PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Annotation”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28Linked to original sources

dbRES: a web-oriented database for annotated RNA editing sites.

Although a large amount of experimentally derived information about RNA editing sites currently exists, this information has remained scattered in a variety of sources and in diverse data formats. Availability of standard collections for high-quality experimental data will be by of great help for systematic studying of RNA editing, especially for developing computational algorithm to predict RNA editing site. dbRES (http://bioinfo.au.tsinghua.edu.cn/dbRES) is a public database of known RNA editing sites. All sites are manually curated from literature and GenBank annotations. dbRES version 1.1 contains 5437 RNA editing sites of 251 transcripts, covering 96 organisms across plant, metazoan, protozoa, fungi and virus. dbRES provides comprehensive annotations and data summaries, including (but not limited to) transcript sequences, RNA editing types, editing site locations, amino acid changes, organisms, subcellular organelles (if available), cited references, etc. A user-friendly web interface is developed to facilitate both retrieving data and online display of RNA edit site information.

Databases, Nucleic Acid↗

Pseudogene.org: a comprehensive database and comparison platform for pseudogene annotation.

The Pseudogene.org knowledgebase serves as a comprehensive repository for pseudogene annotation. The definition of a pseudogene varies within the literature, resulting in significantly different approaches to the problem of identification. Consequently, it is difficult to maintain a consistent collection of pseudogenes in detail necessary for their effective use. Our database is designed to address this issue. It integrates a variety of heterogeneous resources and supports a subset structure that highlights specific groups of pseudogenes that are of interest to the research community. Tools are provided for the comparison of sets and the creation of layered set unions, enabling researchers to derive a current 'consensus' set of pseudogenes. Additional features include versatile search, the capacity for robust interaction with other databases, the ability to reconstruct older versions of the database (accounting for changing genome builds) and an underlying object-oriented interface designed for researchers with a minimal knowledge of programming. At the present time, the database contains more than 100,000 pseudogenes spanning 64 prokaryote and 11 eukaryote genomes, including a collection of human annotations compiled from 16 sources.

Databases, Genetic↗

MMDB: annotating protein sequences with Entrez's 3D-structure database.

Three-dimensional (3D) structure is now known for a large fraction of all protein families. Thus, it has become rather likely that one will find a homolog with known 3D structure when searching a sequence database with an arbitrary query sequence. Depending on the extent of similarity, such neighbor relationships may allow one to infer biological function and to identify functional sites such as binding motifs or catalytic centers. Entrez's 3D-structure database, the Molecular Modeling Database (MMDB), provides easy access to the richness of 3D structure data and its large potential for functional annotation. Entrez's search engine offers several tools to assist biologist users: (i) links between databases, such as between protein sequences and structures, (ii) pre-computed sequence and structure neighbors, (iii) visualization of structure and sequence/structure alignment. Here, we describe an annotation service that combines some of these tools automatically, Entrez's 'Related Structure' links. For all proteins in Entrez, similar sequences with known 3D structure are detected by BLAST and alignments are recorded. The 'Related Structure' service summarizes this information and presents 3D views mapping sequence residues onto all 3D structures available in MMDB (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=structure).

Databases, Protein↗

Sequences annotated by structure: a tool to facilitate the use of structural information in sequence analysis.

With the aim of bridging the gap between protein sequence and structural analyses, we have developed a tool to aid the identification of new protein sequences by recognizing distant homologues using structural information. The tool generates sequence annotated by structure (SAS) files, applying structural information derived from structural analyses to a given protein sequence. A World Wide Web interface allows a given sequence to be submitted either for structural annotation or, where its structure is unknown, for search and alignment against sequences of known structure. In both cases, SAS will colour residues in the sequence of known structure according to a selection of properties, including secondary structure, interatomic contacts and active site information. SAS can also be used to inspect properties of a single structure.

Amino Acid Sequence↗

Sequence annotation of nuclear receptor ligand-binding domains by automated homology modeling.

The quality of three-dimensional homology models derived from protein sequences provides an independent measure of the suitability of a protein sequence for a certain fold. We have used automated homology modeling and model assessment tools to identify putative nuclear hormone receptor ligand-binding domains in the genome of Caenorhabditis elegans. Our results indicate that the availability of multiple crystal structures is crucial to obtaining useful models in this receptor family. The majority of annotated mammalian nuclear hormone receptors could be assigned to a ligand-binding domain fold by using the best model derived from any of four template structures. This strategy also assigned the ligand-binding domain fold to a number of C.elegans. sequences without prior annotation. Interestingly, the retinoic acid receptor crystal structure contributed most to the number of sequences that could be assigned to a ligand-binding domain fold. Several causes for this can be suggested, including the high quality of this protein structure in terms of our assessment tools, similarity between the biological function or ligand of this receptor and the modeled genes and gene duplication in C.elegans.

Animals↗

Nurse-sensitive patient outcomes: an annotated bibliography.

This article is an annotated bibliography on the topic of nurse staffing and patient care outcomes in the acute care setting. The authors have been involved in the developmental and pilot phase of the Veterans Affairs Nursing Outcomes Database project to build a database of acute care nursing-sensitive quality indicators. In the section preceding the annotated bibliography, a context for the development of this literature review is explained and a summary synthesizing key issues is presented.

Nurse-Patient Relations↗

Re-annotation of the genome sequence of Mycobacterium tuberculosis H37Rv.

Original genome annotations need to be regularly updated if the information they contain is to remain accurate and relevant. Here the complete re-annotation of the genome sequence of Mycobacterium tuberculosis strain H37Rv is presented almost 4 years after the first submission. Eighty-two new protein-coding sequences (CDS) have been included and 22 of these have a predicted function. The majority were identified by manual or automated re-analysis of the genome and most of them were shorter than the 100 codon cut-off used in the initial genome analysis. The functional classification of 643 CDS has been changed based principally on recent sequence comparisons and new experimental data from the literature. More than 300 gene names and over 1000 targeted citations have been added and the lengths of 60 genes have been modified. Presently, it is possible to assign a function to 2058 proteins (52% of the 3995 proteins predicted) and only 376 putative proteins share no homology with known proteins and thus could be unique to M. tuberculosis.

Bacterial Proteins↗

Pervasive correlations between causal disease effects of proximal SNPs vary with functional annotations and implicate stabilizing selection.

The genetic architecture of human diseases and complex traits has been extensively studied, but little is known about the relationship of causal disease effect sizes between proximal SNPs, which have largely been assumed to be independent. We introduce a new method, LD SNP-pair effect correlation regression (LDSPEC), to estimate the correlation of causal disease effect sizes of derived alleles between proximal SNPs, depending on their allele frequencies, LD, and functional annotations; LDSPEC produced robust estimates in simulations across various genetic architectures. We applied LDSPEC to 70 diseases and complex traits from the UK Biobank (average N=306K), meta-analyzing results across diseases/traits. We detected significantly nonzero effect correlations for proximal SNP pairs (e.g., -0.37±0.09 for low-frequency positive-LD 0-100bp SNP pairs) that decayed with distance (e.g., -0.07±0.01 for low-frequency positive-LD 1-10kb), varied with allele frequency (e.g., -0.15±0.04 for common positive-LD 0-100bp), and varied with LD between SNPs (e.g., +0.12±0.05 for common negative-LD 0-100bp) (because we consider derived alleles, positive-LD and negative-LD SNP pairs may yield very different results). We further determined that SNP pairs with shared functions had stronger effect correlations that spanned longer genomic distances, e.g., -0.37±0.08 for low-frequency positive-LD same-gene promoter SNP pairs (average genomic distance of 47kb (due to alternative splicing)) and -0.32±0.04 for low-frequency positive-LD H3K27ac 0-1kb SNP pairs. Consequently, SNP-heritability estimates were substantially smaller than estimates of the sum of causal effect size variances across all SNPs (ratio of 0.87±0.02 across diseases/traits), particularly for certain functional annotations (e.g., 0.78±0.01 for common Super enhancer SNPs)-even though these quantities are widely assumed to be equal. We recapitulated our findings via forward simulations with an evolutionary model involving stabilizing selection, implicating the action of linkage masking, whereby haplotypes containing linked SNPs with opposite effects on disease have reduced effects on fitness and escape negative selection.

Journal Article↗

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins.

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

GENCODE↗

DeNoFo: a file format and toolkit for standardised, comparable de novo gene annotation.

MOTIVATION: De novo genes emerge from previously non-coding regions of the genome, challenging the traditional view that new genes primarily arise through duplication and adaptation of existing ones. Characterised by their rapid evolution and their novel structural properties or functional roles, de novo genes represent a young area of research. Therefore, the field currently lacks established standards and methodologies, leading to inconsistent terminology and challenges in comparing and reproducing results. RESULTS: This work presents a standardised annotation format to document the methodology of de novo gene datasets in a reproducible way. We developed DeNoFo, a toolkit to provide easy access to this format that simplifies annotation of datasets and facilitates comparison across studies. Unifying the different protocols and methods in one standardised format, while providing integration into established file formats, such as fasta or gff, ensures comparability of studies and advances new insights in this rapidly evolving field. AVAILABILITY AND IMPLEMENTATION: DeNoFo is available through the official Python Package Index (PyPI) and at https://github.com/EDohmen/denofo . All tools have a graphical user interface and a command line interface. The toolkit is implemented in Python3, available for all major platforms and installable with pip and uv.

Journal Article↗

Drosophila genomic sequence annotation using the BLOCKS+ database.

A simple and general homology-based method for gene finding was applied to the 2.9-Mb Drosophila melanogaster Adh region, the target sequence of the Genome Annotation Assessment Project (GASP). Each strand of the entire sequence was used as query of the BLOCKS+ database of conserved regions of proteins. This led to functional assignments for more than one-third of the genes and two-thirds of the transposons. Considering the enormous size of the query, the fact that only two false-positive matches were reported emphasizes the high selectivity of protein family-based methods for gene finding. We used the search results to improve BLOCKS+ by identifying compositionally biased blocks. Our results confirm that protein family databases can be used effectively in automated sequence annotation efforts.

Alcohol Dehydrogenase↗

Using GeneWise in the Drosophila annotation experiment.

The GeneWise method for combining gene prediction and homology searches was applied to the 2.9-Mb region from Drosophila melanogaster. The results from the Genome Annotation Assessment Project (GASP) showed that GeneWise provided reasonably accurate gene predictions. Further investigation indicates that many of the incorrect gene predictions from GeneWise were due to transposons with valid protein-coding genes and the remaining cases are pseudogenes or possible annotation oversights.

Animals↗

Annotating large genomes with exact word matches.

We have developed a tool for rapidly determining the number of exact matches of any word within large, internally repetitive genomes or sets of genomes. Thus we can readily annotate any sequence, including the entire human genome, with the counts of its constituent words. We create a Burrows-Wheeler transform of the genome, which together with auxiliary data structures facilitating counting, can reside in about one gigabyte of RAM. Our original interest was motivated by oligonucleotide probe design, and we describe a general protocol for defining unique hybridization probes. But our method also has applications for the analysis of genome structure and assembly. We demonstrate the identification of chromosome-specific repeats, and outline a general procedure for finding undiscovered repeats. We also illustrate the changing contents of the human genome assemblies by comparing the annotations built from different genome freezes.

Algorithms↗

Fugu ESTs: new resources for transcription analysis and genome annotation.

The draft Fugu rubripes genome was released in 2002, at which time relatively few cDNAs were available to aid in the annotation of genes. The data presented here describe the sequencing and analysis of 24,398 expressed sequence tags (ESTs) generated from 15 different adult and juvenile Fugu tissues, 74% of which matched protein database entries. Analysis of the EST data compared with the Fugu genome data predicts that approximately 10,116 gene tags have been generated, covering almost one-third of Fugu predicted genes. This represents a remarkable economy of effort. Comparison with the Washington University zebrafish EST assemblies indicates strong conservation within fish species, but significant differences remain. This potentially represents divergence of sequence in the 5' terminal exons and UTRs between these two fish species, although clearly, complete EST data sets are not available for either species. This project provides new Fugu resources, and the analysis adds significant weight to the argument that EST programs remain an essential resource for genome exploitation and annotation. This is particularly timely with the increasing availability of draft genome sequence from different organisms and the mounting emphasis on gene function and regulation.

Animals↗

Annotation transfer between genomes: protein-protein interologs and protein-DNA regulogs.

Proteins function mainly through interactions, especially with DNA and other proteins. While some large-scale interaction networks are now available for a number of model organisms, their experimental generation remains difficult. Consequently, interolog mapping--the transfer of interaction annotation from one organism to another using comparative genomics--is of significant value. Here we quantitatively assess the degree to which interologs can be reliably transferred between species as a function of the sequence similarity of the corresponding interacting proteins. Using interaction information from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Helicobacter pylori, we find that protein-protein interactions can be transferred when a pair of proteins has a joint sequence identity >80% or a joint E-value <10(-70). (These "joint" quantities are the geometric means of the identities or E-values for the two pairs of interacting proteins.) We generalize our interolog analysis to protein-DNA binding, finding such interactions are conserved at specific thresholds between 30% and 60% sequence identity depending on the protein family. Furthermore, we introduce the concept of a "regulog"--a conserved regulatory relationship between proteins across different species. We map interologs and regulogs from yeast to a number of genomes with limited experimental annotation (e.g., Arabidopsis thaliana) and make these available through an online database at http://interolog.gersteinlab.org. Specifically, we are able to transfer approximately 90,000 potential protein-protein interactions to the worm. We test a number of these in two-hybrid experiments and are able to verify 45 overlaps, which we show to be statistically significant.

Amino Acid Sequence↗

Systematic genome-wide annotation of spliceosomal proteins reveals differential gene family expansion.

Although more than 200 human spliceosomal and splicing-associated proteins are known, the evolution of the splicing machinery has not been studied extensively. The recent near-complete sequencing and annotation of distant vertebrate and chordate genomes provides the opportunity for an exhaustive comparative analysis of splicing factors across eukaryotes. We describe here our semiautomated computational pipeline to identify and annotate splicing factors in representative species of eukaryotes. We focused on protein families whose role in splicing is confirmed by experimental evidence. We visually inspected 1894 proteins and manually curated 224 of them. Our analysis shows a general conservation of the core spliceosomal proteins across the eukaryotic lineage, contrasting with selective expansions of protein families known to play a role in the regulation of splicing, most notably of SR proteins in metazoans and of heterogeneous nuclear ribonucleoproteins (hnRNP) in vertebrates. We also observed vertebrate-specific expansion of the CLK and SRPK kinases (which phosphorylate SR proteins), and the CUG-BP/CELF family of splicing regulators. Furthermore, we report several intronless genes amongst splicing proteins in mammals, suggesting that retrotransposition contributed to the complexity of the mammalian splicing apparatus.

Animals↗

ProtoBee: hierarchical classification and annotation of the honey bee proteome.

The recently sequenced genome of the honey bee (Apis mellifera) has produced 10,157 predicted protein sequences, calling for a computational effort to extract biological insights from them. We have applied an unsupervised hierarchical protein-clustering method, which was previously used in the ProtoNet system, to nearly 200,000 proteins consisting of the predicted honey bee proteins, the SWISS-PROT protein database, and the complete set of proteins of the mouse (Mus musculus) and the fruit fly (Drosophila melanogaster). The hierarchy produced by this method has been entitled ProtoBee. In ProtoBee, the proteins are hierarchically organized into 18,936 separate tree hierarchies, each representing a protein functional family. By using the mouse and Drosophila complete proteomes as reference, we are able to highlight functional groups of putative gene-loss events, putative novel proteins of unique functionality, and bee-specific paralogs. We have studied some of the ProtoBee findings and suggest their biological relevance. Examples include novel opsin genes and intriguing nuclear matches of mitochondrial genes. The organization of bee sequences into functional clusters suggests a natural way of automatically inferring functional annotation. Following this notion, we were able to assign functional annotation to about 70% of the sequences. ProtoBee is available at http://www.protobee.cs.huji.ac.il.

Animals↗

Improving gene annotation using peptide mass spectrometry.

Annotation of protein-coding genes is a key goal of genome sequencing projects. In spite of tremendous recent advances in computational gene finding, comprehensive annotation remains a challenge. Peptide mass spectrometry is a powerful tool for researching the dynamic proteome and suggests an attractive approach to discover and validate protein-coding genes. We present algorithms to construct and efficiently search spectra against a genomic database, with no prior knowledge of encoded proteins. By searching a corpus of 18.5 million tandem mass spectra (MS/MS) from human proteomic samples, we validate 39,000 exons and 11,000 introns at the level of translation. We present translation-level evidence for novel or extended exons in 16 genes, confirm translation of 224 hypothetical proteins, and discover or confirm over 40 alternative splicing events. Polymorphisms are efficiently encoded in our database, allowing us to observe variant alleles for 308 coding SNPs. Finally, we demonstrate the use of mass spectrometry to improve automated gene prediction, adding 800 correct exons to our predictions using a simple rescoring strategy. Our results demonstrate that proteomic profiling should play a role in any genome sequencing project.

Algorithms↗