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RiceGAAS: an automated annotation system and database for rice genome sequence.

An extensive effort of the International Rice Genome Sequencing Project (IRGSP) has resulted in rapid accumulation of genome sequence, and >137 Mb has already been made available to the public domain as of August 2001. This requires a high-throughput annotation scheme to extract biologically useful and timely information from the sequence data on a regular basis. A new automated annotation system and database called Rice Genome Automated Annotation System (RiceGAAS) has been developed to execute a reliable and up-to-date analysis of the genome sequence as well as to store and retrieve the results of annotation. The system has the following functional features: (i) collection of rice genome sequences from GenBank; (ii) execution of gene prediction and homology search programs; (iii) integration of results from various analyses and automatic interpretation of coding regions; (iv) re-execution of analysis, integration and automatic interpretation with the latest entries in reference databases; (v) integrated visualization of the stored data using web-based graphical view. RiceGAAS also has a data submission mechanism that allows public users to perform fully automated annotation of their own sequences. The system can be accessed at http://RiceGAAS.dna.affrc.go.jp/.

Automation↗

ParameciumDB: a community resource that integrates the Paramecium tetraurelia genome sequence with genetic data.

ParameciumDB (http://paramecium.cgm.cnrs-gif.fr) is a new model organism database associated with the genome sequencing project of the unicellular eukaryote Paramecium tetraurelia. Built with the core components of the Generic Model Organism Database (GMOD) project, ParameciumDB currently contains the genome sequence and annotations, linked to available genetic data including the Gif Paramecium stock collection. It is thus possible to navigate between sequences and stocks via the genes and alleles. Phenotypes, of mutant strains and of knockdowns obtained by RNA interference, are captured using controlled vocabularies according to the Entity-Attribute-Value model. ParameciumDB currently supports browsing of phenotypes, alleles and stocks as well as querying of sequence features (genes, UniProt matches, InterPro domains, Gene Ontology terms) and of genetic data (phenotypes, stocks, RNA interference experiments). Forms allow submission of RNA interference data and some bioinformatics services are available. Future ParameciumDB development plans include coordination of human curation of the near 40 000 gene models by members of the research community.

Alleles↗

LocustDB: a relational database for the transcriptome and biology of the migratory locust (Locusta migratoria).

BACKGROUND: The migratory locust (Locusta migratoria) is an orthopteran pest and a representative member of hemimetabolous insects for biological studies. Its transcriptomic data provide invaluable information for molecular entomology and pave a way for the comparative research of other medically, agronomically, and ecologically relevant insects. We developed the first transcriptomic database of the locust (LocustDB), building necessary infrastructures to integrate, organize, and retrieve data that are either currently available or to be acquired in the future. DESCRIPTION: LocustDB currently hosts 45,474 high-quality EST sequences from the locust, which were assembled into 12,161 unigenes. It, through user-friendly web interfaces, allows investigators to freely access sequence data, including homologous/orthologous sequences, functional annotations, and pathway analysis, based on conserved orthologous groups (COG), gene ontology (GO), protein domain (InterPro), and functional pathways (KEGG). It also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, including the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. The website address of LocustDB is http://locustdb.genomics.org.cn/. CONCLUSION: LocustDB starts with the first transcriptome information for an orthopteran and hemimetabolous insect and will be extended to provide a framework for incorporating in-coming genomic data of relevant insect groups and a workbench for cross-species comparative studies.

Animals↗

Efficient evidence-based genome annotation with EviAnn.

For many years, machine learning-based ab initio gene finding approaches have been central components of eukaryotic genome annotation pipelines, and they remain so today. The reliance on these approaches was originally sustained by the high cost and low availability of gene expression data, a primary source of evidence for gene annotation along with protein homology. However, innovations in modern sequencing technologies have revolutionized the acquisition of gene expression data, allowing scientists to rely more heavily on this class of evidence. In addition, proteins found in a multitude of well-annotated genomes represent another invaluable resource for gene annotation. Existing annotation packages often underutilize these data sources, which prompted us to develop EviAnn (Evidence-based Annotator), a novel evidence-based eukaryotic gene annotation system. EviAnn takes a strongly data-driven approach, building the exon-intron structure of genes from transcript alignments or protein-sequence homology rather than from purely ab initio gene finding techniques. We show that when provided with the same input data, EviAnn consistently outperforms current state-of-the-art packages including BRAKER3, MAKER2, and FINDER, while utilizing considerably less computer time. Annotation of a mammalian genome can be completed in less than an hour on a single multi-core server. EviAnn is freely available under an open-source license from https://github.com/alekseyzimin/EviAnn_release and from Bioconda as "eviann".

Journal Article↗

Reconstructed protein arrays from 3D HPLC/tandem mass spectrometry and 2D gels: complementary approaches to Porphyromonas gingivalis protein expression.

We compare typical qualitative protein identification data from two-dimensional (2D) polyacrylamide gel electrophoresis and reconstructed protein arrays, in the context of measuring protein expression by the Gram-negative periodontal pathogen Porphyromonas gingivalis. The arrays were assembled computationally from genome annotations and tandem mass spectrometry data from an off-line HPLC fractionation combined with 2D capillary HPLC analysis of whole proteome enzymatic digests. The 2D separation was carried out with a standard binary gradient HPLC system, modified only slightly with readily available components. Compared to 2D gels, the number of annotated open reading frames identified using the 3D HPLC approach was typically larger by at least a factor of 30. However, the newer technology is currently limited in its ability to reflect the many protein variants derived from posttranscriptional and posttranslational processing.

Bacterial Proteins↗

Genome information resources - developments at Ensembl.

Genome information resources such as Ensembl manage and present DNA sequence and annotation arising from genome projects. Recent developments in the Ensembl system include access to inter-species comparisons at both the genomic and protein sequence levels and improvements to the display of polymorphism data. Users can now display their own data in the context of other annotation. In addition, a fast and flexible data retrieval system, EnsMart, has been developed.

Animals↗

Transcriptome analysis for the chicken based on 19,626 finished cDNA sequences and 485,337 expressed sequence tags.

We present an analysis of the chicken (Gallus gallus) transcriptome based on the full insert sequences for 19,626 cDNAs, combined with 485,337 EST sequences. The cDNA data set has been functionally annotated and describes a minimum of 11,929 chicken coding genes, including the sequence for 2260 full-length cDNAs together with a collection of noncoding (nc) cDNAs that have been stringently filtered to remove untranslated regions of coding mRNAs. The combined collection of cDNAs and ESTs describe 62,546 clustered transcripts and provide transcriptional evidence for a total of 18,989 chicken genes, including 88% of the annotated Ensembl gene set. Analysis of the ncRNAs reveals a set that is highly conserved in chickens and mammals, including sequences for 14 pri-miRNAs encoding 23 different miRNAs. The data sets described here provide a transcriptome toolkit linked to physical clones for bioinformaticians and experimental biologists who wish to use chicken systems as a low-cost, accessible alternative to mammals for the analysis of vertebrate development, immunology, and cell biology.

Animals↗

The Swiss-Prot protein knowledgebase and ExPASy: providing the plant community with high quality proteomic data and tools.

The Swiss-Prot protein knowledgebase provides manually annotated entries for all species, but concentrates on the annotation of entries from model organisms to ensure the presence of high quality annotation of representative members of all protein families. A specific Plant Protein Annotation Program (PPAP) was started to cope with the increasing amount of data produced by the complete sequencing of plant genomes. Its main goal is the annotation of proteins from the model plant organism Arabidopsis thaliana. In addition to bibliographic references, experimental results, computed features and sometimes even contradictory conclusions, direct links to specialized databases connect amino acid sequences with the current knowledge in plant sciences. As protein families and groups of plant-specific proteins are regularly reviewed to keep up with current scientific findings, we hope that the wealth of information of Arabidopsis origin accumulated in our knowledgebase, and the numerous software tools provided on the Expert Protein Analysis System (ExPASy) web site might help to identify and reveal the function of proteins originating from other plants. Recently, a single, centralized, authoritative resource for protein sequences and functional information, UniProt, was created by joining the information contained in Swiss-Prot, Translation of the EMBL nucleotide sequence (TrEMBL), and the Protein Information Resource-Protein Sequence Database (PIR-PSD). A rising problem is that an increasing number of nucleotide sequences are not being submitted to the public databases, and thus the proteins inferred from such sequences will have difficulties finding their way to the Swiss-Prot or TrEMBL databases.

Arabidopsis↗

Re-annotating the Mycoplasma pneumoniae genome sequence: adding value, function and reading frames.

Four years after the original sequence submission, we have re-annotated the genome of Mycoplasma pneumoniae to incorporate novel data. The total number of ORFss has been increased from 677 to 688 (10 new proteins were predicted in intergenic regions, two further were newly identified by mass spectrometry and one protein ORF was dismissed) and the number of RNAs from 39 to 42 genes. For 19 of the now 35 tRNAs and for six other functional RNAs the exact genome positions were re-annotated and two new tRNA(Leu) and a small 200 nt RNA were identified. Sixteen protein reading frames were extended and eight shortened. For each ORF a consistent annotation vocabulary has been introduced. Annotation reasoning, annotation categories and comparisons to other published data on M.pneumoniae functional assignments are given. Experimental evidence includes 2-dimensional gel electrophoresis in combination with mass spectrometry as well as gene expression data from this study. Compared to the original annotation, we increased the number of proteins with predicted functional features from 349 to 458. The increase includes 36 new predictions and 73 protein assignments confirmed by the published literature. Furthermore, there are 23 reductions and 30 additions with respect to the previous annotation. mRNA expression data support transcription of 184 of the functionally unassigned reading frames.

Amino Acid Sequence↗

UTRdb and UTRsite: a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs.

The 5' and 3' untranslated regions of eukaryotic mRNAs play crucial roles in the post-transcriptional regulation of gene expression through the modulation of nucleo-cytoplasmic mRNA transport, translation efficiency, subcellular localization and message stability. UTRdb is a curated database of 5' and 3' untranslated sequences of eukaryotic mRNAs, derived from several sources of primary data. Experimentally validated functional motifs are annotated (and also collated as the UTRsite database) and cross-links to genomic and protein data are provided. The integration of UTRdb with genomic and protein data has allowed the implementation of a powerful retrieval resource for the selection and extraction of UTR subsets based on their genomic coordinates and/or features of the protein encoded by the relevant mRNA (e.g. GO term, PFAM domain, etc.). All internet resources implemented for retrieval and functional analysis of 5' and 3' untranslated regions of eukaryotic mRNAs are accessible at http://www.ba.itb.cnr.it/UTR/.

3' Untranslated Regions↗

Automating tissue bank annotation from pathology reports - comparison to a gold standard expert annotation set.

Surgical pathology specimens are an important resource for medical research, particularly for cancer research. Although research studies would benefit from information derived from the surgical pathology reports, access to this information is limited by use of unstructured free-text in the reports. We have previously described a pipeline-based system for automated annotation of surgical pathology reports with UMLS concepts, which has been used to code over 450,000 surgical pathology reports at our institution. In addition to coding UMLS terms, it annotates values of several key variables, such as TNM stage and cancer grade. The object of this study was to evaluate the potential and limitations of automated extraction of these variables, by measuring the performance of the system against a true gold standard - manually encoded data entered by expert tissue annotators. We categorized and analyzed errors to determine the potential and limitations of information extraction from pathology reports for the purpose of automated biospecimen annotation.

Abstracting and Indexing↗

Functional annotation and network reconstruction through cross-platform integration of microarray data.

The rapid accumulation of microarray data translates into a need for methods to effectively integrate data generated with different platforms. Here we introduce an approach, 2(nd)-order expression analysis, that addresses this challenge by first extracting expression patterns as meta-information from each data set (1(st)-order expression analysis) and then analyzing them across multiple data sets. Using yeast as a model system, we demonstrate two distinct advantages of our approach: we can identify genes of the same function yet without coexpression patterns and we can elucidate the cooperativities between transcription factors for regulatory network reconstruction by overcoming a key obstacle, namely the quantification of activities of transcription factors. Experiments reported in the literature and performed in our lab support a significant number of our predictions.

Algorithms↗

Semantic annotation for concept-based cross-language medical information retrieval.

We present a framework for concept-based cross-language information retrieval in the medical domain, which is under development in the MUCHMORE project. Our approach is based on using the Unified Medical Language System (UMLS) as the primary source of semantic data. Documents and queries are annotated with multiple layers of linguistic information. Linguistic processing includes part-of-speech tagging, morphological analysis, phrase recognition and the identification of medical terms and semantic relations between them. The paper describes experiments in monolingual and cross-language document retrieval, performed on a corpus of medical abstracts. Results show that linguistic processing, especially lemmatization and compound analysis for German, is a crucial step in achieving a good baseline performance. On the other hand, they show that semantic information, specifically the combined use of concepts and relations, increases the performance in monolingual and cross-language retrieval.

Humans↗

LINUCS: linear notation for unique description of carbohydrate sequences.

The use of proteomics databases has become indispensable for daily work of molecular biologists, but this situation has not yet been achieved for carbohydrate applications. One obvious reason is that existing data collections are only rarely annotated and no cross-linking to other resources exists. The existence of a generally accepted linear, canonical description for carbohydrates which can be readily processed by computers will enable efficient automatic cross-linking of distributed carbohydrate data collections by serving as a unique and unambiguous database access key. Various possibilities to derive a canonical notation are discussed. They can be divided into attempts that require structure description alone and alternatives that profit from the fact that a preferred graph direction (non-reducing to reducing end) exists within the structure. To open a fruitful discussion among glycoscientists a possible solution is presented where the reducing monosaccharide unit is selected as graph root and linkage information is used to define the priority of the various branches. A Web interface (http://www.dkfz.de/spec/linucs/) has been created that directly converts the commonly used extended representation of complex carbohydrates into the preferred canonical description or into its inverted form.

Algorithms↗

EnsMart: a generic system for fast and flexible access to biological data.

The EnsMart system (www.ensembl.org/EnsMart) provides a generic data warehousing solution for fast and flexible querying of large biological data sets and integration with third-party data and tools. The system consists of a query-optimized database and interactive, user-friendly interfaces. EnsMart has been applied to Ensembl, where it extends its genomic browser capabilities, facilitating rapid retrieval of customized data sets. A wide variety of complex queries, on various types of annotations, for numerous species are supported. These can be applied to many research problems, ranging from SNP selection for candidate gene screening, through cross-species evolutionary comparisons, to microarray annotation. Users can group and refine biological data according to many criteria, including cross-species analyses, disease links, sequence variations, and expression patterns. Both tabulated list data and biological sequence output can be generated dynamically, in HTML, text, Microsoft Excel, and compressed formats. A wide range of sequence types, such as cDNA, peptides, coding regions, UTRs, and exons, with additional upstream and downstream regions, can be retrieved. The EnsMart database can be accessed via a public Web site, or through a Java application suite. Both implementations and the database are freely available for local installation, and can be extended or adapted to 'non-Ensembl' data sets.

Animals↗

Automated clinical annotation of tissue bank specimens.

Modern, molecular bio-medicine is driving a growing demand for extensively annotated tissue bank specimens. With careful clinical, pathologic and outcomes annotation, samples can be better matched to the research question at hand and experimental results better understood and verified. However, the difficulty and expense of detailed specimen annotation is well beyond the capability of most banks and has made access to well documented tissue a major limitation in medical re-search. In this context, we have implemented automated annotation of banked tissue by integrating data from three clinical systems--the cancer registry, the pathology LIS and the tissue bank inventory system--through a classical data warehouse environment. The project required modification of clinical systems, development of methods to identify patients between and map data elements across systems and the creation of de-identified data in data marts for use by researchers. The result has been much more extensive and accurate initial tissue annotation with less effort in the tissue bank, as well as dynamic ongoing annotation as the cancer registry follows patients over time.

Clinical Laboratory Information Systems↗

A 7872 cDNA microarray and its use in bovine functional genomics.

The strategy used to create and annotate a 7872 cDNA microarray from cattle placenta and spleen cDNA sequences is described. This microarray contains approximately 6300 unique genes, as determined by BLASTN and TBLASTX similarity search against the human and mouse UniGene and draft human genome sequence databases (build 34). Sequences on the array were annotated with gene ontology (GO) terms, thereby facilitating data analysis and interpretation. A total of 3244 genes were annotated with GO terms. The array is rich in sequences encoding transcription factors, signal transducers and cell cycle regulators. Current research being conducted with this array is described, and an overview of planned improvements in our microarray platform for cattle functional genomics is presented.

Animals↗

Generation and analysis of 280,000 human expressed sequence tags.

We report the generation of 319,311 single-pass sequencing reactions (known as expressed sequence tags, or ESTs) obtained from the 5' and 3' ends of 194,031 human cDNA clones. Our goal has been to obtain tag sequences from many different genes and to deposit these in the publicly accessible Data Base for Expressed Sequence Tags. Highly efficient automatic screening of the data allows deposition of the annotated sequences without delay. Sequences have been generated from 26 oligo(dT) primed directionally cloned libraries, of which 18 were normalized. The libraries were constructed using mRNA isolated from 17 different tissues representing three developmental states. Comparisons of a subset of our data with nonredundant human mRNA and protein data bases show that the ESTs represent many known sequences and contain many that are novel. Analysis of protein families using Hidden Markov Models confirms this observation and supports the contention that although normalization reduces significantly the relative abundance of redundant cDNA clones, it does not result in the complete removal of members of gene families.

Adult↗