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At least 1,369 records · Page 76Linked to original sources
PubMed2002

Characterization of new Schistosoma mansoni microsatellite loci in sequences obtained from public DNA databases and microsatellite enriched genomic libraries.

In the last decade microsatellites have become one of the most useful genetic markers used in a large number of organisms due to their abundance and high level of polymorphism. Microsatellites have been used for individual identification, paternity tests, forensic studies and population genetics. Data on microsatellite abundance comes preferentially from microsatellite enriched libraries and DNA sequence databases. We have conducted a search in GenBank of more than 16,000 Schistosoma mansoni ESTs and 42,000 BAC sequences. In addition, we obtained 300 sequences from CA and AT microsatellite enriched genomic libraries. The sequences were searched for simple repeats using the RepeatMasker software. Of 16,022 ESTs, we detected 481 (3%) sequences that contained 622 microsatellites (434 perfect, 164 imperfect and 24 compounds). Of the 481 ESTs, 194 were grouped in 63 clusters containing 2 to 15 ESTs per cluster. Polymorphisms were observed in 16 clusters. The 287 remaining ESTs were orphan sequences. Of the 42,017 BAC end sequences, 1,598 (3.8%) contained microsatellites (2,335 perfect, 287 imperfect and 79 compounds). The 1,598 BAC end sequences 80 were grouped into 17 clusters containing 3 to 17 BAC end sequences per cluster. Microsatellites were present in 67 out of 300 sequences from microsatellite enriched libraries (55 perfect, 38 imperfect and 15 compounds). From all of the observed loci 55 were selected for having the longest perfect repeats and flanking regions that allowed the design of primers for PCR amplification. Additionally we describe two new polymorphic microsatellite loci.

Animals↗
PubMed1995

Computer tool FUNSITE for analysis of eukaryotic regulatory genomic sequences.

We present the computer tool FUNSITE for description and analysis of regulatory sequences of eukaryotic genomes. The tool consists of the following main parts: 1) An integrated database for genomic regulatory sequences. The integrated database was designed on the basis of the databases TRANSFAC (Wingender 1994) and TRRD (Kel et al. 1995) that are currently under development. The following functions are performed: i) linkage to the EMBL database; ii) preparing samples of definite types of functional sites with their flanking sequences; iii) preparing samples of promoter sequences; iv) preparing samples of transcription factors classified with regard to structural and functional features of DNA binding and activating domains, functional families of the factors, their tissue specificity and other functional features; v) access to data on mutual disposition of cis-elements within the regulatory regions. 2) The second component of FUNSITE tool is the set of programs for analysis of the structural organization of regulatory sequences: i) Program for revealing of potential transcription factors binding sites based on their consensi; ii) program for revealing of the potential binding sites using homology search with nucleotide sequences of real binding sites; iii) program for analysis of oligonucleotide context features which are characteristic of flank sequences of the binding sites; iv) program for design of recognition method for the functional sites based on generalized weight matrix; v) program for revealing potential composite elements. The results of analysis of the promoter sequences of eukaryotic genes with the FUNSITE are presented, too.

Amino Acid Sequence↗
PubMed2003

OGRe: a relational database for comparative analysis of mitochondrial genomes.

Organellar Genome Retrieval (OGRe) is a relational database of complete mitochondrial genome sequences for over 250 Metazoan species. OGRe provides a resource for the comparative analysis of mitochondrial genomes at several levels. At the sequence level, OGRe allows the retrieval of any selected set of mitochondrial genes from any selected set of species. Species are classified using a taxonomic system that allows easy selection of related groups of species. Sequence alignments are also available for some species. At the level of individual nucleotides, the system contains information on base frequencies and codon usage frequencies that can be compared between organisms. At the level of whole genomes, OGRe provides several ways of visualizing information on gene order. Diagrams illustrating the genome arrangement can be generated for any selected set of species automatically from the information in the database. Searches can be done based on gene arrangement to find sets of species that have the same order as one another. Diagrams for pairwise comparison of species can be produced that show the positions of break-points in the gene order and use colour to highlight the sections of the genome that have moved. OGRe is available from http://www.bioinf.man.ac.uk/ogre.

Animals↗
PubMed2005

TRACTOR_DB: a database of regulatory networks in gamma-proteobacterial genomes.

Experimental data on the Escherichia coli transcriptional regulatory system has been used in the past years to predict new regulatory elements (promoters, transcription factors (TFs), TFs' binding sites and operons) within its genome. As more genomes of gamma-proteobacteria are being sequenced, the prediction of these elements in a growing number of organisms has become more feasible, as a step towards the study of how different bacteria respond to environmental changes at the level of transcriptional regulation. In this work, we present TRACTOR_DB (TRAnscription FaCTORs' predicted binding sites in prokaryotic genomes), a relational database that contains computational predictions of new members of 74 regulons in 17 gamma-proteobacterial genomes. For these predictions we used a comparative genomics approach regarding which several proof-of-principle articles for large regulons have been published. TRACTOR_DB may be currently accessed at http://www.bioinfo.cu/Tractor_DB, http://www.tractor.lncc.br/ or at http://www.cifn.unam.mx/Computational_Genomics/tractorDB. Contact Email id is tractor@cifn.unam.mx.

Base Sequence↗
PubMed2003

The FlyBase database of the Drosophila genome projects and community literature.

FlyBase (http://flybase.bio.indiana.edu/) provides an integrated view of the fundamental genomic and genetic data on the major genetic model Drosophila melanogaster and related species. FlyBase has primary responsibility for the continual reannotation of the D. melanogaster genome. The ultimate goal of the reannotation effort is to decorate the euchromatic sequence of the genome with as much biological information as is available from the community and from the major genome project centers. A complete revision of the annotations of the now-finished euchromatic genomic sequence has been completed. There are many points of entry to the genome within FlyBase, most notably through maps, gene products and ontologies, structured phenotypic and gene expression data, and anatomy.

Animals↗
PubMed2002

The FlyBase database of the Drosophila genome projects and community literature.

FlyBase (http://flybase.bio.indiana.edu/) provides an integrated view of the fundamental genomic and genetic data on the major genetic model Drosophila melanogaster and related species. Following on the success of the Drosophila genome project, FlyBase has primary responsibility for the continual reannotation of the D.melanogaster genome. The ultimate goal of the reannotation effort is to decorate the euchromatic sequence of the genome with as much biological information as is available from the community and from the major genome project centers. The current cycle of reannotation focuses on establishing a comprehensive data set of gene models (i.e. transcription units and CDSs). There are many points of entry to the genome within FlyBase, most notably through maps, gene ontologies, structured phenotypic and gene expression data, and anatomy.

Animals↗
PubMed2005

Functional coverage of the human genome by existing structures, structural genomics targets, and homology models.

The bias in protein structure and function space resulting from experimental limitations and targeting of particular functional classes of proteins by structural biologists has long been recognized, but never continuously quantified. Using the Enzyme Commission and the Gene Ontology classifications as a reference frame, and integrating structure data from the Protein Data Bank (PDB), target sequences from the structural genomics projects, structure homology derived from the SUPERFAMILY database, and genome annotations from Ensembl and NCBI, we provide a quantified view, both at the domain and whole-protein levels, of the current and projected coverage of protein structure and function space relative to the human genome. Protein structures currently provide at least one domain that covers 37% of the functional classes identified in the genome; whole structure coverage exists for 25% of the genome. If all the structural genomics targets were solved (twice the current number of structures in the PDB), it is estimated that structures of one domain would cover 69% of the functional classes identified and complete structure coverage would be 44%. Homology models from existing experimental structures extend the 37% coverage to 56% of the genome as single domains and 25% to 31% for complete structures. Coverage from homology models is not evenly distributed by protein family, reflecting differing degrees of sequence and structure divergence within families. While these data provide coverage, conversely, they also systematically highlight functional classes of proteins for which structures should be determined. Current key functional families without structure representation are highlighted here; updated information on the "most wanted list" that should be solved is available on a weekly basis from http://function.rcsb.org:8080/pdb/function_distribution/index.html.

Databases, Protein↗
PubMed2002

Yeast genomic expression studies using DNA microarrays.

The exploration and characterization of yeast genomic expression programs is providing a wealth of information about yeast biology, as well as other organisms. The intriguing biology of yeast species invites characterization of genomic expression patterns to illuminate the details of cellular physiology. In addition to its value as an interesting organism, yeast maintains its role as an excellent model in which to characterize genomic expression programs. Microarray studies are quickly spreading to plant, animal, and microbial organisms that remain in the early stages of characterization. The extensive knowledge of yeast biology, as well as the relative ease with which yeast studies can be performed and controlled, facilitates interpretation of the genomic expression data. Importantly, existing information about yeast biology, including functional annotations for each gene, is captured and efficiently presented in databases such as the Saccharomyces Genome Database (SGD), the Munich Information Center Yeast Genome Database (MIPS), the Yeast and Pombe Protein Databases (YPD and PPD, respectively), and others. A number of databases also allow the exploration of published genomic expression studies, including the "Expression Connection" at SGD and the Microarray Global Viewer (yMGV) organized by Marc et al. Consulting these databases to retrieve known details about gene function and regulation vastly facilitates interpretation of the genomic expression data, allowing biological hypotheses to be formulated and tested. These hypotheses can be applied to other organisms that may execute genomic expression programs similar to those seen in yeast. Furthermore, as more genomic expression studies in multiple organisms emerge, large-scale data comparisons can be conducted, within and across organisms. Incorporating the results of yeast studies into such comparisons is certain to increase our understanding about the function, regulation, and evolution of genomic expression programs.

Carbocyanines↗
PubMed2005

Ancestral state reconstructions for genomes.

The recent expansion of phylogenetic analysis from the traditional field of molecular evolution, analyzing histories of genes, to the nascent field of "genomic evolution", analyzing histories of entire genomes, enables the construction of trees based on genome information, the quantification of the key processes that shape genome content and, ultimately, plausible parsimony reconstructions of ancestral genomes. Thus, when genomes are considered as phylogenetic characters, it is possible to reconstruct not only the history of species but also the ancestral states in terms of genome structure or function. In the future, we might be able to accurately reconstruct--or retrodict--a chain of events that led to the emergence of a specific genome sequence and, ultimately, to synthesize ancestral genomes at will, creating a "Jurassic database" of genomes.

Evolution, Molecular↗
PubMed2003

Genomic organization and transcriptional analysis of the human l-glutaminase gene.

In mammals, glutaminase (GA) is expressed in most tissues, but the regulation of organ-specific expression is largely unknown. Therefore, as an essential step towards studying the regulation of GA expression, the human liver-type GA (hLGA) gene has been characterized. LGA genomic sequences were isolated using the genome walking technique. Analysis and comparison of these sequences with two LGA cDNA clones and the Human Genome Project database, allowed the determination of the genomic organization of the LGA gene. The gene has 18 exons and is approx. 18 kb long. All exon/intron junction sequences conform to the GT/AG rule. Progressive deletion analysis of LGA promoter-luciferase constructs indicated that the core promoter is located between nt -141 and +410, with several potential regulatory elements: CAAT, GC, TATA-like, Ras-responsive element binding protein and specificity protein 1 (Sp1) sites. The minimal promoter was mapped within +107 and +410, where only an Sp1 binding site is present. Mutation experiments suggested that two CAAT recognition elements near the transcription-initiation site (-138 and -87), play a crucial role for optimal promoter activity. Electrophoretic mobility-shift assays confirmed the importance of CAAT- and TATA-like boxes to enhance basal transcription, and demonstrated that HNF-1 motif is a significant distal element for transcriptional regulation of the hLGA gene.

5' Flanking Region↗
PubMed2003

Identification of a parathyroid hormone in the fish Fugu rubripes.

UNLABELLED: A PTH gene has been isolated from the fish Fugu rubripes. The encoded protein of 80 amino acid has the lowest homology with any of the PTH family members. Fugu PTH(1-34) had 5-fold lower potency than human PTH(1-34) in a mammalian cell system. INTRODUCTION: Parathyroid hormone (PTH) is the major hypercalcemic hormone in higher vertebrates. Fish lack parathyroid glands, but there have numerous attempts to identify and isolate PTH from fish. MATERIALS AND METHODS: Polymerase chain reaction (PCR) was performed with primers based on preliminary data from the Joint Genome Institute database. PCR amplification was performed on genomic DNA isolated from Fugu rubripes. PCR products were purified and DNA was sequenced. All sequence was confirmed from more than one independently amplified PCR product. Multiple sequence alignments were carried out, and the percentage of identities and similarities were calculated. An unrooted phylogenetic tree, using all the known PTH and PTH-related protein (PTHrP) amino acid sequences, was determined. Synthetic peptides were tested in a biological assay that measured cyclic adenosine 3',5'-monophosphate formation in UMR106.1 cells. Rabbit polyclonal antisera specific for N-terminal human PTHrP and one rabbit polyclonal antiserum specific for N terminus hPTH were used to test the cross-reactivity with fPTH(1-34) in immunoblots.

Amino Acid Sequence↗
PubMed2005

Evidence of a large-scale functional organization of mammalian chromosomes.

Evidence from inbred strains of mice indicates that a quarter or more of the mammalian genome consists of chromosome regions containing clusters of functionally related genes. The intense selection pressures during inbreeding favor the coinheritance of optimal sets of alleles among these genetically linked, functionally related genes, resulting in extensive domains of linkage disequilibrium (LD) among a set of 60 genetically diverse inbred strains. Recombination that disrupts the preferred combinations of alleles reduces the ability of offspring to survive further inbreeding. LD is also seen between markers on separate chromosomes, forming networks with scale-free architecture. Combining LD data with pathway and genome annotation databases, we have been able to identify the biological functions underlying several domains and networks. Given the strong conservation of gene order among mammals, the domains and networks we find in mice probably characterize all mammals, including humans.

Animals↗
PubMed2004

The UCSC Table Browser data retrieval tool.

The University of California Santa Cruz (UCSC) Table Browser (http://genome.ucsc.edu/cgi-bin/hgText) provides text-based access to a large collection of genome assemblies and annotation data stored in the Genome Browser Database. A flexible alternative to the graphical-based Genome Browser, this tool offers an enhanced level of query support that includes restrictions based on field values, free-form SQL queries and combined queries on multiple tables. Output can be filtered to restrict the fields and lines returned, and may be organized into one of several formats, including a simple tab- delimited file that can be loaded into a spreadsheet or database as well as advanced formats that may be uploaded into the Genome Browser as custom annotation tracks. The Table Browser User's Guide located on the UCSC website provides instructions and detailed examples for constructing queries and configuring output.

Animals↗
PubMed1998

MIPS: a database for protein sequences and complete genomes.

The MIPS group [Munich Information Center for Protein Sequences of the German National Center for Environment and Health (GSF)] at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, is involved in a number of data collection activities, including a comprehensive database of the yeast genome, a database reflecting the progress in sequencing the Arabidopsis thaliana genome, the systematic analysis of other small genomes and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). Through its WWW server (http://www.mips.biochem.mpg.de ) MIPS provides access to a variety of generic databases, including a database of protein families as well as automatically generated data by the systematic application of sequence analysis algorithms. The yeast genome sequence and its related information was also compiled on CD-ROM to provide dynamic interactive access to the 16 chromosomes of the first eukaryotic genome unraveled.

Amino Acid Sequence↗
PubMed2004

coliBASE: an online database for Escherichia coli, Shigella and Salmonella comparative genomics.

We have constructed coliBASE, a database for Escherichia coli, Shigella and Salmonella comparative genomics available online at http://colibase. bham.ac.uk. Unlike other E.coli databases, which focus on the laboratory model strain K12, coliBASE is intended to reflect the full diversity of E.coli and its relatives. The database contains comparative data including whole genome alignments and lists of putative orthologous genes, together with numerous analytical tools and links to existing online resources. The data are stored in a relational database, accessible by a number of user-friendly search methods and graphical browsers. The database schema is generic and can easily be applied to other bacterial genomes. Two such databases, CampyDB (for the analysis of Campylobacter spp.) and ClostriDB (for Clostridium spp.) are also available at http://campy.bham.ac.uk and http://clostri. bham.ac.uk, respectively. An example of the power of E.coli comparative analyses such as those available through coliBASE is presented.

Computational Biology↗
PubMed2006

Coverage of whole proteome by structural genomics observed through protein homology modeling database.

We have been developing FAMSBASE, a protein homology-modeling database of whole ORFs predicted from genome sequences. The latest update of FAMSBASE ( http://daisy.nagahama-i-bio.ac.jp/Famsbase/ ), which is based on the protein three-dimensional (3D) structures released by November 2003, contains modeled 3D structures for 368,724 open reading frames (ORFs) derived from genomes of 276 species, namely 17 archaebacterial, 130 eubacterial, 18 eukaryotic and 111 phage genomes. Those 276 genomes are predicted to have 734,193 ORFs in total and the current FAMSBASE contains protein 3D structure of approximately 50% of the ORF products. However, cases that a modeled 3D structure covers the whole part of an ORF product are rare. When portion of an ORF with 3D structure is compared in three kingdoms of life, in archaebacteria and eubacteria, approximately 60% of the ORFs have modeled 3D structures covering almost the entire amino acid sequences, however, the percentage falls to about 30% in eukaryotes. When annual differences in the number of ORFs with modeled 3D structure are calculated, the fraction of modeled 3D structures of soluble protein for archaebacteria is increased by 5%, and that for eubacteria by 7% in the last 3 years. Assuming that this rate would be maintained and that determination of 3D structures for predicted disordered regions is unattainable, whole soluble protein model structures of prokaryotes without the putative disordered regions will be in hand within 15 years. For eukaryotic proteins, they will be in hand within 25 years. The 3D structures we will have at those times are not the 3D structure of the entire proteins encoded in single ORFs, but the 3D structures of separate structural domains. Measuring or predicting spatial arrangements of structural domains in an ORF will then be a coming issue of structural genomics.

Amino Acid Sequence↗
PubMed2003

The Z curve database: a graphic representation of genome sequences.

MOTIVATION: Genome projects for many prokaryotic and eukaryotic species have been completed and more new genome projects are being underway currently. The availability of a large number of genomic sequences for researchers creates a need to find graphic tools to study genomes in a perceivable form. The Z curve is one of such tools available for visualizing genomes. The Z curve is a unique three-dimensional curve representation for a given DNA sequence in the sense that each can be uniquely reconstructed given the other. The Z curve database for more than 1000 genomes have been established here. RESULTS: The database contains the Z curves for archaea, bacteria, eukaryota, organelles, phages, plasmids, viroids and viruses, whose genomic sequences are currently available. All the 3-dimensional Z curves and their three component curves are stored in the database. The applications of the Z curve database on comparative genomics, gene prediction, computation of G+C content with a windowless technique, prediction of replication origins and terminations of bacterial and archaeal genomes and study of local deviations from the Chargaff Parity Rule 2 etc. are presented in detail. The Z curve database reported here is a treasure trove in which biologists could find useful biological knowledge.

Animals↗