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At least 1,459 records · Page 81Linked to original sources
PubMed2002

Damage recovery pathways in Saccharomyces cerevisiae revealed by genomic phenotyping and interactome mapping.

We have generated a genomic phenotyping database identifying hundreds of Saccharomyces cerevisiae genes important for viable cellular recovery after mutagen exposure. Systematic phenotyping of 1,615 gene deletion strains produced distinctive signatures for each of four mutagens. Integration of the phenotyping database with mutagen-induced transcriptional profiling data demonstrated that being transcriptionally responsive to a mutagen does not predict whether or not a gene contributes to recovery from exposure to that mutagen. Computational integration of the database with 4,025 interacting proteins, comprising the yeast interactome, identified several multiprotein networks important for damage recovery. Some networks were associated with DNA metabolism and cell cycle control functions, but most were associated with unexpected functions such as cytoskeleton remodeling, chromatin remodeling, protein, RNA, and lipid metabolism. Hence, a plethora of responses other than the DNA damage response is important for recovery. These network mapping results demonstrate how systematic phenotypic assays may be linked directly to underlying molecular mechanisms.

Cell Division↗
PubMed2002

Databases and tools for browsing genomes.

To maximize the value of genome sequences they need to be integrated with other types of biological data and with each other. The entire collection of data then needs to be made available in a way that is easy to view and mine for complex relationships. The recently determined vertebrate genome sequences of human and mouse are so large that building the infrastructure to manage these datasets is a major challenge. This article reviews the database systems and tools for analysis that have so far been developed to address this.

Animals↗
PubMed2005

High throughput functional genomics: identification of novel genes with tumor suppressor phenotypes.

We have used a combination of high throughput functional genomics, computerized database mining and expression analyses to discover novel human tumor suppressor genes (TSGs). A genome-wide high throughput cDNA phenotype screen was established to identify genes that induce apoptosis or reduce cell viability. TSGs are expressed in normal tissue and frequently act by reduction of growth of transformed cells or induce apoptosis. In agreement with that and thus serving as platform validation, our pro-apoptotic hits included genes for which tumor suppressing activities were known, such as kangai1 and CD81 antigen. Additional genes that so far have been claimed as putative TSGs or associated with tumor inhibitory activities (prostate differentiation factor, hRAS-like suppressor 3, DPH2L1-like and the metastasis inhibitor Kiss1) were confirmed in their proposed TSG-like phenotype by functionally defining their growth inhibitory or pro-apoptotic function towards cancer cells. Finally, novel genes were identified for which neither association with cell growth nor with apoptosis were previously described. A subset of these genes show characteristics of TSGs because they (i) reduce the growth or induce apoptosis in tumor cells; (ii) show reduced expression in tumor vs. normal tissue; and (iii) are located on chromosomal (LOH-) loci for which cancer-associated deletions are described. The pro-apoptotic phenotype and differential expression of these genes in normal and malignant tissue make them promising target candidates for the diagnosis and therapy of various tumors.

Apoptosis↗
PubMed2003

Molecular cloning and characterization of the human orthologue of the oppo 1 gene encoding a sperm tail protein.

We report here the molecular cloning and characterization of a human orthologue of oppo 1, a mouse gene encoding a male germ-cell-specific sperm tail protein, and the organization of its genomic structure. The mRNA of the human oppo 1 gene (h-oppo 1) was expressed exclusively in the testis, and the 30 kDa protein encoded by the mRNA was detected in human testis and sperm. Immunohistochemical analyses showed that human OPPO 1 protein was localized in the flagellae of ejaculated sperm. A human genomic DNA database search indicated that the h-oppo 1 gene mapped to chromosome 17. The genomic structure of h-oppo 1 showed differences in exon/intron usage, the sequence of the 5'-flanking region, and the first intron was rich in Alu repeats as compared with the mouse oppo 1 gene. Comparison of the two genomic sequences indicated that human oppo 1 has evolved independently, resulting in substantial differences in the genomic structure after the human-mouse split, whereas the sequence of the basic functional unit of the oppo 1 gene seems to have been relatively well conserved.

Amino Acid Sequence↗
PubMed1996

Improvements to the GDB Human Genome Data Base.

Version 6.0 of the Human Genome Data Base introduces a number of significant improvements over previous releases of GDB. The most important of these are revised data representations for genes and genomic maps and a new curatorial model for the database. GDB 6.0 is the first major genomic database to provide read/write access directly to the scientific community, including capabilities for third-party annotation. The revised database can represent all major categories of genetic and physical maps, along with the underlying order and distance information used to construct them. The improved representation permits more sophisticated map queries to be posed and supports the graphical display of maps. In addition the new GDB has a richer model for gene information, better suited for supporting cross-references to databases describing gene function, structure, products, expression and associated phenotypes.

Animals↗
PubMed2005

Characterization of cancer stroma markers: in silico analysis of an mRNA expression database for fibroblast activation protein and endosialin.

Standardized, high-throughput RNA detection with microarray chips allows for the construction of genome-wide databases for tissue specimens suitable for in silico electronic Northern blot (eNorthern) analysis of marker genes. We used the BioExpress database, which contains transcriptional profiles of normal and cancer samples, to examine two putative markers of cancer stroma: fibroblast activation protein-alpha (FAP-alpha) and endosialin. Analyses for FAP-alpha showed that normal tissues generally lack RNA signals, with the exception of endometrium. Typing of tumors revealed prominent FAP-alpha signals in cancer types marked by desmoplasia, and localization of FAP-alpha in reactive cancer stroma was confirmed by immunohistochemistry. A subset of sarcomas displayed prominent FAP-alpha signals localizing to the malignant cells. For endosialin, eNorthern analyses showed low to moderate RNA signals in many normal organs, whereas immunohistochemistry revealed endosialin in only some tissues, such as endometrium. Endosialin was detected at the RNA and protein level in sarcomas, notably malignant fibrous histiocytomas. Low to moderate endosialin RNA signals were found in epithelial cancer types for which immunostaining identifies expression in subsets of tumor capillaries or fibroblasts. These findings extend the FAP-alpha and endosialin profiling in silico to an unbiased tumor database and place both molecules in a novel context of endometrial biology and sarcoma subtyping. Our findings suggest that BioExpress can be searched directly for tumor stroma markers but may need prior enrichment for markers with narrow cellular representation, such as endosialin. Constructing databases from microdissected cancer tissues may be an essential step for tumor stroma-targeted therapies.

Adult↗
PubMedDate not supplied

Data mining for simple sequence repeats in expressed sequence tags from barley, maize, rice, sorghum and wheat.

Plant genomics projects involving model species and many agriculturally important crops are resulting in a rapidly increasing database of genomic and expressed DNA sequences. The publicly available collection of expressed sequence tags (ESTs) from several grass species can be used in the analysis of both structural and functional relationships in these genomes. We analyzed over 260000 EST sequences from five different cereals for their potential use in developing simple sequence repeat (SSR) markers. The frequency of SSR-containing ESTs (SSR-ESTs) in this collection varied from 1.5% for maize to 4.7% for rice. In addition, we identified several ESTs that are related to the SSR-ESTs by BLAST analysis. The SSR-ESTs and the related sequences were clustered within each species in order to reduce the redundancy and to produce a longer consensus sequence. The consensus and singleton sequences from each species were pooled and clustered to identify cross-species matches. Overall a reduction in the redundancy by 85% was observed when the resulting consensus and singleton sequences (3569) were compared to the total number of SSR-EST and related sequences analyzed (24 606). This information can be useful for the development of SSR markers that can amplify across the grass genera for comparative mapping and genetics. Functional analysis may reveal their role in plant metabolism and gene evolution.

Computational Biology↗
PubMed2002

Patents, genomics, research, and diagnostics.

Two kinds of currently available genomic patents may significantly interfere with medical research: (1) patents such as those on specific single nucleotide polymorphisms (SNPs), which may include claims that control the inference of phenotypic characteristics from specific genotypes, and (2) patents on computer-based genomic information, databases, or manipulation procedures. These will create more serious encumbrances than will patents on expressed sequence tags (ESTs). Two approaches should be considered vis-à-vis these genomic patents: (1) Reconsideration and redefinition of the recent extensions of patentable subject matter into more and more intangible areas. This could be pursued by legislation or by test litigation to seek Supreme Court reversal of certain of the decisions of the Court of Appeals for the Federal Circuit (CAFC). (2) A narrow legislative exemption protecting the ability to use SNPs and phenotypic-genotypic relationships in medical research, including contexts in which medical research and clinical practice are substantially intertwined.

Databases, Nucleic Acid↗
PubMed2001

Indexing huge genome sequences for solving various problems.

Because of the increase in the size of genome sequence databases, the importance of indexing the sequences for fast queries grows. Suffix trees and suffix arrays are used for simple queries. However these are not suitable for complicated queries from huge amount of sequences because the indices are stored in disk which has slow access speed. We propose storing the indices in memory in a compressed form. We use the compressed suffix array. It compactly stores the suffix array at the cost of theoretically a small slowdown in access speed. We experimentally show that the overhead of using the compressed suffix array is reasonable in practice. We also propose an approximate string matching algorithm which is suitable for the compressed suffix array. Furthermore, we have constructed the compressed suffix array of the whole human genome. Because its size is about 2G bytes, a workstation can handle the search index for the whole data in main memory, which will accelerate the speed of solving various problems in genome informatics.

Abstracting and Indexing↗
PubMed2001

Heterogeneous database integration in biomedicine.

The rapid expansion of biomedical knowledge, reduction in computing costs, and spread of internet access have created an ocean of electronic data. The decentralized nature of our scientific community and healthcare system, however, has resulted in a patchwork of diverse, or heterogeneous, database implementations, making access to and aggregation of data across databases very difficult. The database heterogeneity problem applies equally to clinical data describing individual patients and biological data characterizing our genome. Specifically, databases are highly heterogeneous with respect to the data models they employ, the data schemas they specify, the query languages they support, and the terminologies they recognize. Heterogeneous database systems attempt to unify disparate databases by providing uniform conceptual schemas that resolve representational heterogeneities, and by providing querying capabilities that aggregate and integrate distributed data. Research in this area has applied a variety of database and knowledge-based techniques, including semantic data modeling, ontology definition, query translation, query optimization, and terminology mapping. Existing systems have addressed heterogeneous database integration in the realms of molecular biology, hospital information systems, and application portability.

Computational Biology↗
PubMed2000

Storage and utilization of HLA genomic data--new approaches to HLA typing.

Currently available DNA-based HLA typing assays can provide detailed information about sequence motifs of a tested sample. It is still a common practice, however, for information acquired by high-resolution sequence specific oligonucleotide probe (SSOP) typing or sequence specific priming (SSP) to be presented in a low-resolution serological format. Unfortunately, this representation can lead to significant loss of useful data in many cases. An alternative to assigning allele equivalents to suchDNA typing results is simply to store the observed typing pattern and utilize the information with the help of Virtual DNA Analysis (VDA). Interpretation of the stored typing patterns can then be updated based on newly defined alleles, assuming the sequence motifs detected by the typing reagents are known. Rather than updating reagent specificities in individual laboratories, such updates should be performed in a central, publicly available sequence database. By referring to this database, HLA genomic data can then be stored and transferred between laboratories without loss of information. The 13th International Histocompatibility Workshop offers an ideal opportunity to begin building this common database for the entire human MHC.

Base Sequence↗
PubMed2005

GrainGenes 2.0. an improved resource for the small-grains community.

GrainGenes (http://wheat.pw.usda.gov) is an international database for genetic and genomic information about Triticeae species (wheat [Triticum aestivum], barley [Hordeum vulgare], rye [Secale cereale], and their wild relatives) and oat (Avena sativa) and its wild relatives. A major strength of the GrainGenes project is the interaction of the curators with database users in the research community, placing GrainGenes as both a data repository and information hub. The primary intensively curated data classes are genetic and physical maps, probes used for mapping, classical genes, quantitative trait loci, and contact information for Triticeae and oat scientists. Curation of these classes involves important contributions from the GrainGenes community, both as primary data sources and reviewers of published data. Other partially automated data classes include literature references, sequences, and links to other databases. Beyond the GrainGenes database per se, the Web site incorporates other more specific databases, informational topics, and downloadable files. For example, unique BLAST datasets of sequences applicable to Triticeae research include mapped wheat expressed sequence tags, expressed sequence tag-derived simple sequence repeats, and repetitive sequences. In 2004, the GrainGenes project migrated from the AceDB database and separate Web site to an integrated relational database and Internet resource, a major step forward in database delivery. The process of this migration and its impacts on database curation and maintenance are described, and a perspective on how a genomic database can expedite research and crop improvement is provided.

Breeding↗
PubMed2003

The Ciona intestinalis genome: when the constraints are off.

The recent genome sequencing of a non-vertebrate deuterostome, the ascidian tunicate Ciona intestinalis, makes a substantial contribution to the fields of evolutionary and developmental biology.1 Tunicates have some of the smallest bilaterian genomes, embryos with relatively few cells, fixed lineages and early determination of cell fates. Initial analyses of the C. intestinalis genome indicate that it has been evolving rapidly. Comparisons with other bilaterians show that C. intestinalis has lost a number of genes, and that many genes linked together in most other bilaterians have become uncoupled. In addition, a number of independent, lineage-specific gene duplications have been detected. These new results, although interesting in themselves, will take on a deeper significance once the genomes of additional invertebrate deuterostomes (e.g. echinoderms, hemichordates and amphioxus) have been sequenced. With such a broadened database, comparative genomics can begin to ask pointed questions about the relationship between the evolution of genomes and the evolution of body plans.

Animals↗
PubMed2005

Steady-state transposon mutagenesis in inbred maize.

We implement a novel strategy for harnessing the power of high-copy transposons for functional analysis of the maize genome, and report behavioral features of the Mutator system in a uniform inbred background. The unique UniformMu population and database facilitate high-throughput molecular analysis of Mu-tagged mutants and gene knockouts. Key features of the population include: (i) high mutation frequencies (7% independent seed mutations) and moderation of copy number (approximately 57 total Mu elements; 1-2 MuDR copies per plant) were maintained by continuous back-crossing into a phenotypically uniform inbred background; (ii) a bz1-mum9 marker enabled selection of stable lines (loss of MuDR), inhibiting further transpositions in lines selected for molecular analysis; (iii) build-up of mutation load was prevented by screening Mu-active parents to exclude plants carrying pre-existing seed mutations. To create a database of genomic sequences flanking Mu insertions, selected mutant lines were analyzed by sequencing of MuTAIL PCR clone libraries. These sequences were annotated and clustered to facilitate bioinformatic subtraction of ancestral elements and identification of insertions unique to mutant lines. New insertions targeted low-copy, gene-rich sequences, and in silico mapping revealed a random distribution of insertions over the genome. Our results indicate that Mu populations differ markedly in the occurrence of Mu insertion hotspots and the frequency of suppressible mutations. We suggest that controlled MuDR copy number in UniformMu lines is a key determinant of these differences. The public database (http://uniformmu.org; http://endosperm.info) includes pedigree and phenotypic data for over 2000 independent seed mutants selected from a population of 31 548 F2 lines and integrated with analyses of 34 255 MuTAIL sequences.

Breeding↗
PubMed2004

HGVbase: a curated resource describing human DNA variation and phenotype relationships.

The Human Genome Variation Database (HGVbase; http://hgvbase.cgb.ki.se) has provided a curated summary of human DNA variation for more than 5 years, thus facilitating research into DNA sequence variation and human phenotypes. The database has undergone many changes and improvements to accommodate increasing volumes and new types of data. The focus of HGVbase has recently shifted towards information on haplotypes and phenotypes, relationships between phenotypes and DNA variation, and collaborative efforts to provide a global resource for genome-phenome data. Open sharing and precise phenotype definitions are necessary to advance the current understanding of common diseases that are typified by complex aetiologies, small genetic effect sizes and multiple confounding factors that obscure positive study results. Association data will increasingly be collected as part of this new project thrust. This report describes the evolving features of HGVbase, and covers in detail the technological choices we have made to enable efficient storage and data mining of increasingly large and complex data sets.

Computational Biology↗
PubMed2002

FLAGdb/FST: a database of mapped flanking insertion sites (FSTs) of Arabidopsis thaliana T-DNA transformants.

A large collection of T-DNA insertion transformants of Arabidopsis thaliana has been generated at the Institute of Agronomic Research, Versailles, France. The molecular characterisation of the insertion sites is currently performed by sequencing genomic regions flanking the inserted T-DNA (FST). The almost complete sequence of the nuclear genome of A.thaliana provides the framework for organising FSTs in a genome oriented database, FLAGdb/FST (http://genoplante-info.infobiogen.fr). The main scope of FLAGdb/FST is to help biologists to find the FSTs that interrupt the genes in which they are interested. FSTs are anchored to the genome sequences of A.thaliana and positions of both predicted genes and FSTs are shown graphically on sequences. Requests to locate the genomic position of a query sequence are made using BLAST programs. The response delivered by FLAGdb/FST is a graphical representation of the putative FSTs and of predicted genes in a 20 kb region.

Arabidopsis↗
PubMed1999

Grasping at molecular interactions and genetic networks in Drosophila melanogaster using FlyNets, an Internet database.

FlyNets (http://gifts.univ-mrs.fr/FlyNets/FlyNets_home_page.++ +html) is a WWW database describing molecular interactions (protein-DNA, protein-RNA and protein-protein) in the fly Drosophila melanogaster. It is composed of two parts, as follows. (i) FlyNets-base is a specialized database which focuses on molecular interactions involved in Drosophila development. The information content of FlyNets-base is distributed among several specific lines arranged according to a GenBank-like format and grouped into five thematic zones to improve human readability. The FlyNets database achieves a high level of integration with other databases such as FlyBase, EMBL, GenBank and SWISS-PROT through numerous hyperlinks. (ii) FlyNets-list is a very simple and more general databank, the long-term goal of which is to report on any published molecular interaction occuring in the fly, giving direct web access to corresponding s in Medline and in FlyBase. In the context of genome projects, databases describing molecular interactions and genetic networks will provide a link at the functional level between the genome, the proteome and the transcriptome worlds of different organisms. Interaction databases therefore aim at describing the contents, structure, function and behaviour of what we herein define as the interactome world.

Animals↗
PubMed2003

Genome-wide evaluation of the public SNP databases.

The public SNP databases are an important resource for groups performing genetic association and linkage studies. Both academic and commercial groups are developing large numbers of genotyping assays for SNPs in candidate genes or spread across the genome. These databases now contain in excess of 6 million SNPs that have been generated using a large number of methods and cohorts. Today, however, only a small fraction of these SNPs are well characterized and validated. The latest release of dbSNP contains approximately 3.7 million non-redundant entries, only 0.5 million of which are validated, and 0.2 million of which have frequency information. Users of these databases have several common questions. How many of the SNPs are real? What is the frequency spectrum of the SNPs in these databases? What is the distribution picture of these SNPs across different ethnic and geographical populations? What fraction of the total number of SNPs is already captured by these databases? In order to address these questions, we compared the public SNPs against a well-characterized collection of gene-centric SNPs that we have developed. From this comparison, we find that > 50% of high frequency SNPs in the genome (> 20% minor allele frequency) have already been captured by these databases. The coverage drops dramatically below frequencies of 10%. At high frequencies, there is no sampling bias with respect to ethnicity or to regions of the genome. Finally, a relatively large fraction (> 40%) of SNPs in these databases were not seen in our study, which means that they are either of very low frequency, mismapped, or not polymorphic at all.

Databases, Genetic↗