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At least 19 recordsLinked to original sources
PubMed2001

Intrinsic errors in genome annotation.

Genome sequencing is usually followed by routine annotation of protein function based on the assumption that similar sequences will have similar functions. Here, we introduce a simple calculation to estimate the magnitude of any possible annotation errors. We counted the number of discrepancies in the annotation of well-established sets of similar proteins and extrapolated these values to the pairs of similar sequences used for the annotation of different microbial genomes. We conclude that the number of potential errors in the prediction of detailed functions is higher than is usually believed.

Binding Sites↗
PubMed2005

The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes.

The release of the 1000th complete microbial genome will occur in the next two to three years. In anticipation of this milestone, the Fellowship for Interpretation of Genomes (FIG) launched the Project to Annotate 1000 Genomes. The project is built around the principle that the key to improved accuracy in high-throughput annotation technology is to have experts annotate single subsystems over the complete collection of genomes, rather than having an annotation expert attempt to annotate all of the genes in a single genome. Using the subsystems approach, all of the genes implementing the subsystem are analyzed by an expert in that subsystem. An annotation environment was created where populated subsystems are curated and projected to new genomes. A portable notion of a populated subsystem was defined, and tools developed for exchanging and curating these objects. Tools were also developed to resolve conflicts between populated subsystems. The SEED is the first annotation environment that supports this model of annotation. Here, we describe the subsystem approach, and offer the first release of our growing library of populated subsystems. The initial release of data includes 180 177 distinct proteins with 2133 distinct functional roles. This data comes from 173 subsystems and 383 different organisms.

Acyl Coenzyme A↗
PubMed2004

Intraspecies sequence comparisons for annotating genomes.

Analysis of sequence variation among members of a single species offers a potential approach to identify functional DNA elements responsible for biological features unique to that species. Due to its high rate of allelic polymorphism and ease of genetic manipulability, we chose the sea squirt, Ciona intestinalis, to explore intraspecies sequence comparisons for genome annotation. A large number of C. intestinalis specimens were collected from four continents, and a set of genomic intervals were amplified, resequenced, and analyzed to determine the mutation rates at each nucleotide in the sequence. We found that regions with low mutation rates efficiently demarcated functionally constrained sequences: these include a set of noncoding elements, which we showed in C. intestinalis transgenic assays to act as tissue-specific enhancers, as well as the location of coding sequences. This illustrates that comparisons of multiple members of a species can be used for genome annotation, suggesting a path for the annotation of the sequenced genomes of organisms occupying uncharacterized phylogenetic branches of the animal kingdom. It also raises the possibility that the resequencing of a large number of Homo sapiens individuals might be used to annotate the human genome and identify sequences defining traits unique to our species.

Animals↗
PubMed2003

GenDB--an open source genome annotation system for prokaryote genomes.

The flood of sequence data resulting from the large number of current genome projects has increased the need for a flexible, open source genome annotation system, which so far has not existed. To account for the individual needs of different projects, such a system should be modular and easily extensible. We present a genome annotation system for prokaryote genomes, which is well tested and readily adaptable to different tasks. The modular system was developed using an object-oriented approach, and it relies on a relational database backend. Using a well defined application programmers interface (API), the system can be linked easily to other systems. GenDB supports manual as well as automatic annotation strategies. The software currently is in use in more than a dozen microbial genome annotation projects. In addition to its use as a production genome annotation system, it can be employed as a flexible framework for the large-scale evaluation of different annotation strategies. The system is open source.

Amino Acid Sequence↗
PubMed2006

Genepi: a blackboard framework for genome annotation.

BACKGROUND: Genome annotation can be viewed as an incremental, cooperative, data-driven, knowledge-based process that involves multiple methods to predict gene locations and structures. This process might have to be executed more than once and might be subjected to several revisions as the biological (new data) or methodological (new methods) knowledge evolves. In this context, although a lot of annotation platforms already exist, there is still a strong need for computer systems which take in charge, not only the primary annotation, but also the update and advance of the associated knowledge. In this paper, we propose to adopt a blackboard architecture for designing such a system RESULTS: We have implemented a blackboard framework (called Genepi) for developing automatic annotation systems. The system is not bound to any specific annotation strategy. Instead, the user will specify a blackboard structure in a configuration file and the system will instantiate and run this particular annotation strategy. The characteristics of this framework are presented and discussed. Specific adaptations to the classical blackboard architecture have been required, such as the description of the activation patterns of the knowledge sources by using an extended set of Allen's temporal relations. Although the system is robust enough to be used on real-size applications, it is of primary use to bioinformatics researchers who want to experiment with blackboard architectures. CONCLUSION: In the context of genome annotation, blackboards have several interesting features related to the way methodological and biological knowledge can be updated. They can readily handle the cooperative (several methods are implied) and opportunistic (the flow of execution depends on the state of our knowledge) aspects of the annotation process.

Algorithms↗
PubMed2004

5' Long serial analysis of gene expression (LongSAGE) and 3' LongSAGE for transcriptome characterization and genome annotation.

Complete genome annotation relies on precise identification of transcription units bounded by a transcription initiation site (TIS) and a polyadenylation site (PAS). To facilitate this process, we developed a set of two complementary methods, 5' Long serial analysis of gene expression (LS) and 3'LS. These analyses are based on the original SAGE and LS methods coupled with full-length cDNA cloning, and enable the high-throughput extraction of the first and the last 20 bp of each transcript. We demonstrate that the mapping of 5'LS and 3'LS tags to the genome allows the localization of TIS and PAS. By using 537 tag pairs mapping to the region of known genes, we confirmed that >90% of the tag pairs appropriately assigned to the first and last exons. Moreover, by using tag sequences as primers for RT-PCRs, we were able to recover putative full-length transcripts in 81% of the attempts. This large-scale generation of transcript terminal tags is at least 20-40 times more efficient than full-length cDNA cloning and sequencing in the identification of complete transcription units. The apparent precision and deep coverage makes 5'LS and 3'LS an advanced approach for genome annotation through whole-transcriptome characterization.

Animals↗
PubMed2006

Expressed peptide tags: an additional layer of data for genome annotation.

While genome sequencing is becoming ever more routine, genome annotation remains a challenging process. Identification of the coding sequences within the genomic milieu presents a tremendous challenge, especially for eukaryotes with their complex gene architectures. Here, we present a method to assist the annotation process through the use of proteomic data and bioinformatics. Mass spectra of digested protein preparations of the organism of interest were acquired and searched against a protein database created by a six-frame translation of the genome. The identified peptides were mapped back to the genome, compared to the current annotation, and then categorized as supporting or extending the current genome annotation. We named the classified peptides Expressed Peptide Tags (EPTs). The well-annotated bacterium Rhodopseudomonas palustris was used as a control for the method and showed a high degree of correlation between EPT mapping and the current annotation, with 86% of the EPTs confirming existing gene calls and less than 1% of the EPTs expanding on the current annotation. The eukaryotic plant pathogens Phytophthora ramorum and Phytophthora sojae, whose genomes have been recently sequenced and are much less well-annotated, were also subjected to this method. A series of algorithmic steps were taken to increase the confidence of EPT identification for these organisms, including generation of smaller subdatabases to be searched against, and definition of EPT criteria that accommodates the more complex eukaryotic gene architecture. As expected, the analysis of the Phytophthora species showed less correlation between EPT mapping and their current annotation. While approximately 76% of Phytophthora EPTs supported the current annotation, a portion of them (7.7% and 12.9% for P. ramorum and P. sojae, respectively) suggested modification to current gene calls or identified novel genes that were missed by the current genome annotation of these organisms.

Amino Acid Sequence↗
PubMed2006

Genome Annotation Transfer Utility (GATU): rapid annotation of viral genomes using a closely related reference genome.

BACKGROUND: Since DNA sequencing has become easier and cheaper, an increasing number of closely related viral genomes have been sequenced. However, many of these have been deposited in GenBank without annotations, severely limiting their value to researchers. While maintaining comprehensive genomic databases for a set of virus families at the Viral Bioinformatics Resource Center http://www.biovirus.org and Viral Bioinformatics - Canada http://www.virology.ca, we found that researchers were unnecessarily spending time annotating viral genomes that were close relatives of already annotated viruses. We have therefore designed and implemented a novel tool, Genome Annotation Transfer Utility (GATU), to transfer annotations from a previously annotated reference genome to a new target genome, thereby greatly reducing this laborious task. RESULTS: GATU transfers annotations from a reference genome to a closely related target genome, while still giving the user final control over which annotations should be included. GATU also detects open reading frames present in the target but not the reference genome and provides the user with a variety of bioinformatics tools to quickly determine if these ORFs should also be included in the annotation. After this process is complete, GATU saves the newly annotated genome as a GenBank, EMBL or XML-format file. The software is coded in Java and runs on a variety of computer platforms. Its user-friendly Graphical User Interface is specifically designed for users trained in the biological sciences. CONCLUSION: GATU greatly simplifies the initial stages of genome annotation by using a closely related genome as a reference. It is not intended to be a gene prediction tool or a "complete" annotation system, but we have found that it significantly reduces the time required for annotation of genes and mature peptides as well as helping to standardize gene names between related organisms by transferring reference genome annotations to the target genome. The program is freely available under the General Public License and can be accessed along with documentation and tutorial from http://www.virology.ca/gatu.

Amino Acid Sequence↗
PubMed2007

Plant Gene and Alternatively Spliced Variant Annotator. A plant genome annotation pipeline for rice gene and alternatively spliced variant identification with cross-species expressed sequence tag conservation from seven plant species.

The completion of the rice (Oryza sativa) genome draft has brought unprecedented opportunities for genomic studies of the world's most important food crop. Previous rice gene annotations have relied mainly on ab initio methods, which usually yield a high rate of false-positive predictions and give only limited information regarding alternative splicing in rice genes. Comparative approaches based on expressed sequence tags (ESTs) can compensate for the drawbacks of ab initio methods because they can simultaneously identify experimental data-supported genes and alternatively spliced transcripts. Furthermore, cross-species EST information can be used to not only offset the insufficiency of same-species ESTs but also derive evolutionary implications. In this study, we used ESTs from seven plant species, rice, wheat (Triticum aestivum), maize (Zea mays), barley (Hordeum vulgare), sorghum (Sorghum bicolor), soybean (Glycine max), and Arabidopsis (Arabidopsis thaliana), to annotate the rice genome. We developed a plant genome annotation pipeline, Plant Gene and Alternatively Spliced Variant Annotator (PGAA). Using this approach, we identified 852 genes (931 isoforms) not annotated in other widely used databases (i.e. the Institute for Genomic Research, National Center for Biotechnology Information, and Rice Annotation Project) and found 87% of them supported by both rice and nonrice EST evidence. PGAA also identified more than 44,000 alternatively spliced events, of which approximately 20% are not observed in the other three annotations. These novel annotations represent rich opportunities for rice genome research, because the functions of most of our annotated genes are currently unknown. Also, in the PGAA annotation, the isoforms with non-rice-EST-supported exons are significantly enriched in transporter activity but significantly underrepresented in transcription regulator activity. We have also identified potential lineage-specific and conserved isoforms, which are important markers in evolutionary studies. The data and the Web-based interface, RiceViewer, are available for public access at http://RiceViewer.genomics.sinica.edu.tw/.

Base Sequence↗
PubMed2002

Genquire: genome annotation browser/editor.

UNLABELLED: We present a software package, Genquire, that allows visualization, querying, hand editing, and de novo markup of complete or partially annotated genomes. The system is written in Perl/Tk and uses, where possible, existing BioPerl data models and methods for representation and manipulation of the sequence and annotation objects. An adaptor API is provided to allow Genquire to display a wide range of databases and flat files, and a plugins API provides an interface to other sequence analysis software. AVAILABILITY: Genquire v3.03 is open-source software. The code is available for download and/or contribution at http://www.bioinformatics.org/Genquire

Chromosome Mapping↗
PubMed2003

Assessing the Drosophila melanogaster and Anopheles gambiae genome annotations using genome-wide sequence comparisons.

We performed genome-wide sequence comparisons at the protein coding level between the genome sequences of Drosophila melanogaster and Anopheles gambiae. Such comparisons detect evolutionarily conserved regions (ecores) that can be used for a qualitative and quantitative evaluation of the available annotations of both genomes. They also provide novel candidate features for annotation. The percentage of ecores mapping outside annotations in the A. gambiae genome is about fourfold higher than in D. melanogaster. The A. gambiae genome assembly also contains a high proportion of duplicated ecores, possibly resulting from artefactual sequence duplications in the genome assembly. The occurrence of 4063 ecores in the D. melanogaster genome outside annotations suggests that some genes are not yet or only partially annotated. The present work illustrates the power of comparative genomics approaches towards an exhaustive and accurate establishment of gene models and gene catalogues in insect genomes.

Animals↗
PubMed2003

The TIGR rice genome annotation resource: annotating the rice genome and creating resources for plant biologists.

Rice is not only a major food staple for the world's population but it also is a model species for a major group of flowering plants, the monocotyledonous plants. Draft genomic sequence of two subspecies of rice, Oryza sativa spp. japonica and indica ssp. are publicly available. To provide the community with a resource to data-mine the rice genome, we have constructed an annotation resource for rice (http://www.tigr.org/tdb/e2k1/osa1/). In this resource, we have annotated the rice genome for gene content, identified motifs/domains within the predicted genes, constructed a rice repeat database, identified related sequences in other plant species, and identified syntenic sequences between rice and maize. All of the data is available through web-based interfaces, FTP downloads, and a Distributed Annotation System.

Chromosomes, Artificial↗
PubMed2004

Genome Properties: a system for the investigation of prokaryotic genetic content for microbiology, genome annotation and comparative genomics.

MOTIVATION: The presence or absence of metabolic pathways and structures provide a context that makes protein annotation far more reliable. Compiling such information across microbial genomes improves the functional classification of proteins and provides a valuable resource for comparative genomics. RESULTS: We have created a Genome Properties system to present key aspects of prokaryotic biology using standardized computational methods and controlled vocabularies. Properties reflect gene content, phenotype, phylogeny and computational analyses. The results of searches using hidden Markov models allow many properties to be deduced automatically, especially for families of proteins (equivalogs) conserved in function since their last common ancestor. Additional properties are derived from curation, published reports and other forms of evidence. Genome Properties system was applied to 156 complete prokaryotic genomes, and is easily mined to find differences between species, correlations between metabolic features and families of uncharacterized proteins, or relationships among properties. AVAILABILITY: Genome Properties can be found at http://www.tigr.org/Genome_Properties SUPPLEMENTARY INFORMATION: http://www.tigr.org/tigr-scripts/CMR2/genome_properties_references.spl.

Chromosome Mapping↗
PubMed2004

Improving genome annotations using phylogenetic profile anomaly detection.

MOTIVATION: A promising strategy for refining genome annotations is to detect features that conflict with known functional or evolutionary relationships between groups of genes. Previous work in this area has been focused on investigating the absence of 'housekeeping' genes or components of well-studied pathways. We have sought to develop a method for improving new annotations that can automatically synthesize and use the information available in a database of other annotated genomes. RESULTS: We show that a probabilistic model of phylogenetic profiles, trained from a database of curated genome annotations, can be used to reliably detect errors in new annotations. We use our method to identify 22 genes that were missed in previously published annotations of prokaryotic genomes. AVAILABILITY: The method was evaluated using MATLAB and open source software referenced in this work. Scripts and datasets are available from the authors upon request. CONTACT: tarjei@broad.mit.edu.

Algorithms↗
PubMed2003

[MGAP-A microbe genome annotation platform].

A Microbe Genome Annotation Platform (MGAP) was developed and applied to the cynobacterium PCC7002 genome annotation. Various bioinformatics software tools from sequence analysis to gene identification and function prediction were implemented in MGAP. Protein sequence databases SWISSPROT and PDBseq, protein information resource InterPro and COG were also integrated in the platform. The web interface of MGAP has the functionality to display a circular map of gene distribution and GC contents throughout the genome. Detailed information such as the DNA and protein sequence, the location of genes on chromosomes can be viewed by clicking the corresponding object within the map. MGAP is based on a PC/Linux system affordable for small biological laboratories and has the advantage of using free software tools including MySQL, Apache and Perl.

Cyanobacteria↗
PubMed2026

Segzoo: a turnkey system that summarizes genome annotations.

MOTIVATION: Segmentation and automated genome annotation (SAGA) techniques, such as Segway and ChromHMM, assign labels to every part of the genome, identifying similar patterns across multiple genomic input signals. Inferring biological meaning in these patterns remains challenging. Doing so requires a time-consuming process of manually downloading reference data, running multiple analysis methods, and interpreting many individual results. RESULTS: To simplify these tasks, we developed the turnkey system Segzoo. As input, Segzoo only requires a genome annotation file in browser extensible data (BED) format. It automatically downloads the rest of the data required for comparisons. Segzoo performs analyses using these data and summarizes results in a single visualization. AVAILABILITY AND IMPLEMENTATION: The source code for Python ≥ 3.7 on Linux is freely available for download at https://github.com/hoffmangroup/segzoo under the GNU General Public License (GPL) version 2. Segzoo is also available in the Bioconda package segzoo: https://anaconda.org/bioconda/segzoo. We have deposited in Zenodo the version of the Segzoo source which produced the results in this article (https://doi.org/10.5281/zenodo.10988775), other code and data used to produce the results (https://doi.org/10.5281/zenodo.10477083), and the results (https://doi.org/10.5281/zenodo.10477106).

Software↗
PubMed2006

Systems approach to refining genome annotation.

Genome-scale models of Escherichia coli K-12 MG1655 metabolism have been able to predict growth phenotypes in most, but not all, defined growth environments. Here we introduce the use of an optimization-based algorithm that predicts the missing reactions that are required to reconcile computation and experiment when they disagree. The computer-generated hypotheses for missing reactions were verified experimentally in five cases, leading to the functional assignment of eight ORFs (yjjLMN, yeaTU, dctA, idnT, and putP) with two new enzymatic activities and four transport functions. This study thus demonstrates the use of systems analysis to discover metabolic and transport functions and their genetic basis by a combination of experimental and computational approaches.

Biological Transport↗
PubMed2006

MaGe: a microbial genome annotation system supported by synteny results.

Magnifying Genomes (MaGe) is a microbial genome annotation system based on a relational database containing information on bacterial genomes, as well as a web interface to achieve genome annotation projects. Our system allows one to initiate the annotation of a genome at the early stage of the finishing phase. MaGe's main features are (i) integration of annotation data from bacterial genomes enhanced by a gene coding re-annotation process using accurate gene models, (ii) integration of results obtained with a wide range of bioinformatics methods, among which exploration of gene context by searching for conserved synteny and reconstruction of metabolic pathways, (iii) an advanced web interface allowing multiple users to refine the automatic assignment of gene product functions. MaGe is also linked to numerous well-known biological databases and systems. Our system has been thoroughly tested during the annotation of complete bacterial genomes (Acinetobacter baylyi ADP1, Pseudoalteromonas haloplanktis, Frankia alni) and is currently used in the context of several new microbial genome annotation projects. In addition, MaGe allows for annotation curation and exploration of already published genomes from various genera (e.g. Yersinia, Bacillus and Neisseria). MaGe can be accessed at http://www.genoscope.cns.fr/agc/mage.

Computational Biology↗