Comparative analysis of the gene-dense ACHE/TFR2 region on human chromosome 7q22 with the orthologous region on mouse chromosome 5

Chromosome 7q22 has been the focus of many cytogenetic and molecular studies aimed at delineating regions commonly deleted in myeloid leukemias and myelodysplastic syndromes. We have compared a gene-dense, GC-rich sub-region of 7q22 with the orthologous region on mouse chromosome 5. A physical map of 640 kb of genomic DNA from mouse chromosome 5 was derived from a series of overlapping bacterial artificial chromosomes. A 296 kb segment from the physical map, spanning Ache to Tfr2, was compared with 267 kb of human sequence. We identified a conserved linkage of 12 genes including an open reading frame flanked by Ache and Asr2, a novel cation-chloride cotransporter interacting protein Cip1, Ephb4, Zan and Perq1. While some of these genes have been previously described, in each case we present new data derived from our comparative sequence analysis. Adjacent unfinished sequence data from the mouse contains an orthologous block of 10 additional genes including three novel cDNA sequences that we subsequently mapped to human 7q22. Methods for displaying comparative genomic information, including unfinished sequence data, are becoming increasingly important. We supplement our printed comparative analysis with a new, Web-based program called Laj (local alignments with java). Laj provides interactive access to archived pairwise sequence alignments via the WWW. It displays synchronized views of a dot-plot, a percent identity plot, a nucleotide-level local alignment and a variety of relevant annotations. Our mouse–human comparison can be viewed at http://web.uvic.ca/~bioweb/laj.html. Laj is available at http://bio.cse.psu.edu/, along with online documentation and additional examples of annotated genomic regions.

The Mouse Genome Database (MGD): integration nexus for the laboratory mouse

The Mouse Genome Database (MGD) is the community database resource for the laboratory mouse, a key model organism for interpreting the human genome and for understanding human biology and disease (http://www.informatics.jax.org). MGD provides standard nomenclature and consensus map positions for mouse genes and genetic markers; it provides a curated set of mammalian homology records, user-defined chromosomal maps, experimental data sets and the definitive mouse ‘gene to sequence’ reference set for the research community. The integration and standardization of these data sets facilitates the transition between mouse DNA sequence, gene and phenotype annotations. A recent focus on allele and phenotype representations enhances the ability of MGD to organize and present data for exploring the relationship between genotype and phenotype. This link between the genome and the biology of the mouse is especially important as phenotype information grows from large mutagenesis projects and genotype information grows from large-scale sequencing projects.

BAliBASE (Benchmark Alignment dataBASE): enhancements for repeats, transmembrane sequences and circular permutations

BAliBASE is specifically designed to serve as an evaluation resource to address all the problems encountered when aligning complete sequences. The database contains high quality, manually constructed multiple sequence alignments together with detailed annotations. The alignments are all based on three-dimensional structural superpositions, with the exception of the transmembrane sequences. The first release provided sets of reference alignments dealing with the problems of high variability, unequal repartition and large N/C-terminal extensions and internal insertions. Here we describe version 2.0 of the database, which incorporates three new reference sets of alignments containing structural repeats, trans­membrane sequences and circular permutations to evaluate the accuracy of detection/prediction and alignment of these complex sequences. BAliBASE can be viewed at the web site http://www-igbmc.u-strasbg.fr/BioInfo/BAliBASE2/index.html or can be downloaded from ftp://ftp-igbmc.u-strasbg.fr/pub/BAliBASE2/.

GlycoSuiteDB: a new curated relational database of glycoprotein glycan structures and their biological sources

GlycoSuiteDB is a relational database that curates information from the scientific literature on glyco­protein derived glycan structures, their biological sources, the references in which the glycan was described and the methods used to determine the glycan structure. To date, the database includes most published O-linked oligosaccharides from the last 50 years and most N-linked oligosaccharides that were published in the 1990s. For each structure, information is available concerning the glycan type, linkage and anomeric configuration, mass and composition. Detailed information is also provided on native and recombinant sources, including tissue and/or cell type, cell line, strain and disease state. Where known, the proteins to which the glycan structures are attached are reported, and cross-references to the SWISS-PROT/TrEMBL protein sequence databases are given if applicable. The GlycoSuiteDB annotations include literature references which are linked to PubMed, and detailed information on the methods used to determine each glycan structure are noted to help the user assess the quality of the structural assignment. GlycoSuiteDB has a user-friendly web interface which allows the researcher to query the database using mono­isotopic or average mass, monosaccharide composition, glycosylation linkages (e.g. N- or O-linked), reducing terminal sugar, attached protein, taxonomy, tissue or cell type and GlycoSuiteDB accession number. Advanced queries using combinations of these parameters are also possible. GlycoSuiteDB can be accessed on the web at http://www.glycosuite.com.

The RESID Database of protein structure modifications and the NRL-3D Sequence–Structure Database

The RESID Database is a comprehensive collection of annotations and structures for protein post-translational modifications including N-terminal, C-terminal and peptide chain cross-link modifications. The RESID Database includes systematic and frequently observed alternate names, Chemical Abstracts Service registry numbers, atomic formulas and weights, enzyme activities, taxonomic range, keywords, literature citations with database cross-references, structural diagrams and molecular models. The NRL-3D Sequence–Structure Database is derived from the three-dimensional structure of proteins deposited with the Research Collaboratory for Structural Bioinformatics Protein Data Bank. The NRL-3D Database includes standardized and frequently observed alternate names, sources, keywords, literature citations, experimental conditions and searchable sequences from model coordinates. These databases are freely accessible through the National Cancer Institute–Frederick Advanced Biomedical Computing Center at these web sites: http://www.ncifcrf.gov/RESID, http://www.ncifcrf.gov/ NRL-3D; or at these National Biomedical Research Foundation Protein Information Resource web sites: http://pir.georgetown.edu/pirwww/dbinfo/resid.html, http://pir.georgetown.edu/pirwww/dbinfo/nrl3d.html

iProClass: an integrated, comprehensive and annotated protein classification database

The iProClass database is an integrated resource that provides comprehensive family relationships and structural and functional features of proteins, with rich links to various databases. It is extended from ProClass, a protein family database that integrates PIR superfamilies and PROSITE motifs. The iProClass currently consists of more than 200 000 non-redundant PIR and SWISS-PROT proteins organized with more than 28 000 superfamilies, 2600 domains, 1300 motifs, 280 post-translational modification sites and links to more than 30 databases of protein families, structures, functions, genes, genomes, literature and taxonomy. Protein and family summary reports provide rich annotations, including membership information with length, taxonomy and keyword statistics, full family relationships, comprehensive enzyme and PDB cross-references and graphical feature display. The database facilitates classification-driven annotation for protein sequence databases and complete genomes, and supports structural and functional genomic research. The iProClass is implemented in Oracle 8i object-relational system and available for sequence search and report retrieval at http://pir.georgetow n.edu/iproclass/.

The life sciences Global Image Database (GID)

Although a vast amount of life sciences data is generated in the form of images, most scientists still store images on extremely diverse and often incompatible storage media, without any type of metadata structure, and thus with no standard facility with which to conduct searches or analyses. Here we present a solution to unlock the value of scientific images. The Global Image Database (GID) is a web-based (http://www.g wer.ch/qv/gid/gid.htm) structured central repository for scientific annotated images. The GID was designed to manage images from a wide spectrum of imaging domains ranging from microscopy to automated screening. The annotations in the GID define the source experiment of the images by describing who the authors of the experiment are, when the images were created, the biological origin of the experimental sample and how the sample was processed for visualization. A collection of experimental imaging protocols provides details of the sample preparation, and labeling, or visualization procedures. In addition, the entries in the GID reference these imaging protocols with the probe sequences or antibody names used in labeling experiments. The GID annotations are searchable by field or globally. The query results are first shown as image thumbnail previews, enabling quick browsing prior to original-sized annotated image retrieval. The development of the GID continues, aiming at facilitating the management and exchange of image data in the scientific community, and at creating new query tools for mining image data.

trEST, trGEN and Hits: access to databases of predicted protein sequences

High throughput genome (HTG) and expressed sequence tag (EST) sequences are currently the most abundant nucleotide sequence classes in the public database. The large volume, high degree of fragmentation and lack of gene structure annotations prevent efficient and effective searches of HTG and EST data for protein sequence homologies by standard search methods. Here, we briefly describe three newly developed resources that should make discovery of interesting genes in these sequence classes easier in the future, especially to biologists not having access to a powerful local bioinformatics environment. trEST and trGEN are regularly regenerated databases of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Hits is a web-based data retrieval and analysis system providing access to precomputed matches between protein sequences (including sequences from trEST and trGEN) and patterns and profiles from Prosite and Pfam. The three resources can be accessed via the Hits home page (http://hits.isb-sib.ch).