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PubMed2004

Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics.

BACKGROUND: When processing microarray data sets, we recently noticed that some gene names were being changed inadvertently to non-gene names. RESULTS: A little detective work traced the problem to default date format conversions and floating-point format conversions in the very useful Excel program package. The date conversions affect at least 30 gene names; the floating-point conversions affect at least 2,000 if Riken identifiers are included. These conversions are irreversible; the original gene names cannot be recovered. CONCLUSIONS: Users of Excel for analyses involving gene names should be aware of this problem, which can cause genes, including medically important ones, to be lost from view and which has contaminated even carefully curated public databases. We provide work-arounds and scripts for circumventing the problem.

Animals↗
PubMed2006

TF Target Mapper: a BLAST search tool for the identification of Transcription Factor target genes.

BACKGROUND: In the current era of high throughput genomics a major challenge is the genome-wide identification of target genes for specific transcription factors. Chromatin immunoprecipitation (ChIP) allows the isolation of in vivo binding sites of transcription factors and provides a powerful tool for examining gene regulation. Crosslinked chromatin is immunoprecipitated with antibodies against specific transcription factors, thus enriching for sequences bound in vivo by these factors in the immunoprecipitated DNA. Cloning and sequencing the immunoprecipitated sequences allows identification of transcription factor target genes. Routinely, thousands of such sequenced clones are used in BLAST searches to map their exact location in the genome and the genes located in the vicinity. These genes represent potential targets of the transcription factor of interest. Such bioinformatics analysis is very laborious if performed manually and for this reason there is a need for developing bioinformatic tools to automate and facilitate it. RESULTS: In order to facilitate this analysis we generated TF Target Mapper (Transcription Factor Target Mapper). TF Target Mapper is a BLAST search tool allowing rapid extraction of annotated information on genes around each hit. It combines sequence cleaning/filtering, pattern searching and BLAST searches with extraction of information on genes located around each BLAST hit and comparisons of the output list of genes or gene ontology IDs with user-implemented lists. We successfully applied and tested TF Target Mapper to analyse sequences bound in vivo by the transcription factor GATA-1. We show that TF Target Mapper efficiently extracted information on genes around ChIPed sequences, thus identifying known (e.g. alpha-globin and zeta-globin) and potentially novel GATA-1 gene targets. CONCLUSION: TF Target Mapper is a very efficient BLAST search tool that allows the rapid extraction of annotated information on the genes around each hit. It can contribute to the comprehensive bioinformatic transcriptome/regulome analysis, by providing insight into the mechanisms of action of specific transcription factors, thus helping to elucidate the pathways these factors regulate.

Amino Acid Sequence↗
PubMed2006

Splice variant of mouse Stam2 mRNA in nervous and muscle tissue contains additional exon with stop codon within region coding for VHS domain.

AIM: To analyze the alternatively spliced variant of Stam2 mRNA and determine its distribution in mouse tissues. METHODS: We identified a novel alternatively spliced exon by cloning and sequencing of Stam2 cDNA obtained from tissue samples of 3-5 months old male C57Bl/6NCrl mice. The sequence of the alternatively spliced exon was analyzed by bioinformatic tools. The tissue distribution of different Stam2 mRNA variants was determined by reverse transcription-polymerase chain reaction, and the consequences of the alternative splicing at the protein level were analyzed by western blot with the polyclonal anti-STAM2 antibody. RESULTS: The novel alternatively spliced exon 1A of mouse Stam2 gene was inserted within Stam2 coding region and it contained a stop codon. The exon did not bear similarities to any other cDNA or protein sequence in the mouse, rat, or human databases. Both mRNA variants, with and without exon 1A, were present in the cortex, hippocampus, olfactory bulb, medulla oblongata, spinal cord, cerebellum, and the skeletal and heart muscle, while the other analyzed organs contained only the variant without the additional exon. The mRNA with the included exon did not give rise to a protein form detectable by western blotting with the polyclonal anti-STAM2 antibody. CONCLUSION: The alternatively spliced exon 1A was included in mRNA splice variant present in the nervous and muscle tissues. The alternative splicing event did not have major impact on STAM2 production and functionality. It seems that exon 1A is an evolutionary new exon created by exonization of an intronic sequence.

Adaptor Proteins, Signal Transducing↗
PubMed2005

HUPO Brain Proteome Project Pilot Studies: bioinformatics at work.

The data acquisition phase of initial pilot studies (human and mouse brain samples) of the Human Proteome Organisation (HUPO) Brain Proteome Project (BPP) is now complete and the data generated by the participating laboratories has been submitted to the central Data Collection Center. The BPP Bioinformatics Group met on 8th April 2005 at the European Bioinformatics Institute (Hinxton, UK) to discuss strategies for the reanalysis of the pooled data from all the participating laboratories. A summary of the results of the data reprocessing will be presented at the 4th HUPO World Congress that will be held in August/September 2005.

Animals↗
PubMed2001

Target gene identification from expression array data by promoter analysis.

DNA microchips and expression arrays yield enormous amounts of data linking cDNA sequences to gene expression patterns. This now allows the characterization of gene expression in normal and diseased tissues as well as the response of tissues to the application of therapeutic reagents. Software currently exists to analyze DNA array/chip data with respect to corresponding mRNA sequences, which facilitates the precise determination of when and where certain groups of genes are expressed. The information concerning transcriptional regulatory networks responsible for the observed expression patterns is not contained within the cDNA sequences used to generate the arrays, but resides often within the promoter sequences of the individual genes (and/or enhancers). The complete sequence of the human genome will provide the molecular basis for the identification of such regulatory regions. Promoter sequences for specific cDNAs can be obtained reliably from genomic sequences simply by exon mapping. Promoter prediction tools can also be used to locate promoters directly in the genomic sequence in many cases in which cDNAs are 5'-incomplete. Once sufficient numbers of promoter sequences have been obtained, the comparative promoter analysis of the co-regulated genes and groups of genes can be applied in order to generate models describing the higher order levels of the transcription factor binding site organization within these promoter regions. As evident from several examples, this approach can identify promoter modules responsible for the common regulation of promoters solely by the application of bioinformatics methods. Such modules represent the molecular mechanisms through which regulatory networks influence gene expression. Another advantage of this approach is that it also provides a powerful alternative for elucidating functional features of genes with no detectable sequence similarity, by linking them to other genes on the basis of their common promoter structures.

Computational Biology↗
PubMed2003

Informatics and multivariate analysis of toxicogenomics data.

The application of genomics methods to toxicology holds great promise. Toxicogenomics data mapping gene expression to predict toxicity and understand mechanisms are emerging, with data suggesting the possibility to classify, and eventually predict, toxic responses. The overall process of informatics analysis of microarray data is summarized. The relationship between the bioinformatics of gene expression and toxicogenomics is discussed, with reference to emerging themes that may be important as the field of toxicogenomics evolves. Emerging themes include the choice and validation of statistical methods, the use of gene annotation and the impact of genome sequence projects.

Animals↗
PubMed2005

miBLAST: scalable evaluation of a batch of nucleotide sequence queries with BLAST.

A common task in many modern bioinformatics applications is to match a set of nucleotide query sequences against a large sequence dataset. Existing tools, such as BLAST, are designed to evaluate a single query at a time and can be unacceptably slow when the number of sequences in the query set is large. In this paper, we present a new algorithm, called miBLAST, that evaluates such batch workloads efficiently. At the core, miBLAST employs a q-gram filtering and an index join for efficiently detecting similarity between the query sequences and database sequences. This set-oriented technique, which indexes both the query and the database sets, results in substantial performance improvements over existing methods. Our results show that miBLAST is significantly faster than BLAST in many cases. For example, miBLAST aligned 247 965 oligonucleotide sequences in the Affymetrix probe set against the Human UniGene in 1.26 days, compared with 27.27 days with BLAST (an improvement by a factor of 22). The relative performance of miBLAST increases for larger word sizes; however, it decreases for longer queries. miBLAST employs the familiar BLAST statistical model and output format, guaranteeing the same accuracy as BLAST and facilitating a seamless transition for existing BLAST users.

Algorithms↗
PubMed2006

Protein expression in a transformed trabecular meshwork cell line: proteome analysis.

PURPOSE: Characterization of the human trabecular meshwork (TM) proteome is hindered by the small mass of intact tissue and the slow growth of cultured cell strains. We have previously characterized a transformed TM cell strain (GTM3) that demonstrates many of the same protein expression and cell signaling systems of nontransformed cell strains. The aim of this study was to initiate a proteomic survey of GTM3 cells as the initial step toward characterization of the complete human TM proteome. METHODS: GTM3 cells were cultured to confluence, harvested and solubilized in urea/Nonidet. The protein extract (600 mug) was focused in immobilized isoelectric focusing (IEF) strips, separated by 10% SDS PAGE, and visualized with colloidal Coomassie Blue. Spots of interest were excised, destained, and the contained proteins subjected to in-gel reduction, derivatization, and tryptic digestion. Tryptic peptides were extracted and analyzed by electrospray LC/MS/MS. Protein identification was made using the TurboSequest search algorithm and a recent version of the nonredundant human protein database downloaded from the National Center for Biotechnology Information (NCBI). RESULTS: Eighty-seven (87) primary proteins and 93 variants of these proteins were identified. A website was created (TM proteome) that combines data such as graphic spot location within the gel, peptide sequence, apparent and calculated pI, apparent and calculated mass, percentage of coverage, and protein informatic website links. CONCLUSIONS: Proteomic analysis of a transformed human TM cell line has been initiated combining preparative two-dimensional PAGE separation, LC/MS/MS analysis of major proteins, and bioinformatic cataloging of the data. Further investigation of data from the transformed cell strain will be used in a comparative fashion for spot identification of analytical proteomic gels of human TM tissue and cultured normal cells. These initial data will form the base from which the characterization of protein expression in the normal and glaucomatous TM can be accomplished.

Cell Line, Transformed↗
PubMed2003

The biosynthesis of the branched-chain sugar d-apiose in plants: functional cloning and characterization of a UDP-d-apiose/UDP-d-xylose synthase from Arabidopsis.

d-Apiose is a plant-specific branched-chain monosaccharide found in rhamnogalacturonan II (RG-II), apiogalacturonan, and several apioglycosides. Within RG-II, d-apiose serves as the binding site for borate, which leads to the formation of cross-links within the wall. Biochemical studies in duckweed and parsley have established that uridine 5'-diphospho-d-apiose (UDP-d-apiose) is formed from UDP-d-glucuronate by decarboxylation and re-arrangement of the carbon skeleton, leading to ring contraction and branch formation. The enzyme catalyzing this reaction also forms UDP-d-xylose by decarboxylation of UDP-d-glucuronate, and has therefore been named UDP-d-apiose/UDP-d-xylose synthase. Using a bioinformatics approach, we identified a candidate gene (AXS1) for this enzyme in Arabidopsis and functionally expressed its cDNA in Escherichia coli. The recombinant enzyme catalyzed the conversion of UDP-d-glucuronate to a mixture of UDP-d-apiose and UDP-d-xylose with a turnover number of 0.3 min-1. AXS1 required NAD+ for enzymatic activity, and was strongly inhibited by UDP-d-galacturonate. It was highly expressed in all plant organs consistent with a function in synthesizing an essential cell wall precursor. Database searches indicated the presence of closely related sequences in a variety of crop plants. The cloning of the AXS1 gene will help to investigate the biosynthesis of RG-II, and permit insights into the mechanism by which d-apiose and other branched monosaccharides are formed.

Arabidopsis Proteins↗
PubMed2004

Sockeye: a 3D environment for comparative genomics.

Comparative genomics techniques are used in bioinformatics analyses to identify the structural and functional properties of DNA sequences. As the amount of available sequence data steadily increases, the ability to perform large-scale comparative analyses has become increasingly relevant. In addition, the growing complexity of genomic feature annotation means that new approaches to genomic visualization need to be explored. We have developed a Java-based application called Sockeye that uses three-dimensional (3D) graphics technology to facilitate the visualization of annotation and conservation across multiple sequences. This software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization.

Animals↗
PubMed2005

An I/O device driver for bioinformatics tools: the case for BLAST.

There are many bioinformatics tools that deal with input/output (I/O) issues by using filing systems from the most common operating systems, such as Linux or MS Windows. However, as data volumes increase, there is a need for more efficient disk access, ad hoc memory management and specific page-replacement policies. We propose a device driver that can be used by multiple applications. It keeps the application code unchanged, providing a non-intrusive and flexible strategy for I/O calls that may be adopted in a straightforward manner. With our approach, database developers can define their own I/O management strategies. We used our device driver to manage Basic Local Alignment Search Tool (BLAST) I/O calls. Based on preliminary experimental results with National Center for Biotechnology Information (NCBI) BLAST, this approach can provide database management systems-like data management features, which may be used for BLAST and many other computational biology applications.

Algorithms↗
PubMed2005

Understanding protein trafficking in plant cells through proteomics.

The functions of approximately one-third of the proteins encoded by the Arabidopsis thaliana genome are completely unknown. Moreover, many annotations of the remainder of the genome supply tentative functions, at best. Knowing the ultimate localization of these proteins, as well as the pathways used for getting there, may provide clues as to their functions. The putative localization of most proteins currently relies on in silico-based bioinformatics approaches, which, unfortunately, often result in erroneous predictions. Emerging proteomics techniques coupled with other systems biology approaches now provide researchers with a plethora of methods for elucidating the final location of these proteins on a large scale, as well as the ability to dissect protein-sorting pathways in plants.

Databases, Protein↗
PubMed2002

Information requirements of genomics researchers from the patient clinical record.

The integration of bioinformatics and clinical informatics requires the assimilation of genomic information into the clinical record, as well as an understanding of the information needs of genomics researchers. This paper focuses on a methodology to make this information requirements determination and capture an initial set of requirements for future information systems development.

Computational Biology↗
PubMed2003

Bioinformatics support for high-throughput proteomics.

In the "post-genome" era, mass spectrometry (MS) has become an important method for the analysis of proteome data. The rapid advancement of this technique in combination with other methods used in proteomics results in an increasing number of high-throughput projects. This leads to an increasing amount of data that needs to be archived and analyzed. To cope with the need for automated data conversion, storage, and analysis in the field of proteomics, the open source system ProDB was developed. The system handles data conversion from different mass spectrometer software, automates data analysis, and allows the annotation of MS spectra (e.g. assign gene names, store data on protein modifications). The system is based on an extensible relational database to store the mass spectra together with the experimental setup. It also provides a graphical user interface (GUI) for managing the experimental steps which led to the MS data. Furthermore, it allows the integration of genome and proteome data. Data from an ongoing experiment was used to compare manual and automated analysis. First tests showed that the automation resulted in a significant saving of time. Furthermore, the quality and interpretability of the results was improved in all cases.

Algorithms↗
PubMed2006

BASC: an integrated bioinformatics system for Brassica research.

The BASC system provides tools for the integrated mining and browsing of genetic, genomic and phenotypic data. This public resource hosts information on Brassica species supporting the Multinational Brassica Genome Sequencing Project, and is based upon five distinct modules, ESTDB, Microarray, MarkerQTL, CMap and EnsEMBL. ESTDB hosts expressed gene sequences and related annotation derived from comparison with GenBank, UniRef and the genome sequence of Arabidopsis. The Microarray module hosts gene expression information related to genes annotated within ESTDB. MarkerQTL is the most complex module and integrates information on genetic markers, maps, individuals, genotypes and traits. Two further modules include an Arabidopsis EnsEMBL genome viewer and the CMap comparative genetic map viewer for the visualization and integration of genetic and genomic data. The database is accessible at http://bioinformatics.pbcbasc.latrobe.edu.au.

Arabidopsis↗
PubMed2006

An object-oriented programming system for the integration of internet-based bioinformatics resources.

The Internet consists of a vast inhomogeneous reservoir of data. Developing software that can integrate a wide variety of different data sources is a major challenge that must be addressed for the realisation of the full potential of the Internet as a scientific research tool. This article presents a semi-automated object-oriented programming system for integrating web-based resources. We demonstrate that the current Internet standards (HTML, CGI [common gateway interface], Java, etc.) can be exploited to develop a data retrieval system that scans existing web interfaces and then uses a set of rules to generate new Java code that can automatically retrieve data from the Web. The validity of the software has been demonstrated by testing it on several biological databases. We also examine the current limitations of the Internet and discuss the need for the development of universal standards for web-based data.

Computational Biology↗
PubMed2002

Bioinformatical results based on statistical methods for endectocide products against fly-larvae.

The larvicide effects of three endecticide products were studied against house fly larvae. Repeated-measure design was used for the analysis of variance. The observed data followed different distributions. For this reason, instead of the repeated measure ANOVA, three fast statistical methods were applied simultaneously. First, the test for homogeneity was carried out for registered samples by using the Friedman test, and the Wilcoxon-Wilcox test was applied for pairwise comparisons. Secondly, an extended median test was applied for the same problem of test for homogeneity, and the Neményi test was used for pairwise comparisons. Thirdly, a 2 x 2 contingency table analysis was carried out, exploiting the specific feature of the database and informatical tools. The three simultaneous evaluations enabled us to come to sound, affirmative conclusions. In the course of veterinary-biological interpretation we demonstrated the statistically reliable temporal efficiency of the three products. We also presented the relative efficiency and recognizable features of the products. We highlighted the significantly prompt and long release larvicide effects of the drugs. We discussed and compared the information content of the applied statistical methods.

Analysis of Variance↗
PubMed2002

[New aspects of molecular biology diagnosis. Array technology and expression profile for characterization of rheumatic diseases].

Increasing availability of high throughput technologies, exponentially growing information about the human genome and gene expression, and the growing global network of databases on systematic biomedical information will change our view on inflammatory rheumatic diseases in a revolutionary way. Several research laboratories have already generated initial extensive datasets on gene expression analysis. Application of this technique has demonstrated that in addition to a precise analysis, verification and validation of the results also on the level of cell populations, a meticulous characterization of the patients according to current conventional clinical, laboratory, imaging and histological standards is essential. For functional interpretation, in vitro tests, animal models and therapeutic studies will provide further information. Bioinformatic structuring and development is needed for the large amounts of data. After an initial genome-wide screening, the objective is to identify those genes, which will allow characterization of the disease, classification according to molecular pathophysiology, evaluation of the prognosis and prediction of the correct and most potent therapeutic regimen. Derived from the improved knowledge about the molecular mechanisms, new and--as to expect--the crucial approaches for an effective therapy against chronic inflammation, organ destruction and pathological immune response in rheumatic diseases will emerge.

Autoantibodies↗