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PubMed2004

Cross-species global and subset gene expression profiling identifies genes involved in prostate cancer response to selenium.

BACKGROUND: Gene expression technologies have the ability to generate vast amounts of data, yet there often resides only limited resources for subsequent validation studies. This necessitates the ability to perform sorting and prioritization of the output data. Previously described methodologies have used functional pathways or transcriptional regulatory grouping to sort genes for further study. In this paper we demonstrate a comparative genomics based method to leverage data from animal models to prioritize genes for validation. This approach allows one to develop a disease-based focus for the prioritization of gene data, a process that is essential for systems that lack significant functional pathway data yet have defined animal models. This method is made possible through the use of highly controlled spotted cDNA slide production and the use of comparative bioinformatics databases without the use of cross-species slide hybridizations. RESULTS: Using gene expression profiling we have demonstrated a similar whole transcriptome gene expression patterns in prostate cancer cells from human and rat prostate cancer cell lines both at baseline expression levels and after treatment with physiologic concentrations of the proposed chemopreventive agent Selenium. Using both the human PC3 and rat PAII prostate cancer cell lines have gone on to identify a subset of one hundred and fifty-four genes that demonstrate a similar level of differential expression to Selenium treatment in both species. Further analysis and data mining for two genes, the Insulin like Growth Factor Binding protein 3, and Retinoic X Receptor alpha, demonstrates an association with prostate cancer, functional pathway links, and protein-protein interactions that make these genes prime candidates for explaining the mechanism of Selenium's chemopreventive effect in prostate cancer. These genes are subsequently validated by western blots showing Selenium based induction and using tissue microarrays to demonstrate a significant association between downregulated protein expression and tumorigenesis, a process that is the reverse of what is seen in the presence of Selenium. CONCLUSIONS: Thus the outlined process demonstrates similar baseline and selenium induced gene expression profiles between rat and human prostate cancers, and provides a method for identifying testable functional pathways for the action of Selenium's chemopreventive properties in prostate cancer.

Adenocarcinoma↗

PubMed2004

Comparative analysis of gene sets in the Gene Ontology space under the multiple hypothesis testing framework.

The Gene Ontology (GO) resource can be used as a powerful tool to uncover the properties shared among, and specific to, a list of genes produced by high-throughput functional genomics studies, such as microarray studies. In the comparative analysis of several gene lists, researchers maybe interested in knowing which GO terms are enriched in one list of genes but relatively depleted in another. Statistical tests such as Fisher's exact test or Chi-square test can be performed to search for such GO terms. However, because multiple GO terms are tested simultaneously, individual p-values from individual tests do not serve as good indicators for picking GO terms. Furthermore, these multiple tests are highly correlated, usual multiple testing procedures that work under an independence assumption are not applicable. In this paper we introduce a procedure, based on False Discovery Rate (FDR), to treat this correlated multiple testing problem. This procedure calculates a moderately conserved estimator of q-value for every GO term. We identify the GO terms with q-values that satisfy a desired level as the significant GO terms. This procedure has been implemented into the GoSurfer software. GoSurfer is a windows based graphical data mining tool. It is freely available at http://www.gosurfer.org.

Algorithms↗

PubMed2005

GeneKeyDB: a lightweight, gene-centric, relational database to support data mining environments.

BACKGROUND: The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support large scale computational analysis, but rather offer exclusively a web interface to the resource. We have recognized the growing need for a database which can be used successfully as a backend to computational analysis tools and pipelines. Such database should be sufficiently versatile to allow easy system integration. RESULTS: GeneKeyDB is a gene-centered relational database developed to enhance data mining in biological data sets. The system provides an underlying data layer for computational analysis tools and visualization tools. GeneKeyDB relies primarily on existing database identifiers derived from community databases (NCBI, GO, Ensembl, et al.) as well as the known relationships among those identifiers. It is a lightweight, portable, and extensible platform for integration with computational tools and analysis environments. CONCLUSION: GeneKeyDB can enable analysis tools and users to manipulate the intersections, unions, and differences among different data sets.

Algorithms↗

PubMed2001

High-throughput development and characterization of a genomewide collection of gene-based single nucleotide polymorphism markers by chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

We describe here a system for the rapid identification, assay development, and characterization of gene-based single nucleotide polymorphisms (SNPs). This system couples informatics tools that mine candidate SNPs from public expressed sequence tag resources and automatically designs assay reagents with detection by a chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry platform. As a proof of concept of this system, a genomewide collection of reagents for 9,115 gene-based SNP genetic markers was rapidly developed and validated. These data provide preliminary insights into patterns of polymorphism in a genomewide collection of gene-based polymorphisms.

Alleles↗

PubMed2004

yMGV: a cross-species expression data mining tool.

The yeast Microarray Global Viewer (yMGV @ http://transcriptome.ens.fr/ymgv) was created 3 years ago as a database that houses a collection of Saccharomyces cerevisiae and Schizosaccharo myces pombe microarray data sets published in 82 different articles. yMGV couples data mining tools with a user-friendly web interface so that, with a few mouse clicks, one can identify the conditions that affect the expression of a gene or list of genes regulated in a set of experiments. One of the major new features we present here is a set of tools that allows for inter-organism comparisons. This should enable the fission yeast community to take advantage of the large amount of available information on budding yeast transcriptome. New tools and ongoing developments are also presented here.

Computational Biology↗

PubMed2006

Protein therapeutics--lessons learned and a view of the future.

Protein therapeutics represent a rapidly growing proportion of marketed drugs and have an undisputed place alongside chemistry-based oral therapies; indeed, for certain indications they are the only effective therapy. Therapeutic proteins can be mined from diverse sources to target interactions that are not accessible to small molecules, and can be engineered to have optimal pharmacological properties. Nevertheless, the development of such therapeutics is hampered by several issues, such as cost of production, patient compliance, immunogenicity and reticence of reimbursement agencies to pay for their use in chronic treatment. Herein we review some of these issues in detail. The application of technological advancements will address some of these issues and enable the development of a growing number of biological therapies that will continue to improve patient quality of life for decades to come.

Animals↗

PubMed2001

The adaptive evolution database (TAED).

BACKGROUND: The Master Catalog is a collection of evolutionary families, including multiple sequence alignments, phylogenetic trees and reconstructed ancestral sequences, for all protein-sequence modules encoded by genes in GenBank. It can therefore support large-scale genomic surveys, of which we present here The Adaptive Evolution Database (TAED). In TAED, potential examples of positive adaptation are identified by high values for the normalized ratio of nonsynonymous to synonymous nucleotide substitution rates (KA/KS values) on branches of an evolutionary tree between nodes representing reconstructed ancestral sequences. RESULTS: Evolutionary trees and reconstructed ancestral sequences were extracted from the Master Catalog for every subtree containing proteins from the Chordata only or the Embryophyta only. Branches with high KA/KS values were identified. These represent candidate episodes in the history of the protein family when the protein may have undergone positive selection, where the mutant form conferred more fitness than the ancestral form. Such episodes are frequently associated with change in function. An unexpectedly large number of families (between 10% and 20% of those families examined) were found to have at least one branch with high KA/KS values above arbitrarily chosen cut-offs (1 and 0.6). Most of these survived a robustness test and were collected into TAED. CONCLUSIONS: TAED is a raw resource for bioinformaticists interested in data mining and for experimental evolutionists seeking candidate examples of adaptive evolution for further experimental study. It can be expanded to include other evolutionary information (for example changes in gene regulation or splicing) placed in a phylogenetic perspective.

Adaptation, Physiological↗

PubMed2002

Up-regulation of WNT8B mRNA in human gastric cancer.

WNT - beta-catenin - TCF signaling pathway is activated by Xenopus wnt-8 (Xwnt-8) during Xenopus early development, and dysregulated activation of beta-catenin - TCF signaling pathway in mammalian cells leads to carcinogenesis. We have previously cloned and characterized human WNT8A, one of human orthologues of Xwnt-8. Here, we cloned and characterized human WNT8B by using bioinformatics, cDNA-PCR, and RACE. WNT8B gene of about 23-kb in size consisted of six exons, and encoded a 351-amino-acid polypeptide with the N-terminal signal peptide and two N-linked glycosylation sites. C-terminal region of WNT8B, WNT8A, WNT2, and WNT2B were longer than that of other human WNTs. Thirty-five nucleotide changes between WNT8B isolated by us and WNT8B isolated by another group resulted in Gly230Ala and Arg284Leu amino-acid substitutions. Gly230 and Arg284 of WNT8B were conserved in WNT8A. Gly230-Arg284 WNT8B allele was also identified in human genome draft sequences AL133352.10, AL359759.18, and human EST BF732616. These results indicate that the Gly230-Arg284 WNT8B cDNA isolated in this study is derived from the more common WNT8B allele. WNT8B mRNAs of 4.4- and 3.5-kb in size were weakly detected in a colorectal cancer cell line SW480, but were undetectable in any normal human tissues by using Northern blot analyses. WNT8B was significantly up-regulated in gastric cancer cell lines KATO-III (signet-ring cell carcinoma) and MKN45 (poorly differentiated adenocarcinoma), and also in 5 out of 10 cases of primary gastric cancer. WNT8B might play key roles in gastric cancer through activation of the beta-catenin - TCF signaling pathway.

Alleles↗

PubMed2007

ATM gene mutations in former uranium miners of SDAG Wismut: a pilot study.

Ataxia-telangiectasia is an autosomal recessive disease characterized by neurological and immunological symptoms, radiosensitivity and cancer predisposition. Heterozygous carriers of an ataxia-telangiectasia gene mutation are predisposed to epithelial cancers. We initiated a study to elucidate the frequency and clinical relevance of ATM gene mutations in former uranium miners exposed to high levels of radiation from radon and its decay products. Former uranium miners with Schneeberg lung cancer (n=48), former uranium miners suffering from silicosis (n=60) and uranium miners without occupational lung disorders (n=102) were investigated for nine mutations in the ATM gene. One gastric and one prostate cancer occurred in the group of miners without occupational lung diseases. Mutation analyses for S707P, IVS10-6Tright curved arrow G, 2250Gright curved arrow A, E1978X, R2443X, 3801delG, S49C and D2625E-A2626P were performed using genomic DNA obtained from peripheral blood samples. Three ATM gene alterations (S707P, S49C or IVS10-6Tright curved arrow G) were observed. Of all cancer patients, 8.0% were heterozygous, but only 1.9% of the non-cancer controls were [OR=4.6; 95% confidence interval (CI), 0.8-26.8]. In this pilot study a major role of six ATM gene mutations could not be revealed for cancer predisposition in former uranium miners. The results leave the possibility of a moderate risk associated with more subtle ATM gene alterations.

Aged↗

PubMed2006

Discovery of multiple beta-defensin like homologues in teleost fish.

Using a database mining approach, multiple defensin like genes have been discovered for the first time in fish, in species including zebrafish Danio rerio and the pufferfish, Takifugu rubripes and Tetraodon nigroviridis. They share the common features of vertebrate defensins, including small size, net cationic charge, and six conserved cysteines in the mature region. Based on their cysteine arrangement, the identified fish defensin like peptides resemble beta-defensin family members in birds and mammals. Computing modelling detected three beta-strands in all three zebrafish defensins and an extra N-terminal alpha-helix in one of the peptides. The coding regions of the fish genes contain three exons and two introns, the same as avian defensin genes. In zebrafish and tetraodon, two defensin genes identified are located in the same chromosome. An additional locus containing a third defensin gene has also been found in a different chromosome in zebrafish, demonstrating that multiple defensin loci may be present in fish. Comparative studies suggest that beta-defensins may represent the primitive form of the defensin family, which expanded during evolution by gene or genome duplication. In healthy zebrafish, constitutive expression of defensins was detected by RT-PCR in gill, gonad, gut, kidney, muscle, skin and spleen but the levels and patterns varied for individual defensin genes.

Amino Acid Sequence↗

PubMed2002

AgeWa: an integrated approach for antisense experiment design.

One of the major fallouts of the human genome project relates to the investigation of the molecular mechanisms of diseases. Identification of genes which are involved in a specific pathological process and characterization of their interactions is of fundamental importance for supporting the drug design processes. Discovery of targets and the related experimental validation is a critical step in the development of new drugs. The new experimental methods for gene expression analysis, such as microarray technology, allows for the concurrent evaluation of the expression of multiple genes. The outcome of these new experimental methods requires a subsequent validation of the gene function by using in vitro or in vivo models. In the last decade, one of the most promising methodologies for the investigation of gene function relies upon antisense oligonucleotides (ASO). The crucial step in antisense experiment design is the characterization of the nucleotide domains that can efficiently be targeted by this kind of synthetic molecule. At present, no standardized procedures for target selection are available. In this paper, we propose an integrative approach to ASO target selection: the proposed tool Automatic Gene Walk (AgeWa) combines a neural filter with database mining for the prediction of the optimal target for antisense action.

Algorithms↗

PubMed2026

GenBank mining reveals novel insights into Rhizobium phylogeny: Identical 16S rRNA sequences are mainly uncoupled from species designation, host plant, and geographic origin: How this search suggested the definition of a direct 'microbial h-index'.

16S rDNA is the historical gold standard for bacterial identification, particularly in metabarcoding approaches reliant on sequence similarity thresholds. We analyzed 6,660 Rhizobium 16S rRNA gene sequences from GenBank to examine the relationship between sequence identity and three metadata: species name, host plant, and geographic origin. Using an iterative BLAST-based pipeline, we detected 116,069 pairwise matches and assessed concordance among sequences (average length 1,328 bp) sharing 100% identity. For those in which the organism name, host plant and country of isolation were present in the record, surprisingly, 66.59% of identical sequence pairs showed full discordance across all three metadata, while only 1.40% shared the same name, host, and country. The most widespread sequence, detected 371 times, was associated with over 56 different host plants across 25 countries and bore multiple species name designations. These results highlight a striking mismatch between the 16S barcode and the taxonomic, ecological, and phenotypic variability it is assumed to reflect, likely arising from the slow evolution of rRNA genes contrasted with the mobility of ecologically relevant genes via horizontal transfer on plasmids, transposons, and phages. Our findings further challenge the limitations of relying on 16S rRNA alone for fine-scale taxonomic and metadata-based inference in capturing the true functional and ecological diversity of bacteria, endorsing the critical importance of polyphasic taxonomic approaches that integrate genomic, phenotypic, and ecological data. An interesting byproduct of the analysis was to realize the possibility of treating these data as if they were 'citations.' The more one finds the same query sequence, the more that sequence can be considered biologically 'cited', i.e., re-proposed elsewhere in the world. Thus, one can also analyze the h-index of such a ranking. In our Rhizobium dataset, we calculated an h-index = 201, meaning the sequence ranked 201st had 202 identical homologues in GenBank. Although the research effort on given species is directly connected with it, this number provides a quantitative indicator of a taxon's sequence recurrence and distribution within public databases, independent of nomenclatural inconsistencies, offering a novel framework for assessing bacterial representation across global datasets.

RNA, Ribosomal, 16S↗

PubMed2003

Global analysis of cellular transcription following infection with an HIV-based vector.

We have examined the changes in cellular transcription resulting from infection with HIV-based vectors. Previous work suggested that the incoming viral genome may under some circumstances be detected as DNA damage, so to explore this possibility, we compared the transcriptional response to infection with an HIV-based vector to the response to treatment with the DNA-damaging agent etoposide. Expression levels of about 12,000 cellular RNA transcripts were determined in a human B-cell line at different times after either treatment. Statistical analysis revealed that the infection with the lentivirus vector resulted in quite modest changes in gene expression. Treatment with etoposide, in contrast, caused drastic changes in expression of genes known or inferred to be involved in apoptosis. Statistically significant though subtle parallels in the cellular transcriptional responses to etoposide treatment and HIV-vector infection could be detected. Several further data sets analyzing infections with HIV-based vectors or wild-type HIV-1 showed similar modest effects on cellular transcription and very modest parallels among different data sets. These findings establish that HIV-vector or HIV-1 infection has remarkably little effect on cellular transcription. The statistical methods described here may be of wide use in mining microarray data sets. Our observations support the idea that gene therapy with HIV-based vectors should not be particularly toxic to cells due to disruption of cellular transcription.

B-Lymphocytes↗

PubMed2006

Molecular characterization of the developmental gene in eyes: through data-mining on integrated transcriptome databases.

OBJECTIVES: Our aim was to utilize publicly available and proprietary sources to discover candidate genes important for ocular development. DESIGN AND METHODS: The collated information on our 5092 non-redundant clusters was grouped and functional annotation was conducted using gene ontology (FatiGO) for categorizing them with respect to molecular function. The web-based viewer technological platform (H-InvDB) was employed for transcription analyses of in-house high quality fetal eye Expressed Sequence Tags (ESTs). Eye-specific ESTs were also analyzed across species by using EMBEST. RESULTS: According to adult eye cDNA libraries, nucleic acid binding and cell structure/cytoskeletal protein genes were the most abundant among the ESTs of fetal eyes. Using cDNA assembly in H-InvDB, 20 (80%) of the 25 most commonly expressed genes in the human eye are also expressed in extraocular tissues. The crystalline gamma S gene is highly expressed in the eye, but not in other tissues. We used EMBEST to compare human fetal eye and octopus eye ESTs and the expression similarity was low (1.6%). This indicated that our fetal eye library contains genes necessary for the developmental process and biological function of the eye, which may not be expressed in the fully developed octopus eyes. The human fetal eye cDNA library also contained highly abundant eye tissue genes, including alphaA-crystallin, eukaryotic translation elongation factor 1 alpha 1 (EEF1A1), bestrophin (VMD2), cystatin C, and transforming growth factor, beta-induced (BIGH3). CONCLUSIONS: Our annotated EST set provides a valuable resource for gene discovery and functional genomic analysis. This display will help to appreciate the strengths and weaknesses of the different technological platforms, so that in future studies the maximum amount of beneficial information can be derived from the appropriate use of each method.

Animals↗

PubMed2006

fRNAdb: a platform for mining/annotating functional RNA candidates from non-coding RNA sequences.

There are abundance of transcripts that code for no particular protein and that remain functionally uncharacterized. Some of these transcripts may have novel functions while others might be junk transcripts. Unfortunately, the experimental validation of such transcripts to find functional non-coding RNA candidates is very costly. Therefore, our primary interest is to computationally mine candidate functional transcripts from a pool of uncharacterized transcripts. We introduce fRNAdb: a novel database service that hosts a large collection of non-coding transcripts including annotated/non-annotated sequences from the H-inv database, NONCODE and RNAdb. A set of computational analyses have been performed on the included sequences. These analyses include RNA secondary structure motif discovery, EST support evaluation, cis-regulatory element search, protein homology search, etc. fRNAdb provides an efficient interface to help users filter out particular transcripts under their own criteria to sort out functional RNA candidates. fRNAdb is available at http://www.ncrna.org/

Base Sequence↗

PubMed2003

High-throughput proteomic analysis of human infiltrating ductal carcinoma of the breast.

Large-scale proteomics will play a critical role in the rapid display, identification and validation of new protein targets, and elucidation of the underlying molecular events that are associated with disease development, progression and severity. However, because the proteome of most organisms are significantly more complex than the genome, the comprehensive analysis of protein expression changes will require an analytical effort beyond the capacity of standard laboratory equipment. We describe the first high-throughput proteomic analysis of human breast infiltrating ductal carcinoma (IDCA) using OCT (optimal cutting temperature) embedded biopsies, two-dimensional difference gel electrophoresis (2-D DIGE) technology and a fully automated spot handling workstation. Total proteins from four breast IDCAs (Stage I, IIA, IIB and IIIA) were individually compared to protein from non-neoplastic tissue obtained from a female donor with no personal or family history of breast cancer. We detected differences in protein abundance that ranged from 14.8% in stage I IDCA versus normal, to 30.6% in stage IIB IDCA versus normal. A total of 524 proteins that showed > or = three-fold difference in abundance between IDCA and normal tissue were picked, processed and identified by mass spectrometry. Out of the proteins picked, approximately 80% were unambiguously assigned identities by matrix-assisted laser desorbtion/ionization-time of flight mass spectrometry or liquid chromatography-tandem mass spectrometry in the first pass. Bioinformatics tools were also used to mine databases to determine if the identified proteins are involved in important pathways and/or interact with other proteins. Gelsolin, vinculin, lumican, alpha-1-antitrypsin, heat shock protein-60, cytokeratin-18, transferrin, enolase-1 and beta-actin, showed differential abundance between IDCA and normal tissue, but the trend was not consistent in all samples. Out of the proteins with database hits, only heat shock protein-70 (more abundant) and peroxiredoxin-2 (less abundant) displayed the same trend in all the IDCAs examined. This preliminary study demonstrates quantitative and qualitative differences in protein abundance between breast IDCAs and reveals 2-D DIGE portraits that may be a reflection of the histological and pathological status of breast IDCA.

Adult↗

PubMed2006

Global dynamics of biological systems from time-resolved omics experiments.

The emergent properties of biological systems, organized around complex networks of irregularly connected elements, limit the applications of the direct scientific method to their study. The current lack of knowledge opens new perspectives to the inverse scientific paradigm where observations are accumulated and analysed by advanced data-mining techniques to enable a better understanding and the formulation of testable hypotheses about the structure and functioning of these systems. The current technology allows for the wide application of omics analytical methods in the determination of time-resolved molecular profiles of biological samples. Here it is proposed that the theory of dynamical systems could be the natural framework for the proper analysis and interpretation of such experiments. A new method is described, based on the techniques of non-linear time series analysis, which is providing a global view on the dynamics of biological systems probed with time-resolved omics experiments.

Algorithms↗

PubMed2002

Molecular cloning and expression of proto-oncogene FRAT1 in human cancer.

FRAT1 and FRAT2 genes, clustered in human chromosome 10q24, are human homologues to mouse proto-oncogene Frat1, which promotes carcinogenesis through activation of the WNT - beta-catenin - TCF signaling pathway. FRAT1 and FRAT2 mRNAs are up-regulated together in a gastric cancer cell line TMK1, and also in 2 out of 10 cases of primary gastric cancer. Here, we isolated FRAT1 cDNA (AB074890), which showed two amino-acid substitutions (Gln57X and His58Asp) compared with human FRAT1 cDNA previously reported by another group (U58975). The Gln57-His58 FRAT1 allele isolated in this study was also identified in human genome draft sequences. FRAT1 mRNA was almost ubiquitously expressed in human pancreatic cancer cell lines. Expression level of FRAT1 mRNA was relatively higher in esophageal cancer cell lines TE2, TE3, TE4, a cervical cancer cell line SKG-IIIa, and breast cancer cell lines MCF-7 and T-47D. Expression level of FRAT1 mRNA was not significantly changed after all-trans retinoic-acid treatment in NT2 cells with the potential of neuronal differentiation. Expression of FRAT1 mRNA in MCF-7 cells derived from breast cancer was down-regulated by beta-estradiol. This is the first report on isolation of FRAT1 cDNA derived from the more common FRAT1 allele, and also on regulation of FRAT1 mRNA in human cancer cells.

Adaptor Proteins, Signal Transducing↗