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PubMed2001

Go!Poly: A gene-oriented polymorphism database.

Human genome polymorphisms play a key role in defining the molecular basis of phenotypic differences between individuals in aspects such as disease susceptibility and drug responses. The database requirements for supporting the study of human genetic variation have been well recognized. In order to meet these needs, several generalized databases have been built. However, it is still hard for users to find gene-related variation data from these huge and sophisticated databases. In its role as a gene-oriented directory of polymorphism data, Go!Poly (Gene Oriented Polymorphism Database; http://61.139.84.5/gopoly/) utilizes two new highly curated and non-redundant resources, LocusLink (http://www.ncbi.nlm.nih.gov/LocusLink/) and RefSeq (http://www.ncbi.nlm.nih.gov/LocusLink/refseq.html), as the standard for identifying and positioning nucleotide variations. As a generalized polymorphism database, Go!Poly extracts human gene-linked sequence variations of all common types (SNP, insertion-deletion, simple tandem repeat, and complex nucleotides variations) from various public resources including scientific journals and internet resources, such as HGBASE (http://hgbase.cgr.ki.se) and dbSNP (http://www.ncbi.nlm.nih.gov/SNP/). The polymorphism data are then categorized into different gene loci, and the reference sequences given by LocusLink are used as positioning references. Through close integration with LocusLink, Go!Poly also provides facilitated connections among sequence data, gene name, and related biological information. This feature also makes Go!Poly easy to search and navigate. Future automated annotations and internal consistency checking may also benefit from this. Extensive efforts are being taken to make the polymorphism information generated by the Chinese scientific community available from this resource.

China↗
PubMed2005

Analysing the outer membrane subproteome of Methylococcus capsulatus (Bath) using proteomics and novel biocomputing tools.

High-resolution two-dimensional gel electrophoresis and mass spectrometry has been used to identify the outer membrane (OM) subproteome of the Gram-negative bacterium Methylococcus capsulatus (Bath). Twenty-eight unique polypeptide sequences were identified from protein samples enriched in OMs. Only six of these polypeptides had previously been identified. The predictions from novel bioinformatic methods predicting beta-barrel outer membrane proteins (OMPs) and OM lipoproteins were compared to proteins identified experimentally. BOMP ( http://www.bioinfo.no/tools/bomp ) predicted 43 beta-barrel OMPs (1.45%) from the 2,959 annotated open reading frames. This was a lower percentage than predicted from other Gram-negative proteomes (1.8-3%). More than half of the predicted BOMPs in M. capsulatus were annotated as (conserved) hypothetical proteins with significant similarity to very few sequences in Swiss-Prot or TrEMBL. The experimental data and the computer predictions indicated that the protein composition of the M. capsulatus OM subproteome was different from that of other Gram-negative bacteria studied in a similar manner. A new program, Lipo, was developed that can analyse entire predicted proteomes and give a list of recognised lipoproteins categorised according to their lipo-box similarity to known Gram-negative lipoproteins ( http://www.bioinfo.no/tools/lipo ). This report is the first using a proteomics and bioinformatics approach to identify the OM subproteome of an obligate methanotroph.

Bacterial Outer Membrane Proteins↗
PubMed2003

A "polyORFomic" analysis of prokaryote genomes using disabled-homology filtering reveals conserved but undiscovered short ORFs.

Prokaryote gene annotation is complicated by large numbers of short open reading frames (ORFs) that arise naturally from genetic code design. Historically, many hypothetical ORFs have been annotated as genes in microbes, usually with an arbitrary length threshold (e.g. greater than 100 codons). Given the use of such thresholds, what is the extent of genuine undiscovered short genes in the current sampling of prokaryote genomes? To assess rigorously the potential under-annotation of short ORFs with homology, we exhaustively compared the polyORFome--all possible ORFs in 64 prokaryotes (53 bacteria and 11 archaea) plus budding yeast--to itself and to all known proteins. The novelty of our analysis is that, firstly, sequence comparisons to/between both annotated and un-annotated ORFs are considered, and secondly a two-step disabled-homology filter is applied to set aside putative pseudogenes and spurious ORFs. We find that un-annotated homologous short ORFs (uhORFs) correspond to a small but non-negligible fraction of the annotated prokaryote proteomes (0.5-3.8%, depending on selection criteria). Moreover, the disabled-homology filter indicates that about a third of uhORFs correspond to putative pseudogenes or spurious ORFs. Our analysis shows that the use of annotation length thresholds is unnecessary, as there are manageable numbers of short ORF homologies conserved (without disablements) across microbial genomes. Data on uhORFs are available from http://pseudogene.org/polyo

Conserved Sequence↗
PubMed1997

In search of differentially expressed genes and proteins.

A great challenge for modern cell biology is the successful examination of the co-expression of thousands of genes under physiological or pathological conditions and how the expression patterns define the different states of a single cell, tissue or a microorganism. Gene expression can be analyzed today on a large scale by advanced technical approaches for differential screening of proteins and mRNAs. The identification of differentially expressed mRNAs has been successfully applied to understand gene function and the underlying molecular mechanism(-s) of differentiation, development and disease state. Analysis of gene expression by the systematic mapping of thousands of proteins present in a cell or tissue can be achieved by the use of two-dimensional (2D) gel electrophoresis, quantitative computer image analysis, and protein identification techniques. In this article, we comment on some of these techniques and try to stress their advantages and drawbacks. We show how data from RNA/DNA mapping, sequence information from genome projects and protein pattern profiling can be linked with each other and annotated. These comprehensive approaches permit the study of differential gene and protein expressions in cells or tissues.

Animals↗
PubMed2003

Radiation biodosimetry: applications for spaceflight.

The multiparametric dosimetry system that we are developing for medical radiological defense applications could be adapted for spaceflight environments. The system complements the internationally accepted personnel dosimeters and cytogenetic analysis of chromosome aberrations, considered the best means of documenting radiation doses for health records. Our system consists of a portable hematology analyzer, molecular biodosimetry using nucleic acid and antigen-based diagnostic equipment, and a dose assessment management software application. A dry-capillary tube reagent-based centrifuge blood cell counter (QBC Autoread Plus, Becton [correction of Beckon] Dickinson Bioscience) measures peripheral blood lymphocytes and monocytes, which could determine radiation dose based on the kinetics of blood cell depletion. Molecular biomarkers for ionizing radiation exposure (gene expression changes, blood proteins) can be measured in real time using such diagnostic detection technologies as miniaturized nucleic acid sequences and antigen-based biosensors, but they require validation of dose-dependent targets and development of optimized protocols and analysis systems. The Biodosimetry Assessment Tool, a software application, calculates radiation dose based on a patient's physical signs and symptoms and blood cell count analysis. It also annotates location of personnel dosimeters, displays a summary of a patient's dosimetric information to healthcare professionals, and archives the data for further use. These radiation assessment diagnostic technologies can have dual-use applications supporting general medical-related care.

Animals↗
PubMed2001

GeneMachine: gene prediction and sequence annotation.

MOTIVATION: A number of free-standing programs have been developed in order to help researchers find potential coding regions and deduce gene structure for long stretches of what is essentially 'anonymous DNA'. As these programs apply inherently different criteria to the question of what is and is not a coding region, multiple algorithms should be used in the course of positional cloning and positional candidate projects to assure that all potential coding regions within a previously-identified critical region are identified. RESULTS: We have developed a gene identification tool called GeneMachine which allows users to query multiple exon and gene prediction programs in an automated fashion. BLAST searches are also performed in order to see whether a previously-characterized coding region corresponds to a region in the query sequence. A suite of Perl programs and modules are used to run MZEF, GENSCAN, GRAIL 2, FGENES, RepeatMasker, Sputnik, and BLAST. The results of these runs are then parsed and written into ASN.1 format. Output files can be opened using NCBI Sequin, in essence using Sequin as both a workbench and as a graphical viewer. The main feature of GeneMachine is that the process is fully automated; the user is only required to launch GeneMachine and then open the resulting file with Sequin. Annotations can then be made to these results prior to submission to GenBank, thereby increasing the intrinsic value of these data. AVAILABILITY: GeneMachine is freely-available for download at http://genome.nhgri.nih.gov/genemachine. A public Web interface to the GeneMachine server for academic and not-for-profit users is available at http://genemachine.nhgri.nih.gov. The Web supplement to this paper may be found at http://genome.nhgri.nih.gov/genemachine/supplement/.

Animals↗
PubMed2025

Whole-genome phenotype prediction with machine learning: open problems in bacterial genomics.

MOTIVATION: How can we identify causal genetic mechanisms governing bacterial traits? Initial efforts entrusting machine learning models to handle the task of predicting phenotype from genotype yield high accuracy scores. However, attempts to extract meaningful interpretations from the predictive models are found to be corrupted by falsely identified 'causal' features. Relying solely on pattern recognition and correlations is unreliable, significantly so in bacterial genomics settings where high-dimensionality and spurious associations are the norm. Though it is not yet clear whether we can overcome this hurdle, significant efforts are being made towards discovering potential high-risk bacterial genetic variants. In view of this, we set up open problems surrounding phenotype prediction from bacterial whole-genome datasets and extending those approaches to learning causal effects, and discuss challenges that impact the reliability of a machine's decision-making when faced with datasets of this nature. RESULTS: We identify major sources of non-injectivity in the formulation of the genotype-to-phenotype mapping function-linkage-disequilibrium, limited sampling, information loss in representations, unmeasured confounders and observational noise-and analyse their implications for machine learning applications. Using a collection of 4,140 Staphylococcus aureus isolates, we illustrate challenges surrounding the defined open problems. AVAILABILITY AND IMPLEMENTATION: Raw sequencing data are available from the European Nucleotide Archive (ENA) under project accessions ERP001012, PRJEB3174, PRJEB2655, PRJEB2756, and PRJEB2944. Assemblies and annotations were generated with the Sanger bacterial pipeline (https://github.com/sanger-pathogens/vr-codebase) and unitigs extracted using DBGWAS (https://gitlab.com/leoisl/dbgwas).

Machine Learning↗
PubMed2004

Update of NUREBASE: nuclear hormone receptor functional genomics.

Nuclear hormone receptors are an abundant class of ligand-activated transcriptional regulators, found in varying numbers in all animals. Based on our experience of managing the official nomenclature of nuclear receptors, we have developed NUREBASE, a database containing protein and DNA sequences, reviewed protein alignments and phylogenies, taxonomy and annotations for all nuclear receptors. New developments in NUREBASE include explicit declaration of alternative transcripts of each gene, and expression data for human and mouse nuclear receptors. The core of NUREBASE is reviewed, and it is completed by NUREBASE_DAILY, automatically updated every 24 h. All information on accessing and installing NUREBASE may be found at http://www. ens-lyon.fr/LBMC/laudet/nurebase/nurebase.html.

Alternative Splicing↗
PubMed2004

KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains.

KCaM (KEGG Carbohydrate Matcher) is a tool for the analysis of carbohydrate sugar chains, or glycans. It consists of a web-based graphical user interface that allows users to enter glycans easily with the mouse. The glycan structure is then transformed into our KCF (KEGG Chemical Function) file format and sent to our program which implements an efficient tree-structure alignment algorithm, similar to sequence alignment algorithms but for branched tree structures. Users can also retrieve glycan tree structures in KCF format from their local computers for visualization over the web. The tree-matching algorithm provides several options for performing different types of tree-matching procedures on glycans. These options consist of whether to incorporate gaps in a match, whether to take the linkage information into consideration and local versus global alignment. The results of this program are returned as a list of glycan structures in order of similarity based on these options. The actual alignment can be viewed graphically, and the annotation information can also be viewed easily since all this information is linked with KEGG's comprehensive suite of genomic data. Analogously to BLAST, users are thus able to compare glycan structures of interest with glycans from different glycan databases using a variety of tree-alignment options. KCaM is currently available at http://glycan.genome.ad.jp.

Algorithms↗
PubMed2005

The Ashbya Genome Database (AGD)--a tool for the yeast community and genome biologists.

The Ashbya Genome Database (AGD) is a comprehensive online source of information covering genes from the filamentous fungus Ashbya gossypii. The database content is based upon comparative genome annotation between A.gossypii and the closely related budding yeast Saccharomyces cerevisiae taking both sequence similarity and synteny (conserved order and orientation) into account. Release 2 of AGD contains 4718 protein-encoding loci located across seven chromosomes. Information can be retrieved using systematic or standard locus names from A.gossypii as well as budding and fission yeast. Approximately 90% of the genes in the genome of A.gossypii are homologous and syntenic to loci of budding yeast. Therefore, AGD is a useful tool not only for the various yeast communities in general but also for biologists who are interested in evolutionary aspects of genome research and comparative genome annotation. The database provides scientists with a convenient graphical user interface that includes various locus search and genome browsing options, data download and export functionalities and numerous reciprocal links to external databases including SGD, MIPS, GeneDB, KEGG, GermOnline and Swiss-Prot/TrEMBL. AGD is accessible at http://agd.unibas.ch/.

Computer Graphics↗
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↗
PubMed2025

Identification and classification of ion-channels across the tree of life provide functional insights into understudied CALHM channels.

The ion channel (IC) genes encoded in the human genome play fundamental roles in cellular functions and disease and are one of the largest classes of druggable proteins. However, limited knowledge of the diverse molecular and cellular functions carried out by ICs presents a major bottleneck in developing selective chemical probes for modulating their functions in disease states. The wealth of sequence data available on ICs from diverse organisms provides a valuable source of untapped information for illuminating the unique modes of channel regulation and functional specialization. However, the extensive diversification of IC sequences and the lack of a unified resource present a challenge in effectively using existing data for IC research. Here, we perform integrative mining of available sequence, structure, and functional data on 419 human ICs across disparate sources, including extensive literature mining by leveraging advances in large language models to annotate and curate the full complement of the "channelome". We employ a well-established orthology inference approach to identify and extend the IC orthologs across diverse organisms to above 48,000. We show that the depth of conservation and taxonomic representation of IC sequences can further be translated to functional similarities by clustering them into functionally relevant groups, which can be used for downstream functional prediction on understudied members. We demonstrate this by delineating co-conserved patterns characteristic of the understudied family of the Calcium Homeostasis Modulator (CALHM) family of ICs. Through mutational analysis of co-conserved residues altered in human diseases and electrophysiological studies, we show that these evolutionarily-constrained residues play an important role in channel gating functions. Thus, by providing new tools and resources for performing large comparative analyses on ICs, this study addresses the unique needs of the IC community and provides the groundwork for accelerating the functional characterization of dark channels for therapeutic intervention.

CALHM1↗
PubMed2003

Human disease genes and their cloned mouse orthologs: exploration of the FANTOM2 cDNA sequence data set.

The FANTOM2 cDNA sequence data set is an excellent model to demonstrate the power of large-scale cDNA sequencing, with the goal of providing a full-length transcript sequence for each mouse gene. This data set enhances the use of the mouse as a model for human disease. Here we identify mouse cDNA sequences in the FANTOM2 data set for a set of 67 human disease genes that as of May 2002 had no corresponding mouse cDNA annotated in the Mouse Genome Informatics (MGI) database. These 67 human disease genes include genes related to neurological and eye disorders and cancer. We also present a list of the human disease genes and their cloned mouse orthologs found in two public databases, LocusLink and MGI. Allelic variant and gene functional information available in MGI provides additional information relative to these mouse models, whereas computed sequence-based connections at NCBI support facile navigation through multiple genomes.

Alleles↗
PubMed2006

Expression, purification, crystallization and preliminary X-ray analysis of two arginine-biosynthetic enzymes from Mycobacterium tuberculosis.

The gene products of two open reading frames from Mycobacterium tuberculosis (Mtb) have been crystallized using the sitting-drop vapour-diffusion method. Rv1652 encodes a putative N-acetyl-gamma-glutamyl-phosphate reductase (MtbAGPR), while the Rv1656 gene product is annotated as ornithine carbamoyltransferase (MtbOTC). Both MtbAGPR and MtbOTC were expressed in Escherichia coli, purified to homogeneity and crystallized. Native data for each crystal were collected to resolutions of 2.15 and 2.80 A, respectively. Preliminary X-ray data are presented for both enzymes.

Aldehyde Oxidoreductases↗
PubMed2004

Environmental genome shotgun sequencing of the Sargasso Sea.

We have applied "whole-genome shotgun sequencing" to microbial populations collected en masse on tangential flow and impact filters from seawater samples collected from the Sargasso Sea near Bermuda. A total of 1.045 billion base pairs of nonredundant sequence was generated, annotated, and analyzed to elucidate the gene content, diversity, and relative abundance of the organisms within these environmental samples. These data are estimated to derive from at least 1800 genomic species based on sequence relatedness, including 148 previously unknown bacterial phylotypes. We have identified over 1.2 million previously unknown genes represented in these samples, including more than 782 new rhodopsin-like photoreceptors. Variation in species present and stoichiometry suggests substantial oceanic microbial diversity.

Archaea↗
PubMed2005

Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural networks.

BACKGROUND: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of the approximately 30,000 known and predicted human coding genes are characterized and have been assigned at least one function, there remains a fair number of genes (about 12,000) for which no annotation has been made. The recent sequencing of other genomes has provided us with a huge amount of auxiliary sequence data which could help in the characterization of the human genes. Clustering these sequences into families is one of the first steps to perform comparative studies across several genomes. RESULTS: Here we report a novel clustering algorithm (CLUGEN) that has been used to cluster sequences of experimentally verified and predicted proteins from all sequenced genomes using a novel distance metric which is a neural network score between a pair of protein sequences. This distance metric is based on the pairwise sequence similarity score and the similarity between their domain structures. The distance metric is the probability that a pair of protein sequences are of the same Interpro family/domain, which facilitates the modelling of transitive homology closure to detect remote homologues. The hierarchical average clustering method is applied with the new distance metric. CONCLUSION: Benchmarking studies of our algorithm versus those reported in the literature shows that our algorithm provides clustering results with lower false positive and false negative rates. The clustering algorithm is applied to cluster several eukaryotic genomes and several dozens of prokaryotic genomes.

Algorithms↗
PubMed2006

Genomic analysis of Xenopus organizer function.

BACKGROUND: Studies of the Xenopus organizer have laid the foundation for our understanding of the conserved signaling pathways that pattern vertebrate embryos during gastrulation. The two primary activities of the organizer, BMP and Wnt inhibition, can regulate a spectrum of genes that pattern essentially all aspects of the embryo during gastrulation. As our knowledge of organizer signaling grows, it is imperative that we begin knitting together our gene-level knowledge into genome-level signaling models. The goal of this paper was to identify complete lists of genes regulated by different aspects of organizer signaling, thereby providing a deeper understanding of the genomic mechanisms that underlie these complex and fundamental signaling events. RESULTS: To this end, we ectopically overexpress Noggin and Dkk-1, inhibitors of the BMP and Wnt pathways, respectively, within ventral tissues. After isolating embryonic ventral halves at early and late gastrulation, we analyze the transcriptional response to these molecules within the generated ectopic organizers using oligonucleotide microarrays. An efficient statistical analysis scheme, combined with a new Gene Ontology biological process annotation of the Xenopus genome, allows reliable and faithful clustering of molecules based upon their roles during gastrulation. From this data, we identify new organizer-related expression patterns for 19 genes. Moreover, our data sub-divides organizer genes into separate head and trunk organizing groups, which each show distinct responses to Noggin and Dkk-1 activity during gastrulation. CONCLUSION: Our data provides a genomic view of the cohorts of genes that respond to Noggin and Dkk-1 activity, allowing us to separate the role of each in organizer function. These patterns demonstrate a model where BMP inhibition plays a largely inductive role during early developmental stages, thereby initiating the suites of genes needed to pattern dorsal tissues. Meanwhile, Wnt inhibition acts later during gastrulation, and is essential for maintenance of organizer gene expression throughout gastrulation, a role which may depend on its ability to block the expression of a host of ventral, posterior, and lateral fate-specifying factors.

Animals↗
PubMed2005

The Sequence Ontology: a tool for the unification of genome annotations.

The Sequence Ontology (SO) is a structured controlled vocabulary for the parts of a genomic annotation. SO provides a common set of terms and definitions that will facilitate the exchange, analysis and management of genomic data. Because SO treats part-whole relationships rigorously, data described with it can become substrates for automated reasoning, and instances of sequence features described by the SO can be subjected to a group of logical operations termed extensional mereology operators.

Alternative Splicing↗