Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Molecular Sequence 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.

At least 865 records · Page 48Linked to original sources
PubMed2004

Tracking repeats using significance and transitivity.

MOTIVATION: Internal repeats in coding sequences correspond to structural and functional units of proteins. Moreover, duplication of fragments of coding sequences is known to be a mechanism to facilitate evolution. Identification of repeats is crucial to shed light on the function and structure of proteins, and explain their evolutionary past. The task is difficult because during the course of evolution many repeats diverged beyond recognition. RESULTS: We introduce a new method TRUST, for ab initio determination of internal repeats in proteins. It provides an improvement in prediction quality as compared to alternative state-of-the-art methods. The increased sensitivity and accuracy of the method is achieved by exploiting the concept of transitivity of alignments. Starting from significant local suboptimal alignments, the application of transitivity allows us to (1) identify distant repeat homologues for which no alignments were found; (2) gain confidence about consistently well-aligned regions; and (3) recognize and reduce the contribution of non-homologous repeats. This re-assessment step enables us to derive a virtually noise-free profile representing a generalized repeat with high fidelity. We also obtained superior specificity by employing rigid statistical testing for self-sequence and profile-sequence alignments. Assessment was done using a database of repeat annotations based on structural superpositioning. The results show that TRUST is a useful and reliable tool for mining tandem and non-tandem repeats in protein sequence databases, capable of predicting multiple repeat types with varying intervening segments within a single sequence. AVAILABILITY: The TRUST server (together with the source code) is available at http://ibivu.cs.vu.nl/programs/trustwww

Algorithms↗
PubMed2005

Isolation and analysis of candidate myeloid tumor suppressor genes from a commonly deleted segment of 7q22.

Monosomy 7 and deletions of 7q are recurring leukemia-associated cytogenetic abnormalities that correlate with adverse outcomes in children and adults. We describe a 2.52-Mb genomic DNA contig that spans a commonly deleted segment of chromosome band 7q22 identified in myeloid malignancies. This interval currently includes 14 genes, 19 predicted genes, and 5 predicted pseudogenes. We have extensively characterized the FBXL13, NAPE-PLD, and SVH genes as candidate myeloid tumor suppressors. FBXL13 encodes a novel F-box protein, SVHis a member of a gene family that contains Armadillo-like repeats, and NAPE-PLD encodes a phospholipase D-type phosphodiesterase. Analysis of a panel of leukemia specimens with monosomy 7 did not reveal mutations in these or in the candidate genes LRRC17, PRO1598, and SRPK2. This fully sequenced and annotated contig provides a resource for candidate myeloid tumor suppressor gene discovery.

Base Sequence↗
PubMed2002

PROSITE: a documented database using patterns and profiles as motif descriptors.

Among the various databases dedicated to the identification of protein families and domains, PROSITE is the first one created and has continuously evolved since. PROSITE currently consists of a large collection of biologically meaningful motifs that are described as patterns or profiles, and linked to documentation briefly describing the protein family or domain they are designed to detect. The close relationship of PROSITE with the SWISS-PROT protein database allows the evaluation of the sensitivity and specificity of the PROSITE motifs and their periodic reviewing. In return, PROSITE is used to help annotate SWISS-PROT entries. The main characteristics and the techniques of family and domain identification used by PROSITE are reviewed in this paper.

Amino Acid Motifs↗
PubMed1999

The PRESAGE database for structural genomics.

The PRESAGE database is a collaborative resource for structural genomics. It provides a database of proteins to which researchers add annotations indicating current experimental status, structural predictions and suggestions. The database is intended to enhance communication among structural genomics researchers and aid dissemination of their results. The PRESAGE database may be accessed at http://presage.stanford.edu/

Databases, Factual↗
PubMed2004

Identification of genes with fast-evolving regions in microbial genomes.

Complete sequences of multiple strains of the same microbial species provide an invaluable source for studying the evolutionary dynamics between orthologous genes over a relatively short time scale. Usually the intensity of the selection pressure is inferred from a comparison between the nonsynonymous substitution rate and the synonymous substitution rate. In this paper, we propose an alternative method for detecting genes with one or more fast-evolving regions from pairwise comparisons of orthologous genes. Our method looks for regions with overrepresented nonsynonymous mutations along the alignment, and requires a higher nonsynonymous evolution rate in those regions than the neutral evolution rate. It identifies gene targets under intensive selection pressure that are not detected from the conventional rate comparison analysis. For those identified genes with known annotations, most of them have a clear role in processes such as bacterial defense and host-pathogen interactions. Gene sets reported from our method provide a measure of the phenotypic divergence between two closely related genomes.

Amino Acid Sequence↗
PubMed1998

Analogous enzymes: independent inventions in enzyme evolution.

It is known that the same reaction may be catalyzed by structurally unrelated enzymes. We performed a systematic search for such analogous (as opposed to homologous) enzymes by evaluating sequence conservation among enzymes with the same enzyme classification (EC) number using sensitive, iterative sequence database search methods. Enzymes without detectable sequence similarity to each other were found for 105 EC numbers (a total of 243 distinct proteins). In 34 cases, independent evolutionary origin of the suspected analogous enzymes was corroborated by showing that they possess different structural folds. Analogous enzymes were found in each class of enzymes, but their overall distribution on the map of biochemical pathways is patchy, suggesting multiple events of gene transfer and selective loss in evolution, rather than acquisition of entire pathways catalyzed by a set of unrelated enzymes. Recruitment of enzymes that catalyze a similar but distinct reaction seems to be a major scenario for the evolution of analogous enzymes, which should be taken into account for functional annotation of genomes. For many analogous enzymes, the bacterial form of the enzyme is different from the eukaryotic one; such enzymes may be promising targets for the development of new antibacterial drugs.

Amino Acid Sequence↗
PubMed2002

Computational modeling of gene structure in Arabidopsis thaliana.

Computational gene identification by sequence inspection remains a challenging problem. For a typical Arabidopsis thaliana gene with five exons, at least one of the exons is expected to have at least one of its borders predicted incorrectly by ab initio gene finding programs. More detailed analysis for individual genomic loci can often resolve the uncertainty on the basis of EST evidence or similarity to potential protein homologues. Such methods are part of the routine annotation process. However, because the EST and protein databases are constantly growing, in many cases original annotation must be re-evaluated, extended, and corrected on the basis of the latest evidence. The Arabidopsis Genome Initiative is undertaking this task on the whole-genome scale via its participating genome centers. The current Arabidopsis genome annotation provides an excellent starting point for assessing the protein repertoire of a flowering plant. More accurate whole-genome annotation will require the combination of high-throughput and individual gene experimental approaches and computational methods. The purpose of this article is to discuss tools available to an individual researcher to evaluate gene structure prediction for a particular locus.

Algorithms↗
PubMed2004

EyeSite: a semi-automated database of protein families in the eye.

The EyeSite is a web-based database of protein families for proteins that function in the eye and their homologous sequences. The resource clusters proteins at different levels of homology in order to facilitate functional annotation of sequences and modelling of proteins from structural homologues. Eye proteins are organized into the tissue types in which they function and are clustered into homologous families using a novel protocol employing the TribeMCL algorithm. Homologous families are further subdivided into sequence clusters for which multiple sequence alignments are generated. Structural annotations from the CATH domain database are provided for nearly 90% of the sequences, and protein family annotations from the Pfam database for approximately 86%. Homology models have also been generated where appropriate. The EyeSite is stored in a relational database and is extensively linked to other online bioinformatics resources to help relate allelic variants, annotations and clinical details to the derived data in the database. The EyeSite is available for online search, sequence information and model retrieval at http://eyesite.cryst.bbk.ac.uk/.

Amino Acid Sequence↗
PubMed2006

FeatureMap3D--a tool to map protein features and sequence conservation onto homologous structures in the PDB.

FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) for structures of homologous proteins. The results are displayed both as an annotated sequence alignment, where the user-provided annotations as well as the sequence conservation between the query and the target sequence are displayed, and also as a publication-quality image of the 3D protein structure with the selected features and sequence conservation enhanced. The results are also returned in a readily parsable text format as well as a PyMol (http://pymol.sourceforge.net/) script file, which allows the user to easily modify the protein structure image to suit a specific purpose. FeatureMap3D can also be used without sequence annotation, to evaluate the quality of the alignment of the input sequences to the most homologous structures in the PDB, through the sequence conservation colored 3D structure visualization tool. FeatureMap3D is available at: http://www.cbs.dtu.dk/services/FeatureMap3D/.

Amino Acid Sequence↗
PubMed2025

The chromosome-level genome of Stylosanthes guianensis provides insights into genome evolution and environmental adaptation.

Stylosanthes guianensis is a leguminous forage crop of significant economic importance, primarily distributed in tropical and subtropical regions. It exhibits strong adaptability to various stresses, yet the genetic basis underlying this trait remains unclear. In this study, we constructed the first chromosome-scale reference genome of S. guianensis using a combination of Nanopore and Hi-C sequencing technologies. The assembled genome size is 1254 Mb, with 10 pseudochromosomes. Using Nanopore full-length transcriptome data, we generated high-quality transcript-level gene annotations, identifying 36 585 gene models and 110 601 transcripts. The repetitive sequences in S. guianensis account for 79.16% of the genome, with the extensive expansion of Gypsy elements in long terminal repeats contributing to its genome size enlargement. Comparative genomic and transcriptomic analyses revealed that flavonoid metabolism plays a pivotal role in stress adaptation, providing new insights into the genetic basis of stress tolerance. Additionally, we generated whole-genome methylation profiles under cold treatment and control conditions, offering valuable data for future epigenomic research. These findings provide essential molecular resources for understanding stress resilience in S. guianensis and advancing its molecular breeding.

Genome, Plant↗
PubMed2001

Computational methods for gene annotation: the Arabidopsis genome.

Since the structure of the DNA molecule was identified half a century ago, the complete genome sequence has been determined for 37 prokaryotes and several eukaryotes. With the exponential growth of genetic information, bioinformatics has attempted to predict gene locations and functions in cyberspace prior to experimental confirmation at the bench.

Arabidopsis↗
PubMed2004

Identification of MEF2-regulated genes during muscle differentiation.

Although a great deal has been elucidated concerning the mechanisms regulating muscle differentiation, little is known about transcription factor-specific gene regulation. Our understanding of the genetic mechanisms regulating cell differentiation is quite limited. Much of what has been defined centers on regulatory signaling cascades and transcription factors. Surprisingly few studies have investigated the association of genes with specific transcription factors. To address these issues, we have utilized a method coupling chromatin immunoprecipitation and CpG microarrays to characterize the genes associated with MEF2 in differentiating C(2)C(12) cells. Results demonstrated a defined binding pattern over the course of differentiation. Filtered data demonstrated 9 clones to be elevated at 0 h, 792 at 6 h, 163 by 1 day, and 316 at 3 days. Using unbiased selection parameters, we selected a subset of 291 prospective candidates. Clones were sequenced and filtered for removal of redundancy between clones and for the presence of repetitive elements. We were able to place 50 of these on the mouse genome, and 20 were found to be located near well-annotated genes. From this list, previously undefined associations with MEF2 were discovered. Many of these genes represent proteins involved in neurogenesis, neuromuscular junctions, signaling and metabolism. The remaining clones include many full-length cDNA and represent novel gene targets. The results of this study provides for the first time, a unique look at gene regulation at the level of transcription factor binding in differentiating muscle.

Actins↗
PubMed2004

Characterization of the type I interferon locus and identification of novel genes.

The human type I interferon (IFN) genes are clustered on human chromosome 9p21 and the mouse genes are located in the region of conserved synteny on mouse chromosome 4. We have identified two novel mouse Ifna genes (Ifna12, Ifna13) and Ifnl2 (IFN-like 2, a homologue of Limitin/IFN-like 1). Another type I IFN gene was designated Ifne1. Mouse Ifne1 was expressed in ovaries and uterus but not in tissues of hematopoietic origin. IFN-epsilon1 has general structural characteristics of a type I IFN. These studies represent the first detailed annotation of the mouse type I IFN locus, and the products of these novel genes may have important functions in reproduction and host defense.

Amino Acid Sequence↗
PubMed2005

Molecular decomposition of complex clinical phenotypes using biologically structured analysis of microarray data.

MOTIVATION: Today, the characterization of clinical phenotypes by gene-expression patterns is widely used in clinical research. If the investigated phenotype is complex from the molecular point of view, new challenges arise and these have not been addressed systematically. For instance, the same clinical phenotype can be caused by various molecular disorders, such that one observes different characteristic expression patterns in different patients. RESULTS: In this paper we describe a novel algorithm called Structured Analysis of Microarrays (StAM), which accounts for molecular heterogeneity of complex clinical phenotypes. Our algorithm goes beyond established methodology in several aspects: in addition to the expression data, it exploits functional annotations from the Gene Ontology database to build biologically focussed classifiers. These are used to uncover potential molecular disease subentities and associate them to biological processes without compromising overall prediction accuracy. AVAILABILITY: Bioconductor compliant R package SUPPLEMENTARY INFORMATION: Complete analyses are available at http://compdiag.molgen.mpg.de/supplements/lottaz05.

Biomarkers, Tumor↗
PubMed2001

Sequence specific recognition of ligand-DNA complexes studied by NMR.

The last few years have represented an accelerated accumulation in detailed information about ligand-DNA interactions. A collected view of literature information is essential for advancing our understanding of the principles of ligand-DNA recognition, utilizing this valuable information for construction of a modeling database, and eventually the rational design of DNA-binding ligands possessing desired properties. This review is concentrated on structure-based information on ligand-oligodeoxyribonucleotide (DON) complexes published since 1995, especially focusing on the results obtained from NMR structure elucidation. The discussions emphasize the sequence specific recognition of novel binding motifs or binding modules of ligand molecules rather than specific atomic details. A comprehensive list of DNA binding ligands are discussed in the text and are also summarized in a table. The DNA sequences that are recognized by specific ligand molecules as studied by NMR are annotated in a figure to provide a clear view of target selection. This review also briefly describes NMR methods for characterization and structure elucidation of ligand-DNA complexes.

Antineoplastic Agents↗
PubMed2005

Sequence and comparative genomic analysis of actin-related proteins.

Actin-related proteins (ARPs) are key players in cytoskeleton activities and nuclear functions. Two complexes, ARP2/3 and ARP1/11, also known as dynactin, are implicated in actin dynamics and in microtubule-based trafficking, respectively. ARP4 to ARP9 are components of many chromatin-modulating complexes. Conventional actins and ARPs codefine a large family of homologous proteins, the actin superfamily, with a tertiary structure known as the actin fold. Because ARPs and actin share high sequence conservation, clear family definition requires distinct features to easily and systematically identify each subfamily. In this study we performed an in depth sequence and comparative genomic analysis of ARP subfamilies. A high-quality multiple alignment of approximately 700 complete protein sequences homologous to actin, including 148 ARP sequences, allowed us to extend the ARP classification to new organisms. Sequence alignments revealed conserved residues, motifs, and inserted sequence signatures to define each ARP subfamily. These discriminative characteristics allowed us to develop ARPAnno (http://bips.u-strasbg.fr/ARPAnno), a new web server dedicated to the annotation of ARP sequences. Analyses of sequence conservation among actins and ARPs highlight part of the actin fold and suggest interactions between ARPs and actin-binding proteins. Finally, analysis of ARP distribution across eukaryotic phyla emphasizes the central importance of nuclear ARPs, particularly the multifunctional ARP4.

Actins↗
PubMed2003

Finding functional features in Saccharomyces genomes by phylogenetic footprinting.

The sifting and winnowing of DNA sequence that occur during evolution cause nonfunctional sequences to diverge, leaving phylogenetic footprints of functional sequence elements in comparisons of genome sequences. We searched for such footprints among the genome sequences of six Saccharomyces species and identified potentially functional sequences. Comparison of these sequences allowed us to revise the catalog of yeast genes and identify sequence motifs that may be targets of transcriptional regulatory proteins. Some of these conserved sequence motifs reside upstream of genes with similar functional annotations or similar expression patterns or those bound by the same transcription factor and are thus good candidates for functional regulatory sequences.

Algorithms↗
PubMed2003

Automatic methods for predicting functionally important residues.

Sequence analysis is often the first guide for the prediction of residues in a protein family that may have functional significance. A few methods have been proposed which use the division of protein families into subfamilies in the search for those positions that could have some functional significance for the whole family, but at the same time which exhibit the specificity of each subfamily ("Tree-determinant residues"). However, there are still many unsolved questions like the best division of a protein family into subfamilies, or the accurate detection of sequence variation patterns characteristic of different subfamilies. Here we present a systematic study in a significant number of protein families, testing the statistical meaning of the Tree-determinant residues predicted by three different methods that represent the range of available approaches. The first method takes as a starting point a phylogenetic representation of a protein family and, following the principle of Relative Entropy from Information Theory, automatically searches for the optimal division of the family into subfamilies. The second method looks for positions whose mutational behavior is reminiscent of the mutational behavior of the full-length proteins, by directly comparing the corresponding distance matrices. The third method is an automation of the analysis of distribution of sequences and amino acid positions in the corresponding multidimensional spaces using a vector-based principal component analysis. These three methods have been tested on two non-redundant lists of protein families: one composed by proteins that bind a variety of ligand groups, and the other composed by proteins with annotated functionally relevant sites. In most cases, the residues predicted by the three methods show a clear tendency to be close to bound ligands of biological relevance and to those amino acids described as participants in key aspects of protein function. These three automatic methods provide a wide range of possibilities for biologists to analyze their families of interest, in a similar way to the one presented here for the family of proteins related with ras-p21.

Algorithms↗