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As one of the first model organism knowledgebases, Saccharomyces Genome Database (SGD) has been supporting the scientific research community since 1993. As technologies and research evolve, so does SGD: from updates in software architecture, to curation of novel data types, to incorporation of data from, and collaboration with, other knowledgebases. We are continuing to make steps toward providing the community with an S. cerevisiae pan-genome. Here, we describe software upgrades, a new nomenclature system for genes not found in the reference strain, and additions to gene pages. With these improvements, we aim to remain a leading resource for students, researchers, and the broader scientific community., Competing Interests: Conflicts of interest None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Genetics Society of America.)

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project., Competing Interests: Conflicts of interest The authors declare no conflicts of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America.)

Saccharomyces cerevisiae is used to provide fundamental understanding of eukaryotic genetics, gene product function, and cellular biological processes. Saccharomyces Genome Database (SGD) has been supporting the yeast research community since 1993, serving as its de facto hub. Over the years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation, and developed various tools and methods for analysis and curation of a variety of emerging data types. More recently, SGD and six other model organism focused knowledgebases have come together to create the Alliance of Genome Resources to develop sustainable genome information resources that promote and support the use of various model organisms to understand the genetic and genomic bases of human biology and disease. Here we describe recent activities at SGD, including the latest reference genome annotation update, the development of a curation system for mutant alleles, and new pages addressing homology across model organisms as well as the use of yeast to study human disease., (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America.)

The Candida Genome Database provides access to biological information about genes and proteins of several medically important Candida species. The website is organized into easily navigable pages that enable data retrieval and analysis. This chapter shows how to explore the CGD Home page and Locus Summary pages, which are the main access points to the database. It also provides a description of how to use the GO analysis tools, GO Term Finder, and GO Slim Mapper and how to browse large-scale datasets using the JBrowse genome browser. Finally, it shows how to search and retrieve data for user-defined sets of genes using the Advanced Search and Batch Download tools., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The Saccharomyces Genome Database (SGD; www.yeastgenome.org) maintains the official annotation of all genes in the Saccharomyces cerevisiae reference genome and aims to elucidate the function of these genes and their products by integrating manually curated experimental data. Technological advances have allowed researchers to profile RNA expression and identify transcripts at high resolution. These data can be configured in web-based genome browser applications for display to the general public. Accordingly, SGD has incorporated published transcript isoform data in our instance of JBrowse, a genome visualization platform. This resource will help clarify S. cerevisiae biological processes by furthering studies of transcriptional regulation, untranslated regions, genome engineering, and expression quantification in S. cerevisiae., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Proteins seldom function individually. Instead, they interact with other proteins or nucleic acids to form stable macromolecular complexes that play key roles in important cellular processes and pathways. One of the goals of Saccharomyces Genome Database (SGD; www.yeastgenome.org) is to provide a complete picture of budding yeast biological processes. To this end, we have collaborated with the Molecular Interactions team that provides the Complex Portal database at EMBL-EBI to manually curate the complete yeast complexome. These data, from a total of 589 complexes, were previously available only in SGD's YeastMine data warehouse (yeastmine.yeastgenome.org) and the Complex Portal (www.ebi.ac.uk/complexportal). We have now incorporated these macromolecular complex data into the SGD core database and designed complex-specific reports to make these data easily available to researchers. These web pages contain referenced summaries focused on the composition and function of individual complexes. In addition, detailed information about how subunits interact within the complex, their stoichiometry and the physical structure are displayed when such information is available. Finally, we generate network diagrams displaying subunits and Gene Ontology annotations that are shared between complexes. Information on macromolecular complexes will continue to be updated in collaboration with the Complex Portal team and curated as more data become available.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is an expertly curated database of literature-derived functional information for the model organism budding yeast, Saccharomyces cerevisiae. SGD constantly strives to synergize new types of experimental data and bioinformatics predictions with existing data, and to organize them into a comprehensive and up-to-date information resource. The primary mission of SGD is to facilitate research into the biology of yeast and to provide this wealth of information to advance, in many ways, research on other organisms, even those as evolutionarily distant as humans. To build such a bridge between biological kingdoms, SGD is curating data regarding yeast-human complementation, in which a human gene can successfully replace the function of a yeast gene, and/or vice versa. These data are manually curated from published literature, made available for download, and incorporated into a variety of analysis tools provided by SGD., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Studying Candida biology requires access to genomic sequence data in conjunction with experimental information that together provide functional context to genes and proteins, and aid in interpreting newly generated experimental data. The Candida Genome Database (CGD) curates the Candida literature, and integrates functional information about Candida genes and their products with a set of analysis tools that facilitate searching for sets of genes and exploring their biological roles. This chapter describes how the various types of information available at CGD can be searched, retrieved, and analyzed. Starting with the guided tour of the CGD Home page and Locus Summary page, this unit shows how to navigate the various assemblies of the C. albicans genome, how to use Gene Ontology tools to make sense of large-scale data, and how to access the microarray data archived at CGD, as well as visualize high-throughput sequencing data through the use of JBrowse.

Database Url: http://www.yeastgenome.org.

The Candida Genome Database (CGD, http://www.candidagenome.org/) is a freely available online resource that provides gene, protein and sequence information for multiple Candida species, along with web-based tools for accessing, analyzing and exploring these data. The mission of CGD is to facilitate and accelerate research into Candida pathogenesis and biology, by curating the scientific literature in real time, and connecting literature-derived annotations to the latest version of the genomic sequence and its annotations. Here, we report the incorporation into CGD of Assembly 22, the first chromosome-level, phased diploid assembly of the C. albicans genome, coupled with improvements that we have made to the assembly using additional available sequence data. We also report the creation of systematic identifiers for C. albicans genes and sequence features using a system similar to that adopted by the yeast community over two decades ago. Finally, we describe the incorporation of JBrowse into CGD, which allows online browsing of mapped high throughput sequencing data, and its implementation for several RNA-Seq data sets, as well as the whole genome sequencing data that was used in the construction of Assembly 22., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The Saccharomyces Genome Database (SGD; www.yeastgenome.org ), the primary genetics and genomics resource for the budding yeast S. cerevisiae , provides free public access to expertly curated information about the yeast genome and its gene products. As the central hub for the yeast research community, SGD engages in a variety of social outreach efforts to inform our users about new developments, promote collaboration, increase public awareness of the importance of yeast to biomedical research, and facilitate scientific discovery. Here we describe these various outreach methods, from networking at scientific conferences to the use of online media such as blog posts and webinars, and include our perspectives on the benefits provided by outreach activities for model organism databases., Database Url: http://www.yeastgenome.org., (© The Author(s) 2017. Published by Oxford University Press.)

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Studying Candida biology requires access to genomic sequence data in conjunction with experimental information that provides functional context to genes and proteins. The Candida Genome Database (CGD) integrates functional information about Candida genes and their products with a set of analysis tools that facilitate searching for sets of genes and exploring their biological roles. This chapter describes how the various types of information available at CGD can be searched, retrieved, and analyzed. Starting with the guided tour of the CGD Home page and Locus Summary page, this unit shows how to navigate the various assemblies of the C. albicans genome, how to use Gene Ontology tools to make sense of large-scale data, and how to access the microarray data archived at CGD.

Saccharomyces Genome Database is an online resource dedicated to managing information about the biology and genetics of the model organism, yeast (Saccharomyces cerevisiae). This information is derived primarily from scientific publications through a process of human curation that involves manual extraction of data and their organization into a comprehensive system of knowledge. This system provides a foundation for further analysis of experimental data coming from research on yeast as well as other organisms. In this review we will demonstrate how biocuration and biocurators add a key component, the biological context, to our understanding of how genes, proteins, genomes and cells function and interact. We will explain the role biocurators play in sifting through the wealth of biological data to incorporate and connect key information. We will also discuss the many ways we assist researchers with their various research needs. We hope to convince the reader that manual curation is vital in converting the flood of data into organized and interconnected knowledge, and that biocurators play an essential role in the integration of scientific information into a coherent model of the cell., (© 2015 Wiley Periodicals, Inc.)

Cryptococcus, a major cause of disseminated infections in immunocompromised patients, kills over 600,000 people per year worldwide. Genes involved in the virulence of the meningitis-causing fungus are being characterized at an increasing rate, and to date, at least 648 Cryptococcus gene names have been published. However, these data are scattered throughout the literature and are challenging to find. Furthermore, conflicts in locus identification exist, so that named genes have been subsequently published under new names or names associated with one locus have been used for another locus. To avoid these conflicts and to provide a central source of Cryptococcus gene information, we have collected all published Cryptococcus gene names from the scientific literature and associated them with standard Cryptococcus locus identifiers and have incorporated them into FungiDB (www.fungidb.org). FungiDB is a panfungal genome database that collects gene information and functional data and provides search tools for 61 species of fungi and oomycetes. We applied these published names to a manually curated ortholog set of all Cryptococcus species currently in FungiDB, including Cryptococcus neoformans var. neoformans strains JEC21 and B-3501A, C. neoformans var. grubii strain H99, and Cryptococcus gattii strains R265 and WM276, and have written brief descriptions of their functions. We also compiled a protocol for gene naming that summarizes guidelines proposed by members of the Cryptococcus research community. The centralization of genomic and literature-based information for Cryptococcus at FungiDB will help researchers communicate about genes of interest, such as those related to virulence, and will further facilitate research on the pathogen., (Copyright © 2014, American Society for Microbiology. All Rights Reserved.)

The genome of the budding yeast Saccharomyces cerevisiae was the first completely sequenced from a eukaryote. It was released in 1996 as the work of a worldwide effort of hundreds of researchers. In the time since, the yeast genome has been intensively studied by geneticists, molecular biologists, and computational scientists all over the world. Maintenance and annotation of the genome sequence have long been provided by the Saccharomyces Genome Database, one of the original model organism databases. To deepen our understanding of the eukaryotic genome, the S. cerevisiae strain S288C reference genome sequence was updated recently in its first major update since 1996. The new version, called "S288C 2010," was determined from a single yeast colony using modern sequencing technologies and serves as the anchor for further innovations in yeast genomic science.

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available web-based resource that was designed for Aspergillus researchers and is also a valuable source of information for the entire fungal research community. In addition to being a repository and central point of access to genome, transcriptome and polymorphism data, AspGD hosts a comprehensive comparative genomics toolbox that facilitates the exploration of precomputed orthologs among the 20 currently available Aspergillus genomes. AspGD curators perform gene product annotation based on review of the literature for four key Aspergillus species: Aspergillus nidulans, Aspergillus oryzae, Aspergillus fumigatus and Aspergillus niger. We have iteratively improved the structural annotation of Aspergillus genomes through the analysis of publicly available transcription data, mostly expressed sequenced tags, as described in a previous NAR Database article (Arnaud et al. 2012). In this update, we report substantive structural annotation improvements for A. nidulans, A. oryzae and A. fumigatus genomes based on recently available RNA-Seq data. Over 26 000 loci were updated across these species; although those primarily comprise the addition and extension of untranslated regions (UTRs), the new analysis also enabled over 1000 modifications affecting the coding sequence of genes in each target genome.

The Candida Genome Database (CGD, http://www.candidagenome.org/) is a freely available online resource that provides gene, protein and sequence information for multiple Candida species, along with web-based tools for accessing, analyzing and exploring these data. The goal of CGD is to facilitate and accelerate research into Candida pathogenesis and biology. The CGD Web site is organized around Locus pages, which display information collected about individual genes. Locus pages have multiple tabs for accessing different types of information; the default Summary tab provides an overview of the gene name, aliases, phenotype and Gene Ontology curation, whereas other tabs display more in-depth information, including protein product details for coding genes, notes on changes to the sequence or structure of the gene and a comprehensive reference list. Here, in this update to previous NAR Database articles featuring CGD, we describe a new tab that we have added to the Locus page, entitled the Homology Information tab, which displays phylogeny and gene similarity information for each locus.

Background: Secondary metabolite production, a hallmark of filamentous fungi, is an expanding area of research for the Aspergilli. These compounds are potent chemicals, ranging from deadly toxins to therapeutic antibiotics to potential anti-cancer drugs. The genome sequences for multiple Aspergilli have been determined, and provide a wealth of predictive information about secondary metabolite production. Sequence analysis and gene overexpression strategies have enabled the discovery of novel secondary metabolites and the genes involved in their biosynthesis. The Aspergillus Genome Database (AspGD) provides a central repository for gene annotation and protein information for Aspergillus species. These annotations include Gene Ontology (GO) terms, phenotype data, gene names and descriptions and they are crucial for interpreting both small- and large-scale data and for aiding in the design of new experiments that further Aspergillus research., Results: We have manually curated Biological Process GO annotations for all genes in AspGD with recorded functions in secondary metabolite production, adding new GO terms that specifically describe each secondary metabolite. We then leveraged these new annotations to predict roles in secondary metabolism for genes lacking experimental characterization. As a starting point for manually annotating Aspergillus secondary metabolite gene clusters, we used antiSMASH (antibiotics and Secondary Metabolite Analysis SHell) and SMURF (Secondary Metabolite Unknown Regions Finder) algorithms to identify potential clusters in A. nidulans, A. fumigatus, A. niger and A. oryzae, which we subsequently refined through manual curation., Conclusions: This set of 266 manually curated secondary metabolite gene clusters will facilitate the investigation of novel Aspergillus secondary metabolites.

The opportunistic fungal pathogen Candida albicans is a significant medical threat, especially for immunocompromised patients. Experimental research has focused on specific areas of C. albicans biology, with the goal of understanding the multiple factors that contribute to its pathogenic potential. Some of these factors include cell adhesion, invasive or filamentous growth, and the formation of drug-resistant biofilms. The Gene Ontology (GO) (www.geneontology.org) is a standardized vocabulary that the Candida Genome Database (CGD) (www.candidagenome.org) and other groups use to describe the functions of gene products. To improve the breadth and accuracy of pathogenicity-related gene product descriptions and to facilitate the description of as yet uncharacterized but potentially pathogenicity-related genes in Candida species, CGD undertook a three-part project: first, the addition of terms to the biological process branch of the GO to improve the description of fungus-related processes; second, manual recuration of gene product annotations in CGD to use the improved GO vocabulary; and third, computational ortholog-based transfer of GO annotations from experimentally characterized gene products, using these new terms, to uncharacterized orthologs in other Candida species. Through genome annotation and analysis, we identified candidate pathogenicity genes in seven non-C. albicans Candida species and in one additional C. albicans strain, WO-1. We also defined a set of C. albicans genes at the intersection of biofilm formation, filamentous growth, pathogenesis, and phenotypic switching of this opportunistic fungal pathogen, which provides a compelling list of candidates for further experimentation.

The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.

The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available, web-based resource for researchers studying fungi of the genus Aspergillus, which includes organisms of clinical, agricultural and industrial importance. AspGD curators have now completed comprehensive review of the entire published literature about Aspergillus nidulans and Aspergillus fumigatus, and this annotation is provided with streamlined, ortholog-based navigation of the multispecies information. AspGD facilitates comparative genomics by providing a full-featured genomics viewer, as well as matched and standardized sets of genomic information for the sequenced aspergilli. AspGD also provides resources to foster interaction and dissemination of community information and resources. We welcome and encourage feedback at aspergillus-curator@lists.stanford.edu.

The Saccharomyces Genome Database (SGD, http://www.yeastgenome.org) is the community resource for the budding yeast Saccharomyces cerevisiae. The SGD project provides the highest-quality manually curated information from peer-reviewed literature. The experimental results reported in the literature are extracted and integrated within a well-developed database. These data are combined with quality high-throughput results and provided through Locus Summary pages, a powerful query engine and rich genome browser. The acquisition, integration and retrieval of these data allow SGD to facilitate experimental design and analysis by providing an encyclopedia of the yeast genome, its chromosomal features, their functions and interactions. Public access to these data is provided to researchers and educators via web pages designed for optimal ease of use.

The Candida Genome Database (CGD, http://www.candidagenome.org/) is an internet-based resource that provides centralized access to genomic sequence data and manually curated functional information about genes and proteins of the fungal pathogen Candida albicans and other Candida species. As the scope of Candida research, and the number of sequenced strains and related species, has grown in recent years, the need for expanded genomic resources has also grown. To answer this need, CGD has expanded beyond storing data solely for C. albicans, now integrating data from multiple species. Herein we describe the incorporation of this multispecies information, which includes curated gene information and the reference sequence for C. glabrata, as well as orthology relationships that interconnect Locus Summary pages, allowing easy navigation between genes of C. albicans and C. glabrata. These orthology relationships are also used to predict GO annotations of their products. We have also added protein information pages that display domains, structural information and physicochemical properties; bibliographic pages highlighting important topic areas in Candida biology; and a laboratory strain lineage page that describes the lineage of commonly used laboratory strains. All of these data are freely available at http://www.candidagenome.org/. We welcome feedback from the research community at candida-curator@lists.stanford.edu.

Analysis of genomic data requires access to software tools that place the sequence-derived information in the context of biology. The Saccharomyces Genome Database (SGD) integrates functional information about budding yeast genes and their products with a set of analysis tools that facilitate exploring their biological details. This unit describes how the various types of functional data available at SGD can be searched, retrieved, and analyzed. Starting with the guided tour of the SGD Home page and Locus Summary page, this unit highlights how to retrieve data using YeastMine, how to visualize genomic information with GBrowse, how to explore gene expression patterns with SPELL, and how to use Gene Ontology tools to characterize large-scale datasets., (© 2011 by John Wiley & Sons, Inc.)

Background: Journal articles and databases are two major modes of communication in the biological sciences, and thus integrating these critical resources is of urgent importance to increase the pace of discovery. Projects focused on bridging the gap between journals and databases have been on the rise over the last five years and have resulted in the development of automated tools that can recognize entities within a document and link those entities to a relevant database. Unfortunately, automated tools cannot resolve ambiguities that arise from one term being used to signify entities that are quite distinct from one another. Instead, resolving these ambiguities requires some manual oversight. Finding the right balance between the speed and portability of automation and the accuracy and flexibility of manual effort is a crucial goal to making text markup a successful venture., Results: We have established a journal article mark-up pipeline that links GENETICS journal articles and the model organism database (MOD) WormBase. This pipeline uses a lexicon built with entities from the database as a first step. The entity markup pipeline results in links from over nine classes of objects including genes, proteins, alleles, phenotypes and anatomical terms. New entities and ambiguities are discovered and resolved by a database curator through a manual quality control (QC) step, along with help from authors via a web form that is provided to them by the journal. New entities discovered through this pipeline are immediately sent to an appropriate curator at the database. Ambiguous entities that do not automatically resolve to one link are resolved by hand ensuring an accurate link. This pipeline has been extended to other databases, namely Saccharomyces Genome Database (SGD) and FlyBase, and has been implemented in marking up a paper with links to multiple databases., Conclusions: Our semi-automated pipeline hyperlinks articles published in GENETICS to model organism databases such as WormBase. Our pipeline results in interactive articles that are data rich with high accuracy. The use of a manual quality control step sets this pipeline apart from other hyperlinking tools and results in benefits to authors, journals, readers and databases.

The Aspergillus Genome Database (AspGD) is an online genomics resource for researchers studying the genetics and molecular biology of the Aspergilli. AspGD combines high-quality manual curation of the experimental scientific literature examining the genetics and molecular biology of Aspergilli, cutting-edge comparative genomics approaches to iteratively refine and improve structural gene annotations across multiple Aspergillus species, and web-based research tools for accessing and exploring the data. All of these data are freely available at http://www.aspgd.org. We welcome feedback from users and the research community at aspergillus-curator@genome.stanford.edu.

The Candida Genome Database (CGD, http://www.candidagenome.org/) provides online access to genomic sequence data and manually curated functional information about genes and proteins of the human pathogen Candida albicans. Herein, we describe two recently added features, Candida Biochemical Pathways and the Textpresso full-text literature search tool. The Biochemical Pathways tool provides visualization of metabolic pathways and analysis tools that facilitate interpretation of experimental data, including results of large-scale experiments, in the context of Candida metabolism. Textpresso for Candida allows searching through the full-text of Candida-specific literature, including clinical and epidemiological studies.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is a scientific database for the molecular biology and genetics of the yeast Saccharomyces cerevisiae, which is commonly known as baker's or budding yeast. The information in SGD includes functional annotations, mapping and sequence information, protein domains and structure, expression data, mutant phenotypes, physical and genetic interactions and the primary literature from which these data are derived. Here we describe how published phenotypes and genetic interaction data are annotated and displayed in SGD.

The Gene Ontology (GO) is a structured controlled vocabulary developed to describe the roles and locations of gene products in a consistent manner and in a way that can be shared across organisms. The unicellular fungus Candida albicans is similar in many ways to the model organism Saccharomyces cerevisiae but, as both a commensal and a pathogen of humans, differs greatly in its lifestyle. With an expanding at-risk population of immunosuppressed patients, increased use of invasive medical procedures, the increasing prevalence of drug resistance and the emergence of additional Candida species as serious pathogens, it has never been more crucial to improve our understanding of Candida biology to guide the development of better treatments. In this brief review, we examine the importance of GO in the annotation of C. albicans gene products, with a focus on those involved in pathogenesis. We also discuss how sequence information combined with GO facilitates the transfer of knowledge across related species and the challenges and opportunities that such an approach presents.

Candida species are the most common cause of opportunistic fungal infection worldwide. Here we report the genome sequences of six Candida species and compare these and related pathogens and non-pathogens. There are significant expansions of cell wall, secreted and transporter gene families in pathogenic species, suggesting adaptations associated with virulence. Large genomic tracts are homozygous in three diploid species, possibly resulting from recent recombination events. Surprisingly, key components of the mating and meiosis pathways are missing from several species. These include major differences at the mating-type loci (MTL); Lodderomyces elongisporus lacks MTL, and components of the a1/2 cell identity determinant were lost in other species, raising questions about how mating and cell types are controlled. Analysis of the CUG leucine-to-serine genetic-code change reveals that 99% of ancestral CUG codons were erased and new ones arose elsewhere. Lastly, we revise the Candida albicans gene catalogue, identifying many new genes.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) organizes and displays molecular and genetic information about the genes and proteins of baker's yeast, Saccharomyces cerevisiae. Mutant phenotype screens have been the starting point for a large proportion of yeast molecular biological studies, and are still used today to elucidate the functions of uncharacterized genes and discover new roles for previously studied genes. To greatly facilitate searching and comparison of mutant phenotypes across genes, we have devised a new controlled-vocabulary system for capturing phenotype information. Each phenotype annotation is represented as an 'observable', which is the entity, or process that is observed, and a 'qualifier' that describes the change in that entity or process in the mutant (e.g. decreased, increased, or abnormal). Additional information about the mutant, such as strain background, allele name, conditions under which the phenotype is observed, or the identity of relevant chemicals, is captured in separate fields. For each gene, a summary of the mutant phenotype information is displayed on the Locus Summary page, and the complete information is displayed in tabular format on the Phenotype Details Page. All of the information is searchable and may also be downloaded in bulk using SGD's Batch Download Tool or Download Data Files Page. In the future, phenotypes will be integrated with other curated data to allow searching across different types of functional information, such as genetic and physical interaction data and Gene Ontology annotations.Database URL:http://www.yeastgenome.org/

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) collects and organizes biological information about the chromosomal features and gene products of the budding yeast Saccharomyces cerevisiae. Although published data from traditional experimental methods are the primary sources of evidence supporting Gene Ontology (GO) annotations for a gene product, high-throughput experiments and computational predictions can also provide valuable insights in the absence of an extensive body of literature. Therefore, GO annotations available at SGD now include high-throughput data as well as computational predictions provided by the GO Annotation Project (GOA UniProt; http://www.ebi.ac.uk/GOA/). Because the annotation method used to assign GO annotations varies by data source, GO resources at SGD have been modified to distinguish data sources and annotation methods. In addition to providing information for genes that have not been experimentally characterized, GO annotations from independent sources can be compared to those made by SGD to help keep the literature-based GO annotations current.

The Candida Genome Database (CGD, http://www.candidagenome.org/) contains a curated collection of genomic information and community resources for researchers who are interested in the molecular biology of the opportunistic pathogen Candida albicans. With the recent release of a new assembly of the C.albicans genome, Assembly 20, C.albicans genomics has entered a new era. Although the C.albicans genome assembly continues to undergo refinement, multiple assemblies and gene nomenclatures will remain in widespread use by the research community. CGD has now taken on the responsibility of maintaining the most up-to-date version of the genome sequence by providing the data from this new assembly alongside the data from the previous assemblies, as well as any future corrections and refinements. In this database update, we describe the sequence information available for C.albicans, the sequence information contained in CGD, and the tools for sequence retrieval, analysis and comparison that CGD provides. CGD is freely accessible at http://www.candidagenome.org/ and CGD curators may be contacted by email at candida-curator@genome.stanford.edu.

The Candida Genome Database (CGD; http://www.candidagenome.org) is a resource for information about the Candida albicans genomic sequence and the molecular biology of its encoded gene products. CGD collects and organizes data from the biological literature concerning C. albicans, and provides tools for viewing, searching, analysing, and downloading these data. CGD also serves as an organizing centre for the C. albicans research community, providing a gene-name registry, contact information, and research community news. This article describes the information contained in CGD and how to access it, either from the perspective of a bench scientist interested in the function of one or a few genes, or from the perspective of a biologist or bioinformatician interpreting large-scale functional genomic datasets.

Microarray technology has resulted in an explosion of complex, valuable data. Integrating data analysis tools with a comprehensive underlying database would allow efficient identification of common properties among differentially regulated genes. In this study we sought to compare the utility of various databases in microarray analysis. The Proteome BioKnowledge Library (BKL), a manually curated, proteome-wide compilation of the scientific literature, was used to generate a list of Gene Ontology (GO) Biological Process (BP) terms enriched among proteins involved in cardiovascular disease. Analysis of DNA microarray data generated in a study of rat vascular smooth muscle cell responses revealed significant enrichment in a number of GO BPs that were also enriched among cardiovascular disease-related proteins. Using annotation from LocusLink and chip annotation from the Gene Expression Omnibus yielded fewer enriched cardiovascular disease-associated GO BP terms. Data sets of orthologous genes from mouse and human were generated using the BKL Retriever. Analysis of these sets focusing on BKL Disease annotation, revealed a significant association of these genes with cardiovascular disease. These results and the extensive presence of experimental evidence for BKL GO and Disease features, underscore the benefits of using this database for microarray analysis.

The Candida Genome Database (CGD) is a new database that contains genomic information about the opportunistic fungal pathogen Candida albicans. CGD is a public resource for the research community that is interested in the molecular biology of this fungus. CGD curators are in the process of combing the scientific literature to collect all C.albicans gene names and aliases; to assign gene ontology terms that describe the molecular function, biological process, and subcellular localization of each gene product; to annotate mutant phenotypes; and to summarize the function and biological context of each gene product in free-text description lines. CGD also provides community resources, including a reservation system for gene names and a colleague registry through which Candida researchers can share contact information and research interests. CGD is publicly funded (by NIH grant R01 DE15873-01 from the NIDCR) and is freely available at http://www.candidagenome.org/.

Sphingolipid long chain bases (LCBs) in Saccharomyces cerevisiae, dihydrosphingosine (DHS) and phytosphingosine (PHS) and their phosphates (DHS-P and PHS-P) are thought to play roles in heat stress. However, quantitative studies of LCBs and LCBPs have been limited by analytical methods. A new analytical procedure allowed us to measure changes in all known LCBPs and LCBs in wild-type and mutant cells during heat shock and to correlate the changes with heat stress resistance. All five molecular species of LCBPs increased rapidly but transiently when log and stationary phase cells were heat-stressed and when log-phase cells were induced for thermotolerance, suggesting that LCBPs play a role in heat stress. In support of this hypothesis, cells lacking the minor LCB kinase, Lcb5p, but not the major kinase, Lcb4p, were two-fold less resistant to killing when log-phase cells were induced for thermotolerance. Thus, LCBPs seem to play a minor role in heat-stress resistance. However, their role may be masked by LCBs, which are elevated in mutant strains, such as one lacking Lcb4p. This elevation demonstrates that one function of Lcb4p is to regulate LCB levels. Two new compounds, C(16) DHS and C(16) DHS-P, were identified, with the latter being degraded by the Dpl1p lyase. Our data provide a basis for determining how the basal and heat-induced levels of individual species of LCBs and LCBPs are governed by the Lcb4p and Lcb5p kinases, the Dpl1p lyase and the Lcb3p phosphatase., (Copyright 2002 John Wiley & Sons, Ltd.)

Sphingolipid long-chain base phosphates (LCBPs) regulate cell proliferation, movement and differentiation in higher eukaryotes. To study the function of LCBPs in Saccharomyces cerevisiae, we inactivated LCBP breakdown pathways. Elimination of both the Dpll lyase and the Lcb3 phosphatase pathways by gene deletion was lethal, indicating that these enzymes regulate LCBP levels to prevent accumulation. Lethality was prevented by eliminating the major LCB kinase. Lcb4p, which synthesizes LCBPs, but not by eliminating the minor LCB kinase, Lcb5p. These data imply that death results from an accumulation of LCBPs made by the Lcb4p kinase. By regulating Lcb4 kinase activity, we found that cell death correlates with LCBP accumulation and that C18 dihydrosphingosine-l-P (DHS-P) and C20 DHS-P are most likely the killing molecules. LCB levels were found to be most elevated in a strain lacking Lcb4 kinase, Dpll lyase and Lcb3 phosphatase activity. Analysis of mutant strains suggests that the C18 and C20 species of LCBPs are preferentially degraded by the Lcb3 phosphate phosphatase, while the Dpll lyase prefers C16 DHS-P as a substrate. These and other data indicate the existence of an unknown mechanism(s) for regulating LCB levels. Our results demonstrate that LCBPs may be used in some circumstances to regulate yeast cell growth.

The BioKnowledge Library is a relational database and web site (http://www.proteome.com) composed of protein-specific information collected from the scientific literature. Each Protein Report on the web site summarizes and displays published information about a single protein, including its biochemical function, role in the cell and in the whole organism, localization, mutant phenotype and genetic interactions, regulation, domains and motifs, interactions with other proteins and other relevant data. This report describes four species-specific volumes of the BioKnowledge Library, concerned with the model organisms Saccharomyces cerevisiae (YPD), Schizosaccharomyces pombe (PombePD) and Caenorhabditis elegans (WormPD), and with the fungal pathogen Candida albicans (CalPD). Protein Reports of each species are unified in format, easily searchable and extensively cross-referenced between species. The relevance of these comprehensively curated resources to analysis of proteins in other species is discussed, and is illustrated by a survey of model organism proteins that have similarity to human proteins involved in disease.

Sphingolipid long-chain bases and their phosphorylated derivatives, for example, sphingosine-1-phosphate in mammals, have been implicated as signaling molecules. The possibility that Saccharomyces cerevisiae cells also use long-chain-base phosphates to regulate cellular processes has only recently begun to be examined. Here we present a simple and sensitive procedure for analyzing and quantifying long-chain-base phosphates in S. cerevisiae cells. Our data show for the first time that phytosphingosine-1-phosphate (PHS-1-P) is present at a low but detectable level in cells grown on a fermentable carbon source at 25 degreesC, while dihydrosphingosine-1-phosphate (DHS-1-P) is only barely detectable. Shifting cells to 37 degreesC causes transient eight- and fivefold increases in levels of PHS-1-P and DHS-1-P, respectively, which peak after about 10 min. The amounts of both compounds return to the unstressed levels by 20 min after the temperature shift. These data are consistent with PHS-1-P and DHS-1-P being signaling molecules. Cells unable to break down long-chain-base phosphates, due to deletion of DPL1 and LCB3, show a 500-fold increase in PHS-1-P and DHS-1-P levels, grow slowly, and survive a 44 degreesC heat stress 10-fold better than parental cells. These and other data for dpl1 or lcb3 single-mutant strains suggest that DHS-1-P and/or PHS-1-P act as signals for resistance to heat stress. Our procedure should expedite experiments to determine how the synthesis and breakdown of these compounds is regulated and how the compounds mediate resistance to elevated temperature.