A manually curated functional annotation of the human X chromosome.
Explore the source record for details and available documents.
Alternative Splicing↗
SEARCH · Search PubMed
Results for “protein function annotation”
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
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↗
Functional reclassification of the putative cinnamyl alcohol dehydrogenase multigene family in Arabidopsis.
Of 17 genes annotated in the Arabidopsis genome database as cinnamyl alcohol dehydrogenase (CAD) homologues, an in silico analysis revealed that 8 genes were misannotated. Of the remaining nine, six were catalytically competent for NADPH-dependent reduction of p-coumaryl, caffeyl, coniferyl, 5-hydroxyconiferyl, and sinapyl aldehydes, whereas three displayed very low activity and only at very high substrate concentrations. Of the nine putative CADs, two (AtCAD5 and AtCAD4) had the highest activity and homology (approximately 83% similarity) relative to bona fide CADs from other species. AtCAD5 used all five substrates effectively, whereas AtCAD4 (of lower overall catalytic capacity) poorly used sinapyl aldehyde; the corresponding 270-fold decrease in k(enz) resulted from higher K(m) and lower k(cat) values, respectively. No CAD homologue displayed a specific requirement for sinapyl aldehyde, which was in direct contrast with unfounded claims for a so-called sinapyl alcohol dehydrogenase in angiosperms. AtCAD2, 3, as well as AtCAD7 and 8 (highest homology to sinapyl alcohol dehydrogenase) were catalytically less active overall by at least an order of magnitude, due to increased K(m) and lower k(cat) values. Accordingly, alternative and/or bifunctional metabolic roles of these proteins in plant defense cannot be ruled out. Comprehensive analyses of lignified tissues of various Arabidopsis knockout mutants (for AtCAD5, 6, and 9) at different stages of growth/development indicated the presence of functionally redundant CAD metabolic networks. Moreover, disruption of AtCAD5 expression had only a small effect on either overall lignin amounts deposited, or on syringyl-guaiacyl compositions, despite being the most catalytically active form in vitro.
Alcohol Dehydrogenase↗
Whole-genome annotation by using evidence integration in functional-linkage networks.
The advent of high-throughput biology has catalyzed a remarkable improvement in our ability to identify new genes. A large fraction of newly discovered genes have an unknown functional role, particularly when they are specific to a particular lineage or organism. These genes, currently labeled "hypothetical," might support important biological cell functions and could potentially serve as targets for medical, diagnostic, or pharmacogenomic studies. An important challenge to the scientific community is to associate these newly predicted genes with a biological function that can be validated by experimental screens. In the absence of sequence or structural homology to known genes, we must rely on advanced biotechnological methods, such as DNA chips and protein-protein interaction screens as well as computational techniques to assign putative functions to these genes. In this article, we propose an effective methodology for combining biological evidence obtained in several high-throughput experimental screens and integrating this evidence in a way that provides consistent functional assignments to hypothetical genes. We use the visualization method of propagation diagrams to illustrate the flow of functional evidence that supports the functional assignments produced by the algorithm. Our results contain a number of predictions and furnish strong evidence that integration of functional information is indeed a promising direction for improving the accuracy and robustness of functional genomics.
Chromosome Mapping↗
Crystal structure of a novel shikimate dehydrogenase from Haemophilus influenzae.
To date two classes of shikimate dehydrogenases have been identified and characterized, YdiB and AroE. YdiB is a bifunctional enzyme that catalyzes the reversible reductions of dehydroquinate to quinate and dehydroshikimate to shikimate in the presence of either NADH or NADPH. In contrast, AroE catalyzes the reversible reduction of dehydroshikimate to shikimate in the presence of NADPH. Here we report the crystal structure and biochemical characterization of HI0607, a novel class of shikimate dehydrogenase annotated as shikimate dehydrogenase-like. The kinetic properties of HI0607 are remarkably different from those of AroE and YdiB. In comparison with YdiB, HI0607 catalyzes the oxidation of shikimate but not quinate. The turnover rate for the oxidation of shikimate is approximately 1000-fold lower compared with that of AroE. Phylogenetic analysis reveals three independent clusters representing three classes of shikimate dehydrogenases, namely AroE, YdiB, and this newly characterized shikimate dehydrogenase-like protein. In addition, mutagenesis studies of two invariant residues, Asp-103 and Lys-67, indicate that they are important catalytic groups that may function as a catalytic pair in the shikimate dehydrogenase reaction. This is the first study that describes the crystal structure as well as mutagenesis and mechanistic analysis of this new class of shikimate dehydrogenase.
Alcohol Oxidoreductases↗
Prediction of glycosylphosphatidylinositol-anchored proteins in Arabidopsis. A genomic analysis.
Glycosylphosphatidylinositol (GPI) anchoring of proteins provides a potential mechanism for targeting to the plant plasma membrane and cell wall. However, relatively few such proteins have been identified. Here, we develop a procedure for database analysis to identify GPI-anchored proteins (GAP) based on their possession of common features. In a comprehensive search of the annotated Arabidopsis genome, we identified 167 novel putative GAP in addition to the 43 previously described candidates. Many of these 210 proteins show similarity to characterized cell surface proteins. The predicted GAP include homologs of beta-1,3-glucanases (16), metallo- and aspartyl proteases (13), glycerophosphodiesterases (6), phytocyanins (25), multi-copper oxidases (2), extensins (6), plasma membrane receptors (19), and lipid-transfer-proteins (18). Classical arabinogalactan (AG) proteins (13), AG peptides (9), fasciclin-like proteins (20), COBRA and 10 homologs, and novel potential signaling peptides that we name GAPEPs (8) were also identified. A further 34 proteins of unknown function were predicted to be GPI anchored. A surprising finding was that over 40% of the proteins identified here have probable AG glycosylation modules, suggesting that AG glycosylation of cell surface proteins is widespread. This analysis shows that GPI anchoring is likely to be a major modification in plants that is used to target a specific subset of proteins to the cell surface for extracellular matrix remodeling and signaling.
Arabidopsis↗
CoGenT++: an extensive and extensible data environment for computational genomics.
MOTIVATION: CoGenT++ is a data environment for computational research in comparative and functional genomics, designed to address issues of consistency, reproducibility, scalability and accessibility. DESCRIPTION: CoGenT++ facilitates the re-distribution of all fully sequenced and published genomes, storing information about species, gene names and protein sequences. We describe our scalable implementation of ProXSim, a continually updated all-against-all similarity database, which stores pairwise relationships between all genome sequences. Based on these similarities, derived databases are generated for gene fusions--AllFuse, putative orthologs--OFAM, protein families--TRIBES, phylogenetic profiles--ProfUse and phylogenetic trees. Extensions based on the CoGenT++ environment include disease gene prediction, pattern discovery, automated domain detection, genome annotation and ancestral reconstruction. CONCLUSION: CoGenT++ provides a comprehensive environment for computational genomics, accessible primarily for large-scale analyses as well as manual browsing.
Chromosome Mapping↗
New knowledge from old: in silico discovery of novel protein domains in Streptomyces coelicolor.
BACKGROUND: Streptomyces coelicolor has long been considered a remarkable bacterium with a complex life-cycle, ubiquitous environmental distribution, linear chromosomes and plasmids, and a huge range of pharmaceutically useful secondary metabolites. Completion of the genome sequence demonstrated that this diversity carried through to the genetic level, with over 7000 genes identified. We sought to expand our understanding of this organism at the molecular level through identification and annotation of novel protein domains. Protein domains are the evolutionary conserved units from which proteins are formed. RESULTS: Two automated methods were employed to rapidly generate an optimised set of targets, which were subsequently analysed manually. A final set of 37 domains or structural repeats, represented 204 times in the genome, was developed. Using these families enabled us to correlate items of information from many different resources. Several immediately enhance our understanding both of S. coelicolor and also general bacterial molecular mechanisms, including cell wall biosynthesis regulation and streptomycete telomere maintenance. DISCUSSION: Delineation of protein domain families enables detailed analysis of protein function, as well as identification of likely regions or residues of particular interest. Hence this kind of prior approach can increase the rate of discovery in the laboratory. Furthermore we demonstrate that using this type of in silico method it is possible to fairly rapidly generate new biological information from previously uncorrelated data.
Amino Acid Motifs↗
GOChase: correcting errors from Gene Ontology-based annotations for gene products.
SUMMARY: The Gene Ontology (GO) is a controlled biological vocabulary that provides three structured networks of terms to describe biological processes, cellular components and molecular functions. Many databases of gene products are annotated using the GO vocabularies. We found that some GO-updating operations are not easily traceable by the current biological databases and GO browsers. Consequently, numerous annotation errors arise and are propagated throughout biological databases and GO-based high-level analyses. GOChase is a set of web-based utilities to detect and correct the errors in GO-based annotations.
Database Management Systems↗
eMelanoBase: an online locus-specific variant database for familial melanoma.
A proportion of melanoma-prone individuals in both familial and non-familial contexts has been shown to carry inactivating mutations in either CDKN2A or, rarely, CDK4. CDKN2A is a complex locus that encodes two unrelated proteins from alternately spliced transcripts that are read in different frames. The alpha transcript (exons 1alpha, 2, and 3) produces the p16INK4A cyclin-dependent kinase inhibitor, while the beta transcript (exons 1beta and 2) is translated as p14ARF, a stabilizing factor of p53 levels through binding to MDM2. Mutations in exon 2 can impair both polypeptides and insertions and deletions in exons 1alpha, 1beta, and 2, which can theoretically generate p16INK4A-p14ARF fusion proteins. No online database currently takes into account all the consequences of these genotypes, a situation compounded by some problematic previous annotations of CDKN2A-related sequences and descriptions of their mutations. As an initiative of the international Melanoma Genetics Consortium, we have therefore established a database of germline variants observed in all loci implicated in familial melanoma susceptibility. Such a comprehensive, publicly accessible database is an essential foundation for research on melanoma susceptibility and its clinical application. Our database serves two types of data as defined by HUGO. The core dataset includes the nucleotide variants on the genomic and transcript levels, amino acid variants, and citation. The ancillary dataset includes keyword description of events at the transcription and translation levels and epidemiological data. The application that handles users' queries was designed in the model-view-controller architecture and was implemented in Java. The object-relational database schema was deduced using functional dependency analysis. We hereby present our first functional prototype of eMelanoBase. The service is accessible via the URL www.wmi.usyd.edu.au:8080/melanoma.html.
Computer Security↗
Predicting deleterious nsSNPs: an analysis of sequence and structural attributes.
BACKGROUND: There has been an explosion in the number of single nucleotide polymorphisms (SNPs) within public databases. In this study we focused on non-synonymous protein coding single nucleotide polymorphisms (nsSNPs), some associated with disease and others which are thought to be neutral. We describe the distribution of both types of nsSNPs using structural and sequence based features and assess the relative value of these attributes as predictors of function using machine learning methods. We also address the common problem of balance within machine learning methods and show the effect of imbalance on nsSNP function prediction. We show that nsSNP function prediction can be significantly improved by 100% undersampling of the majority class. The learnt rules were then applied to make predictions of function on all nsSNPs within Ensembl. RESULTS: The measure of prediction success is greatly affected by the level of imbalance in the training dataset. We found the balanced dataset that included all attributes produced the best prediction. The performance as measured by the Matthews correlation coefficient (MCC) varied between 0.49 and 0.25 depending on the imbalance. As previously observed, the degree of sequence conservation at the nsSNP position is the single most useful attribute. In addition to conservation, structural predictions made using a balanced dataset can be of value. CONCLUSION: The predictions for all nsSNPs within Ensembl, based on a balanced dataset using all attributes, are available as a DAS annotation. Instructions for adding the track to Ensembl are at http://www.brightstudy.ac.uk/das_help.html.
Algorithms↗
Network approaches to genome annotation and the challenge of Anopheles gambiae.
The rapid advancement of current sequencing projects has provided significant challenges for the swift and accurate processing, integration and analysis of biological data. Such challenges will only become greater as a new round of organisms, both well known and obscure, await sequencing and further study. While perhaps less well studied at the molecular level than Drosophila melanogaster, the recently sequenced mosquito, Anopheles gambiae, provides an example of what will be faced by many of these awaiting projects. This review presents a brief overview of some of the challenges associated with these future genome projects (including Anopheles) as well as a description of recent computational approaches that utilize genome context for the prediction of gene and/or protein function. Such approaches show promise not only for the study of Anopheles, but also in the study of biological processes in general.
Animals↗
Molecular characterization of mouse gastric epithelial progenitor cells.
The adult mouse gastric epithelium undergoes continuous renewal in discrete anatomic units. Lineage tracing studies have previously disclosed the morphologic features of gastric epithelial lineage progenitors (GEPs), including those of the presumptive multipotent stem cell. However, their molecular features have not been defined. Here, we present the results of an analysis of genes and pathways expressed in these cells. One hundred forty-seven transcripts enriched in GEPs were identified using an approach that did not require physical disruption of the stem cell niche. Real-time quantitative RT-PCR studies of laser capture microdissected cells retrieved from this niche confirmed enriched expression of a selected set of genes from the GEP list. An algorithm that allows quantitative comparisons of the functional relatedness of automatically annotated expression profiles showed that the GEP profile is similar to a dataset of genes that defines mouse hematopoietic stem cells, and distinct from the profiles of two differentiated GEP descendant lineages (parietal and zymogenic cell). Overall, our analysis revealed that growth factor response pathways are prominent in GEPs, with insulin-like growth factor appearing to play a key role. A substantial fraction of GEP transcripts encode products required for mRNA processing and cytoplasmic localization, including numerous homologs of Drosophila genes (e.g., Y14, staufen, mago nashi) needed for axis formation during oogenesis. mRNA targeting proteins may help these epithelial progenitors establish differential communications with neighboring cells in their niche.
Adenosine Triphosphate↗
From ORFeome to biology: a functional genomics pipeline.
As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy.
Animals↗
Oligonucleotide frequencies in DNA follow a Yule distribution.
We show that ranked oligonucleotide frequencies in both protein-coding and non-coding regions from several genomes fit poorly to the Zipf distribution, but that the same frequency data give excellent fit to the Yule distribution. The parameters of the Yule distribution for oligonucleotide frequencies in exons are the same (within error limits) as the parameters for introns. This precludes application of Yule or Zipf distribution of ranked oligonucleotide frequencies to annotating new genomic sequences.
DNA↗
Mining DNA microarray data using a novel approach based on graph theory.
The recent demonstration that biochemical pathways from diverse organisms are arranged in scale-free, rather than random, systems [Jeong et al., Nature 407 (2000) 651-654], emphasizes the importance of developing methods for the identification of biochemical nexuses--the nodes within biochemical pathways that serve as the major input/output hubs, and therefore represent potentially important targets for modulation. Here we describe a bioinformatics approach that identifies candidate nexuses for biochemical pathways without requiring functional gene annotation; we also provide proof-of-principle experiments to support this technique. This approach, called Nexxus, may lead to the identification of new signal transduction pathways and targets for drug design.
Apoptosis↗
A profile of differentially expressed genes in primary colorectal cancer using suppression subtractive hybridization.
As a step towards understanding the complex differences between normal cells and cancer cells, we have used suppression subtractive hybridization (SSH) to generate a profile of genes overexpressed in primary colorectal cancer (CRC). From a 35¿ omitted¿000 clone SSH-cDNA repertoire, we have screened 400 random clones by reverse Northern blotting, of which 45 clones were scored as overexpressed in tumor compared to matched normal mucosa. Sequencing showed 37 different genes and of these, 16 genes corresponded to known genes in the public databases. Twelve genes, including Smad5 and Fls353, have previously been shown to be overexpressed in CRC. A series of known genes which have not previously been reported to be overexpressed in cancer were also recovered: Hsc70, PBEF, ribophorin II and Ese-3B. The remaining 21 genes have as yet no functional annotation. These results show that SSH in conjunction with high throughput screening provides a very efficient means to produce a broad profile of genes differentially expressed in cancer. Some of the genes identified may provide novel points of therapeutic intervention.
Adenocarcinoma↗
ORENZA: a web resource for studying ORphan ENZyme activities.
BACKGROUND: Despite the current availability of several hundreds of thousands of amino acid sequences, more than 36% of the enzyme activities (EC numbers) defined by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) are not associated with any amino acid sequence in major public databases. This wide gap separating knowledge of biochemical function and sequence information is found for nearly all classes of enzymes. Thus, there is an urgent need to explore these sequence-less EC numbers, in order to progressively close this gap. DESCRIPTION: We designed ORENZA, a PostgreSQL database of ORphan ENZyme Activities, to collate information about the EC numbers defined by the NC-IUBMB with specific emphasis on orphan enzyme activities. Complete lists of all EC numbers and of orphan EC numbers are available and will be periodically updated. ORENZA allows one to browse the complete list of EC numbers or the subset associated with orphan enzymes or to query a specific EC number, an enzyme name or a species name for those interested in particular organisms. It is possible to search ORENZA for the different biochemical properties of the defined enzymes, the metabolic pathways in which they participate, the taxonomic data of the organisms whose genomes encode them, and many other features. The association of an enzyme activity with an amino acid sequence is clearly underlined, making it easy to identify at once the orphan enzyme activities. Interactive publishing of suggestions by the community would provide expert evidence for re-annotation of orphan EC numbers in public databases. CONCLUSION: ORENZA is a Web resource designed to progressively bridge the unwanted gap between function (enzyme activities) and sequence (dataset present in public databases). ORENZA should increase interactions between communities of biochemists and of genomicists. This is expected to reduce the number of orphan enzyme activities by allocating gene sequences to the relevant enzymes.
Amino Acid Sequence↗