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PubMed2001

An insight into domain combinations.

Domains are the building blocks of all globular proteins, and are units of compact three-dimensional structure as well as evolutionary units. There is a limited repertoire of domain families, so that these domain families are duplicated and combined in different ways to form the set of proteins in a genome. Proteins are gene products. The processes that produce new genes are duplication and recombination as well as gene fusion and fission. We attempt to gain an overview of these processes by studying the structural domains in the proteins of seven genomes from the three kingdoms of life: Eubacteria, Archaea and Eukaryota. We use here the domain and superfamily definitions in Structural Classification of Proteins Database (SCOP) in order to map pairs of adjacent domains in genome sequences in terms of their superfamily combinations. We find 624 out of the 764 superfamilies in SCOP in these genomes, and the 624 families occur in 585 pairwise combinations. Most families are observed in combination with one or two other families, while a few families are very versatile in their combinatorial behaviour. This type of pattern can be described by a scale-free network. Finally, we study domain repeats and we compare the set of the domain combinations in the genomes to those in PDB, and discuss the implications for structural genomics.

Computational Biology↗

PubMed2002

In silico discovery of gene-coding variants in murine quantitative trait loci using strain-specific genome sequence databases.

BACKGROUND: The identification of genes underlying complex traits has been aided by quantitative trait locus (QTL) mapping approaches, which in turn have benefited from advances in mammalian genome research. Most recently, whole-genome draft sequences and assemblies have been generated for mouse strains that have been used for a large fraction of QTL mapping studies. Here we show how such strain-specific mouse genome sequence databases can be used as part of a high-throughput pipeline for the in silico discovery of gene-coding variations within murine QTLs. As a test of this approach we focused on two QTLs on mouse chromosomes 1 and 13 that are involved in physical dependence on alcohol. RESULTS: Interstrain alignment of sequences derived from the relevant mouse strain genome sequence databases for 199 QTL-localized genes spanning 210,020 base-pairs of coding sequence identified 21 genes with different coding sequences for the progenitor strains. Several of these genes, including four that exhibit strong phenotypic links to chronic alcohol withdrawal, are promising candidates to underlie these QTLs. CONCLUSIONS: This approach has wide general utility, and should be applicable to any of the several hundred mouse QTLs, encompassing over 60 different complex traits, that have been identified using strains for which relatively complete genome sequences are available.

Alcohol Withdrawal Seizures↗

PubMed2004

Exploring the portability of informatics capabilities from a clinical application to a bioscience application.

This report describes XDesc (eXperiment Description), a pilot project that serves as a case study exploring the degree to which an informatics capability developed in a clinical application can be ported for use in the biosciences. In particular, XDesc uses the Entity-Attribute-Value database implementation (including a great deal of metadata-based functionality) developed in TrialDB, a clinical research database, for use in describing the samples used in microarray experiments stored in the Yale Microarray Database (YMD). XDesc was linked successfully to both TrialDB and YMD, and was used to describe the data in three different microarray research projects involving Drosophila. In the process, a number of new desirable capabilities were identified in the bioscience domain. These were implemented on a pilot basis in XDesc, and subsequently "folded back" into TrialDB itself, enhancing its capabilities for dealing with clinical data. This case study provides a concrete example of how informatics research and development in clinical and bioscience domains has the potential for synergy and for cross-fertilization.

Clinical Medicine↗

PubMed2003

The NCI/CIT microArray database (mAdb) system - bioinformatics for the management and analysis of Affymetrix and spotted gene expression microarrays.

A scalable, modular, enterprise-level system for both microarray databasing and analysis over the Internet has been developed over the past four years by the National Cancer Institute's Center for Cancer Research in collaboration with NIH's Center for Information Technology. This completely Web-based system, called mAdb (for microArray database), is currently supporting over 810 registered users and collaborators at NIH and contains over 22,000 microarray experiments, making it one of the largest collections of microarray data in existence. In addition, the mAdb system has been ported for the Netherlands Cancer Institute, the Genome Institute of Singapore, and the CDC. This system has been used for a wide variety of scientific experiments spanning the range from cancer to studies of early development, and for human, mouse, rat, yeast, and numerous microbial organisms.

Animals↗

PubMed2004

cpnDB: a chaperonin sequence database.

Type I chaperonins are molecular chaperones present in virtually all bacteria, some archaea and the plastids and mitochondria of eukaryotes. Sequences of cpn60 genes, encoding 60-kDa chaperonin protein subunits (CPN60, also known as GroEL or HSP60), are useful for phylogenetic studies and as targets for detection and identification of organisms. Conveniently, a 549-567-bp segment of the cpn60 coding region can be amplified with universal PCR primers. Here, we introduce cpnDB, a curated collection of cpn60 sequence data collected from public databases or generated by a network of collaborators exploiting the cpn60 target in clinical, phylogenetic, and microbial ecology studies. The growing database currently contains approximately 2000 records covering over 240 genera of bacteria, eukaryotes, and archaea. The database also contains over 60 sequences for the archaeal Type II chaperonin (thermosome, a homolog of eukaryotic cytoplasmic chaperonin) from 19 archaeal genera. As the largest curated collection of sequences available for a protein-encoding gene, cpnDB provides a resource for researchers interested in exploiting the power of cpn60 as a diagnostic or as a target for phylogenetic or microbial ecology studies, as well as those interested in broader subjects such as lateral gene transfer and codon usage. We built cpnDB from open source tools and it is available at http://cpndb.cbr.nrc.ca.

Animals↗

PubMed2004

Prediction of functional sites by analysis of sequence and structure conservation.

We present a method for prediction of functional sites in a set of aligned protein sequences. The method selects sites which are both well conserved and clustered together in space, as inferred from the 3D structures of proteins included in the alignment. We tested the method using 86 alignments from the NCBI CDD database, where the sites of experimentally determined ligand and/or macromolecular interactions are annotated. In agreement with earlier investigations, we found that functional site predictions are most successful when overall background sequence conservation is low, such that sites under evolutionary constraint become apparent. In addition, we found that averaging of conservation values across spatially clustered sites improves predictions under certain conditions: that is, when overall conservation is relatively high and when the site in question involves a large macromolecular binding interface. Under these conditions it is better to look for clusters of conserved sites than to look for particular conserved sites.

Algorithms↗

PubMed2002

Grouping and identification of sequence tags (GRIST): bioinformatics tools for the NEIBank database.

NEIBank is a project to develop and organize genomics and bioinformatics resources for the eye. As part of this effort, tools have been developed for bioinformatics analysis and web based display of data from expressed sequence tag (EST) analyses. EST sequences are identified and formed into groups or clusters representing related transcripts from the same gene. This is carried out by a rules-based procedure called GRIST (GRouping and Identification of Sequence Tags) that uses sequence match parameters derived from BLAST programs. Linked procedures are used to eliminate non-mRNA contaminants. All data are assembled in a relational database and assembled for display as web pages with annotations and links to other informatics resources. Genome projects generate huge amounts of data that need to be classified and organized to become easily accessible to the research community. GRIST provides a useful tool for assembling and displaying the results of EST analyses. The NEIBank web site contains a growing set of pages cataloging the known transcriptional repertoire of eye tissues, derived from new NEIBank cDNA libraries and from eye-related data deposited in the dbEST section of GenBank.

Animals↗

PubMed2001

Bioinformatics and mass spectrometry for microorganism identification: proteome-wide post-translational modifications and database search algorithms for characterization of intact H. pylori.

MALDI-TOF mass spectrometry has been coupled with Internet-based proteome database search algorithms in an approach for direct microorganism identification. This approach is applied here to characterize intact H. pylori (strain 26695) Gram-negative bacteria, the most ubiquitous human pathogen. A procedure for including a specific and common posttranslational modification, N-terminal Met cleavage, in the search algorithm is described. Accounting for posttranslational modifications in putative protein biomarkers improves the identification reliability by at least an order of magnitude. The influence of other factors, such as number of detected biomarker peaks, proteome size, spectral calibration, and mass accuracy, on the microorganism identification success rate is illustrated as well.

Algorithms↗

PubMed2004

PlantGDB, plant genome database and analysis tools.

PlantGDB (http://www.plantgdb.org/) is a database of molecular sequence data for all plant species with significant sequencing efforts. The database organizes EST sequences into contigs that represent tentative unique genes. Contigs are annotated and, whenever possible, linked to their respective genomic DNA. Genome sequence fragments are assembled similarly. The goal of the PlantGDB web site is to establish the basis for identifying sets of genes common to all plants or specific to particular species by integrating a number of bioinformatics tools that facilitate gene prediction and cross- species comparisons. For species with large-scale genome sequencing efforts, PlantGDB provides genome browsing capabilities that integrate all available EST and cDNA evidence for current gene models (for Arabidopsis thaliana, see the AtGDB site at http://www.plantgdb.org/AtGDB/).

Computational Biology↗

PubMed2000

Global properties of the metabolic map of Escherichia coli.

The EcoCyc database characterizes the known network of Escherichia coli small-molecule metabolism. Here we present a computational analysis of the global properties of that network, which consists of 744 reactions that are catalyzed by 607 enzymes. The reactions are organized into 131 pathways. Of the metabolic enzymes, 100 are multifunctional, and 68 of the reactions are catalyzed by >1 enzyme. The network contains 791 chemical substrates. Other properties considered by the analysis include the distribution of enzyme subunit organization, and the distribution of modulators of enzyme activity and of enzyme cofactors. The dimensions chosen for this analysis can be employed for comparative functional analysis of complete genomes.

Catalysis↗

PubMedDate not supplied

ArrayExpress: a public database of gene expression data at EBI.

ArrayExpress is a public repository for microarray-based gene expression data, resulting from the implementation of the MAGE object model to ensure accurate data structuring and the MIAME standard, which defines the annotation requirements. ArrayExpress accepts data as MAGE-ML files for direct submissions or data from MIAMExpress, the MIAME compliant web-based annotation and submission tool of EBI. A team of curators supports the submission process, providing assistance in data annotation. Data retrieval is performed through a dedicated web interface. Relevant results may be exported to ExpressionProfiler, the EBI based expression analysis tool available online (http://www.ebi.ac.uk/arrayexpress).

Computational Biology↗

PubMed2006

Leveraging enzyme structure-function relationships for functional inference and experimental design: the structure-function linkage database.

The study of mechanistically diverse enzyme superfamilies-collections of enzymes that perform different overall reactions but share both a common fold and a distinct mechanistic step performed by key conserved residues-helps elucidate the structure-function relationships of enzymes. We have developed a resource, the structure-function linkage database (SFLD), to analyze these structure-function relationships. Unique to the SFLD is its hierarchical classification scheme based on linking the specific partial reactions (or other chemical capabilities) that are conserved at the superfamily, subgroup, and family levels with the conserved structural elements that mediate them. We present the results of analyses using the SFLD in correcting misannotations, guiding protein engineering experiments, and elucidating the function of recently solved enzyme structures from the structural genomics initiative. The SFLD is freely accessible at http://sfld.rbvi.ucsf.edu.

Animals↗

PubMed2002

Tolerating some redundancy significantly speeds up clustering of large protein databases.

MOTIVATION: Sequence clustering replaces groups of similar sequences in a database with single representatives. Clustering large protein databases like the NCBI Non-Redundant database (NR) using even the best currently available clustering algorithms is very time-consuming and only practical at relatively high sequence identity thresholds. Our previous program, CD-HI, clustered NR at 90% identity in approximately 1 h and at 75% identity in approximately 1 day on a 1 GHz Linux PC (Li et al., Bioinformatics, 17, 282, 2001); however even faster clustering speed is needed because the size of protein databases are rapidly growing and many applications desire a lower attainable thresholds. RESULTS: For our previous algorithm (CD-HI), we have employed short-word filters to speed up the clustering. In this paper, we show that tolerating some redundancy makes for more efficient use of these short-word filters and increases the program's speed 100 times. Our new program implements this technique and clusters NR at 70% identity within 2 h, and at 50% identity in approximately 5 days. Although some redundancy is present after clustering, our new program's results only differ from our previous program's by less than 0.4%.

Algorithms↗

PubMed2006

ARED 3.0: the large and diverse AU-rich transcriptome.

A comprehensive search that utilized a large set of mRNA data from human genome databases and additionally, expressed sequence tag (EST) database characterized this latest update of AU-rich elements (AREs) containing mRNA database (ARED). A large number of ARE-mRNA, as much as 4000, were recovered and include many of ARE alternative forms. This number represents as much as 5-8% of the human genes depending on the entire number of genes. The new ARED does not contain only larger and diverse number of ARE-mRNAs but additional functionality and enhanced search capabilities are given in the database website http://rc.kfshrc.edu.sa/ared/. These include class and cluster of AREs, source mRNAs, EST evidence, buildup information, retrieval of lists of genes, and integration with current and new NCBI data, such as Entrez ID and Unigene. Gene Ontology analysis shows there are significant differences in functional diversity of ARED when compared with the overall genome. Many of ARE-genes mediate regulatory processes, reactions to outside stimuli, RNA metabolism, and developmental processes particularly those of early and transient responses. The wide interest in mRNA turnover and importance of AREs in health and disease signify the compilation of ARE-genes.

3' Untranslated Regions↗

PubMed2006

Variation in evolutionary processes at different codon positions.

Evolutionary studies commonly model single nucleotide substitutions and assume that they occur as independent draws from a unique probability distribution across the sequence studied. This assumption is violated for protein-coding sequences, and we consider modeling approaches where codon positions (CPs) are treated as separate categories of sites because within each category the assumption is more reasonable. Such "codon-position" models have been shown to explain the evolution of codon data better than homogenous models in previous studies. This paper examines the ways in which codon-position models outperform homogeneous models and characterizes the differences in estimates of model parameters across CPs. Using the PANDIT database of multiple species DNA sequence alignments, we quantify the differences in the evolutionary processes at the 3 CPs in a systematic and comprehensive manner, characterizing previously undescribed features of protein evolution. We relate our findings to the functional constraints imposed by the genetic code, protein function, and the types of mutation that cause synonymous and nonsynonymous codon changes. The results increase our understanding of selective constraints and could be incorporated into phylogenetic analyses or gene-finding techniques in the future. The methods used are extended to an overlapping reading frame data set, and we discover that overlapping reading frames do not necessarily cause more stringent evolutionary constraints.

Base Sequence↗

PubMed2004

TransportDB: a relational database of cellular membrane transport systems.

TransportDB (http://www.membranetransport.org) is a relational database designed for describing the predicted cellular membrane transport proteins in organisms whose complete genome sequences are available. For each organism, the complete set of membrane transport systems was identified and classified into different types and families according to putative membrane topology, protein family, bioenergetics and substrate specificities. Web pages were created to provide user-friendly interfaces to easily access, query and download the data. Additional features, such as a BLAST search tool against known transporter protein sequences, comparison of transport systems from different organisms and phylogenetic trees of individual transporter families are also provided. TransportDB will be regularly updated with data obtained from newly sequenced genomes.

Animals↗

PubMed2004

Human protein reference database as a discovery resource for proteomics.

The rapid pace at which genomic and proteomic data is being generated necessitates the development of tools and resources for managing data that allow integration of information from disparate sources. The Human Protein Reference Database (http://www.hprd.org) is a web-based resource based on open source technologies for protein information about several aspects of human proteins including protein-protein interactions, post-translational modifications, enzyme-substrate relationships and disease associations. This information was derived manually by a critical reading of the published literature by expert biologists and through bioinformatics analyses of the protein sequence. This database will assist in biomedical discoveries by serving as a resource of genomic and proteomic information and providing an integrated view of sequence, structure, function and protein networks in health and disease.

Computational Biology↗

PubMed2005

Topology, tinkering and evolution of the human transcription factor network.

Patterns of protein interactions are organized around complex heterogeneous networks. Their architecture has been suggested to be of relevance in understanding the interactome and its functional organization, which pervades cellular robustness. Transcription factors are particularly relevant in this context, given their central role in gene regulation. Here we present the first topological study of the human protein-protein interacting transcription factor network built using the TRANSFAC database. We show that the network exhibits scale-free and small-world properties with a hierarchical and modular structure, which is built around a small number of key proteins. Most of these proteins are associated with proliferative diseases and are typically not linked to each other, thus reducing the propagation of failures through compartmentalization. Network modularity is consistent with common structural and functional features and the features are generated by two distinct evolutionary strategies: amplification and shuffling of interacting domains through tinkering and acquisition of specific interacting regions. The function of the regulatory complexes may have played an active role in choosing one of them.

Algorithms↗