Plant Ontology (PO): a Controlled Vocabulary of Plant Structures and Growth Stages

The Plant Ontology Consortium (POC) (www.plantontology.org) is a collaborative effort among several plant databases and experts in plant systematics, botany and genomics. A primary goal of the POC is to develop simple yet robust and extensible controlled vocabularies that accurately reflect the biology of plant structures and developmental stages. These provide a network of vocabularies linked by relationships (ontology) to facilitate queries that cut across datasets within a database or between multiple databases. The current version of the ontology integrates diverse vocabularies used to describe Arabidopsis, maize and rice (Oryza sp.) anatomy, morphology and growth stages. Using the ontology browser, over 3500 gene annotations from three species-specific databases, The Arabidopsis Information Resource (TAIR) for Arabidopsis, Gramene for rice and MaizeGDB for maize, can now be queried and retrieved.     

The Plant Ontology Consortium and plant ontologies

The goal of the Plant Ontology Consortium is to produce structured controlled vocabularies, arranged in ontologies, that can be applied to plant-based database information even as knowledge of the biology of the relevant plant taxa (e.g. development, anatomy, morphology, genomics, proteomics) is accumulating and changing. The collaborators of the Plant Ontology Consortium (POC) represent a number of core participant database groups. The Plant Ontology Consortium is expanding the paradigm of the Gene Ontology Consortium (http://www.geneontology.org). Various trait ontologies (agronomic traits, mutant phenotypes, phenotypes, traits, and QTL) and plant ontologies (plant development, anatomy [incl. morphology]) for several taxa (Arabidopsis, maize/corn/Zea mays and rice/Oryza) are under development. The products of the Plant Ontology Consortium will be open-source.     

Gramene: development and integration of trait and gene ontologies for rice

Gramene (http://www.gramene.org/) is a comparative genome database for cereal crops and a community resource for rice. We are populating and curating Gramene with annotated rice (Oryza sativa) genomic sequence data and associated biological information including molecular markers, mutants, phenotypes, polymorphisms and Quantitative Trait Loci (QTL). In order to support queries across various data sets as well as across external databases, Gramene will employ three related controlled vocabularies. The specific goal of Gramene is, first to provide a Trait Ontology (TO) that can be used across the cereal crops to facilitate phenotypic comparisons both within and between the genera. Second, a vocabulary for plant anatomy terms, the Plant Ontology (PO) will facilitate the curation of morphological and anatomical feature information with respect to expression, localization of genes and gene products and the affected plant parts in a phenotype. The TO and PO are both in the early stages of development in collaboration with the International Rice Research Institute, TAIR and MaizeDB as part of the Plant Ontology Consortium. Finally, as part of another consortium comprising macromolecular databases from other model organisms, the Gene Ontology Consortium, we are annotating the confirmed and predicted protein entries from rice using both electronic and manual curation.     

Zea mays ontology--a database of international terms

Data retrieval, comprehension and sharing within and between plant-based databases are essential to exploit comparative genomic information to elucidate functional aspects of plant biology and to conduct studies of synteny and homology. However, the functionality is often hampered by the variability of terms used to describe comparable objects. The Zea mays Plant Structure Ontology database is designed to overcome this problem via the provision of a controlled vocabulary that facilitates knowledge sharing. It comprises international botanical terms, references, synonyms, and phylogenetic information and is open-source.     

Microarray expression profiling resources for plant genomics

Large volumes of genomic data have been generated for several plant species over the past decade, including structural sequence data and functional annotation at the genome level. Various technologies such as expressed sequence tags (ESTs), massively parallel signature sequencing (MPSS) and microarrays have been used to study gene expression and to provide functional data for many genes simultaneously. This review focuses on recent advances in the application of microarrays in plant genomic research and in gene expression databases available for plants. Large sets of Arabidopsis microarray data are publicly available. Recently developed array platforms are currently being used to generate genome-wide expression profiles for several crop species. Coupled to these platforms are public databases that provide access to these large-scale expression data, which can be used to aid the functional discovery of gene function.     

The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized,curated gateway to Arabidopsis biology,research materials and community

Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.     

GOChase: correcting errors from Gene Ontology-based annotations for gene products

SUMMARY: The Gene Ontology (GO) is a controlled biological vocabulary that provides three structured networks of terms to describe biological processes, cellular components and molecular functions. Many databases of gene products are annotated using the GO vocabularies. We found that some GO-updating operations are not easily traceable by the current biological databases and GO browsers. Consequently, numerous annotation errors arise and are propagated throughout biological databases and GO-based high-level analyses. GOChase is a set of web-based utilities to detect and correct the errors in GO-based annotations.     

It's all GO for plant scientists

The Gene Ontology project (http://www.geneontology.org/) produces structured, controlled vocabularies and gene product annotations. Gene products are classified according to the cellular locations and biological process in which they act, and the molecular functions that they carry out. We annotate gene products from a broad range of model species and provide support for those groups that wish to contribute annotation of further model species. The Gene Ontology facilitates the exchange of information between groups of scientists studying similar processes in different model organisms, and so provides a broad range of opportunities for plant scientists.     

Genome-wide comparative analysis of putative bidirectional promoters from rice, Arabidopsis and Populus

A bidirectional promoter can regulate the expression of two flanking genes arranged in a divergent manner. Although reports pertaining to bidirectional promoters on a genomic scale exist in mammals, little progress has been made in plants. In the present study, we performed a computational analysis of this unique class of promoters to identify overrepresented cis-regulatory motifs from three sequenced plant genomes: rice (Oryza sativa), Arabidopsis thaliana, and Populus trichocarpa using the Plant Cis-acting Regulatory DNA Elements (PLACE) and PLANT CARE databases. We describe these overrepresented elements and their possible regulatory mechanisms. We also discuss similarities and differences with human bidirectional promoters. Furthermore, we describe in detail a few coexpressed and evolutionarily conserved divergent gene pairs and their bidirectional promoters. This study provides insights into bidirectional promoters in three plant species, thereby laying a foundation for their experimental analysis.     

Finding New Order in Biological Functions from the Network Structure of Gene Annotations

The Gene Ontology (GO) provides biologists with a controlled terminology that describes how genes are associated with functions and how functional terms are related to one another. These term-term relationships encode how scientists conceive the organization of biological functions, and they take the form of a directed acyclic graph (DAG). Here, we propose that the network structure of gene-term annotations made using GO can be employed to establish an alternative approach for grouping functional terms that captures intrinsic functional relationships that are not evident in the hierarchical structure established in the GO DAG. Instead of relying on an externally defined organization for biological functions, our approach connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different sources. We show that grouping terms by this alternate scheme provides a new framework with which to describe and predict the functions of experimentally identified sets of genes.     

A Unified Anatomy Ontology of the Vertebrate Skeletal System

The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO), to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish) and multispecies (teleost, amphibian) vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO), Gene Ontology (GO), Uberon, and Cell Ontology (CL), and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity.     

RGMIMS: a web-based Laboratory Information Management System for plant functional genomics research

A robust Laboratory Information Management System (LIMS) is required for the efficient handling of data generated from large-scale insertional mutagenesis projects. The Rice Gene Machine Information Management System (RGMIMS), a web-based modular LIMS, developed in a rice functional genomics laboratory at CSIRO, currently has four core modules: Seed Management, Transformation Management, Plant/Progeny Management, Phenotype Management, and an ad hoc querying module. RGMIMS manages, preserves and tracks large inventories of transgenic germplasm and enables efficient and accurate record keeping of the large quantities of experimental data. RGMIMS automates and seamlessly integrates multi-step experimental processes. A web user interface, incorporating barcoding utilities, enables rapid data capture and tracking of biological resources. Ontologies from Gramene and Plant Ontology consortium are used to describe mutant phenotypes. RGMIMS supports generic research processes in plant mutagenesis and could readily be adapted to general LIMS for high-throughput plant research.     

NetAffx: Affymetrix probesets and annotations

NetAffx (http://www.affymetrix.com) details and annotates probesets on Affymetrix GeneChip microarrays. These annotations include (i) static information specific to the probeset composition; (ii) sequence annotations extracted from public databases; and (iii) protein sequence-level annotations derived from public domain programs, as well as libraries of hidden Markov models (HMMs) developed at Affymetrix. For each probeset, NetAffx lists the probe sequences, and the consensus sequence interrogated by the probes; for the larger chip sets, interactive maps display this sequence data in genomic context. Sequence annotations include Gene Ontology (GO) terms and depiction of GO graph relationships; predicted protein domains and motifs; orthologous sequences; links to relevant pathways; and links to public databases including UniGene, LocusLink, SWISS-PROT and OMIM.