Plant Genome Databases Research Articles

Plant pectin acetylesterase structure and function: new insights from bioinformatic analysis

BackgroundPectins are plant cell wall polysaccharides that can be acetylated on C2 and/or C3 of galacturonic acid residues. The degree of acetylation of pectin can be modulated by pectin acetylesterase (EC 3.1.1.6, PAE). The function and structure of plant PAEs remain poorly understood and the role of the fine-tuning of pectin acetylation on cell wall properties has not yet been elucidated.ResultsIn the present study, a bioinformatic approach was used on 72 plant PAEs from 16 species among 611 plant PAEs available in plant genomic databases. An overview of plant PAE proteins, particularly Arabidopsis thaliana PAEs, based on phylogeny analysis, protein motif identification and modeled 3D structure is presented. A phylogenetic tree analysis using protein sequences clustered the plant PAEs into five clades. AtPAEs clustered in four clades in the plant kingdom PAE tree while they formed three clades when a phylogenetic tree was performed only on Arabidopsis proteins, due to isoform AtPAE9. Primitive plants that display a smaller number of PAEs clustered into two clades, while in higher plants, the presence of multiple members of PAE genes indicated a diversification of AtPAEs. 3D homology modeling of AtPAE8 from clade 2 with a human Notum protein showed an α/β hydrolase structure with the hallmark Ser-His-Asp of the active site. A 3D model of AtPAE4 from clade 1 and AtPAE10 from clade 3 showed a similar shape suggesting that the diversification of AtPAEs is unlikely to arise from the shape of the protein. Primary structure prediction analysis of AtPAEs showed a specific motif characteristic of each clade and identified one major group of AtPAEs with a signal peptide and one group without a signal peptide. A multiple sequence alignment of the putative plant PAEs revealed consensus sequences with important putative catalytic residues: Ser, Asp, His and a pectin binding site. Data mining of gene expression profiles of AtPAE revealed that genes from clade 2 including AtPAE7, AtPAE8 and AtPAE11, which are duplicated genes, are highly expressed during plant growth and development while AtPAEs without a signal peptide, including AtPAE2 and AtPAE4, are more regulated in response to plant environmental conditions.ConclusionBioinformatic analysis of plant, and particularly Arabidopsis, AtPAEs provides novel insights, including new motifs that could play a role in pectin binding and catalytic sites. The diversification of AtPAEs is likely to be related to neofunctionalization of some AtPAE genes.

PGSB/MIPS PlantsDB Database Framework for the Integration and Analysis of Plant Genome Data.

Plant Genome and Systems Biology (PGSB), formerly Munich Institute for Protein Sequences (MIPS) PlantsDB, is a database framework for the integration and analysis of plant genome data, developed and maintained for more than a decade now. Major components of that framework are genome databases and analysis resources focusing on individual (reference) genomes providing flexible and intuitive access to data. Another main focus is the integration of genomes from both model and crop plants to form a scaffold for comparative genomics, assisted by specialized tools such as the CrowsNest viewer to explore conserved gene order (synteny). Data exchange and integrated search functionality with/over many plant genome databases is provided within the transPLANT project.

Plant Genome DataBase Japan (PGDBj).

A portal website that integrates a variety of information related to genomes of model and crop plants from databases (DBs) and the literature was generated. This website, named the Plant Genome DataBase Japan (PGDBj, http://pgdbj. jp/en/ ), is comprised of three component DBs and a cross-search engine which provides a seamless search over their contents. One of the three component DBs is the Ortholog DB, which provides gene cluster information based on the amino acid sequence similarity. Over 1,000,000 amino acid sequences of 40 Viridiplantae species were collected from the public DNA DBs, and plant genome DBs such as TAIR and RAP-DB were subjected to reciprocal BLAST searches for clustering. Another component DB is the Plant Resource DB for genomic- and bio-resources. This DB also integrates the SABRE DB, which provides cDNA and genome sequence resources maintained in the RIKEN BioResource Center and National BioResource Projects Japan. The third component DB of PGDBj is the DNA Marker DB, which manually or automatically collects curated information on DNA markers, quantitative trait loci (QTL), and related genetic linkage maps, from the literature and external DBs. By combining these component DBs and a cross-search engine, PGDBj serves as a useful platform to study genetic systems for both fundamental and applied researches for a wide range of plant species.

Bioinformatics Approach in Plant Genomic Research.

The advance in genomics technology leads to the dramatic change in plant biology research. Plant biologists now easily access to enormous genomic data to deeply study plant high-density genetic variation at molecular level. Therefore, fully understanding and well manipulating bioinformatics tools to manage and analyze these data are essential in current plant genome research. Many plant genome databases have been established and continued expanding recently. Meanwhile, analytical methods based on bioinformatics are also well developed in many aspects of plant genomic research including comparative genomic analysis, phylogenomics and evolutionary analysis, and genome-wide association study. However, constantly upgrading in computational infrastructures, such as high capacity data storage and high performing analysis software, is the real challenge for plant genome research. This review paper focuses on challenges and opportunities which knowledge and skills in bioinformatics can bring to plant scientists in present plant genomics era as well as future aspects in critical need for effective tools to facilitate the translation of knowledge from new sequencing data to enhancement of plant productivity.

NO-Mediated [Ca2+]cyt Increases Depend on ADP-Ribosyl Cyclase Activity in Arabidopsis

Cyclic ADP ribose (cADPR) is a Ca(2+)-mobilizing intracellular second messenger synthesized from NAD by ADP-ribosyl cyclases (ADPR cyclases). In animals, cADPR targets the ryanodine receptor present in the sarcoplasmic/endoplasmic reticulum to promote Ca(2+) release from intracellular stores to increase the concentration of cytosolic free Ca(2+) in Arabidopsis (Arabidopsis thaliana), and cADPR has been proposed to play a central role in signal transduction pathways evoked by the drought and stress hormone, abscisic acid, and the circadian clock. Despite evidence for the action of cADPR in Arabidopsis, no predicted proteins with significant similarity to the known ADPR cyclases have been reported in any plant genome database, suggesting either that there is a unique route for cADPR synthesis or that a homolog of ADPR cyclase with low similarity might exist in plants. We sought to determine whether the low levels of ADPR cyclase activity reported in Arabidopsis are indicative of a bona fide activity that can be associated with the regulation of Ca(2+) signaling. We adapted two different fluorescence-based assays to measure ADPR cyclase activity in Arabidopsis and found that this activity has the characteristics of a nucleotide cyclase that is activated by nitric oxide to increase cADPR and mobilize Ca(2.)

PGSB/MIPS Plant Genome Information Resources and Concepts for the Analysis of Complex Grass Genomes.

PGSB (Plant Genome and Systems Biology; formerly MIPS-Munich Institute for Protein Sequences) has been involved in developing, implementing and maintaining plant genome databases for more than a decade. Genome databases and analysis resources have focused on individual genomes and aim to provide flexible and maintainable datasets for model plant genomes as a backbone against which experimental data, e.g., from high-throughput functional genomics, can be organized and analyzed. In addition, genomes from both model and crop plants form a scaffold for comparative genomics, assisted by specialized tools such as the CrowsNest viewer to explore conserved gene order (synteny) between related species on macro- and micro-levels.The genomes of many economically important Triticeae plants such as wheat, barley, and rye present a great challenge for sequence assembly and bioinformatic analysis due to their enormous complexity and large genome size. Novel concepts and strategies have been developed to deal with these difficulties and have been applied to the genomes of wheat, barley, rye, and other cereals. This includes the GenomeZipper concept, reference-guided exome assembly, and "chromosome genomics" based on flow cytometry sorted chromosomes.

PGSB PlantsDB: updates to the database framework for comparative plant genome research.

PGSB (Plant Genome and Systems Biology: formerly MIPS) PlantsDB (http://pgsb.helmholtz-muenchen.de/plant/index.jsp) is a database framework for the comparative analysis and visualization of plant genome data. The resource has been updated with new data sets and types as well as specialized tools and interfaces to address user demands for intuitive access to complex plant genome data. In its latest incarnation, we have re-worked both the layout and navigation structure and implemented new keyword search options and a new BLAST sequence search functionality. Actively involved in corresponding sequencing consortia, PlantsDB has dedicated special efforts to the integration and visualization of complex triticeae genome data, especially for barley, wheat and rye. We enhanced CrowsNest, a tool to visualize syntenic relationships between genomes, with data from the wheat sub-genome progenitor Aegilops tauschii and added functionality to the PGSB RNASeqExpressionBrowser. GenomeZipper results were integrated for the genomes of barley, rye, wheat and perennial ryegrass and interactive access is granted through PlantsDB interfaces. Data exchange and cross-linking between PlantsDB and other plant genome databases is stimulated by the transPLANT project (http://transplantdb.eu/).

The LAILAPS search engine – travel through the network of plant genome databases

The LAILAPS search engine – travel through the network of plant genome databases

PLANT GENOMIC DATABASES FOR OILSEEDS CROP IMPROVEMENT

Plant genomic databases are collections of huge information on plants, germplasm accessions, descriptors, plant genetics, physical and genomic sequence maps, QTLs, loci, sequence information, molecular markers, references etc. At present more than 100 plants genomic databases are available. These are dedicated to generic genome data focusing on specific crops. Some of the important oilseeds plant databases include Castor Bean Genome Database, CGPDB, SoyBase, Legume Information System (LIS), Brassica database, Sinbase etc. Due to availability of number of genomic databases for crop plants before using any of these databases the researcher needs to visit most appropriate database and choose suitable parameters for genomic information mining. The wealth of information available to researchers today can be overwhelming hence; understanding the plant databases for harnessing genomic information is the need of the hour for crop improvement research programmes.

Plant Genome DataBase Japan (PGDBj): A Portal Website for the Integration of Plant Genome-Related Databases

The Plant Genome DataBase Japan (PGDBj, http://pgdbj.jp/?ln=en) is a portal website that aims to integrate plant genome-related information from databases (DBs) and the literature. The PGDBj is comprised of three component DBs and a cross-search engine, which provides a seamless search over the contents of the DBs. The three DBs are as follows. (i) The Ortholog DB, providing gene cluster information based on the amino acid sequence similarity. Over 500,000 amino acid sequences of 20 Viridiplantae species were subjected to reciprocal BLAST searches and clustered. Sequences from plant genome DBs (e.g. TAIR10 and RAP-DB) were also included in the cluster with a direct link to the original DB. (ii) The Plant Resource DB, integrating the SABRE DB, which provides cDNA and genome sequence resources accumulated and maintained in the RIKEN BioResource Center and National BioResource Projects. (iii) The DNA Marker DB, providing manually or automatically curated information of DNA markers, quantitative trait loci and related linkage maps, from the literature and external DBs. As the PGDBj targets various plant species, including model plants, algae, and crops important as food, fodder and biofuel, researchers in the field of basic biology as well as a wide range of agronomic fields are encouraged to perform searches using DNA sequences, gene names, traits and phenotypes of interest. The PGDBj will return the search results from the component DBs and various types of linked external DBs.

Transcriptome Analysis in Sheepgrass (Leymus chinensis): A Dominant Perennial Grass of the Eurasian Steppe

BackgroundSheepgrass [Leymus chinensis (Trin.) Tzvel.] is an important perennial forage grass across the Eurasian Steppe and is known for its adaptability to various environmental conditions. However, insufficient data resources in public databases for sheepgrass limited our understanding of the mechanism of environmental adaptations, gene discovery and molecular marker development.ResultsThe transcriptome of sheepgrass was sequenced using Roche 454 pyrosequencing technology. We assembled 952,328 high-quality reads into 87,214 unigenes, including 32,416 contigs and 54,798 singletons. There were 15,450 contigs over 500 bp in length. BLAST searches of our database against Swiss-Prot and NCBI non-redundant protein sequences (nr) databases resulted in the annotation of 54,584 (62.6%) of the unigenes. Gene Ontology (GO) analysis assigned 89,129 GO term annotations for 17,463 unigenes. We identified 11,675 core Poaceae-specific and 12,811 putative sheepgrass-specific unigenes by BLAST searches against all plant genome and transcriptome databases. A total of 2,979 specific freezing-responsive unigenes were found from this RNAseq dataset. We identified 3,818 EST-SSRs in 3,597 unigenes, and some SSRs contained unigenes that were also candidates for freezing-response genes. Characterizations of nucleotide repeats and dominant motifs of SSRs in sheepgrass were also performed. Similarity and phylogenetic analysis indicated that sheepgrass is closely related to barley and wheat.ConclusionsThis research has greatly enriched sheepgrass transcriptome resources. The identified stress-related genes will help us to decipher the genetic basis of the environmental and ecological adaptations of this species and will be used to improve wheat and barley crops through hybridization or genetic transformation. The EST-SSRs reported here will be a valuable resource for future gene-phenotype studies and for the molecular breeding of sheepgrass and other Poaceae species.

Integrating genome annotation and QTL position to identify candidate genes for productivity, architecture and water-use efficiency in Populus spp

BackgroundHybrid poplars species are candidates for biomass production but breeding efforts are needed to combine productivity and water use efficiency in improved cultivars. The understanding of the genetic architecture of growth in poplar by a Quantitative Trait Loci (QTL) approach can help us to elucidate the molecular basis of such integrative traits but identifying candidate genes underlying these QTLs remains difficult. Nevertheless, the increase of genomic information together with the accessibility to a reference genome sequence (Populus trichocarpa Nisqually-1) allow to bridge QTL information on genetic maps and physical location of candidate genes on the genome. The objective of the study is to identify QTLs controlling productivity, architecture and leaf traits in a P. deltoides x P. trichocarpa F1 progeny and to identify candidate genes underlying QTLs based on the anchoring of genetic maps on the genome and the gene ontology information linked to genome annotation. The strategy to explore genome annotation was to use Gene Ontology enrichment tools to test if some functional categories are statistically over-represented in QTL regions.ResultsFour leaf traits and 7 growth traits were measured on 330 F1 P. deltoides x P. trichocarpa progeny. A total of 77 QTLs controlling 11 traits were identified explaining from 1.8 to 17.2% of the variation of traits. For 58 QTLs, confidence intervals could be projected on the genome. An extended functional annotation was built based on data retrieved from the plant genome database Phytozome and from an inference of function using homology between Populus and the model plant Arabidopsis. Genes located within QTL confidence intervals were retrieved and enrichments in gene ontology (GO) terms were determined using different methods. Significant enrichments were found for all traits. Particularly relevant biological processes GO terms were identified for QTLs controlling number of sylleptic branches: intervals were enriched in GO terms of biological process like ‘ripening’ and ‘adventitious roots development’.ConclusionBeyond the simple identification of QTLs, this study is the first to use a global approach of GO terms enrichment analysis to fully explore gene function under QTLs confidence intervals in plants. This global approach may lead to identification of new candidate genes for traits of interest.

Genomic Databases for Crop Improvement

Genomics is playing an increasing role in plant breeding and this is accelerating with the rapid advances in genome technology. Translating the vast abundance of data being produced by genome technologies requires the development of custom bioinformatics tools and advanced databases. These range from large generic databases which hold specific data types for a broad range of species, to carefully integrated and curated databases which act as a resource for the improvement of specific crops. In this review, we outline some of the features of plant genome databases, identify specific resources for the improvement of individual crops and comment on the potential future direction of crop genome databases.

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.

Multi-source and ontology-based retrieval engine for maize mutant phenotypes

Model Organism Databases, including the various plant genome databases, collect and enable access to massive amounts of heterogeneous information, including sequence data, gene product information, images of mutant phenotypes, etc, as well as textual descriptions of many of these entities. While a variety of basic browsing and search capabilities are available to allow researchers to query and peruse the names and attributes of phenotypic data, next-generation search mechanisms that allow querying and ranking of text descriptions are much less common. In addition, the plant community needs an innovative way to leverage the existing links in these databases to search groups of text descriptions simultaneously. Furthermore, though much time and effort have been afforded to the development of plant-related ontologies, the knowledge embedded in these ontologies remains largely unused in available plant search mechanisms. Addressing these issues, we have developed a unique search engine for mutant phenotypes from MaizeGDB. This advanced search mechanism integrates various text description sources in MaizeGDB to aid a user in retrieving desired mutant phenotype information. Currently, descriptions of mutant phenotypes, loci and gene products are utilized collectively for each search, though expansion of the search mechanism to include other sources is straightforward. The retrieval engine, to our knowledge, is the first engine to exploit the content and structure of available domain ontologies, currently the Plant and Gene Ontologies, to expand and enrich retrieval results in major plant genomic databases.Database URL: http:www.PhenomicsWorld.org/QBTA.php

A MODEL PLANT GENOME RESOURCE AND COMPARATIVE GENOMICS

The goal of a novel model plant genomics resource database is to provide a community resource that allows researchers to build their research models by making use of data derived from one or more approaches, for example the forward and reverse genetics, comparative genomics, in silico predictions etc. This resource can be built for a given plant species/genus or even for any plant taxonomic clade covering many species and tribes. A database may house diverse types of data including annotated sequenced genomes of plant(s), individual sequence entries, markers, genetic maps, associated pathways, gene networks, phenotypes, quantitative trait loci (QTL) and the genetic diversity datasets that include genotype-phenotype associations. To support queries across various data sets, as well as across other collaborative databases, a model plant genome database should strive to make extensive use of the five controlled vocabularies (ontologies): Trait Ontology (TO), Plant Ontology (PO), Environment Ontology (EO), Gene Ontology (GO), and the Taxonomy. Users can query the database using various filters to find phenotypes, genes, QTLs, markers, maps, genomic landmarks, associated proteins, pathways and sequences. Through such an effort, the database can foster discovery of candidate gene(s), regulatory elements, comparisons of genetic and genomic maps from plant models, phenotype features associated to mutant genes and mapped QTLs, gene functions and interating partners. The ability to make connections across various data types presents a significant advance over the capabilities of previously existing resources. With this view we will discuss the design and example queries using a well known plant genome database.

Helitron mediated amplification of cytochrome P450 monooxygenase gene in maize

The mass movement of gene sequences by Helitrons has significantly contributed to the lack of gene collinearity reported between different maize inbred lines. However, Helitron captured-genes reported to date represent truncated versions of their progenitor genes. In this report, we provide evidence that maize CYP72A27-Zm gene represents a cytochrome P450 monooxygenase (P450) gene recently captured by a Helitron and transposed into an Opie-2 retroposon. The four exons of the CYP72A27 gene contained within the element contain a putative open reading frame (ORF) for 428 amino acid residues. We provide evidence that Helitron captured CYP72A27-Zm is transcribed. To identify the progenitor gene and the evolutionary time of capture, we searched the plant genome database and discovered other closely related CYP72A27-Zm genes in maize and grasses. Our analysis indicates that CYP72A27-Zm represents an almost complete copy of maize CYP72A26-Zm gene captured by a Helitron about 3.1 million years ago (mya). The Helitron-captured gene then duplicated twice, approximately 1.5-1.6 mya giving rise to CYP72A36-Zm and CYP72A37-Zm. These data provide evidence that Helitrons can capture and mobilize intact genes that are transcribed and potentially encode biologically relevant proteins.

The Plant Ontology Database: a community resource for plant structure and developmental stages controlled vocabulary and annotations

The Plant Ontology Consortium (POC, http://www.plantontology.org) is a collaborative effort among model plant genome databases and plant researchers that aims to create, maintain and facilitate the use of a controlled vocabulary (ontology) for plants. The ontology allows users to ascribe attributes of plant structure (anatomy and morphology) and developmental stages to data types, such as genes and phenotypes, to provide a semantic framework to make meaningful cross-species and database comparisons. The POC builds upon groundbreaking work by the Gene Ontology Consortium (GOC) by adopting and extending the GOC's principles, existing software and database structure. Over the past year, POC has added hundreds of ontology terms to associate with thousands of genes and gene products from Arabidopsis, rice and maize, which are available through a newly updated web-based browser (http://www.plantontology.org/amigo/go.cgi) for viewing, searching and querying. The Consortium has also implemented new functionalities to facilitate the application of PO in genomic research and updated the website to keep the contents current. In this report, we present a brief description of resources available from the website, changes to the interfaces, data updates, community activities and future enhancement.

PROTEOMIC ANALYSIS AND FRUIT RIPENING

The study of complex biological processes, such as fruit ripening, through comparative proteomics is becoming increasingly attractive to plant biologists as the rapidly expanding plant genomic and EST sequence databases provide improved opportunities for protein identification. This review summarizes some typical experimental approaches that are used to evaluate complex protein populations and to identify differentially expressed proteins. In addition a number of practical issues are highlighted that are associated with comparative proteomic analysis including the challenges of effective protein extraction and separation from problematic plant tissues, that often includes fruits, the pros and cons of 2-D gel-based analysis and the challenge of identifying proteins from species that are not recognized models for functional genomic studies.

BioMOBY Successfully Integrates Distributed Heterogeneous Bioinformatics Web Services. The PlaNet Exemplar Case

The burden of non-interoperability between on-line genomic resources is increasingly the rate-limiting step in large-scale genomic analysis. BioMOBY is a biological Web Service interoperability initiative that began as a retreat of representatives from the model organism database community in September, 2001. Its long-term goal is to provide a simple, extensible platform through which the myriad of on-line biological databases and analytical tools can offer their information and analytical services in a fully automated and interoperable way. Of the two branches of the larger BioMOBY project, the Web Services branch (MOBY-S) has now been deployed over several dozen data sources worldwide, revealing some significant observations about the nature of the integrative biology problem; in particular, that Web Service interoperability in the domain of bioinformatics is, unexpectedly, largely a syntactic rather than a semantic problem. That is to say, interoperability between bioinformatics Web Services can be largely achieved simply by specifying the data structures being passed between the services (syntax) even without rich specification of what those data structures mean (semantics). Thus, one barrier of the integrative problem has been overcome with a surprisingly simple solution. Here, we present a non-technical overview of the critical components that give rise to the interoperable behaviors seen in MOBY-S and discuss an exemplar case, the PlaNet consortium, where MOBY-S has been deployed to integrate the on-line plant genome databases and analytical services provided by a European consortium of databases and data service providers.