SGD: Saccharomyces Genome Database.

The Saccharomyces Genome Database (SGD) provides Internet access to the complete Saccharomyces cerevisiae genomic sequence, its genes and their products, the phenotypes of its mutants, and the literature supporting these data. The amount of information and the number of features provided by SGD have increased greatly following the release of the S.cerevisiae genomic sequence, which is currently the only complete sequence of a eukaryotic genome. SGD aids researchers by providing not only basic information, but also tools such as sequence similarity searching that lead to detailed information about features of the genome and relationships between genes. SGD presents information using a variety of user-friendly, dynamically created graphical displays illustrating physical, genetic and sequence feature maps. SGD can be accessed via the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/     

Using the Saccharomyces Genome Database (SGD) for analysis of protein similarities and structure.

The Saccharomyces Genome Database (SGD) collects and organizes information about the molecular biology and genetics of the yeast Saccharomyces cerevisiae. The latest protein structure and comparison tools available at SGD are presented here. With the completion of the yeast sequence and the Caenorhabditis elegans sequence soon to follow, comparison of proteins from complete eukaryotic proteomes will be an extremely powerful way to learn more about a particular protein's structure, its function, and its relationships with other proteins. SGD can be accessed through the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/     

New data and collaborations at the Saccharomyces Genome Database: updated reference genome,alleles, and the Alliance of Genome Resources

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 typological approach to submarine groundwater discharge (SGD)

Coastal zone managers need to factor submarine groundwater discharge (SGD) in their integration. SGD provides a pathway for the transfer of freshwater, and its dissolved chemical burden, from the land to the coastal ocean. SGD reduces salinities and provides nutrients to specialized coastal habitats. It also can be a pollutant source, often undetected, causing eutrophication and triggering nuisance algal blooms. Despite its importance, SGD remains somewhat of a mystery in most places because it is usually unseen and difficult to measure. SGD has been directly measured at only about a hundred sites worldwide. A typology generated by the Land–Ocean Interaction in the Coastal Zone (LOICZ) Project is one of the few tools globally available to coastal resource managers for identifying areas in their jurisdiction where SGD may be a confounding process. (LOICZ is a core project of the International Geosphere/Biosphere Programme.) Of the hundreds of globally distributed parameters in the LOICZ typology, a SGD subset of potentially relevant parameters may be culled. A quantitative combination of the relevant hydrological parameters can serve as a proxy for the SGD conditions not directly measured. Web-LOICZ View, geospatial software then provides an automated approach to clustering these data into groups of locations that have similar characteristics. It permits selection of variables, of the number of clusters desired, and of the clustering criteria, and provides means of testing predictive results against independent variables. Information on the occurrence of a variety of SGD indicators can then be incorporated into regional clustering analysis. With such tools, coastal managers can focus attention on the most likely sites of SGD in their jurisdiction and design the necessary measurement and modeling programs needed for integrated management.     

Saccharomyces Genome Database (SGD) provides biochemical and structural information for budding yeast proteins

The Saccharomyces Genome Database (SGD: http://genome-www.stanford.edu/Saccharomyces/) has recently developed new resources to provide more complete information about proteins from the budding yeast Saccharomyces cerevisiae. The PDB Homologs page provides structural information from the Protein Data Bank (PDB) about yeast proteins and/or their homologs. SGD has also created a resource that utilizes the eMOTIF database for motif information about a given protein. A third new resource is the Protein Information page, which contains protein physical and chemical properties, such as molecular weight and hydropathicity scores, predicted from the translated ORF sequence.     

The TRIPLES database: a community resource for yeast molecular biology

TRIPLES is a web-accessible database of TRansposon-Insertion Phenotypes, Localization and Expression in Saccharomyces cerevisiae—a relational database housing nearly half a million data points generated from an ongoing study using large-scale transposon mutagenesis to characterize gene function in yeast. At present, TRIPLES contains three principal data sets (i.e. phenotypic data, protein localization data and expression data) for over 3500 annotated yeast genes as well as several hundred non-annotated open reading frames. In addition, the TRIPLES web site provides online order forms linked to each data set so that users may request any strain or reagent generated from this project free of charge. In response to user requests, the TRIPLES web site has undergone several recent modifications. Our localization data have been supplemented with approximately 500 fluorescent micrographs depicting actual staining patterns observed upon indirect immunofluorescence analysis of indicated epitope-tagged proteins. These localization data, as well as all other data sets within TRIPLES, are now available in full as tab-delimited text. To accommodate increased reagent requests, all orders are now cataloged in a separate database, and users are notified immediately of order receipt and shipment. Also, TRIPLES is one of five sites incorporated into the new functional analysis tool Function Junction provided by the Saccharomyces Genome Database. TRIPLES may be accessed from the Yale Genome Analysis Center (YGAC) homepage at http://ygac.med.yale.edu.     

PlasmoDB: the Plasmodium genome resource. An integrated database providing tools for accessing, analyzing and mapping expression and sequence data (both finished and unfinished)

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates finished and draft genome sequence data and annotation emerging from Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for cross-species comparisons. Sequence information is also integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects. The relational schemas used to build PlasmoDB [Genomics Unified Schema (GUS) and RNA Abundance Database (RAD)] employ a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically based queries of the database. A version of the database is also available on CD-ROM (Plasmodium GenePlot), facilitating access to the data in situations where Internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to enhance utilization of the vast quantities of data emerging from genome-scale projects by the global malaria research community.     

PlasmoDB: the Plasmodium genome resource. A database integrating experimental and computational data

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates the recently completed P. falciparum genome sequence and annotation, as well as draft sequence and annotation emerging from other Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for intra- and inter-species comparisons. Sequence information is integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects and proteomics studies. The relational schema used to build PlasmoDB, GUS (Genomics Unified Schema) employs a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically-based, queries of the database. A stand-alone version of the database is also available on CD-ROM (P. falciparum GenePlot), facilitating access to the data in situations where internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to facilitate utilization of the vast quantities of genomic-scale data produced by the global malaria research community. The software used to develop PlasmoDB has been used to create a second Apicomplexan parasite genome database, ToxoDB (http://ToxoDB.org).     

植物的功能基因组学研究进展

基因组研究计划包括以全基因组测序为目标的结构基因组学和以基因功能鉴定为目标的功能基因组学两方面的内容。目前基因功能鉴定的方法主要有：基因表达的系统分析(SAGE)、cDNA微阵列、DNA(基因)芯片、蛋白组技术以及基于转座子标签和T_DNA标签的反求遗传学技术等。本文对上述各种技术的优缺点以及它们在植物基因功能鉴定中的应用进行了综述。 Abstract: The genome projects comprise the structural genomics focusing on determining the complete sequences of the genome and the functional genomics focusing on elucidating the biological function of genes.The rapidly evolving tools for functional genomics research include Serial Analysis of Gene Expression (SAGE),cDNA microarray,DNA (or gene) chips,proteome project and the reverse genetics technique based on the well-established transposon tagging and T?DNA tagging systems.In this paper,the advantages and disadvantages of such techniques and application of these techniques in plant functional genomics research are reviewed and future prospective are also presented.     

READ: RIKEN Expression Array Database

READ, the RIKEN Expression Array Database, is a database of expression profile data from the RIKEN mouse cDNA microarray. It stores the microarray experimental data and information, and provides Web interfaces for researchers to use to retrieve, analyze and display their data. The goals for READ are to serve as a storage site for microarray data from ongoing research in the RIKEN mouse encyclopedia project and to provide useful links and tools to decipher biologically important information. The gene information is based mainly on the fully annotated FANTOM database. READ can be accessed at http://read.gsc.riken.go.jp/. READ also provides a search tool [READ integrates gene expression neighbor (RINGENE)] for genes with similarities in expression profiling.     

Strand-biased Gene Distribution in Bacteria Is Related to both Horizontal Gene Transfer and Strand-biased Nucleotide Composition

Although strand-biased gene distribution(SGD) was described some two decades ago,the underlying molecular mechanisms and their relationship remain elusive.Its facets include,but are not limited to,the degree of biases,the strand-preference of genes,and the influence of background nucleotide composition variations.Using a dataset composed of 364 non-redundant bacterial genomes,we sought to illustrate our current understanding of SGD.First,when we divided the collection of bacterial genomes into non-polC and polC groups according to their possession of DnaE isoforms that correlate closely with taxonomy,the SGD of the polC group stood out more significantly than that of the non-polC group.Second,when examining horizontal gene transfer,coupled with gene functional conservation(essentiality) and expressivity(level of expression),we realized that they all contributed to SGD.Third,we further demonstrated a weaker G-dominance on the leading strand of the non-polC group but strong purine dominance(both G and A) on the leading strand of the polC group.We propose that strand-biased nucleotide composition plays a decisive role for SGD since the polC-bearing genomes are not only AT-rich but also have pronounced purine-rich leading strands,and we believe that a special mutation spectrum that leads to a strong purine asymmetry and a strong strand-biased nucleotide composition coupled with functional selections for genes and their functions are both at work.     

GenColors: accelerated comparative analysis and annotation of prokaryotic genomes at various stages of completeness

SUMMARY: GenColors is a new web-based software/database system aimed at an improved and accelerated annotation of prokaryotic genomes, considering information on related genomes and making extensive use of genome comparison. It offers a seamless integration of data from ongoing sequencing projects and annotated genomic sequences obtained from GenBank. The genome comparison tools determine, for example, best-bidirectional hits, gene conservation, syntenies and gene core sets. Swiss-Prot/TrEMBL hits allow annotations in an effective manner. To further support the annotation base-specific quality data can also be displayed if available. With GenColors dedicated genome browsers containing a group of related genomes can be easily set up and maintained. It has been efficiently used for Borrelia garinii and is currently applied to various ongoing genome projects. AVAILABILITY: Detailed information on GenColors is available at http://gencolors.imb-jena.de. Online usage of GenColors-based genome browsers is the preferred application mode. The system is also available upon request for local installation.     

Molecular cloning and analysis of strictosidine beta-D-glucosidase, an enzyme in terpenoid indole alkaloid biosynthesis in Catharanthus roseus

Strictosidine beta-D-glucosidase (SGD) is an enzyme involved in the biosynthesis of terpenoid indole alkaloids (TIAs) by converting strictosidine to cathenamine. The biosynthetic pathway toward strictosidine is thought to be similar in all TIA-producing plants. Somewhere downstream of strictosidine formation, however, the biosynthesis diverges to give rise to the different TIAs found. SGD may play a role in creating this biosynthetic diversity. We have studied SGD at both the molecular and enzymatic levels. Based on the homology between different plant beta-glucosidases, degenerate polymerase chain reaction primers were designed and used to isolate a cDNA clone from a Catharanthus roseus cDNA library. A full-length clone gave rise to SGD activity when expressed in Saccharomyces cerevisiae. SGD shows approximately 60% homology at the amino acid level to other beta-glucosidases from plants and is encoded by a single-copy gene. Sgd expression is induced by methyl jasmonate with kinetics similar to those of two other genes acting prior to Sgd in TIA biosynthesis. These results show that coordinate induction of the biosynthetic genes forms at least part of the mechanism for the methyl jasmonate-induced increase in TIA production. Using a novel in vivo staining method, subcellular localization studies of SGD were performed. This showed that SGD is most likely associated with the endoplasmic reticulum, which is in accordance with the presence of a putative signal sequence, but in contrast to previous localization studies. This new insight in SGD localization has significant implications for our understanding of the complex intracellular trafficking of metabolic intermediates during TIA biosynthesis.     

Submarine groundwater discharge alters coral reef ecosystem metabolism

Submarine groundwater discharge (SGD) influences near-shore coral reef ecosystems worldwide. SGD biogeochemistry is distinct, typically with higher nutrients, lower pH, cooler temperature and lower salinity than receiving waters. SGD can also be a conduit for anthropogenic nutrients and other pollutants. Using Bayesian structural equation modelling, we investigate pathways and feedbacks by which SGD influences coral reef ecosystem metabolism at two Hawai''i sites with distinct aquifer chemistry. The thermal and biogeochemical environment created by SGD changed net ecosystem production (NEP) and net ecosystem calcification (NEC). NEP showed a nonlinear relationship with SGD-enhanced nutrients: high fluxes of moderately enriched SGD (Wailupe low tide) and low fluxes of highly enriched SGD (Kūpikipiki''ō high tide) increased NEP, but high fluxes of highly enriched SGD (Kūpikipiki''ō low tide) decreased NEP, indicating a shift toward microbial respiration. pH fluctuated with NEP, driving changes in the net growth of calcifiers (NEC). SGD enhances biological feedbacks: changes in SGD from land use and climate change will have consequences for calcification of coral reef communities, and thereby shoreline protection.     

YPL.db: the Yeast Protein Localization database

The Yeast Protein Localization database (YPL.db) contains information about the localization patterns of yeast proteins resulting from microscopic analyses. The data and parameters of the experiments to obtain the localization information, together with images from confocal or video microscopy, are stored in a relational database, building an archive of, and the documentation for, all experiments. The database can be queried based on gene name, protein localization, growth conditions and a number of additional parameters. All experiment parameters are selectable from predefined lists to ensure database integrity and conformity across different investigators. The database provides a structure reference resource to allow for better characterization of unknown or ambiguous localization patterns. Links to MIPS, YPD and SGD databases are provided to allow fast access to further information not contained in the localization database itself. YPL.db is available at http://ypl.tugraz.at.     

Replication-associated purine asymmetry may contribute to strand-biased gene distribution

Among prokaryotic genomes, the distribution of genes on the leading and lagging strands of the replication fork is known to be biased. Several hypotheses explaining this strand-biased gene distribution (SGD) have been proposed, but none have been tested or supported by sufficient data analyses. In this work we have analyzed 211 prokaryotic genomes in terms of compositional strand asymmetries and the presence or absence of polC and have found that SGD correlates not only with polC, but also with purine asymmetry (PAS). Furthermore, SGD, PAS, and polC are all features associated with a group of low-GC, gram-positive bacteria (Firmicutes). We conclude that PAS is a characteristic of organisms with a heterodimeric DNA polymerase III alpha-subunit constituted by polC and dnaE, which may play a direct role in the maintenance of SGD.     

PEDB: the Prostate Expression Database.

The Prostate Expression Database (PEDB) is a curated relational database and suite of analysis tools designed for the study of prostate gene expression in normal and disease states. Expressed Sequence Tags (ESTs) and full-length cDNA sequences derived from more than 40 human prostate cDNA libraries are maintained and represent a wide spectrum of normal and pathological conditions. Detailed library information including tissue source, library construction methods, sequence diversity and abundance are available in a library archive. Prostate ESTs are assembled into distinct species groups using the multiple alignment program CAP2 and are annotated with information from the GenBank, dbEST and Unigene public sequence databases. Annotated sequences in PEDB are searched using the BLAST algorithm. The differential expression of each EST species can be viewed across all libraries using a Virtual Expression Analysis Tool (VEAT), a graphical user interface written in Java for intra- and inter-library species comparisons. PEDB may be accessed via the World Wide Web at http://www.mbt.washington.edu/PEDB/     

Towards the integration of spatially and temporally resolved murine gene expression databases

Several large-scale projects are evaluating gene expression in the mouse brain, both spatially and temporally. These range from projects that cover a broad spectrum of genes and developmental stages to those with high-spatial resolution and gene coverage but for only a single developmental stage. Each project contains its own self-consistent data set and tools for analysis and mining. Preliminary efforts are under way to construct tools and an infrastructure with which the data from across these different projects can be statistically pooled and analyzed. However, many obstacles remain, and these must be addressed and overcome soon if we are to unify the data sets, otherwise the preliminary efforts will be wasted. Here, the various projects for collecting and mining this information are reviewed, some challenges in data set comparisons are discussed, and some basic proposals are made for overcoming the challenges.