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PubMed2001

Comparing vertebrate whole-genome shotgun reads to the human genome.

Multi-species sequence comparisons are a very efficient way to reveal conserved genes. Because sequence finishing is expensive and time consuming, many genome sequences are likely to stay incomplete. A challenge is to use these fragmented data for understanding the human genome. Methods for using cross-species whole-genome shotgun sequence (WGS) for genome annotation are described in this paper. About one-half million high-quality rat WGS reads (covering 7.5% of the rat genome) generated at the Baylor College of Medicine Human Genome Sequencing Center were compared with the human genome. Using computer-generated random reads as a negative control, a set of parameters was determined for reliable interpretation of BLAST search results. About 10% of the rat reads contain regions that are conserved in the human genomic sequence and about one-third of these include known gene-coding regions. Mapping the conserved regions to human chromosomes showed a 23-fold enrichment for coding regions compared with noncoding regions. This approach can also be applied to other mammalian genomes for gene finding. These data predicted approximately 42,500 genes in the human, slightly more than reported previously.

Animals↗
PubMed2005

Improving interoperability between microbial information and sequence databases.

BACKGROUND: Biological resources are essential tools for biomedical research. Their availability is promoted through on-line catalogues. Common Access to Biological Resources and Information (CABRI) is a service for distribution of biological resources and related data collected by 28 European culture collections. Linking this information to bioinformatics databanks can make the collections' holdings more visible after a search in molecular biology databanks and vice-versa. Identification of links to sequence databases can be useful, but annotation and indexing problems, together with compilation errors, immediately arise. In this paper, we present our efforts for the identification of cross-references between CABRI catalogues and the EMBL Data Library and related results. RESULTS: An SRS site with both EMBL and CABRI catalogues has been set up. Ad-hoc changes in indexing scripts allowed to achieve homogeneous index keys and SRS link features have been used to identify links between databases. After manual checking and comparison with an alternative procedure, about 67,500 valid cross-references were identified, added to the EMBL Data Library and are now distributed with it. HTML links can be established from EMBL to CABRI network service. Procedures can be executed whenever needed. CONCLUSION: Links between EMBL and CABRI catalogues constitute an improved access to micro-organisms of certified quality and can produce positive effects on biomedical research. Further links between CABRI catalogues and other bioinformatics databases can now easily be defined by using these cross-references. Linking genetic information onto natural resources information may stand model for the integration of other databases containing empirical data on these materials.

Base Sequence↗
PubMed2001

Gene expression analysis with the parametric bootstrap.

Recent developments in microarray technology make it possible to capture the gene expression profiles for thousands of genes at once. With this data researchers are tackling problems ranging from the identification of 'cancer genes' to the formidable task of adding functional annotations to our rapidly growing gene databases. Specific research questions suggest patterns of gene expression that are interesting and informative: for instance, genes with large variance or groups of genes that are highly correlated. Cluster analysis and related techniques are proving to be very useful. However, such exploratory methods alone do not provide the opportunity to engage in statistical inference. Given the high dimensionality (thousands of genes) and small sample sizes (often <30) encountered in these datasets, an honest assessment of sampling variability is crucial and can prevent the over-interpretation of spurious results. We describe a statistical framework that encompasses many of the analytical goals in gene expression analysis; our framework is completely compatible with many of the current approaches and, in fact, can increase their utility. We propose the use of a deterministic rule, applied to the parameters of the gene expression distribution, to select a target subset of genes that are of biological interest. In addition to subset membership, the target subset can include information about relationships between genes, such as clustering. This target subset presents an interesting parameter that we can estimate by applying the rule to the sample statistics of microarray data. The parametric bootstrap, based on a multivariate normal model, is used to estimate the distribution of these estimated subsets and relevant summary measures of this sampling distribution are proposed. We focus on rules that operate on the mean and covariance. Using Bernstein's Inequality, we obtain consistency of the subset estimates, under the assumption that the sample size converges faster to infinity than the logarithm of the number of genes. We also provide a conservative sample size formula guaranteeing that the sample mean and sample covariance matrix are uniformly within a distance epsilon > 0 of the population mean and covariance. The practical performance of the method using a cluster-based subset rule is illustrated with a simulation study. The method is illustrated with an analysis of a publicly available leukemia data set.

Journal Article↗
PubMed2001

FOUNTAIN: a JAVA open-source package to assist large sequencing projects.

BACKGROUND: Better automation, lower cost per reaction and a heightened interest in comparative genomics has led to a dramatic increase in DNA sequencing activities. Although the large sequencing projects of specialized centers are supported by in-house bioinformatics groups, many smaller laboratories face difficulties managing the appropriate processing and storage of their sequencing output. The challenges include documentation of clones, templates and sequencing reactions, and the storage, annotation and analysis of the large number of generated sequences. RESULTS: We describe here a new program, named FOUNTAIN, for the management of large sequencing projects http://genetics.hpi.uni-hamburg.de/FOUNTAIN.html. FOUNTAIN uses the JAVA computer language and data storage in a relational database. Starting with a collection of sequencing objects (clones), the program generates and stores information related to the different stages of the sequencing project using a web browser interface for user input. The generated sequences are subsequently imported and annotated based on BLAST searches against the public databases. In addition, simple algorithms to cluster sequences and determine putative polymorphic positions are implemented. CONCLUSIONS: A simple, but flexible and scalable software package is presented to facilitate data generation and storage for large sequencing projects. Open source and largely platform and database independent, we wish FOUNTAIN to be improved and extended in a community effort.

Algorithms↗
PubMed2004

Absolute expression values for mouse transcripts: re-annotation of the READ expression database by the use of CAGE and EST sequence tags.

The RIKEN expression array database (READ) provides comprehensive gene expression data for the mouse, which were obtained as relative values from microarray double-staining experiments with E17.5 mRNA as common reference. To assign absolute expression values for mouse transcripts within READ, we applied the E17.5 reference sample to CAGE (cap analysis of gene expression) and expressed sequence tag (EST) high-throughput tag sequencing. Newly assigned values within the READ database were validated by comparison to expression data from serial analysis of gene expression, CAGE and EST experiments. These experiments confirmed the great significance of the absolute expression values within the improved READ database. The new Absolute READ database on absolute expression data is available under.

Animals↗
PubMed1999

The SWISS-PROT protein sequence data bank and its supplement TrEMBL in 1999.

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation (such as the description of the function of a protein, its domain structure, post-translational modifications, variants, etc.), a minimal level of redundancy and high level of integration with other databases. Recent developments of the database include: cross-references to additional databases; a variety of new documentation files and improvements to TrEMBL, a computer annotated supplement to SWISS-PROT. TrEMBL consists of entries in SWISS-PROT-like format derived from the translation of all coding sequences (CDS) in the EMBL nucleotide sequence database, except the CDS already included in SWISS-PROT. The URLs for SWISS-PROT on the WWW are: http://www.expasy.ch/sprot and http://www. ebi.ac.uk/sprot

Amino Acid Sequence↗
PubMed2003

Analysis and functional annotation of an expressed sequence tag collection for tropical crop sugarcane.

To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST) program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. Of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged.

Computational Biology↗
PubMed2006

SAGE2Splice: unmapped SAGE tags reveal novel splice junctions.

Serial analysis of gene expression (SAGE) not only is a method for profiling the global expression of genes, but also offers the opportunity for the discovery of novel transcripts. SAGE tags are mapped to known transcripts to determine the gene of origin. Tags that map neither to a known transcript nor to the genome were hypothesized to span a splice junction, for which the exon combination or exon(s) are unknown. To test this hypothesis, we have developed an algorithm, SAGE2Splice, to efficiently map SAGE tags to potential splice junctions in a genome. The algorithm consists of three search levels. A scoring scheme was designed based on position weight matrices to assess the quality of candidates. Using optimized parameters for SAGE2Splice analysis and two sets of SAGE data, candidate junctions were discovered for 5%-6% of unmapped tags. Candidates were classified into three categories, reflecting the previous annotations of the putative splice junctions. Analysis of predicted tags extracted from EST sequences demonstrated that candidate junctions having the splice junction located closer to the center of the tags are more reliable. Nine of these 12 candidates were validated by RT-PCR and sequencing, and among these, four revealed previously uncharacterized exons. Thus, SAGE2Splice provides a new functionality for the identification of novel transcripts and exons. SAGE2Splice is available online at http://www.cisreg.ca.

Algorithms↗
PubMed2026

Enzyme-Metabolite Network Analysis of Endometrial Cancer-Derived Extracellular Vesicles Through Integrated Proteomics and Metabolomics.

Endometrial cancer (EC) is the most common gynecological malignancy in high-income countries. Extracellular vesicles (EVs) are key mediators of intercellular communication and metabolic reprogramming, but their molecular cargo in EC remains poorly characterized. EVs were isolated from four EC cell lines representing Type I and Type II subtypes (AN3CA, ISHIKAWA, HEC1A, and KLE). Untargeted metabolomics was performed by HILIC-LC-MS/MS, proteomics by data-independent acquisition (DIA) mass spectrometry, and multi-omics integration using MetaboAnalyst and OmicsNet. Metabolomic profiling identified 1463 annotated features and revealed significant differences among EC cell lines (PERMANOVA, p = 0.002). Twenty-eight differentially abundant metabolites, including lactic acid, succinic acid, and uric acid, were identified. Proteomic analysis quantified 8513 proteins with subtype-specific expression patterns. Integrated analysis revealed seven significantly enriched pathways, including glycolysis/gluconeogenesis, central carbon metabolism in cancer, and the pentose phosphate pathway. Increased LDHA abundance in metastatic AN3CA-derived EVs was confirmed by Western blot (p = 0.047). EC-derived EVs display subtype- and metastatic-status-specific metabolo-proteomic signatures, with glycolysis, TCA cycle remodeling, and central carbon metabolism as convergent pathway signatures of molecular reprogramming. These findings establish a multi-omics framework for characterizing EV cargo in EC and identify candidate enzyme-metabolite nodes for future biomarker validation in patient-derived specimens.

Female↗
PubMed2004

prot4EST: translating expressed sequence tags from neglected genomes.

BACKGROUND: The genomes of an increasing number of species are being investigated through generation of expressed sequence tags (ESTs). However, ESTs are prone to sequencing errors and typically define incomplete transcripts, making downstream annotation difficult. Annotation would be greatly improved with robust polypeptide translations. Many current solutions for EST translation require a large number of full-length gene sequences for training purposes, a resource that is not available for the majority of EST projects. RESULTS: As part of our ongoing EST programs investigating these "neglected" genomes, we have developed a polypeptide prediction pipeline, prot4EST. It incorporates freely available software to produce final translations that are more accurate than those derived from any single method. We show that this integrated approach goes a long way to overcoming the deficit in training data. CONCLUSIONS: prot4EST provides a portable EST translation solution and can be usefully applied to >95% of EST projects to improve downstream annotation. It is freely available from http://www.nematodes.org/PartiGene.

Animals↗
PubMed2004

New approaches towards integrated proteomic databases and depositories.

Since the publication of the human genome, two key points have emerged. First, it is still not certain which regions of the genome code for proteins. Second, the number of discrete protein-coding genes is far fewer than the number of different proteins. Proteomics has the potential to address some of these postgenomic issues if the obstacles that we face can be overcome in our efforts to combine proteomic and genomic data. There are many challenges associated with high-throughput and high-output proteomic technologies. Consequently, for proteomics to continue at its current growth rate, new approaches must be developed to ease data management and data mining. Initiatives have been launched to develop standard data formats for exchanging mass spectrometry proteomic data, including the Proteomics Standards Initiative formed by the Human Proteome Organization. Databases such as SwissProt and Uniprot are publicly available repositories for protein sequences annotated for function, subcellular location and known potential post-translational modifications. The availability of bioinformatics solutions is crucial for proteomics technologies to fulfil their promise of adding further definition to the functional output of the human genome. The aim of the Oxford Genome Anatomy Project is to provide a framework for integrating molecular, cellular, phenotypic and clinical information with experimental genetic and proteomics data. This perspective also discusses models to make the Oxford Genome Anatomy Project accessible and beneficial for academic and commercial research and development.

Databases, Protein↗
PubMed2002

Genetic, physical, and comparative map of the subtelomeric region of mouse Chromosome 4.

The subtelomeric region of mouse chromosome (Chr) 4 harbors loci with effects on behavior, development, and disease susceptibility. Regions near the telomeres are more difficult to map and characterize than other areas because of the unique features of subtelomeric DNA. As a result of these problems, the available mapping information for this part of mouse Chr 4 was insufficient to pursue candidate gene evaluation. Therefore, we sought to characterize the area in greater detail by creating a comprehensive genetic, physical, and comparative map. We constructed a genetic map that contained 30 markers and covered 13.3 cM; then we created a 1.2-Mb sequence-ready BAC contig, representing a 5.1-cM area, and sequenced a 246-kb mouse BAC from this contig. The resulting sequence, as well as approximately 40 kb of previously deposited genomic sequence, yielded a total of 284 kb of sequence, which contained over 20 putative genes. These putative genes were confirmed by matching ESTs or cDNA in the public databases to the genomic sequence and/or by direct sequencing of cDNA. Comparative genome sequence analysis demonstrated conserved synteny between the mouse and the human genomes (1p36.3). DNA from two strains of mice (C57BL/6ByJ and 129P3/J) was sequenced to detect single nucleotide polymorphisms (SNPs). The frequency of SNPs in this region was more than threefold higher than the genome-wide average for comparable mouse strains (129/Sv and C57BL/6J). The resulting SNP map, in conjunction with the sequence annotation and with physical and genetic maps, provides a detailed description of this gene-rich region. These data will facilitate genetic and comparative mapping studies and identification of a large number of novel candidate genes for the trait loci mapped to this region.

Animals↗
PubMed2002

Brucella proteomes--a review.

The proteomes of selected Brucella spp. have been extensively analyzed by utilizing current proteomic technology involving 2-DE and MALDI-MS. In Brucella melitensis, more than 500 proteins were identified. The rapid and large-scale identification of proteins in this organism was accomplished by using the annotated B. melitensis genome which is now available in the GenBank. Coupled with new and powerful tools for data analysis, differentially expressed proteins were identified and categorized into several classes. A global overview of protein expression patterns emerged, thereby facilitating the simultaneous analysis of different metabolic pathways in B. melitensis. Such a global characterization would not have been possible by using time consuming and traditional biochemical approaches. The era of post-genomic technology offers new and exciting opportunities to understand the complete biology of different Brucella species.

Bacterial Proteins↗
PubMedDate not supplied

Learning from the data: mining of large high-throughput screening databases.

High-throughput screening (HTS) campaigns in pharmaceutical companies have accumulated a large amount of data for several million compounds over a couple of hundred assays. Despite the general awareness that rich information is hidden inside the vast amount of data, little has been reported for a systematic data mining method that can reliably extract relevant knowledge of interest for chemists and biologists. We developed a data mining approach based on an algorithm called ontology-based pattern identification (OPI) and applied it to our in-house HTS database. We identified nearly 1500 scaffold families with statistically significant structure-HTS activity profile relationships. Among them, dozens of scaffolds were characterized as leading to artifactual results stemming from the screening technology employed, such as assay format and/or readout. Four types of compound scaffolds can be characterized based on this data mining effort: tumor cytotoxic, general toxic, potential reporter gene assay artifact, and target family specific. The OPI-based data mining approach can reliably identify compounds that are not only structurally similar but also share statistically significant biological activity profiles. Statistical tests such as Kruskal-Wallis test and analysis of variance (ANOVA) can then be applied to the discovered scaffolds for effective assignment of relevant biological information. The scaffolds identified by our HTS data mining efforts are an invaluable resource for designing SAR-robust diversity libraries, generating in silico biological annotations of compounds on a scaffold basis, and providing novel target family specific scaffolds for focused compound library design.

Algorithms↗
PubMed2004

CLENCH: a program for calculating Cluster ENriCHment using the Gene Ontology.

SUMMARY: Analysis of microarray data most often produces lists of genes with similar expression patterns, which are then subdivided into functional categories for biological interpretation. Such functional categorization is most commonly accomplished using Gene Ontology (GO) categories. Although there are several programs that identify and analyze functional categories for human, mouse and yeast genes, none of them accept Arabidopsis thaliana data. In order to address this need for A.thaliana community, we have developed a program that retrieves GO annotations for A.thaliana genes and performs functional category analysis for lists of genes selected by the user. AVAILABILITY: http://www.personal.psu.edu/nhs109/Clench

Abstracting and Indexing↗
PubMed2004

Drosophila DNase I footprint database: a systematic genome annotation of transcription factor binding sites in the fruitfly, Drosophila melanogaster.

UNLABELLED: Despite increasing numbers of computational tools developed to predict cis-regulatory sequences, the availability of high-quality datasets of transcription factor binding sites limits advances in the bioinformatics of gene regulation. Here we present such a dataset based on a systematic literature curation and genome annotation of DNase I footprints for the fruitfly, Drosophila melanogaster. Using the experimental results of 201 primary references, we annotated 1367 binding sites from 87 transcription factors and 101 target genes in the D.melanogaster genome sequence. These data will provide a rich resource for future bioinformatics analyses of transcriptional regulation in Drosophila such as constructing motif models, training cis-regulatory module detectors, benchmarking alignment tools and continued text mining of the extensive literature on transcriptional regulation in this important model organism. AVAILABILITY: http://www.flyreg.org/ CONTACT: cbergman@gen.cam.ac.uk.

Binding Sites↗
PubMed2006

NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins.

NCBI's reference sequence (RefSeq) database (http://www.ncbi.nlm.nih.gov/RefSeq/) is a curated non-redundant collection of sequences representing genomes, transcripts and proteins. The database includes 3774 organisms spanning prokaryotes, eukaryotes and viruses, and has records for 2,879,860 proteins (RefSeq release 19). RefSeq records integrate information from multiple sources, when additional data are available from those sources and therefore represent a current description of the sequence and its features. Annotations include coding regions, conserved domains, tRNAs, sequence tagged sites (STS), variation, references, gene and protein product names, and database cross-references. Sequence is reviewed and features are added using a combined approach of collaboration and other input from the scientific community, prediction, propagation from GenBank and curation by NCBI staff. The format of all RefSeq records is validated, and an increasing number of tests are being applied to evaluate the quality of sequence and annotation, especially in the context of complete genomic sequence.

Amino Acid Sequence↗
PubMed2002

Temperature-regulated transcription in the pathogenic fungus Cryptococcus neoformans.

The basidiomycete fungus Cryptococcus neoformans is an opportunistic pathogen of worldwide importance that causes meningitis, leading to death in immunocompromised individuals. Unlike many basidiomycete fungi, C. neoformans is thermotolerant, and its ability to grow at 37 degrees C is considered to be a virulence factor. We used serial analysis of gene expression (SAGE) to characterize the transcriptomes of C. neoformans strains that represent two varieties with different polysaccharide capsule serotypes. These include a serotype D strain of the C. neoformans variety neoformans and a serotype A strain of variety grubii. In this report, we describe the construction and characterization of SAGE libraries from each strain grown at 25 degrees C and 37 degrees C. The SAGE data reveal transcriptome differences between the two strains, even at this early stage of analysis, and identify sets of genes with higher transcript levels at 25 degrees C or 37 degrees C. Notably, growth at the lower temperature increased transcript levels for histone genes, indicating a general influence of temperature on chromatin structure. At 37 degrees C, we noted elevated transcript levels for several genes encoding heat shock proteins and translation machinery. Some of these genes may play a role in temperature-regulated phenotypes in C. neoformans, such as the adaptation of the fungus to growth in the host and the dimorphic transition between budding and filamentous growth. Overall, this work provides the most comprehensive gene expression data available for C. neoformans; this information will be a critical resource both for gene discovery and genome annotation in this pathogen.

Blotting, Northern↗