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The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) is a comprehensive web resource of Arabidopsis biology for plant scientists. TAIR curates and integrates information about genes, proteins, gene function, orthologs, gene expression, mutant phenotypes, biological materials such as clones and seed stocks, genetic markers, genetic and physical maps, genome organization, images of mutant plants, protein sub-cellular localizations, publications, and the research community. The various data types are extensively interconnected and can be accessed through a variety of web-based search and display tools. This article primarily focuses on some basic methods for searching, browsing, visualizing, and analyzing information about Arabidopsis genes and genomes. Additionally, we describe how members of the community can share data via JBrowse and the Generic Online Annotation Submission Tool (GOAT) in order to make their published research more accessible and visible. © 2022 Wiley Periodicals LLC. Basic Protocol 1: TAIR homepage, sitemap, and navigation Basic Protocol 2: Finding comprehensive information about Arabidopsis genes Basic Protocol 3: Using the Arabidopsis genome browser: JBrowse Basic Protocol 4: Using the Gene Ontology annotations for gene discovery and gene function analysis Basic Protocol 5: Using gene lists to download bulk datasets Basic Protocol 6: Using TAIR's analysis tools to find short sequences and motifs Basic Protocol 7: Using the TAIR generic online annotation tool (GOAT) to submit functional annotations for Arabidopsis (or any other species) genes Basic Protocol 8: Using PhyloGenes to visualize gene families and predict functions Basic Protocol 9: Using TAIR to browse Arabidopsis literature Basic Protocol 10: Using the synteny viewer to find and display syntenic regions from Arabidopsis and other plant species.

Ban et al. (2014) proposed a nomenclature for ribosomal proteins (r-proteins) that reflects the current understanding of ribosomal protein evolution. In the past few years, this nomenclature has been widely adopted among biomedical researchers and microbiologists. This homology-based r-protein nomenclature has not been as widely adopted among plant biologists, however, presumably because r-protein nomenclature is much more complicated in plants due to gene duplication. Here, we propose compatible upgrades to the homology-guided nomenclature proposed by Ban et al. (2014) so that this naming system can be adopted for widespread use in the plant biology community. We note that Lan et al. (2022) recently proposed updated nomenclature for plant cytosolic ribosomal proteins, focused on Arabidopsis and rice. The nomenclature outlined here is an extension of that proposed by Lan et al. (2022), expanding to include organellar ribosomes and additional species, with the intent that this nomenclature can serve as a template to guide future plant genome annotations. A more detailed comparison highlighting how this naming system builds on the Ban et al. (2014) and Lan et al. (2022) nomenclatures is offered below.At this time, we request community feedback on this proposed nomenclature so that the naming system ultimately chosen represents a broad consensus. Feedback can be communicated to the this working group at plantribosome@gmail.com before July 25th, 2022. Coauthors of this letter and anyone in the scientific community expressing significant interest will then discuss this feedback as a group, reach a consensus agreement, and communicate the updated nomenclature rules through a letter to the editor (expected to be published at The Plant Cell) and the databases at TAIR and MaizeGDB.

High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The representation of high-throughput data in the Gene Ontology (GO) therefore presents a challenging annotation problem, when the overarching goal of GO curation is to provide the most precise view of a gene's role in biology. To address this, representatives from annotation teams within the GO Consortium reviewed high-throughput data annotation practices. We present an annotation framework for high-throughput studies that will facilitate good standards in GO curation and, through the use of new high-throughput evidence codes, increase the visibility of these annotations to the research community.

The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the ‘GO ribbon’ widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page. This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© The Author(s) 2018. Published by Oxford University Press. The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.

The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) is a comprehensive Web resource of Arabidopsis biology for plant scientists. TAIR curates and integrates information about genes, proteins, gene function, orthologs, gene expression, mutant phenotypes, biological materials such as clones and seed stocks, genetic markers, genetic and physical maps, genome organization, images of mutant plants, protein sub-cellular localizations, publications, and the research community. The various data types are extensively interconnected and can be accessed through a variety of Web-based search and display tools. This unit primarily focuses on some basic methods for searching, browsing, visualizing, and analyzing information about Arabidopsis genes and genome. Additionally, we describe how members of the community can share data using TAIR's Online Annotation Submission Tool (TOAST), in order to make their published research more accessible and visible. © 2017 by John WileySons, Inc.

The Arabidopsis Information Resource (TAIR) is a continuously updated, online database of genetic and molecular biology data for the model plant Arabidopsis thaliana that provides a global research community with centralized access to data for over 30,000 Arabidopsis genes. TAIR's biocurators systematically extract, organize, and interconnect experimental data from the literature along with computational predictions, community submissions, and high throughput datasets to present a high quality and comprehensive picture of Arabidopsis gene function. TAIR provides tools for data visualization and analysis, and enables ordering of seed and DNA stocks, protein chips, and other experimental resources. TAIR actively engages with its users who contribute expertise and data that augments the work of the curatorial staff. TAIR's focus in an extensive and evolving ecosystem of online resources for plant biology is on the critically important role of extracting experimentally based research findings from the literature and making that information computationally accessible. In response to the loss of government grant funding, the TAIR team founded a nonprofit entity, Phoenix Bioinformatics, with the aim of developing sustainable funding models for biological databases, using TAIR as a test case. Phoenix has successfully transitioned TAIR to subscription-based funding while still keeping its data relatively open and accessible.

Literature curation by model organism databases (MODs) results in the interconnection of papers, genes, gene functions, and other experimentally supported biological information, and aims to make research data more discoverable and accessible to the research community. That said, there is a paucity of quantitative data about if and how literature curation affects access and reuse of the curated data. One potential measure of data reuse is the citation rate of the article used in curation. If articles and their corresponding data are easier to find, then we might expect that curated articles would exhibit different citation profiles when compared to articles that are not curated. That is, what are the effects of having scholarly articles curated by MODs on their citation rates? To address this question we have been comparing the citation behavior of different groups of articles and asking the following questions: (1) given a collection of 'similar' articles about Arabidopsis, is there a difference in the citation numbers between articles that have been curated in TAIR (The Arabidopsis Information Resource) and ones that have not, (2) for articles annotated in TAIR, is there a difference in the citation behavior before vs. after curation and, (3) is there a difference in citation behavior between Arabidopsis articles added to TAIR's database and those that are not in TAIR? Our data indicate that curated articles do have a different citation profile than non-curated articles that appears to result from increased visibility in TAIR. We believe data of this type could be used to quantify the impact of literature curation on data reuse and may also be useful for MODs and funders seeking incentives for community literature curation. This project is a research partnership between TAIR and Elsevier Labs.

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.

The Arabidopsis Information Resource (TAIR) is a continuously updated, online database of genetic and molecular biology data for the model plant Arabidopsis thaliana that provides a global research community with centralized access to data for over 30,000 Arabidopsis genes. TAIR's biocurators systematically extract, organize, and interconnect experimental data from the literature along with computational predictions, community submissions, and high throughput datasets to present a high quality and comprehensive picture of Arabidopsis gene function. TAIR provides tools for data visualization and analysis, and enables ordering of seed and DNA stocks, protein chips, and other experimental resources. TAIR actively engages with its users who contribute expertise and data that augments the work of the curatorial staff. TAIR's focus in an extensive and evolving ecosystem of online resources for plant biology is on the critically important role of extracting experimentally based research findings from the literature and making that information computationally accessible. In response to the loss of government grant funding, the TAIR team founded a nonprofit entity, Phoenix Bioinformatics, with the aim of developing sustainable funding models for biological databases, using TAIR as a test case. Phoenix has successfully transitioned TAIR to subscription-based funding while still keeping its data relatively open and accessible.

Formal description of plant phenotypes and standardized annotation of gene expression and protein localization data require uniform terminology that accurately describes plant anatomy and morphology. This facilitates cross species comparative studies and quantitative comparison of phenotypes and expression patterns. A major drawback is variable terminology that is used to describe plant anatomy and morphology in publications and genomic databases for different species. The same terms are sometimes applied to different plant structures in different taxonomic groups. Conversely, similar structures are named by their species-specific terms. To address this problem, we created the Plant Structure Ontology (PSO), the first generic ontological representation of anatomy and morphology of a flowering plant. The PSO is intended for a broad plant research community, including bench scientists, curators in genomic databases, and bioinformaticians. The initial releases of the PSO integrated existing ontologies for Arabidopsis (Arabidopsis thaliana), maize (Zea mays), and rice (Oryza sativa); more recent versions of the ontology encompass terms relevant to Fabaceae, Solanaceae, additional cereal crops, and poplar (Populus spp.). Databases such as The Arabidopsis Information Resource, Nottingham Arabidopsis Stock Centre, Gramene, MaizeGDB, and SOL Genomics Network are using the PSO to describe expression patterns of genes and phenotypes of mutants and natural variants and are regularly contributing new annotations to the Plant Ontology database. The PSO is also used in specialized public databases, such as BRENDA, GENEVESTIGATOR, NASCArrays, and others. Over 10,000 gene annotations and phenotype descriptions from participating databases can be queried and retrieved using the Plant Ontology browser. The PSO, as well as contributed gene associations, can be obtained at www.plantontology.org.

Plant growth stages are identified as distinct morphological landmarks in a continuous developmental process. The terms describing these developmental stages record the morphological appearance of the plant at a specific point in its life cycle. The widely differing morphology of plant species consequently gave rise to heterogeneous vocabularies describing growth and development. Each species or family specific community developed distinct terminologies for describing whole-plant growth stages. This semantic heterogeneity made it impossible to use growth stage description contained within plant biology databases to make meaningful computational comparisons. The Plant Ontology Consortium (http://www.plantontology.org) was founded to develop standard ontologies describing plant anatomical as well as growth and developmental stages that can be used for annotation of gene expression patterns and phenotypes of all flowering plants. In this article, we describe the development of a generic whole-plant growth stage ontology that describes the spatiotemporal stages of plant growth as a set of landmark events that progress from germination to senescence. This ontology represents a synthesis and integration of terms and concepts from a variety of species-specific vocabularies previously used for describing phenotypes and genomic information. It provides a common platform for annotating gene function and gene expression in relation to the developmental trajectory of a plant described at the organismal level. As proof of concept the Plant Ontology Consortium used the plant ontology growth stage ontology to annotate genes and phenotypes in plants with initial emphasis on those represented in The Arabidopsis Information Resource, Gramene database, and MaizeGDB.

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 describeArabidopsis, maize and rice (Oryzasp.) anatomy, morphology and growth stages. Using the ontology browser, over 3500 gene annotations from three species-specific databases, The Arabidopsis Information Resource (TAIR) forArabidopsis, Gramene for rice and MaizeGDB for maize, can now be queried and retrieved.

Controlled vocabularies are increasingly used by databases to describe genes and gene products because they facilitate identification of similar genes within an organism or among different organisms. One of The Arabidopsis Information Resource's goals is to associate all Arabidopsis genes with terms developed by the Gene Ontology Consortium that describe the molecular function, biological process, and subcellular location of a gene product. We have also developed terms describing Arabidopsis anatomy and developmental stages and use these to annotate published gene expression data. As of March 2004, we used computational and manual annotation methods to make 85,666 annotations representing 26,624 unique loci. We focus on associating genes to controlled vocabulary terms based on experimental data from the literature and use The Arabidopsis Information Resource-developed PubSearch software to facilitate this process. Each annotation is tagged with a combination of evidence codes, evidence descriptions, and references that provide a robust means to assess data quality. Annotation of all Arabidopsis genes will allow quantitative comparisons between sets of genes derived from sources such as microarray experiments. The Arabidopsis annotation data will also facilitate annotation of newly sequenced plant genomes by using sequence similarity to transfer annotations to homologous genes. In addition, complete and up-to-date annotations will make unknown genes easy to identify and target for experimentation. Here, we describe the process of Arabidopsis functional annotation using a variety of data sources and illustrate several ways in which this information can be accessed and used to infer knowledge about Arabidopsis and other plant species.

The National Science Foundation’s recent mandate that all Principal Investigators address the broader impacts of their research has prompted an unprecedented number of scientists to seek opportunities to participate in precollege education and outreach. To help interested geneticists avoid duplicating efforts and make use of existing resources, we examined several precollege genetics, genomics, and biotechnology education efforts and noted the elements that contributed to their success, indicated by program expansion, participant satisfaction, or participant learning. Identifying a specific audience and their needs and resources, involving K–12 teachers in program development, and evaluating program efforts are integral to program success. We highlighted a few innovative programs to illustrate these findings. Challenges that may compromise further development and dissemination of these programs include absence of reward systems for participation in outreach as well as lack of training for scientists doing outreach. Several programs and institutions are tackling these issues in ways that will help sustain outreach efforts while allowing them to be modified to meet the changing needs of their participants, including scientists, teachers, and students. Most importantly, resources and personnel are available to facilitate greater and deeper involvement of scientists in precollege and public education.

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.

The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) provides an integrated view of genomic data for Arabidopsis thaliana. The information is obtained from a battery of sources, including the Arabidopsis user community, the literature, and the major genome centers. Currently TAIR provides information about genes, markers, polymorphisms, maps, sequences, clones, DNA and seed stocks, gene families and proteins. In addition, users can find Arabidopsis publications and information about Arabidopsis researchers. Our emphasis is now on incorporating functional annotations of genes and gene products, genome-wide expression, and biochemical pathway data. Among the tools developed at TAIR, the most notable is the Sequence Viewer, which displays gene annotation, clones, transcripts, markers and polymorphisms on the Arabidopsis genome, and allows zooming in to the nucleotide level. A tool recently released is AraCyc, which is designed for visualization of biochemical pathways. We are also developing tools to extract information from the literature in a systematic way, and building controlled vocabularies to describe biological concepts in collaboration with other database groups. A significant new feature is the integration of the ABRC database functions and stock ordering system, which allows users to place orders for seed and DNA stocks directly from the TAIR site.

Arabidopsis thaliana, a small annual plant belonging to the mustard family, is the subject of study by an estimated 7000 researchers around the world. In addition to the large body of genetic, physiological and biochemical data gathered for this plant, it will be the first higher plant genome to be completely sequenced, with completion expected at the end of the year 2000. The sequencing effort has been coordinated by an international collaboration, the Arabidopsis Genome Initiative (AGI). The rationale for intensive investigation of Arabidopsis is that it is an excellent model for higher plants. In order to maximize use of the knowledge gained about this plant, there is a need for a comprehensive database and information retrieval and analysis system that will provide user-friendly access to Arabidopsis information. This paper describes the initial steps we have taken toward realizing these goals in a project called The Arabidopsis Information Resource (TAIR) (www.arabidopsis.org).

Knotted-like homeobox (knox) genes constitute a gene family in plants. Class I knox genes are expressed in shoot apical meristems, and (with notable exceptions) not in lateral organ primordia. Class II genes have more diverse expression patterns. Loss and gain of function mutations indicate that knox genes are important regulators of meristem function. Gene duplication has contributed to the evolution of families of homeodomain proteins in metazoans. We believe that similar mechanisms have contributed to the diversity of knox gene function in plants. Knox genes may have contributed to the evolution of compound leaves in tomato and could be involved in the evolution of morphological traits in other species. Alterations in cis-regulatory regions in some knox genes correlate with novel patterns of gene expression and distinctive morphologies. Preliminary data from the analysis of class I knox gene expression illustrates the evolution of complex patterns of knox expression is likely to have occurred through loss and gain of domains of gene expression.

The volume of Arabidopsis information has increased enormously in recent years as a result of the sequencing of the reference genome and other large-scale functional genomics projects. Much of the data is stored in public databases, where data are organized, analyzed, and made freely accessible to the research community. These databases are resources that researchers can utilize for making predictions and developing testable hypotheses. The methods in this chapter describe ways to access and utilize Arabidopsis data and genomic resources found in databases and stock centers.

Ovules play a central role in plant reproduction, generating the female gametophyte within sporophytic integuments. When fertilized, the integuments differentiate into the seed coat and support the development of the embryo and endosperm. Mutations in the AINTEGUMENTA (ANT) locus of Arabidopsis have a profound effect on ovule development. Strong ant mutants have ovules that fail to form integuments or a female gametophyte. Flower development is also altered, with a random reduction of organs in the outer three whorls. In addition, organs present in the outer three floral whorls often have abnormal morphology. Ovules from a weak ant mutant contain both inner and outer integuments but generally fail to produce a functional female gametophyte. We isolated the ANT gene by using a mutation derived by T-DNA insertional mutagenesis. ANT is a member of a gene family that includes the floral homeotic gene APETALA2 (AP2). Like AP2, ANT contains two AP2 domains homologous with the DNA binding domain of ethylene response element binding proteins. ANT is expressed most highly in developing flowers but is also expressed in vegetative tissue. Taken together, these results suggest that ANT is a transcription factor that plays a critical role in regulating ovule and female gametophyte development.

Databases and data repositories provide essential functions for the research community by integrating, curating, archiving and otherwise packaging data to facilitate discovery and reuse. Despite their importance, funding for maintenance of these resources is increasingly hard to obtain. Fueled by a desire to find long term, sustainable solutions to database funding, staff from the Arabidopsis Information Resource (TAIR), founded the nonprofit organization, Phoenix Bioinformatics, using TAIR as a test case for user-based funding. Subscription-based funding has been proposed as an alternative to grant funding but its application has been very limited within the nonprofit sector. Our testing of this model indicates that it is a viable option, at least for some databases, and that it is possible to strike a balance that maximizes access while still incentivizing subscriptions. One year after transitioning to subscription support, TAIR is self-sustaining and Phoenix is poised to expand and support additional resources that wish to incorporate user-based funding strategies. Database URL: www.arabidopsis.org.

The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) is a comprehensive Web resource of Arabidopsis biology for plant scientists. TAIR curates and integrates information about genes, proteins, gene function, gene expression, mutant phenotypes, biological materials such as clones and seed stocks, genetic markers, genetic and physical maps, biochemical pathways, genome organization, images of mutant plants, protein sub-cellular localizations, publications, and the research community. The various data types are extensively interconnected and can be accessed through a variety of Web-based search and display tools. This unit primarily focuses on some basic methods for searching, browsing, visualizing, and analyzing information about Arabidopsis genes and describes several new tools such as a new TAIR genome browser (GBrowse), and the TAIR synteny viewer (GBrowse_syn). We also describe how to use AraCyc for mining plant metabolic pathways.

The volume of Arabidopsis information has increased enormously in recent years as a result of the sequencing of the genome and other large-scale genomic projects. Much of the data are stored in public databases, where data are organized, analyzed, and made freely accessible to the research community. These databases are resources that researchers can utilize for making predictions and developing testable hypotheses. The methods in this chapter describe ways to access and utilize Arabidopsis data and genomic resources found in databases.

The volume of Arabidopsis information has increased enormously in recent years as a result of the sequencing of the genome and other large-scale genomic projects. Much of the data are stored in public databases, where data are organized, analyzed, and made freely accessible to the research community. These databases are resources that researchers can utilize for making predictions and developing testable hypotheses. The methods in this chapter describe ways to access and utilize Arabidopsis data and genomic resources found in databases.

The Arabidopsis Information Resource (TAIR; http://www.arabidopsis.org) is a comprehensive Web resource of Arabidopsis biology for plant scientists. TAIR curates and integrates information about genes, proteins, gene expression, mutant phenotypes, biological materials such as DNA and seed stocks, genetic markers, genetic and physical maps, biochemical pathways, genome organization, images of mutant plants and protein sub-cellular localizations, publications, and the research community Data in TAIR are extensively interconnected and can be accessed through a variety of Web-based search and display tools. This unit primarily focuses on some basic methods for searching, browsing, visualizing, and analyzing information about Arabidopsis genes. Gene expression data from microarrays is a recent addition to the database and methods for accessing these data are also described. Two pattern identification programs are described for mining TAIR's unique Arabidopsis sequence data sets. We also describe how to use AraCyc for mining plant metabolic pathways.

Exponential growth of data, largely from whole-genome analyses, has changed the way biologists think about and handle data. Optimal use of these data requires effective methods to analyze and manage these data sets. Computers, software and the World Wide Web are now integral components of biological discovery. Understanding how information is obtained, processed and annotated in public databases allows researchers to effectively organize, analyze and export their own data into these databases. In this review we focus largely on two areas related to management of genomic data. We cite examples of resources available in the public domain and describe some of the software for data management systems currently available for plant research. In addition, we discuss a few concepts of data management from the perspective of an individual or group that wishes to provide data to the public databases, to use the information in the public databases more efficiently, or to develop a database to manage large data sets internally or for public access. These concepts include data descriptions, exchange format, curation, attribution, and database implementation.

Exponential growth of data, largely from whole-genome analyses, has changed the way biologists think about and handle data. Optimal use of these data requires effective methods to analyze and manage these data sets. Computers, software and the World Wide Web are now integral components of biological discovery. Understanding how information is obtained, processed and annotated in public databases allows researchers to effectively organize, analyze and export their own data into these databases. In this review we focus largely on two areas related to management of genomic data. We cite examples of resources available in the public domain and describe some of the software for data management systems currently available for plant research. In addition, we discuss a few concepts of data management from the perspective of an individual or group that wishes to provide data to the public databases, to use the information in the public databases more efficiently, or to develop a database to manage large data sets internally or for public access. These concepts include data descriptions, exchange format, curation, attribution, and database implementation.

GeneCalling, a new expression profiling technique, has been used to elucidate regulatory gene networks in plants.

Ovule development in Arabidopsis involves the formation of three morphologically defined proximal-distal pattern elements. Integuments arise from the central pattern element. Analysis of Bell1 (Bell) mutant ovules indicated that BEL1 was required for integument development. Cloning of the BEL1 locus reveals that it encodes a homeodomain transcription factor. Prior to integument initiation, BEL1 RNA localizes to the central domain, providing molecular evidence for a central pattern element. Therefore, proximal-distal patterning of the ovule involves the regulated expression of the BEL1 gene that controls integument morphogenesis. A model for BEL1 function is evaluated with regard to new data showing the expression pattern of the floral homeotic gene AGAMOUS (AG) early in wild-type and Bell ovule development.

The plant life cycle is characterized by the alternation of generations between a diploid sporophyte and a haploid gametophyte. The sporophyte functions to produce spores, which then develop into gametophytes. The differentiated gametophytes in turn produce either the male gametes (sperm) or female gametes (egg cells). In contrast to lower plant species, in which the gametophyte is the dominant, free-living generation (see Cove and Knight, 1993, this issue), gametophytes of angiosperms are smaller and less complex than the sporophyte and are formed within specialized organs of the flower. The male gametophyte (pollen or microgametophyte) develops within the anther, whereas the female gametophyte (embryo sac or megagametophyte) is a product of the ovule. Sexual reproduction requires the delivery of the sperm nuclei, via the pollen, to the embryo sac, where fertilization occurs and the new diploid sporophyte is formed (see Dumas and Mogensen, 1993, this issue).

The knotted1 (kn1) gene of maize is expressed in meristems and is absent from leaves, including the site of leaf initiation within the meristem. Recessive mutations of kn1 have been described that limit the capacity to make branches and result in extra carpels. Dominant mutations suggest that kn1 function plays a role in maintaining cells in an undifferentiated state. We took advantage of a Ds-induced dominant allele in order to screen for additional recessive alleles resulting from mobilization of the Ds element. Analysis of one such allele revealed a novel embryonic shoot phenotype in which the shoot initiated zero to few organs after the cotyledon was made, resulting in plants that arrested as seedlings. We refer to this phenotype as a limited shoot. The limited shoot phenotype reflected loss of kn1 function, but its penetrance was background dependent. We examined meristem size and found that plants lacking kn1 function had shorter meristems than non-mutant siblings. Furthermore, meristems of restrictive inbreds were significantly shorter than meristems of permissive inbreds, implying a correlation between meristem height and kn1 gene function in the embryo. Analysis of limited shoot plants during embryogenesis indicated a role for kn1 in shoot meristem maintenance. We discuss a model for kn1 in maintenance of the morphogenetic zone of the shoot apical meristem.