Discovery of a divergent HPIV4 from respiratory secretions using second and third generation metagenomic sequencing.

Molecular detection of viruses has been aided by high-throughput sequencing, permitting the genomic characterization of emerging strains. In this study, we comprehensively screened 500 respiratory secretions from children with upper and/or lower respiratory tract infections for viral pathogens. The viruses detected are described, including a divergent human parainfluenza virus type 4 from GS FLX pyrosequencing of 92 specimens. Complete full-genome characterization of the virus followed, using Single Molecule, Real-Time (SMRT) sequencing. Subsequent "primer walking" combined with Sanger sequencing validated the RS platform's utility in viral sequencing from complex clinical samples. Comparative genomics reveals the divergent strain clusters with the only completely sequenced HPIV4a subtype. However, it also exhibits various structural features present in one of the HPIV4b reference strains, opening questions regarding their lifecycle and evolutionary relationships among these viruses. Clinical data from patients infected with the strain, as well as viral prevalence estimates using real-time PCR, is also described.

Genome sequence of the palaeopolyploid soybean.

Soybean (Glycine max) is one of the most important crop plants for seed protein and oil content, and for its capacity to fix atmospheric nitrogen through symbioses with soil-borne microorganisms. We sequenced the 1.1-gigabase genome by a whole-genome shotgun approach and integrated it with physical and high-density genetic maps to create a chromosome-scale draft sequence assembly. We predict 46,430 protein-coding genes, 70% more than Arabidopsis and similar to the poplar genome which, like soybean, is an ancient polyploid (palaeopolyploid). About 78% of the predicted genes occur in chromosome ends, which comprise less than one-half of the genome but account for nearly all of the genetic recombination. Genome duplications occurred at approximately 59 and 13 million years ago, resulting in a highly duplicated genome with nearly 75% of the genes present in multiple copies. The two duplication events were followed by gene diversification and loss, and numerous chromosome rearrangements. An accurate soybean genome sequence will facilitate the identification of the genetic basis of many soybean traits, and accelerate the creation of improved soybean varieties.

Expanded protein information at SGD: new pages and proteome browser.

The recent explosion in protein data generated from both directed small-scale studies and large-scale proteomics efforts has greatly expanded the quantity of available protein information and has prompted the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) to enhance the depth and accessibility of protein annotations. In particular, we have expanded ongoing efforts to improve the integration of experimental information and sequence-based predictions and have redesigned the protein information web pages. A key feature of this redesign is the development of a GBrowse-derived interactive Proteome Browser customized to improve the visualization of sequence-based protein information. This Proteome Browser has enabled SGD to unify the display of hidden Markov model (HMM) domains, protein family HMMs, motifs, transmembrane regions, signal peptides, hydropathy plots and profile hits using several popular prediction algorithms. In addition, a physico-chemical properties page has been introduced to provide easy access to basic protein information. Improvements to the layout of the Protein Information page and integration of the Proteome Browser will facilitate the ongoing expansion of sequence-specific experimental information captured in SGD, including post-translational modifications and other user-defined annotations. Finally, SGD continues to improve upon the availability of genetic and physical interaction data in an ongoing collaboration with BioGRID by providing direct access to more than 82,000 manually-curated interactions.

Saccharomyces cerevisiae S288C genome annotation: a working hypothesis.

The S. cerevisiae genome is the most well-characterized eukaryotic genome and one of the simplest in terms of identifying open reading frames (ORFs), yet its primary annotation has been updated continually in the decade since its initial release in 1996 (Goffeau et al., 1996). The Saccharomyces Genome Database (SGD; www.yeastgenome.org) (Hirschman et al., 2006), the community-designated repository for this reference genome, strives to ensure that the S. cerevisiae annotation is as accurate and useful as possible. At SGD, the S. cerevisiae genome sequence and annotation are treated as a working hypothesis, which must be repeatedly tested and refined. In this paper, in celebration of the tenth anniversary of the completion of the S. cerevisiae genome sequence, we discuss the ways in which the S. cerevisiae sequence and annotation have changed, consider the multiple sources of experimental and comparative data on which these changes are based, and describe our methods for evaluating, incorporating and documenting these new data.

Genome Snapshot: a new resource at the Saccharomyces Genome Database (SGD) presenting an overview of the Saccharomyces cerevisiae genome.

Sequencing and annotation of the entire Saccharomyces cerevisiae genome has made it possible to gain a genome-wide perspective on yeast genes and gene products. To make this information available on an ongoing basis, the Saccharomyces Genome Database (SGD) (http://www.yeastgenome.org/) has created the Genome Snapshot (http://db.yeastgenome.org/cgi-bin/genomeSnapShot.pl). The Genome Snapshot summarizes the current state of knowledge about the genes and chromosomal features of S.cerevisiae. The information is organized into two categories: (i) number of each type of chromosomal feature annotated in the genome and (ii) number and distribution of genes annotated to Gene Ontology terms. Detailed lists are accessible through SGD's Advanced Search tool (http://db.yeastgenome.org/cgi-bin/search/featureSearch), and all the data presented on this page are available from the SGD ftp site (ftp://ftp.yeastgenome.org/yeast/).

Tetrahymena Genome Database (TGD): a new genomic resource for Tetrahymena thermophila research.

We have developed a web-based resource (available at www.ciliate.org) for researchers studying the model ciliate organism Tetrahymena thermophila. Employing the underlying database structure and programming of the Saccharomyces Genome Database, the Tetrahymena Genome Database (TGD) integrates the wealth of knowledge generated by the Tetrahymena research community about genome structure, genes and gene products with the newly sequenced macronuclear genome determined by The Institute for Genomic Research (TIGR). TGD provides information curated from the literature about each published gene, including a standardized gene name, a link to the genomic locus in our graphical genome browser, gene product annotations utilizing the Gene Ontology, links to published literature about the gene and more. TGD also displays automatic annotations generated for the gene models predicted by TIGR. A variety of tools are available at TGD for searching the Tetrahymena genome, its literature and information about members of the research community.

A DNA microarray survey of gene expression in normal human tissues.

BACKGROUND: Numerous studies have used DNA microarrays to survey gene expression in cancer and other disease states. Comparatively little is known about the genes expressed across the gamut of normal human tissues. Systematic studies of global gene-expression patterns, by linking variation in the expression of specific genes to phenotypic variation in the cells or tissues in which they are expressed, provide clues to the molecular organization of diverse cells and to the potential roles of the genes. RESULTS: Here we describe a systematic survey of gene expression in 115 human tissue samples representing 35 different tissue types, using cDNA microarrays representing approximately 26,000 different human genes. Unsupervised hierarchical cluster analysis of the gene-expression patterns in these tissues identified clusters of genes with related biological functions and grouped the tissue specimens in a pattern that reflected their anatomic locations, cellular compositions or physiologic functions. In unsupervised and supervised analyses, tissue-specific patterns of gene expression were readily discernable. By comparative hybridization to normal genomic DNA, we were also able to estimate transcript abundances for expressed genes. CONCLUSIONS: Our dataset provides a baseline for comparison to diseased tissues, and will aid in the identification of tissue-specific functions. In addition, our analysis identifies potential molecular markers for detection of injury to specific organs and tissues, and provides a foundation for selection of potential targets for selective anticancer therapy.

Fungal BLAST and Model Organism BLASTP Best Hits: new comparison resources at the Saccharomyces Genome Database (SGD).

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) is a scientific database of gene, protein and genomic information for the yeast Saccharomyces cerevisiae. SGD has recently developed two new resources that facilitate nucleotide and protein sequence comparisons between S.cerevisiae and other organisms. The Fungal BLAST tool provides directed searches against all fungal nucleotide and protein sequences available from GenBank, divided into categories according to organism, status of completeness and annotation, and source. The Model Organism BLASTP Best Hits resource displays, for each S.cerevisiae protein, the single most similar protein from several model organisms and presents links to the database pages of those proteins, facilitating access to curated information about potential orthologs of yeast proteins.

Saccharomyces genome database: underlying principles and organisation.

A scientific database can be a powerful tool for biologists in an era where large-scale genomic analysis, combined with smaller-scale scientific results, provides new insights into the roles of genes and their products in the cell. However, the collection and assimilation of data is, in itself, not enough to make a database useful. The data must be incorporated into the database and presented to the user in an intuitive and biologically significant manner. Most importantly, this presentation must be driven by the user's point of view; that is, from a biological perspective. The success of a scientific database can therefore be measured by the response of its users - statistically, by usage numbers and, in a less quantifiable way, by its relationship with the community it serves and its ability to serve as a model for similar projects. Since its inception ten years ago, the Saccharomyces Genome Database (SGD) has seen a dramatic increase in its usage, has developed and maintained a positive working relationship with the yeast research community, and has served as a template for at least one other database. The success of SGD, as measured by these criteria, is due in large part to philosophies that have guided its mission and organisation since it was established in 1993. This paper aims to detail these philosophies and how they shape the organisation and presentation of the database.

Saccharomyces Genome Database (SGD) provides tools to identify and analyze sequences from Saccharomyces cerevisiae and related sequences from other organisms.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/), a scientific database of the molecular biology and genetics of the yeast Saccharomyces cerevisiae, has recently developed several new resources that allow the comparison and integration of information on a genome-wide scale, enabling the user not only to find detailed information about individual genes, but also to make connections across groups of genes with common features and across different species. The Fungal Alignment Viewer displays alignments of sequences from multiple fungal genomes, while the Sequence Similarity Query tool displays PSI-BLAST alignments of each S.cerevisiae protein with similar proteins from any species whose sequences are contained in the non-redundant (nr) protein data set at NCBI. The Yeast Biochemical Pathways tool integrates groups of genes by their common roles in metabolism and displays the metabolic pathways in a graphical form. Finally, the Find Chromosomal Features search interface provides a versatile tool for querying multiple types of information in SGD.

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.

Saccharomyces Genome Database (SGD) provides secondary gene annotation using the Gene Ontology (GO).

The Saccharomyces Genome Database (SGD) resources, ranging from genetic and physical maps to genome-wide analysis tools, reflect the scientific progress in identifying genes and their functions over the last decade. As emphasis shifts from identification of the genes to identification of the role of their gene products in the cell, SGD seeks to provide its users with annotations that will allow relationships to be made between gene products, both within Saccharomyces cerevisiae and across species. To this end, SGD is annotating genes to the Gene Ontology (GO), a structured representation of biological knowledge that can be shared across species. The GO consists of three separate ontologies describing molecular function, biological process and cellular component. The goal is to use published information to associate each characterized S.cerevisiae gene product with one or more GO terms from each of the three ontologies. To be useful, this must be done in a manner that allows accurate associations based on experimental evidence, modifications to GO when necessary, and careful documentation of the annotations through evidence codes for given citations. Reaching this goal is an ongoing process at SGD. For information on the current progress of GO annotations at SGD and other participating databases, as well as a description of each of the three ontologies, please visit the GO Consortium page at http://www.geneontology.org. SGD gene associations to GO can be found by visiting our site at http://genome-www.stanford.edu/Saccharomyces/.