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Results for “functional annotations”

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PubMed2001

The TIGR Gene Indices: analysis of gene transcript sequences in highly sampled eukaryotic species.

While genome sequencing projects are advancing rapidly, EST sequencing and analysis remains a primary research tool for the identification and categorization of gene sequences in a wide variety of species and an important resource for annotation of genomic sequence. The TIGR Gene Indices (http://www.tigr.org/tdb/tgi. shtml) are a collection of species-specific databases that use a highly refined protocol to analyze EST sequences in an attempt to identify the genes represented by that data and to provide additional information regarding those genes. Gene Indices are constructed by first clustering, then assembling EST and annotated gene sequences from GenBank for the targeted species. This process produces a set of unique, high-fidelity virtual transcripts, or Tentative Consensus (TC) sequences. The TC sequences can be used to provide putative genes with functional annotation, to link the transcripts to mapping and genomic sequence data, to provide links between orthologous and paralogous genes and as a resource for comparative sequence analysis.

Animals↗

PubMed2005

Efficient gene-driven germ-line point mutagenesis of C57BL/6J mice.

BACKGROUND: Analysis of an allelic series of point mutations in a gene, generated by N-ethyl-N-nitrosourea (ENU) mutagenesis, is a valuable method for discovering the full scope of its biological function. Here we present an efficient gene-driven approach for identifying ENU-induced point mutations in any gene in C57BL/6J mice. The advantage of such an approach is that it allows one to select any gene of interest in the mouse genome and to go directly from DNA sequence to mutant mice. RESULTS: We produced the Cryopreserved Mutant Mouse Bank (CMMB), which is an archive of DNA, cDNA, tissues, and sperm from 4,000 G1 male offspring of ENU-treated C57BL/6J males mated to untreated C57BL/6J females. Each mouse in the CMMB carries a large number of random heterozygous point mutations throughout the genome. High-throughput Temperature Gradient Capillary Electrophoresis (TGCE) was employed to perform a 32-Mbp sequence-driven screen for mutations in 38 PCR amplicons from 11 genes in DNA and/or cDNA from the CMMB mice. DNA sequence analysis of heteroduplex-forming amplicons identified by TGCE revealed 22 mutations in 10 genes for an overall mutation frequency of 1 in 1.45 Mbp. All 22 mutations are single base pair substitutions, and nine of them (41%) result in nonconservative amino acid substitutions. Intracytoplasmic sperm injection (ICSI) of cryopreserved spermatozoa into B6D2F1 or C57BL/6J ova was used to recover mutant mice for nine of the mutations to date. CONCLUSIONS: The inbred C57BL/6J CMMB, together with TGCE mutation screening and ICSI for the recovery of mutant mice, represents a valuable gene-driven approach for the functional annotation of the mammalian genome and for the generation of mouse models of human genetic diseases. The ability of ENU to induce mutations that cause various types of changes in proteins will provide additional insights into the functions of mammalian proteins that may not be detectable by knockout mutations.

Animals↗

PubMed2002

Gene expression profiling of prolonged cold ischemia and reperfusion in murine heart transplants.

BACKGROUND: Heart transplantation causes complex changes in the biological homeostasis of the graft. Current knowledge is restricted to a few genes and regulation of certain factors involved in ischemia-reperfusion (I/R) injury. Efficient strategies to prevent I/R injury, however, require a better understanding of its mechanisms. Using cDNA microarrays, we investigated gene expression profiles of murine cardiac isografts. METHODS: For microarray hybridization experiments, chips with 8,734 individual target sequences were used. Messenger RNA was extracted from hearts subjected to warm ischemia and different time periods of reperfusion or to prolonged cold ischemia or warm ischemia and transplantation. Native hearts served as controls. RESULTS: A set of 68 sequences was regulated in all hearts. In addition, grafts without cold ischemia showed differential expression of 65 sequences, which were not found in hearts transplanted after cold storage, and which in turn had 38 sequences regulated and not detected in grafts without cold ischemia. Overall, approximately 50% of regulated transcripts are expressed sequence tags (ESTs) with unknown function. Annotated genes encoded immune modulators (20% of sequences), receptor proteins, structural proteins, and proteins involved in metabolism. CONCLUSION: Our data demonstrate expression profiles of hearts subjected to prolonged cold ischemia or transplantation in an isogeneic setting. We have defined functional complexes and detected a substantial amount of ESTs encoding novel proteins. These studies may provide a molecular basis for further functional experiments and may help identify potential targets for modulation of postischemic inflammation.

Animals↗

PubMed2006

Using ontologies to annotate microarray experiments.

Consistent annotation of studies using microarrays is critical to optimal management and use of microarray data. Ontologies provide defined and structured terminology suited for this purpose. The Gene Ontology (GO) has aided the analysis of expression studies greatly by providing consistent functional annotation of array sequence features. The intent of the MGED Ontology (MO) is to provide consistent experimental annotation. The MO has been developed as a community effort in support of the Minimum Information About a Microarray Experiment standard and is tied to the Microarray Gene Expression object model. The MO is freely available and has been incorporated into the annotation systems of several public microarray database systems.

Animals↗

PubMed2006

Assessing semantic similarity measures for the characterization of human regulatory pathways.

MOTIVATION: Pathway modeling requires the integration of multiple data including prior knowledge. In this study, we quantitatively assess the application of Gene Ontology (GO)-derived similarity measures for the characterization of direct and indirect interactions within human regulatory pathways. The characterization would help the integration of prior pathway knowledge for the modeling. RESULTS: Our analysis indicates information content-based measures outperform graph structure-based measures for stratifying protein interactions. Measures in terms of GO biological process and molecular function annotations can be used alone or together for the validation of protein interactions involved in the pathways. However, GO cellular component-derived measures may not have the ability to separate true positives from noise. Furthermore, we demonstrate that the functional similarity of proteins within known regulatory pathways decays rapidly as the path length between two proteins increases. Several logistic regression models are built to estimate the confidence of both direct and indirect interactions within a pathway, which may be used to score putative pathways inferred from a scaffold of molecular interactions.

Databases, Protein↗

PubMed2003

Predicting phenotype from patterns of annotation.

MOTIVATION: Predicting the outcome of specific experiments (such as the growth of a particular mutant strain in a particular medium) has the potential to allow researchers to devote resources to experiments with higher expected numbers of 'hits'. RESULTS: We use decision trees to predict phenotypes associated with Saccharomyces cerevisiae genes on the basis of Gene Ontology (GO) functional annotations from the Saccharomyces Genome Database (SGD) and other phenotypic annotations from the Yeast Phenotype Catalog at the Munich Information Center for Protein Sequences (MIPS). We assess the methodology in three ways: (1) we use cross-validation on the phenotypic annotations listed in MIPS, and show ROC curves indicating the tradeoff between true-positive rate and false-positive rate; (2) we do a literature-search for 100 of the predicted gene-phenotype associations that are not listed in MIPS, and find evidence for 43 of them; (3) we use deletion strains to experimentally assess 61 predicted gene-phenotype associations not listed in MIPS; significantly more of these deletion strains show abnormal growth than would be expected by chance.

Algorithms↗

PubMed2007

Transcriptional profiling of wheat caryopsis development using cDNA microarrays.

The expression of 7,835 genes in developing wheat caryopses was analyzed using cDNA arrays. Using a mixed model analysis of variance (ANOVA) method, 29% (2,237) of the genes on the array were identified to be differentially expressed at the 6 different time-points examined, which covers the developmental stages from coenocytic endosperm to physiological maturity. Comparison of genes differentially expressed between two time-points revealed a dynamic transcript accumulation profile with major re-programming events that occur at 3-7, 7-14 and 21-28 DPA. A k-means clustering algorithm grouped the differentially expressed genes into 10 clusters, revealing co-expression of genes involved in the same pathway such as carbohydrate and protein synthesis or preparation for desiccation. Functional annotation of genes that show peak expression at specific time-points correlated with the developmental events associated with the respective stages. Results provide information on the temporal expression during caryopsis development for a significant number of differentially expressed genes with unknown function.

DNA, Complementary↗

PubMed2005

Methods for the functional genomic analysis of ubiquitin ligases.

Ubiquitin ligases (E3s) are critical components of the ubiquitin-proteasome system as they are the major determinants of specificity in ubiquitin conjugation. The number of predicted E3s in the mammalian genome is exceeding 400 and is represented by two major subfamilies: HECT domain-containing E3s and RING finger-type E3s. Given the size of this protein family and lack of knowledge on the functions of most of these 400 proteins, their functional annotation should benefit from modern genomic tools. This article presents a methodology consisting of the use of a cDNA expression library to identify suppressors of polyglutamine (polyQ)-mediated protein aggregate formation in cells, as an example of a genomic approach to assign functions to E3s. In this screen, we identified novel RING finger-type E3s exhibiting suppressor activity among >50% of all the potential E3s in the mouse and human genomes. This method could be adapted easily to identify E3s that function in other processes and signaling pathways.

Algorithms↗

PubMed2001

Annotated draft genomic sequence from a Streptococcus pneumoniae type 19F clinical isolate.

The public availability of numerous microbial genomes is enabling the analysis of bacterial biology in great detail and with an unprecedented, organism-wide and taxon-wide, broad scope. Streptococcus pneumoniae is one of the most important bacterial pathogens throughout the world. We present here sequences and functional annotations for 2.1-Mbp of pneumococcal DNA, covering more than 90% of the total estimated size of the genome. The sequenced strain is a clinical isolate resistant to macrolides and tetracycline. It carries a type 19F capsular locus, but multilocus sequence typing for several conserved genetic loci suggests that the strain sequenced belongs to a pneumococcal lineage that most often expresses a serotype 15 capsular polysaccharide. A total of 2,046 putative open reading frames (ORFs) longer than 100 amino acids were identified (average of 1,009 bp per ORF), including all described two-component systems and aminoacyl tRNA synthetases. Comparisons to other complete, or nearly complete, bacterial genomes were made and are presented in a graphical form for all the predicted proteins.

DNA, Bacterial↗

PubMed2000

Can sequence determine function?

The functional annotation of proteins identified in genome sequencing projects is based on similarities to homologs in the databases. As a result of the possible strategies for divergent evolution, homologous enzymes frequently do not catalyze the same reaction, and we conclude that assignment of function from sequence information alone should be viewed with some skepticism.

Animals↗

PubMed2005

Go molecular function terms are predictive of subcellular localization.

A protein's function is closely linked to its subcellular localization. Use of Gene Ontology (GO) molecular function terms to extend sequence-based subcellular localization prediction has been previously shown to improve predictive performance. Here, we explore directly the relationship between GO function annotations and localization information, identifying both highly predictive single terms, and terms with large information gain with respect to location. The results identify a number of predictive and informative GO terms with respect to subcellular location, particularly nucleus, extracellular space, membrane, mitochondrion, endoplasmic reticulum and Golgi. There are several clear examples illustrating why the addition of function information provides additional predictive power over sequence alone. Other interesting phenomena can also be seen in the results. Most predictive or informative terms are imperfect, and incorrect prediction may often call out significant biological phenomena. Finally, these results may be useful in the GO annotation process.

Amino Acid Sequence↗

PubMed2006

Differential evolutionary conservation of motif modes in the yeast protein interaction network.

BACKGROUND: The importance of a network motif (a recurring interconnected pattern of special topology which is over-represented in a biological network) lies in its position in the hierarchy between the protein molecule and the module in a protein-protein interaction network. Until now, however, the methods available have greatly restricted the scope of research. While they have focused on the analysis in the resolution of a motif topology, they have not been able to distinguish particular motifs of the same topology in a protein-protein interaction network. RESULTS: We have been able to assign the molecular function annotations of Gene Ontology to each protein in the protein-protein interactions of Saccharomyces cerevisiae. For various motif topologies, we have developed an algorithm, enabling us to unveil one million "motif modes", each of which features a unique topological combination of molecular functions. To our surprise, the conservation ratio, i.e., the extent of the evolutionary constraints upon the motif modes of the same motif topology, varies significantly, clearly indicative of distinct differences in the evolutionary constraints upon motifs of the same motif topology. Equally important, for all motif modes, we have found a power-law distribution of the motif counts on each motif mode. We postulate that motif modes may very well represent the evolutionary-conserved topological units of a protein interaction network. CONCLUSION: For the first time, the motifs of a protein interaction network have been investigated beyond the scope of motif topology. The motif modes determined in this study have not only enabled us to differentiate among different evolutionary constraints on motifs of the same topology but have also opened up new avenues through which protein interaction networks can be analyzed.

Algorithms↗

PubMed2004

The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology.

The Gene Ontology Annotation (GOA) database (http://www.ebi.ac.uk/GOA) aims to provide high-quality electronic and manual annotations to the UniProt Knowledgebase (Swiss-Prot, TrEMBL and PIR-PSD) using the standardized vocabulary of the Gene Ontology (GO). As a supplementary archive of GO annotation, GOA promotes a high level of integration of the knowledge represented in UniProt with other databases. This is achieved by converting UniProt annotation into a recognized computational format. GOA provides annotated entries for nearly 60,000 species (GOA-SPTr) and is the largest and most comprehensive open-source contributor of annotations to the GO Consortium annotation effort. By integrating GO annotations from other model organism groups, GOA consolidates specialized knowledge and expertise to ensure the data remain a key reference for up-to-date biological information. Furthermore, the GOA database fully endorses the Human Proteomics Initiative by prioritizing the annotation of proteins likely to benefit human health and disease. In addition to a non-redundant set of annotations to the human proteome (GOA-Human) and monthly releases of its GO annotation for all species (GOA-SPTr), a series of GO mapping files and specific cross-references in other databases are also regularly distributed. GOA can be queried through a simple user-friendly web interface or downloaded in a parsable format via the EBI and GO FTP websites. The GOA data set can be used to enhance the annotation of particular model organism or gene expression data sets, although increasingly it has been used to evaluate GO predictions generated from text mining or protein interaction experiments. In 2004, the GOA team will build on its success and will continue to supplement the functional annotation of UniProt and work towards enhancing the ability of scientists to access all available biological information. Researchers wishing to query or contribute to the GOA project are encouraged to email: goa@ebi.ac.uk.

Animals↗

PubMed2006

A factor analysis model for functional genomics.

BACKGROUND: Expression array data are used to predict biological functions of uncharacterized genes by comparing their expression profiles to those of characterized genes. While biologically plausible, this is both statistically and computationally challenging. Typical approaches are computationally expensive and ignore correlations among expression profiles and functional categories. RESULTS: We propose a factor analysis model (FAM) for functional genomics and give a two-step algorithm, using genome-wide expression data for yeast and a subset of Gene-Ontology Biological Process functional annotations. We show that the predictive performance of our method is comparable to the current best approach while our total computation time was faster by a factor of 4000. We discuss the unique challenges in performance evaluation of algorithms used for genome-wide functions genomics. Finally, we discuss extensions to our method that can incorporate the inherent correlation structure of the functional categories to further improve predictive performance. CONCLUSION: Our factor analysis model is a computationally efficient technique for functional genomics and provides a clear and unified statistical framework with potential for incorporating important gene ontology information to improve predictions.

Algorithms↗

PubMed2006

Using local gene expression similarities to discover regulatory binding site modules.

BACKGROUND: We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to relate the combinations of transcription factor binding sites (also referred to as binding site modules) identified in gene promoters to the expression of these genes. The novel aspects include local expression similarity clustering and an exact IF-THEN rule inference algorithm. We also provide a method of rule generalization to include genes with unknown expression profiles. RESULTS: We have implemented the proposed framework and tested it on publicly available datasets from yeast S. cerevisae. The testing procedure consists of thorough statistical analyses of the groups of genes matching the rules we infer from expression data against known sets of co-regulated genes. For this purpose we have used published ChIP-Chip data and Gene Ontology annotations. In order to make these tests more objective we compare our results with recently published similar studies. CONCLUSION: Results we obtain show that local expression similarity clustering greatly enhances overall quality of the derived rules, both in terms of enrichment of Gene Ontology functional annotation and coherence with ChIP-Chip binding data. Our approach thus provides reliable hypotheses on co-regulation that can be experimentally verified. An important feature of the method is its reliance only on widely accessible sequence and expression data. The same procedure can be easily applied to other microbial organisms.

Binding Sites↗

PubMedDate not supplied

Methods to map protein interactions in mammalian cells: different tools to address different questions.

In the post-genome era, functional annotation of the predicted gene-sets will be one of the most important upcoming challenges. So-called interactome analysis positions a protein in its subcellular environment by mapping its interaction partners. Such interaction maps are essential for an accurate insight into protein function since many cellular processes are organised to operate in protein complexes. These assemblies have dynamic structures and can interact with each other, two properties which are often controlled by regulated protein expression and modification. Various methods exist to unravel protein interaction circuitries, which can be roughly divided into biochemical and genetic strategies. In this review we focus on the different strategies to study protein-protein interactions in living mammalian cells. Recently developed analytical and screening methods are also addressed.

Animals↗

PubMed2025

Annotated genome of the Atlantic dog whelk, Nucella lapillus.

Nucella lapillus is an important player in rocky shore food chains and has been a focal organism of ecological and evolutionary studies for decades. Despite poor dispersal, they have a broad geographic range, which makes them an ideal species to examine isolation by distance and selection across environmental gradients. Here we present the fully annotated genome of N. lapillus generated with Oxford Nanopore Techonology sequencing at ∼37× coverage. The genome assembly is 2.32 Gbp and consists of 2,525 contigs, with an N50 length of 2 Mbp. Repeat annotation identified 2,491 families that cover 67.56% of the genome, which is similar to other gastropods. Despite its large size and high proportion of repeats, the genome is of high quality. Benchmarking Universal Single-Copy Ortholog (BUSCO) analysis revealed a score of 96.8%. Functional annotation of the genome produced 45,848 protein-coding genes with a 96.6% BUSCO score. Genomic resources for mollusks lag behind that of other phyla, perhaps because many of their innate characteristics complicate DNA extraction, sequencing, and assembly. This new N. lapillus genome will increase our genomic understanding of the second largest phylum (and the most diverse class within said phylum) and serve as a key resource to advance studies on the organismal biology and population genetics of this iconic species as well as the connection between genomic variation and community-level processes.

Animals↗

PubMed2006

Genome-wide prediction of C. elegans genetic interactions.

To obtain a global view of functional interactions among genes in a metazoan genome, we computationally integrated interactome data, gene expression data, phenotype data, and functional annotation data from three model organisms-Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster-and predicted genome-wide genetic interactions in C. elegans. The resulting genetic interaction network (consisting of 18,183 interactions) provides a framework for system-level understanding of gene functions. We experimentally tested the predicted interactions for two human disease-related genes and identified 14 new modifiers.

Algorithms↗