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At least 469 records · Page 26Linked to original sources
PubMed2005

G2D: a tool for mining genes associated with disease.

BACKGROUND: Human inherited diseases can be associated by genetic linkage with one or more genomic regions. The availability of the complete sequence of the human genome allows examining those locations for an associated gene. We previously developed an algorithm to prioritize genes on a chromosomal region according to their possible relation to an inherited disease using a combination of data mining on biomedical databases and gene sequence analysis. RESULTS: We have implemented this method as a web application in our site G2D (Genes to Diseases). It allows users to inspect any region of the human genome to find candidate genes related to a genetic disease of their interest. In addition, the G2D server includes pre-computed analyses of candidate genes for 552 linked monogenic diseases without an associated gene, and the analysis of 18 asthma loci. CONCLUSION: G2D can be publicly accessed at http://www.ogic.ca/projects/g2d_2/.

Algorithms↗
PubMed2000

Identification and analysis of the myosin superfamily in Drosophila: a database approach.

The recent sequencing of the genome of Drosophila melanogaster has provided a valuable resource for mining the database for genes of interest. We took advantage of this opportunity in an attempt to identify novel myosins in Drosophila and confirm the presence of the previously identified myosins from classes I, II, III, V, VI, and VII. The Drosophila database annotators predicted the structure of three additional proteins which we identified as novel unconventional myosins, two of which fell into classes XV and XVIII, respectively. Our own efforts predicted the presence of four additional partial sequences that appear to be myosin proteins which did not fall into any specific class. In the future comparative genomics will hopefully lead to the placement of these myosins into new classes.

Animals↗
PubMed2004

Integration of high-resolution array comparative genomic hybridization analysis of chromosome 16q with expression array data refines common regions of loss at 16q23-qter and identifies underlying candidate tumor suppressor genes in prostate cancer.

We have constructed a high-resolution genomic microarray of human chromosome 16q, and used it for comparative genomic hybridization analysis of 16 prostate tumors. We demarcated 10 regions of genomic loss between 16q23.1 and 16qter that occurred in five or more samples. Mining expression array data from four independent studies allowed us to identify 11 genes that were frequently underexpressed in prostate cancer and that co-localized with a region of genomic loss. Quantitative expression analyses of these genes in matched tumor and benign tissue from 13 patients showed that six of these 11 (WWOX, WFDC1, MAF, FOXF1, MVD and the predicted novel transcript Q9H0B8 (NM_031476)) had significant and consistent downregulation in the tumors relative to normal prostate tissue expression making them candidate tumor suppressor genes.

Chromosomes, Human, Pair 16↗
PubMed2005

Data mining for protein-protein interactions in invertebrate model organisms.

Well-annotated genome databases are available for many invertebrate species, notably the fruitfly, Drosophila melanogaster, and the nematode, Caenorhabditis elegans. An adequate interpretation of this information at the biological level requires the exploration of the interactions between the gene products. Knowledge of protein interactions and the components of cell signalling pathways in the fly and worm are particularly valuable as hypotheses can be rapidly tested using the powerful genetic toolkits available. Invertebrates offer additional experimental advantages when attempting to characterise protein-protein interactions (PPIs). Their relatively small genome size compared to mammals helps to reduce missed interactions due to redundancy, and their function can be addressed using forward (mutants) and reverse (RNA interference) genetics. However, the researcher looking for evidence of PPIs for a protein of interest is faced with the challenge of extracting interaction data from sources that are highly varied, such as the results of microarray experiments in the unstructured text of research papers. This challenge is greatly reduced by a range of public databases of curated information, as well as publicly available, enhanced search engines, which can provide either direct experimental evidence for a PPI, or valuable clues for generating new hypotheses.

Animals↗
PubMed2003

Mining microorganism EST databases in the quest for new proteins.

Microorganisms with large genomes are commonly the subjects of single-round partial sequencing of cDNA, generating expressed sequence tags (ESTs). Usually there is a great distance between gene discovery by EST projects and submission of amino acid sequences to public databases. We analyzed the relationship between available ESTs and protein sequences and used the sequences available in the secondary database, clusters of orthologous groups (COG), to investigate ESTs from eight microorganisms of medical and/or economic relevance, selecting for candidate ESTs that may be further pursued for protein characterization. The organisms chosen were Paracoccidioides brasiliensis, Dictyostelium discoideum, Fusarium graminearum, Plasmodium yoelii, Magnaporthe grisea, Emericella nidulans, Chlamydomonas reinhardtii and Eimeria tenella, which have more than 10,000 ESTs available in dbEST. A total of 77,114 protein sequences from COG were used, corresponding to 3,201 distinct genes. At least 212 of these were capable of identifying candidate ESTs for further studies (E. tenella). This number was extended to over 700 candidate ESTs (C. reinhardtii, F. graminearum). Remarkably, even the organism that presents the highest number of ESTs corresponding to known proteins, P. yoelii, showed a considerable number of candidate ESTs for protein characterization (477). For some organisms, such as P. brasiliensis, M. grisea and F. graminearum, bioinformatics has allowed for automatic annotation of up to about 20% of the ESTs that did not correspond to proteins already characterized in the organism. In conclusion, 4093 ESTs from these eight organisms that are homologous to COG genes were selected as candidates for protein characterization.

Animals↗
PubMed2001

Genome analysis with gene-indexing databases.

The recent release of the draft sequence and the eventual completion of the human genome present the scientific community with a rich source of data to mine. Yet, these data are content poor in the absence of additional correlative information. Expressed sequence tag (EST) datasets and their associated gene indices have existed for many years, and represent the first attempt at understanding the complexity of the genome. These datasets remain extremely important as information sources and, in particular, as tools for analyzing the completed genomes. Here, we discuss the nature of ESTs and their associated tools and gene-indexing databases. In particular, we will compare three EST gene indices (UNIGENE, Merck Gene Index Version 2.0 and Doubletwist CAT), discuss how these gene indices are applied for both genome analysis and drug discovery, and demonstrate their importance as a complementary dataset to the annotated human genome.

Databases, Factual↗
PubMed2005

Genome cluster database. A sequence family analysis platform for Arabidopsis and rice.

The genome-wide protein sequences from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) spp. japonica were clustered into families using sequence similarity and domain-based clustering. The two fundamentally different methods resulted in separate cluster sets with complementary properties to compensate the limitations for accurate family analysis. Functional names for the identified families were assigned with an efficient computational approach that uses the description of the most common molecular function gene ontology node within each cluster. Subsequently, multiple alignments and phylogenetic trees were calculated for the assembled families. All clustering results and their underlying sequences were organized in the Web-accessible Genome Cluster Database (http://bioinfo.ucr.edu/projects/GCD) with rich interactive and user-friendly sequence family mining tools to facilitate the analysis of any given family of interest for the plant science community. An automated clustering pipeline ensures current information for future updates in the annotations of the two genomes and clustering improvements. The analysis allowed the first systematic identification of family and singlet proteins present in both organisms as well as those restricted to one of them. In addition, the established Web resources for mining these data provide a road map for future studies of the composition and structure of protein families between the two species.

Algorithms↗
PubMed2005

A microsatellite-based, gene-rich linkage map for the AA genome of Arachis (Fabaceae).

Cultivated peanut (Arachis hypogaea) is an important crop, widely grown in tropical and subtropical regions of the world. It is highly susceptible to several biotic and abiotic stresses to which wild species are resistant. As a first step towards the introgression of these resistance genes into cultivated peanut, a linkage map based on microsatellite markers was constructed, using an F(2) population obtained from a cross between two diploid wild species with AA genome (A. duranensis and A. stenosperma). A total of 271 new microsatellite markers were developed in the present study from SSR-enriched genomic libraries, expressed sequence tags (ESTs), and by "data-mining" sequences available in GenBank. Of these, 66 were polymorphic for cultivated peanut. The 271 new markers plus another 162 published for peanut were screened against both progenitors and 204 of these (47.1%) were polymorphic, with 170 codominant and 34 dominant markers. The 80 codominant markers segregating 1:2:1 (P<0.05) were initially used to establish the linkage groups. Distorted and dominant markers were subsequently included in the map. The resulting linkage map consists of 11 linkage groups covering 1,230.89 cM of total map distance, with an average distance of 7.24 cM between markers. This is the first microsatellite-based map published for Arachis, and the first map based on sequences that are all currently publicly available. Because most markers used were derived from ESTs and genomic libraries made using methylation-sensitive restriction enzymes, about one-third of the mapped markers are genic. Linkage group ordering is being validated in other mapping populations, with the aim of constructing a transferable reference map for Arachis.

Arachis↗
PubMed2005

Mining genetic epidemiology data with Bayesian networks I: Bayesian networks and example application (plasma apoE levels).

MOTIVATION: The wealth of single nucleotide polymorphism (SNP) data within candidate genes and anticipated across the genome poses enormous analytical problems for studies of genotype-to-phenotype relationships, and modern data mining methods may be particularly well suited to meet the swelling challenges. In this paper, we introduce the method of Belief (Bayesian) networks to the domain of genotype-to-phenotype analyses and provide an example application. RESULTS: A Belief network is a graphical model of a probabilistic nature that represents a joint multivariate probability distribution and reflects conditional independences between variables. Given the data, optimal network topology can be estimated with the assistance of heuristic search algorithms and scoring criteria. Statistical significance of edge strengths can be evaluated using Bayesian methods and bootstrapping. As an example application, the method of Belief networks was applied to 20 SNPs in the apolipoprotein (apo) E gene and plasma apoE levels in a sample of 702 individuals from Jackson, MS. Plasma apoE level was the primary target variable. These analyses indicate that the edge between SNP 4075, coding for the well-known epsilon2 allele, and plasma apoE level was strong. Belief networks can effectively describe complex uncertain processes and can both learn from data and incorporate prior knowledge. AVAILABILITY: Various alternative and supplemental networks (not given in the text) as well as source code extensions, are available from the authors. SUPPLEMENTARY INFORMATION: http://bioinformatics.oxfordjournals.org.

Apolipoproteins E↗
PubMed2002

Sequence variations in the public human genome data reflect a bottlenecked population history.

Single-nucleotide polymorphisms (SNPs) constitute the great majority of variations in the human genome, and as heritable variable landmarks they are useful markers for disease mapping and resolving population structure. Redundant coverage in overlaps of large-insert genomic clones, sequenced as part of the Human Genome Project, comprises a quarter of the genome, and it is representative in terms of base compositional and functional sequence features. We mined these regions to produce 500,000 high-confidence SNP candidates as a uniform resource for describing nucleotide diversity and its regional variation within the genome. Distributions of marker density observed at different overlap length scales under a model of recombination and population size change show that the history of the population represented by the public genome sequence is one of collapse followed by a recent phase of mild size recovery. The inferred times of collapse and recovery are Upper Paleolithic, in agreement with archaeological evidence of the initial modern human colonization of Europe.

Databases, Nucleic Acid↗
PubMed2003

A semiautomated approach to gene discovery through expressed sequence tag data mining: discovery of new human transporter genes.

Identification and functional characterization of the genes in the human genome remain a major challenge. A principal source of publicly available information used for this purpose is the National Center for Biotechnology Information database of expressed sequence tags (dbEST), which contains over 4 million human ESTs. To extract the information buried in this data more effectively, we have developed a semiautomated method to mine dbEST for uncharacterized human genes. Starting with a single protein input sequence, a family of related proteins from all species is compiled. This entire family is then used to mine the human EST database for new gene candidates. Evaluation of putative new gene candidates in the context of a family of characterized proteins provides a framework for inference of the structure and function of the new genes. When applied to a test data set of 28 families within the major facilitator superfamily (MFS) of membrane transporters, our protocol found 73 previously characterized human MFS genes and 43 new MFS gene candidates. Development of this approach provided insights into the problems and pitfalls of automated data mining using public databases.

Biological Transport, Active↗
PubMed2006

TcruziDB: an integrated, post-genomics community resource for Trypanosoma cruzi.

TcruziDB (http://TcruziDB.org) is an integrated post-genomics database for the parasitic organism, Trypanosoma cruzi, the causative agent of Chagas' disease. TcruziDB was established in 2003 as a flat-file database with tools for mining the unannotated sequence reads and preliminary contig assemblies emerging from the Tri-Tryp genome consortium (TIGR/SBRI/Karolinska). Today, TcruziDB houses the recently published assembled genomic contigs and annotation provided by the genome consortium in a relational database supported by the Genomics Unified Schema (GUS) architecture. The combination of an annotated genome and a relational architecture has facilitated the integration of genomic data with expression data (proteomic and EST) and permitted the construction of automated analysis pipelines. TcruziDB has accepted, and will continue to accept the deposition of genomic and functional genomic datasets contributed by the research community.

Animals↗
PubMed2003

A genome-wide identification of E2F-regulated genes in Arabidopsis.

The completion of the Arabidopsis genomic sequence offers the possibility to extract global information about regulatory mechanisms. Here, we describe a data mining strategy in combination with gene expression analysis to identify bona fide genes regulated by the E2F transcription factor. Starting with a genome-wide search of chromosomal sites containing E2F-binding sites, we studied in depth two of the most abundant E2F-binding sites within the Arabidopsis genome and identified over 180 potential E2F target genes. Among them and in addition to cell cycle-related genes, we have also identified genes belonging to other functional categories, e.g. transcription, stress and defense or signaling. We have determined the expression levels of genes selected from different categories under two experimental situations. Using cultured cells partially synchronized with aphidicolin, we found that most potential E2F targets identified in silico show a cell cycle-regulated expression pattern with a peak in early/mid S-phase. In addition, we used Arabidopsis transgenic plants expressing a DP gene containing a truncated DNA-binding domain, which likely has a dominant-negative effect on AtE2Fa, b and c (also named AtE2F3, 1 and 2, respectively), which require DP for efficient DNA binding. Contrary to the up-regulation observed in early/mid S-phase-cultured cells, the expression of a large number of potential E2F targets was decreased in the transgenic plants. Our results strongly support that the RBR/E2F pathway plays a crucial role in regulating the expression of the genes identified in this study.

Amino Acid Sequence↗
PubMed2006

Mining Alzheimer disease relevant proteins from integrated protein interactome data.

Huge unrealized post-genome opportunities remain in the understanding of detailed molecular mechanisms for Alzheimer Disease (AD). In this work, we developed a computational method to rank-order AD-related proteins, based on an initial list of AD-related genes and public human protein interaction data. In this method, we first collected an initial seed list of 65 AD-related genes from the OMIM database and mapped them to 70 AD seed proteins. We then expanded the seed proteins to an enriched AD set of 765 proteins using protein interactions from the Online Predicated Human Interaction Database (OPHID). We showed that the expanded AD-related proteins form a highly connected and statistically significant protein interaction sub-network. We further analyzed the sub-network to develop an algorithm, which can be used to automatically score and rank-order each protein for its biological relevance to AD pathways(s). Our results show that functionally relevant AD proteins were consistently ranked at the top: among the top 20 of 765 expanded AD proteins, 19 proteins are confirmed to belong to the original 70 AD seed protein set. Our method represents a novel use of protein interaction network data for Alzheimer disease studies and may be generalized for other disease areas in the future.

Algorithms↗
PubMed2005

Applications of the double-barreled data in whole-genome shotgun sequence assembly and analysis.

Double-barreled (DB) data have been widely used for the assembly of large genomes. Based on the experience of building the whole-genome working draft of Oryza sativa L. ssp. Indica, we present here the prevailing and improved uses of DB data in the assembly procedure and report on novel applications during the following data-mining processes such as acquiring precise insert fragment information of each clone across the genome, and a new kind of low-cost whole-genome microarray. With the increasing number of organisms being sequenced, we believe that DB data will play an important role both in other assembly procedures and in future genomic studies.

Cloning, Molecular↗
PubMed2005

Identification of cyanobacterial cell division genes by comparative and mutational analyses.

We performed comparative and mutational analyses to define more comprehensively the repertoire of genes involved in cyanobacterial cell division. Genes ftsE, ftsI, ftsQ, ftsW, and (previously recognized) ftsZ, minC, minD, minE and sulA were identified as homologues of cell division genes of Gram-negative and Gram-positive bacteria. Transposon mutagenesis of Synechococcus elongatus PCC 7942 identified five additional genes, cdv1, cdv2, cdv3, ftn6 and cikA, involved in cell division. cdv1 encodes a presumptive periplasmic peptidyl-prolyl cis-trans isomerase. cdv2 has similarity to ylmF which, like divIVA, lies within the Gram-positive bacterial ylm gene cluster whose members have functions associated with division. Conservation of other ylm genes in cyanobacteria suggests that cyanobacteria and Gram-positive bacteria share specific division proteins. Two ylm homologues are also found in algal and plant genomes. cdv3 has low but significant similarity to divIVA, suggesting that minE and cdv3 both mediate division-site determination in cyanobacteria. In contrast, Gram-positive bacteria lack minE, and (Gram-negative) proteobacteria lack divIVA. ftn6, of unknown function, and the circadian input kinase, cikA, are specific to cyanobacteria. In S. elongatus, unlike in other bacteria, FtsZ rings are formed at sites occupied by nucleoids. Thus, the division machinery of cyanobacteria differs in its composition and regulation from that of Gram-negative and Gram-positive bacteria.

Bacillus subtilis↗
PubMed2003

Identification and functional analysis of six mycolyltransferase genes of Corynebacterium glutamicum ATCC 13032: the genes cop1, cmt1, and cmt2 can replace each other in the synthesis of trehalose dicorynomycolate, a component of the mycolic acid layer of the cell envelope.

By data mining in the sequence of the Corynebacterium glutamicum ATCC 13032 genome, six putative mycolyltransferase genes were identified that code for proteins with similarity to the N-terminal domain of the mycolic acid transferase PS1 of the related C. glutamicum strain ATCC 17965. The genes identified were designated cop1, cmt1, cmt2, cmt3, cmt4, and cmt5 ( cmt from corynebacterium mycolyl transferases). cop1 encodes a protein of 657 amino acids, which is larger than the proteins encoded by the cmt genes with 365, 341, 483, 483, and 411 amino acids. Using bioinformatics tools, it was shown that all six gene products are equipped with signal peptides and esterase domains. Proteome analyses of the cell envelope of C. glutamicum ATCC 13032 resulted in identification of the proteins Cop1, Cmt1, Cmt2, and Cmt4. All six mycolyltransferase genes were used for mutational analysis. cmt4 could not be mutated and is considered to be essential. cop1 was found to play an additional role in cell shape formation. A triple mutant carrying mutations in cop1, cmt1, and cmt2 aggregated when cultivated in MM1 liquid medium. This mutant was also no longer able to synthesize trehalose di coryno mycolate (TDCM). Since single and double mutants of the genes cop1, cmt1, and cmt2 could form TDCM, it is concluded that the three genes, cop1, cmt1, and cmt2, are involved in TDCM biosynthesis. The presence of the putative esterase domain makes it highly possible that cop1, cmt1, and cmt2 encode enzymes synthesizing TDCM from trehalose monocorynomycolate.

Arabidopsis Proteins↗
PubMed2006

Expression and variability of molecular chaperones in the sugarcane expressome.

Molecular chaperones perform folding assistance in newly synthesized polypeptides preventing aggregation processes, recovering proteins from aggregates, among other important cellular functions. Thus their study presents great biotechnological importance. The present work discusses the mining for chaperone-related sequences within the sugarcane EST genome project database, which resulted in approximately 300 different sequences. Since molecular chaperones are highly conserved in most organisms studied so far, the number of sequences related to these proteins in sugarcane was very similar to the number found in the Arabidopsis thaliana genome. The Hsp70 family was the main molecular chaperone system present in the sugarcane expressome. However, many other relevant molecular chaperones systems were also present. A digital RNA blot analysis showed that 5'ESTs from all molecular chaperones were found in every sugarcane library, despite their heterogeneous expression profiles. The results presented here suggest the importance of molecular chaperones to polypeptide metabolism in sugarcane cells, based on their abundance and variability. Finally, these data have being used to guide more in deep analysis, permitting the choice of specific targets to study.

Arabidopsis↗