to late blight.

Integrated omics analysis of specialized metabolism in medicinal plants

Medicinal plants are a rich source of highly diverse specialized metabolites with important pharmacological properties. Until recently, plant biologists were limited in their ability to explore the biosynthetic pathways of these metabolites, mainly due to the scarcity of plant genomics resources. However, recent advances in high-throughput large-scale analytical methods have enabled plant biologists to discover biosynthetic pathways for important plant-based medicinal metabolites. The reduced cost of generating omics datasets and the development of computational tools for their analysis and integration have led to the elucidation of biosynthetic pathways of several bioactive metabolites of plant origin. These discoveries have inspired synthetic biology approaches to develop microbial systems to produce bioactive metabolites originating from plants, an alternative sustainable source of medicinally important chemicals. Since the demand for medicinal compounds are increasing with the world's population, understanding the complete biosynthesis of specialized metabolites becomes important to identify or develop reliable sources in the future. Here, we review the contributions of major omics approaches and their integration to our understanding of the biosynthetic pathways of bioactive metabolites. We briefly discuss different approaches for integrating omics datasets to extract biologically relevant knowledge and the application of omics datasets in the construction and reconstruction of metabolic models.

Characterization of the caleosin gene family in the Triticeae

Background

The caleosin genes encode proteins with a single conserved EF hand calcium-binding domain and comprise small gene families found in a wide range of plant species. Some members of the gene family have been shown to be upregulated by environmental stresses including low water availability and high salinity. Caleosin 3 from wheat has been shown to interact with the α-subunit of the heterotrimeric G proteins, and to act as a GTPase activating protein (GAP). This study characterizes the size and diversity of the gene family in wheat and related species and characterizes the differential tissue-specific expression of members of the gene family.

Results

A total of 34 gene family members that belong to eleven paralogous groups of caleosins were identified in the hexaploid bread wheat, T. aestivum. Each group was represented by three homeologous copies of the gene located on corresponding homeologous chromosomes, except the caleosin 10, which has four gene copies. Ten gene family members were identified in diploid barley, Hordeum vulgare, and in rye, Secale cereale, seven in Brachypodium distachyon, and six in rice, Oryza sativa. The analysis of gene expression was assayed in triticale and rye by RNA-Seq analysis of 454 sequence sets and members of the gene family were found to have diverse patterns of gene expression in the different tissues that were sampled in rye and in triticale, the hybrid hexaploid species derived from wheat and rye. Expression of the gene family in wheat and barley was also previously determined by microarray analysis, and changes in expression during development and in response to environmental stresses are presented.

Conclusions

The caleosin gene family had a greater degree of expansion in the Triticeae than in the other monocot species, Brachypodium and rice. The prior implication of one member of the gene family in the stress response and heterotrimeric G protein signaling, points to the potential importance of the caleosin gene family. The complexity of the family and differential expression in various tissues and under conditions of abiotic stress suggests the possibility that caleosin family members may play diverse roles in signaling and development that warrants further investigation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-239) contains supplementary material, which is available to authorized users.

ProfileDB: a resource for proteomics and cross-omics biomarker discovery

The increasing size and complexity of high-throughput datasets pose a growing challenge for researchers. Often very different (cross-omics) techniques with individual data analysis pipelines are employed making a unified biomarker discovery strategy and a direct comparison of different experiments difficult and time consuming. Here we present the comprehensive web-based application ProfileDB. The application is designed to integrate data from different high-throughput 'omics' data types (Transcriptomics, Proteomics, Metabolomics) with clinical parameters and prior knowledge on pathways and ontologies. Beyond data storage, ProfileDB provides a set of dedicated tools for study inspection and data visualization. The user can gain insights into a complex experiment with just a few mouse clicks. We will demonstrate the application by presenting typical use cases for the identification of proteomics biomarkers. All presented analyses can be reproduced using the public ProfileDB web server. The ProfileDB application is available by standard browser (Firefox 18+, Internet Explorer Version 9+) technology via http://profileDB.-microdiscovery.de/ (login and pass-word: profileDB). The installation contains several public datasets including different cross-'omics' experiments. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.

BSTA: a targeted approach combines bulked segregant analysis with next- generation sequencing and de novo transcriptome assembly for SNP discovery in sunflower

Background

Sunflower belongs to the largest plant family on earth, the genomically poorly explored Compositae. Downy mildew Plasmopara halstedii (Farlow) Berlese & de Toni is one of the major diseases of cultivated sunflower (Helianthus annuus L.). In the search for new sources of downy mildew resistance, the locus Pl_ARG on linkage group 1 (LG1) originating from H. argophyllus is promising since it confers resistance against all known races of the pathogen. However, the mapping resolution in the Pl_ARG region is hampered by significantly suppressed recombination and by limited availability of polymorphic markers. Here we examined a strategy developed for the enrichment of molecular markers linked to this specific genomic region. We combined bulked segregant analysis (BSA) with next-generation sequencing (NGS) and de novo assembly of the sunflower transcriptome for single nucleotide polymorphism (SNP) discovery in a sequence resource combining reads originating from two sunflower species, H. annuus and H. argophyllus.

Results

A computational pipeline developed for SNP calling and pattern detection identified 219 candidate genes. For a proof of concept, 42 resistance gene-like sequences were subjected to experimental SNP validation. Using a high-resolution mapping population, 12 SNP markers were mapped to LG1. We successfully verified candidate sequences either co-segregating with or closely flanking Pl_ARG.

Conclusions

This study is the first successful example to improve bulked segregant analysis with de novo transcriptome assembly using next generation sequencing. The BSTA pipeline we developed provides a useful guide for similar studies in other non-model organisms. Our results demonstrate this method is an efficient way to enrich molecular markers and to identify candidate genes in a specific mapping interval.

Data management pipeline for plant phenotyping in a multisite project

In plant breeding, plants have to be characterised precisely, consistently and rapidly by different people at several field sites within defined time spans. For a meaningful data evaluation and statistical analysis, standardised data storage is required. Data access must be provided on a long-term basis and be independent of organisational barriers without endangering data integrity or intellectual property rights. We discuss the associated technical challenges and demonstrate adequate solutions exemplified in a data management pipeline for a project to identify markers for drought tolerance in potato. This project involves 11 groups from academia and breeding companies, 11 sites and four analytical platforms. Our data warehouse concept combines central data storage in databases and a file server and integrates existing and specialised database solutions for particular data types with new, project-specific databases. The strict use of controlled vocabularies and the application of web-access technologies proved vital to the successful data exchange between diverse institutes and data management concepts and infrastructures. By presenting our data management system and making the software available, we aim to support related phenotyping projects.

Phenotyping plants: genes, phenes and machines

No matter how fascinating the discoveries in the field of molecular biology are, in the end it is the phenotype that matters. In this paper we pay attention to various aspects of plant phenotyping. The challenges to unravel the relationship between genotype and phenotype are discussed, as well as the case where 'plants do not have a phenotype'. More emphasis has to be placed on automation to match the increased output in the molecular sciences with analysis of relevant traits under laboratory, greenhouse and field conditions. Currently, non-destructive measurements with cameras are becoming widely used to assess plant structural properties, but a wider range of non-invasive approaches and evaluation tools has to be developed to combine physiologically meaningful data with structural information of plants. Another field requiring major progress is the handling and processing of data. A better e-infrastructure will enable easier establishment of links between phenotypic traits and genetic data. In the final part of this paper we briefly introduce the range of contributions that form the core of a special issue of this journal on plant phenotyping.

Evidence of cryptic introgression in tomato (Solanum lycopersicum L.) based on wild tomato species alleles

BACKGROUND

Many highly beneficial traits (e.g. disease or abiotic stress resistance) have been transferred into crops through crosses with their wild relatives. The 13 recognized species of tomato (Solanum section Lycopersicon) are closely related to each other and wild species genes have been extensively used for improvement of the crop, Solanum lycopersicum L. In addition, the lack of geographical barriers has permitted natural hybridization between S. lycopersicum and its closest wild relative Solanum pimpinellifolium in Ecuador, Peru and northern Chile. In order to better understand patterns of S. lycopersicum diversity, we sequenced 47 markers ranging in length from 130 to 1200 bp (total of 24 kb) in genotypes of S. lycopersicum and wild tomato species S. pimpinellifolium, Solanum arcanum, Solanum peruvianum, Solanum pennellii and Solanum habrochaites. Between six and twelve genotypes were comparatively analyzed per marker. Several of the markers had previously been hypothesized as carrying wild species alleles within S. lycopersicum, i.e., cryptic introgressions.

RESULTS

Each marker was mapped with high confidence (e<1 x 10-30) to a single genomic location using BLASTN against tomato whole genome shotgun chromosomes (SL2.40) database. Neighbor-joining trees showed high mean bootstrap support (86.8 ± 2.34%) for distinguishing red-fruited from green-fruited taxa for 38 of the markers. Hybridization and parsimony splits networks, genomic map positions of markers relative to documented introgressions, and historical origins of accessions were used to interpret evolutionary patterns at nine markers with putatively introgressed alleles.

CONCLUSION

Of the 47 genetic markers surveyed in this study, four were involved in linkage drag on chromosome 9 during introgression breeding, while alleles at five markers apparently originated from natural hybridization with S. pimpinellifolium and were associated with primitive genotypes of S. lycopersicum. The positive identification of introgressed genes within crop species such as S. lycopersicum will help inform conservation and utilization of crop germplasm diversity, for example, facilitating the purging of undesirable linkage drag or the exploitation of novel, favorable alleles.

GabiPD - The GABI Primary Database integrates plant proteomic data with gene-centric information

GabiPD is an integrative plant "omics" database that has been established as part of the German initiative for Genome Analysis of the Plant Biological System (GABI). Data from different "omics" disciplines are integrated and interactively visualized. Proteomics is represented by data and tools aiding studies on the identification of post-translational modification and function of proteins. Annotated 2D electrophoresis-gel images are offered to inspect protein sets expressed in different tissues of Arabidopsis thaliana and Brassica napus. From a given protein spot, a link will direct the user to the related GreenCard Gene entry where detailed gene-centric information will support the functional annotation. Beside MapMan- and GO-classification, information on conserved protein domains and on orthologs is integrated in this GreenCard service. Moreover, all other GabiPD data related to the gene, including transcriptomic data, as well as gene-specific links to external resources are provided. Researches interested in plant protein phosphorylation will find information on potential MAP kinase substrates identified in different protein microarray studies integrated in GabiPD's Phosphoproteomics page. These data can be easily compared to experimentally identified or predicted phosphorylation sites in PhosPhAt via the related Gene GreenCard. This will allow the selection of interesting candidates for further experimental validation of their phosphorylation.

A case study for efficient management of high throughput primary lab data

BACKGROUND

In modern life science research it is very important to have an efficient management of high throughput primary lab data. To realise such an efficient management, four main aspects have to be handled: (I) long term storage, (II) security, (III) upload and (IV) retrieval.

FINDINGS

In this paper we define central requirements for a primary lab data management and discuss aspects of best practices to realise these requirements. As a proof of concept, we introduce a pipeline that has been implemented in order to manage primary lab data at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK). It comprises: (I) a data storage implementation including a Hierarchical Storage Management system, a relational Oracle Database Management System and a BFiler package to store primary lab data and their meta information, (II) the Virtual Private Database (VPD) implementation for the realisation of data security and the LIMS Light application to (III) upload and (IV) retrieve stored primary lab data.

CONCLUSIONS

With the LIMS Light system we have developed a primary data management system which provides an efficient storage system with a Hierarchical Storage Management System and an Oracle relational database. With our VPD Access Control Method we can guarantee the security of the stored primary data. Furthermore the system provides high performance upload and download and efficient retrieval of data.

From RNA-seq to large-scale genotyping - genomics resources for rye (Secale cereale L.)

BACKGROUND

The improvement of agricultural crops with regard to yield, resistance and environmental adaptation is a perpetual challenge for both breeding and research. Exploration of the genetic potential and implementation of genome-based breeding strategies for efficient rye (Secale cereale L.) cultivar improvement have been hampered by the lack of genome sequence information. To overcome this limitation we sequenced the transcriptomes of five winter rye inbred lines using Roche/454 GS FLX technology.

RESULTS

More than 2.5 million reads were assembled into 115,400 contigs representing a comprehensive rye expressed sequence tag (EST) resource. From sequence comparisons 5,234 single nucleotide polymorphisms (SNPs) were identified to develop the Rye5K high-throughput SNP genotyping array. Performance of the Rye5K SNP array was investigated by genotyping 59 rye inbred lines including the five lines used for sequencing, and five barley, three wheat, and two triticale accessions. A balanced distribution of allele frequencies ranging from 0.1 to 0.9 was observed. Residual heterozygosity of the rye inbred lines varied from 4.0 to 20.4% with higher average heterozygosity in the pollen compared to the seed parent pool.

CONCLUSIONS

The established sequence and molecular marker resources will improve and promote genetic and genomic research as well as genome-based breeding in rye.

Proteomics - The key to understanding systems biology of Arabidopsis trichomes

Every multicellular organism consists of numerous organs, tissues and specific cell types. To gain detailed knowledge about the morphogenesis of these complex structures, it is inevitable to advance biochemical analyses to ultimate spatial and temporal resolution since individual cell types contribute differently to the overall performance of living objects. Single cell sampling combined with systems biological approaches was recently applied to investigations of Arabidopsis thaliana trichomes (leaf hairs). These are single celled structures that provide ideal model systems to address various aspects of plant cell development and differentiation at the level of individual cells. A previously suggested function of trichomes in plant stress responses could thus be confirmed. Furthermore, trichome-specific "omics" data collected in several laboratories are mutually conclusive which demonstrates the applicability of systems biological approaches at the single cell level.

Proteome databases and other online resources for chloroplast research in Arabidopsis

Proteomics aimed at addressing sub cellular fractions, such as chloroplasts, are a complex challenge. In the past few years, several studies in different laboratories have identified and, more recently, quantified, thousands of proteins within whole chloroplasts or chloroplast fractions. A considerable number of these studies are available for querying, using online resources, such as databases containing the proteins identified, encoding genes, acquired spectra, and phosphopeptides. The main purpose of this review is to identity and highlight useful features of these online resourses, mainly focused in proteomics databases related to chloroplast research in Arabidopsis thaliana. Several web sites were consulted. Among them, 11 were selected and discussed herein. The databases were classified into Plastid Databases, General Organelle Proteome Databases, and General Arabidopsis Proteome Databases. Special care was taken to present information regarding protein identification, protein quantification, and data integration. A selected list of online resources is presented in two tables. The databases analyzed are a useful source of information for researchers in the plastid organelle and plant proteomics fields.

Proteome-wide survey of phosphorylation patterns affected by nuclear DNA polymorphisms in Arabidopsis thaliana

Background

Protein phosphorylation is an important post-translational modification influencing many aspects of dynamic cellular behavior. Site-specific phosphorylation of amino acid residues serine, threonine, and tyrosine can have profound effects on protein structure, activity, stability, and interaction with other biomolecules. Phosphorylation sites can be affected in diverse ways in members of any species, one such way is through single nucleotide polymorphisms (SNPs). The availability of large numbers of experimentally identified phosphorylation sites, and of natural variation datasets in Arabidopsis thaliana prompted us to analyze the effect of non-synonymous SNPs (nsSNPs) onto phosphorylation sites.

Results

From the analyses of 7,178 experimentally identified phosphorylation sites we found that: (i) Proteins with multiple phosphorylation sites occur more often than expected by chance. (ii) Phosphorylation hotspots show a preference to be located outside conserved domains. (iii) nsSNPs affected experimental phosphorylation sites as much as the corresponding non-phosphorylated amino acid residues. (iv) Losses of experimental phosphorylation sites by nsSNPs were identified in 86 A. thaliana proteins, among them receptor proteins were overrepresented.

These results were confirmed by similar analyses of predicted phosphorylation sites in A. thaliana. In addition, predicted threonine phosphorylation sites showed a significant enrichment of nsSNPs towards asparagines and a significant depletion of the synonymous substitution. Proteins in which predicted phosphorylation sites were affected by nsSNPs (loss and gain), were determined to be mainly receptor proteins, stress response proteins and proteins involved in nucleotide and protein binding. Proteins involved in metabolism, catalytic activity and biosynthesis were less affected.

Conclusions

We analyzed more than 7,100 experimentally identified phosphorylation sites in almost 4,300 protein-coding loci in silico, thus constituting the largest phosphoproteomics dataset for A. thaliana available to date. Our findings suggest a relatively high variability in the presence or absence of phosphorylation sites between different natural accessions in receptor and other proteins involved in signal transduction. Elucidating the effect of phosphorylation sites affected by nsSNPs on adaptive responses represents an exciting research goal for the future.

Comparison of the chromosome maps around a resistance hot spot on chromosome 5 of potato and tomato using BAC-FISH painting

Potato chromosome 5 harbours numerous genes for important qualitative and quantitative traits, such as resistance to the root cyst nematode Globodera pallida and the late blight fungus, Phytophthora infestans. The genes make up part of a "hot spot" for resistances to various pathogens covering a genetic map length of 3 cM between markers GP21 and GP179. We established the physical size and position of this region on chromosome 5 in potato and tomato using fluorescence in situ hybridization (FISH) on pachytene chromosomes. Five potato bacterial artificial chromosome (BAC) clones with the genetically anchored markers GP21, R1-contig (proximal end), CosA, GP179, and StPto were selected, labeled with different fluorophores, and hybridized in a five-colour FISH experiment. Our results showed the location of the BAC clones in the middle of the long arm of chromosome 5 in both potato and tomato. Based on chromosome measurements, we estimate the physical size of the GP21-GP179 interval at 0.85 Mb and 1.2 Mb in potato and tomato, respectively. The GP21-GP179 interval is part of a genome segment known to have inverted map positions between potato and tomato.

Omics meet networks - using systems approaches to infer regulatory networks in plants

Many genomic-scale datasets in plants have been generated over the last few years. This substantial achievement has led to impressive progress, including some of the most detailed molecular maps in any multicellular organism. Networks and pathways have been reconstructed using transcriptome, genome-wide transcription factor binding, proteome and metabolome data, and subsequently used to infer functional interactions among genes, proteins, and metabolites. However, more sophisticated systems biology approaches are needed to integrate different omics datasets. Ultimately, the integration of diverse and massive datasets into coherent models will improve our understanding of the molecular networks that underlie biological processes.

Documentation system for plant transformation service and research

BACKGROUND

In plant transformation, method compliance is critical for success. Transformation methods are complicated and tend to evolve over time. Until the complete method is published, method details are often partially orally transmitted and thus bound to a few people. Their documentation in text files are often a mixture of material and method description with many references to other sources especially to media description. These media are complex and often composed from several commercially available mixtures plus individually prepared stocks. The actual transformation experiment is generally documented in lab books, in which deviations from the methods and results are reported. Additionally, work schedules are planned in diaries. Both paper-based sources lack backup copies and miss unambiguous links to method descriptions and media recipes.

DESCRIPTION

To solve the problem, we devised a standard-operation-procedure system based on a Microsoft Access database containing the interlinked modules 'Media', 'Methods' and 'Experiments'. The Media module contains all basic chemicals, stocks and complex media. In this module, complex media are composed from other elements of the Media module, thus mimicking the workflows of media preparation in the lab. The Media module is made attractive to the user by functions that generate file cards and labels. The Methods module describes each method stepwise and links the steps to the media. Copy functions allow cloning of old methods to document method evolution without alteration of the old methods. Activation and inactivation functions in the Media and the Methods module remove outdated entries from active use. The Experiments module links the method to experiment specific information. This module generates a lab-book like user interface and a work schedule, and it contains a simple result section.

CONCLUSION

The system has been evolved and tested over several years in a transformation service unit, where it increased efficiency. Additionally, the system provided rapid access to data for quality control and decision making. The system can be easily modified for the use in other research environments.

PhosPhAt: the Arabidopsis thaliana phosphorylation site database. An update

The PhosPhAt database of Arabidopsis phosphorylation sites was initially launched in August 2007. Since then, along with 10-fold increase in database entries, functionality of PhosPhAt (phosphat.mpimp-golm.mpg.de) has been considerably upgraded and re-designed. PhosPhAt is now more of a web application with the inclusion of advanced search functions allowing combinatorial searches by Boolean terms. The results output now includes interactive visualization of annotated fragmentation spectra and the ability to export spectra and peptide sequences as text files for use in other applications. We have also implemented dynamic links to other web resources thus augmenting PhosPhAt-specific information with external protein-related data. For experimental phosphorylation sites with information about dynamic behavior in response to external stimuli, we display simple time-resolved diagrams. We have included predictions for pT and pY sites and updated pS predictions. Access to prediction algorithm now allows 'on-the-fly' prediction of phosphorylation of any user-uploaded protein sequence. Protein Pfam domain structures are now mapped onto the protein sequence display next to experimental and predicted phosphorylation sites. Finally, we have implemented functional annotation of proteins using MAPMAN ontology. These new developments make the PhosPhAt resource a useful and powerful tool for the scientific community as a whole beyond the plant sciences.

Plant phosphoproteomics: an update

Phosphoproteomics involves identification of phosphoproteins, precise mapping, and quantification of phosphorylation sites, and eventually, revealing their biological function. In plants, several systematic phosphoproteomic analyses have recently been performed to optimize in vitro and in vivo technologies to reveal components of the phosphoproteome. The discovery of novel substrates for specific protein kinases is also an important issue. Development of a new tool has enabled rapid identification of potential kinase substrates such as kinase assays using plant protein microarrays. Progress has also been made in quantitative and dynamic analysis of mapped phosphorylation sites. Increased quantity of experimentally verified phosphorylation sites in plants has prompted the creation of dedicated web-resources for plant-specific phosphoproteomics data. This resulted in development of computational prediction methods yielding significantly improved sensitivity and specificity for the detection of phosphorylation sites in plants when compared to methods trained on less plant-specific data. In this review, we present an update on phosphoproteomic studies in plants and summarize the recent progress in the computational prediction of plant phosphorylation sites. The application of the experimental and computed results in understanding the phosphoproteomic networks of cellular and metabolic processes in plants is discussed. This is a continuation of our comprehensive review series on plant phosphoproteomics.

A high-resolution map of the Grp1 locus on chromosome V of potato harbouring broad-spectrum resistance to the cyst nematode species Globodera pallida and Globodera rostochiensis

The Grp1 locus confers broad-spectrum resistance to the potato cyst nematode species Globodera pallida and Globodera rostochiensis and is located in the GP21-GP179 interval on the short arm of chromosome V of potato. A high-resolution map has been developed using the diploid mapping population RHAM026, comprising 1,536 genotypes. The flanking markers GP21 and GP179 have been used to screen the 1,536 genotypes for recombination events. Interval mapping of the resistances to G. pallida Pa2 and G. rostochiensis Ro5 resulted in two nearly identical LOD graphs with the highest LOD score just north of marker TG432. Detailed analysis of the 44 recombinant genotypes showed that G. pallida and G. rostochiensis resistance could not be separated and map to the same location between marker SPUD838 and TG432. It is suggested that the quantitative resistance to both nematode species at the Grp1 locus is mediated by one or more tightly linked R genes that might belong to the NBS-LRR class.

ChlamyCyc: an integrative systems biology database and web-portal for Chlamydomonas reinhardtii

Background

The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern high-throughput technologies there is an imperative need to integrate large-scale data sets from high-throughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism.

Results

In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc) was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification.

Conclusion

ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under .

Web-queryable large-scale data sets for hypothesis generation in plant biology

The approaching end of the 21st century's first decade marks an exciting time for plant biology. Several National Science Foundation Arabidopsis 2010 Projects will conclude, and whether or not the stated goal of the National Science Foundation 2010 Program-to determine the function of 25,000 Arabidopsis genes by 2010-is reached, these projects and others in a similar vein, such as those performed by the AtGenExpress Consortium and various plant genome sequencing initiatives, have generated important and unprecedented large-scale data sets. While providing significant biological insights for the individual laboratories that generated them, these data sets, in conjunction with the appropriate tools, are also permitting plant biologists worldwide to gain new insights into their own biological systems of interest, often at a mouse click through a Web browser. This review provides an overview of several such genomic, epigenomic, transcriptomic, proteomic, and metabolomic data sets and describes Web-based tools for querying them in the context of hypothesis generation for plant biology. We provide five biological examples of how such tools and data sets have been used to provide biological insight.