WorldWideScience

Sample records for gene structure annotation

  1. Automated Eukaryotic Gene Structure Annotation Using EVidenceModeler and the Program to Assemble Spliced Alignments

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    Haas, B J; Salzberg, S L; Zhu, W; Pertea, M; Allen, J E; Orvis, J; White, O; Buell, C R; Wortman, J R

    2007-12-10

    EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation.

  2. ParsEval: parallel comparison and analysis of gene structure annotations

    Directory of Open Access Journals (Sweden)

    Standage Daniel S

    2012-08-01

    Full Text Available Abstract Background Accurate gene structure annotation is a fundamental but somewhat elusive goal of genome projects, as witnessed by the fact that (model genomes typically undergo several cycles of re-annotation. In many cases, it is not only different versions of annotations that need to be compared but also different sources of annotation of the same genome, derived from distinct gene prediction workflows. Such comparisons are of interest to annotation providers, prediction software developers, and end-users, who all need to assess what is common and what is different among distinct annotation sources. We developed ParsEval, a software application for pairwise comparison of sets of gene structure annotations. ParsEval calculates several statistics that highlight the similarities and differences between the two sets of annotations provided. These statistics are presented in an aggregate summary report, with additional details provided as individual reports specific to non-overlapping, gene-model-centric genomic loci. Genome browser styled graphics embedded in these reports help visualize the genomic context of the annotations. Output from ParsEval is both easily read and parsed, enabling systematic identification of problematic gene models for subsequent focused analysis. Results ParsEval is capable of analyzing annotations for large eukaryotic genomes on typical desktop or laptop hardware. In comparison to existing methods, ParsEval exhibits a considerable performance improvement, both in terms of runtime and memory consumption. Reports from ParsEval can provide relevant biological insights into the gene structure annotations being compared. Conclusions Implemented in C, ParsEval provides the quickest and most feature-rich solution for genome annotation comparison to date. The source code is freely available (under an ISC license at http://parseval.sourceforge.net/.

  3. Comparative Annotation of Viral Genomes with Non-Conserved Gene Structure

    DEFF Research Database (Denmark)

    de Groot, Saskia; Mailund, Thomas; Hein, Jotun

    2007-01-01

    allows for coding in unidirectional nested and overlapping reading frames, to annotate two homologous aligned viral genomes. Our method does not insist on conserved gene structure between the two sequences, thus making it applicable for the pairwise comparison of more distantly related sequences. Results......: We apply our method to 15 pairwise alignments of six different HIV2 genomes. Given sufficient evolutionary distance between the two sequences, we achieve sensitivity of about 84% and specificity of about 97%. We additionally annotate three pairwise alignments of the more distantly related HIV1...... and HIV2, as well as of two different Hepatitis Viruses, attaining results of ~87% sensitivity and ~98.5% specificity. We subsequently incorporate prior knowledge by "knowing" the gene structure of one sequence and annotating the other conditional on it. Boosting accuracy close to perfect we demonstrate...

  4. Comparative Annotation of Viral Genomes with Non-Conserved Gene Structure

    DEFF Research Database (Denmark)

    de Groot, Saskia; Mailund, Thomas; Hein, Jotun

    2007-01-01

    Motivation: Detecting genes in viral genomes is a complex task. Due to the biological necessity of them being constrained in length, RNA viruses in particular tend to code in overlapping reading frames. Since one amino acid is encoded by a triplet of nucleic acids, up to three genes may be coded...... allows for coding in unidirectional nested and overlapping reading frames, to annotate two homologous aligned viral genomes. Our method does not insist on conserved gene structure between the two sequences, thus making it applicable for the pairwise comparison of more distantly related sequences. Results...... and HIV2, as well as of two different Hepatitis Viruses, attaining results of ~87% sensitivity and ~98.5% specificity. We subsequently incorporate prior knowledge by "knowing" the gene structure of one sequence and annotating the other conditional on it. Boosting accuracy close to perfect we demonstrate...

  5. Gene Ontology annotations and resources.

    Science.gov (United States)

    Blake, J A; Dolan, M; Drabkin, H; Hill, D P; Li, Ni; Sitnikov, D; Bridges, S; Burgess, S; Buza, T; McCarthy, F; Peddinti, D; Pillai, L; Carbon, S; Dietze, H; Ireland, A; Lewis, S E; Mungall, C J; Gaudet, P; Chrisholm, R L; Fey, P; Kibbe, W A; Basu, S; Siegele, D A; McIntosh, B K; Renfro, D P; Zweifel, A E; Hu, J C; Brown, N H; Tweedie, S; Alam-Faruque, Y; Apweiler, R; Auchinchloss, A; Axelsen, K; Bely, B; Blatter, M -C; Bonilla, C; Bouguerleret, L; Boutet, E; Breuza, L; Bridge, A; Chan, W M; Chavali, G; Coudert, E; Dimmer, E; Estreicher, A; Famiglietti, L; Feuermann, M; Gos, A; Gruaz-Gumowski, N; Hieta, R; Hinz, C; Hulo, C; Huntley, R; James, J; Jungo, F; Keller, G; Laiho, K; Legge, D; Lemercier, P; Lieberherr, D; Magrane, M; Martin, M J; Masson, P; Mutowo-Muellenet, P; O'Donovan, C; Pedruzzi, I; Pichler, K; Poggioli, D; Porras Millán, P; Poux, S; Rivoire, C; Roechert, B; Sawford, T; Schneider, M; Stutz, A; Sundaram, S; Tognolli, M; Xenarios, I; Foulgar, R; Lomax, J; Roncaglia, P; Khodiyar, V K; Lovering, R C; Talmud, P J; Chibucos, M; Giglio, M Gwinn; Chang, H -Y; Hunter, S; McAnulla, C; Mitchell, A; Sangrador, A; Stephan, R; Harris, M A; Oliver, S G; Rutherford, K; Wood, V; Bahler, J; Lock, A; Kersey, P J; McDowall, D M; Staines, D M; Dwinell, M; Shimoyama, M; Laulederkind, S; Hayman, T; Wang, S -J; Petri, V; Lowry, T; D'Eustachio, P; Matthews, L; Balakrishnan, R; Binkley, G; Cherry, J M; Costanzo, M C; Dwight, S S; Engel, S R; Fisk, D G; Hitz, B C; Hong, E L; Karra, K; Miyasato, S R; Nash, R S; Park, J; Skrzypek, M S; Weng, S; Wong, E D; Berardini, T Z; Huala, E; Mi, H; Thomas, P D; Chan, J; Kishore, R; Sternberg, P; Van Auken, K; Howe, D; Westerfield, M

    2013-01-01

    The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.

  6. Evidence-based gene models for structural and functional annotations of the oil palm genome.

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    Chan, Kuang-Lim; Tatarinova, Tatiana V; Rosli, Rozana; Amiruddin, Nadzirah; Azizi, Norazah; Halim, Mohd Amin Ab; Sanusi, Nik Shazana Nik Mohd; Jayanthi, Nagappan; Ponomarenko, Petr; Triska, Martin; Solovyev, Victor; Firdaus-Raih, Mohd; Sambanthamurthi, Ravigadevi; Murphy, Denis; Low, Eng-Ti Leslie

    2017-09-08

    Oil palm is an important source of edible oil. The importance of the crop, as well as its long breeding cycle (10-12 years) has led to the sequencing of its genome in 2013 to pave the way for genomics-guided breeding. Nevertheless, the first set of gene predictions, although useful, had many fragmented genes. Classification and characterization of genes associated with traits of interest, such as those for fatty acid biosynthesis and disease resistance, were also limited. Lipid-, especially fatty acid (FA)-related genes are of particular interest for the oil palm as they specify oil yields and quality. This paper presents the characterization of the oil palm genome using different gene prediction methods and comparative genomics analysis, identification of FA biosynthesis and disease resistance genes, and the development of an annotation database and bioinformatics tools. Using two independent gene-prediction pipelines, Fgenesh++ and Seqping, 26,059 oil palm genes with transcriptome and RefSeq support were identified from the oil palm genome. These coding regions of the genome have a characteristic broad distribution of GC3 (fraction of cytosine and guanine in the third position of a codon) with over half the GC3-rich genes (GC3 ≥ 0.75286) being intronless. In comparison, only one-seventh of the oil palm genes identified are intronless. Using comparative genomics analysis, characterization of conserved domains and active sites, and expression analysis, 42 key genes involved in FA biosynthesis in oil palm were identified. For three of them, namely EgFABF, EgFABH and EgFAD3, segmental duplication events were detected. Our analysis also identified 210 candidate resistance genes in six classes, grouped by their protein domain structures. We present an accurate and comprehensive annotation of the oil palm genome, focusing on analysis of important categories of genes (GC3-rich and intronless), as well as those associated with important functions, such as FA

  7. Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation

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    Poos, Kathrin; Smida, Jan; Nathrath, Michaela; Maugg, Doris; Baumhoer, Daniel; Neumann, Anna; Korsching, Eberhard

    2014-01-01

    Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific

  8. Structuring osteosarcoma knowledge: an osteosarcoma-gene association database based on literature mining and manual annotation.

    Science.gov (United States)

    Poos, Kathrin; Smida, Jan; Nathrath, Michaela; Maugg, Doris; Baumhoer, Daniel; Neumann, Anna; Korsching, Eberhard

    2014-01-01

    Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers. Up to now, clinico-pathological factors are the key determinants to guide prognosis and therapeutic treatments. Each day, new studies about OS are published and complicate the acquisition of information to support biomarker discovery and therapeutic improvements. Thus, it is necessary to provide a structured and annotated view on the current OS knowledge that is quick and easily accessible to researchers of the field. Therefore, we developed a publicly available database and Web interface that serves as resource for OS-associated genes and microRNAs. Genes and microRNAs were collected using an automated dictionary-based gene recognition procedure followed by manual review and annotation by experts of the field. In total, 911 genes and 81 microRNAs related to 1331 PubMed abstracts were collected (last update: 29 October 2013). Users can evaluate genes and microRNAs according to their potential prognostic and therapeutic impact, the experimental procedures, the sample types, the biological contexts and microRNA target gene interactions. Additionally, a pathway enrichment analysis of the collected genes highlights different aspects of OS progression. OS requires pathways commonly deregulated in cancer but also features OS-specific alterations like deregulated osteoclast differentiation. To our knowledge, this is the first effort of an OS database containing manual reviewed and annotated up-to-date OS knowledge. It might be a useful resource especially for the bone tumor research community, as specific

  9. COGNATE: comparative gene annotation characterizer.

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    Wilbrandt, Jeanne; Misof, Bernhard; Niehuis, Oliver

    2017-07-17

    The comparison of gene and genome structures across species has the potential to reveal major trends of genome evolution. However, such a comparative approach is currently hampered by a lack of standardization (e.g., Elliott TA, Gregory TR, Philos Trans Royal Soc B: Biol Sci 370:20140331, 2015). For example, testing the hypothesis that the total amount of coding sequences is a reliable measure of potential proteome diversity (Wang M, Kurland CG, Caetano-Anollés G, PNAS 108:11954, 2011) requires the application of standardized definitions of coding sequence and genes to create both comparable and comprehensive data sets and corresponding summary statistics. However, such standard definitions either do not exist or are not consistently applied. These circumstances call for a standard at the descriptive level using a minimum of parameters as well as an undeviating use of standardized terms, and for software that infers the required data under these strict definitions. The acquisition of a comprehensive, descriptive, and standardized set of parameters and summary statistics for genome publications and further analyses can thus greatly benefit from the availability of an easy to use standard tool. We developed a new open-source command-line tool, COGNATE (Comparative Gene Annotation Characterizer), which uses a given genome assembly and its annotation of protein-coding genes for a detailed description of the respective gene and genome structure parameters. Additionally, we revised the standard definitions of gene and genome structures and provide the definitions used by COGNATE as a working draft suggestion for further reference. Complete parameter lists and summary statistics are inferred using this set of definitions to allow down-stream analyses and to provide an overview of the genome and gene repertoire characteristics. COGNATE is written in Perl and freely available at the ZFMK homepage ( https://www.zfmk.de/en/COGNATE ) and on github ( https

  10. Integrative structural annotation of de novo RNA-Seq provides an accurate reference gene set of the enormous genome of the onion (Allium cepa L.).

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    Kim, Seungill; Kim, Myung-Shin; Kim, Yong-Min; Yeom, Seon-In; Cheong, Kyeongchae; Kim, Ki-Tae; Jeon, Jongbum; Kim, Sunggil; Kim, Do-Sun; Sohn, Seong-Han; Lee, Yong-Hwan; Choi, Doil

    2015-02-01

    The onion (Allium cepa L.) is one of the most widely cultivated and consumed vegetable crops in the world. Although a considerable amount of onion transcriptome data has been deposited into public databases, the sequences of the protein-coding genes are not accurate enough to be used, owing to non-coding sequences intermixed with the coding sequences. We generated a high-quality, annotated onion transcriptome from de novo sequence assembly and intensive structural annotation using the integrated structural gene annotation pipeline (ISGAP), which identified 54,165 protein-coding genes among 165,179 assembled transcripts totalling 203.0 Mb by eliminating the intron sequences. ISGAP performed reliable annotation, recognizing accurate gene structures based on reference proteins, and ab initio gene models of the assembled transcripts. Integrative functional annotation and gene-based SNP analysis revealed a whole biological repertoire of genes and transcriptomic variation in the onion. The method developed in this study provides a powerful tool for the construction of reference gene sets for organisms based solely on de novo transcriptome data. Furthermore, the reference genes and their variation described here for the onion represent essential tools for molecular breeding and gene cloning in Allium spp.

  11. Improving the gene structure annotation of the apicomplexan parasite Neospora caninum fulfils a vital requirement towards an in silico-derived vaccine.

    Science.gov (United States)

    Goodswen, Stephen J; Barratt, Joel L N; Kennedy, Paul J; Ellis, John T

    2015-04-01

    Neospora caninum is an apicomplexan parasite which can cause abortion in cattle, instigating major economic burden. Vaccination has been proposed as the most cost-effective control measure to alleviate this burden. Consequently the overriding aspiration for N. caninum research is the identification and subsequent evaluation of vaccine candidates in animal models. To save time, cost and effort, it is now feasible to use an in silico approach for vaccine candidate prediction. Precise protein sequences, derived from the correct open reading frame, are paramount and arguably the most important factor determining the success or failure of this approach. The challenge is that publicly available N. caninum sequences are mostly derived from gene predictions. Annotated inaccuracies can lead to erroneously predicted vaccine candidates by bioinformatics programs. This study evaluates the current N. caninum annotation for potential inaccuracies. Comparisons with annotation from a closely related pathogen, Toxoplasma gondii, are also made to distinguish patterns of inconsistency. More importantly, a mRNA sequencing (RNA-Seq) experiment is used to validate the annotation. Potential discrepancies originating from a questionable start codon context and exon boundaries were identified in 1943 protein coding sequences. We conclude, where experimental data were available, that the majority of N. caninum gene sequences were reliably predicted. Nevertheless, almost 28% of genes were identified as questionable. Given the limitations of RNA-Seq, the intention of this study was not to replace the existing annotation but to support or oppose particular aspects of it. Ideally, many studies aimed at improving the annotation are required to build a consensus. We believe this study, in providing a new resource on gene structure and annotation, is a worthy contributor to this endeavour.

  12. Metagenomic gene annotation by a homology-independent approach

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    Froula, Jeff; Zhang, Tao; Salmeen, Annette; Hess, Matthias; Kerfeld, Cheryl A.; Wang, Zhong; Du, Changbin

    2011-06-02

    Fully understanding the genetic potential of a microbial community requires functional annotation of all the genes it encodes. The recently developed deep metagenome sequencing approach has enabled rapid identification of millions of genes from a complex microbial community without cultivation. Current homology-based gene annotation fails to detect distantly-related or structural homologs. Furthermore, homology searches with millions of genes are very computational intensive. To overcome these limitations, we developed rhModeller, a homology-independent software pipeline to efficiently annotate genes from metagenomic sequencing projects. Using cellulases and carbonic anhydrases as two independent test cases, we demonstrated that rhModeller is much faster than HMMER but with comparable accuracy, at 94.5percent and 99.9percent accuracy, respectively. More importantly, rhModeller has the ability to detect novel proteins that do not share significant homology to any known protein families. As {approx}50percent of the 2 million genes derived from the cow rumen metagenome failed to be annotated based on sequence homology, we tested whether rhModeller could be used to annotate these genes. Preliminary results suggest that rhModeller is robust in the presence of missense and frameshift mutations, two common errors in metagenomic genes. Applying the pipeline to the cow rumen genes identified 4,990 novel cellulases candidates and 8,196 novel carbonic anhydrase candidates.In summary, we expect rhModeller to dramatically increase the speed and quality of metagnomic gene annotation.

  13. Discovering gene annotations in biomedical text databases

    Directory of Open Access Journals (Sweden)

    Ozsoyoglu Gultekin

    2008-03-01

    Full Text Available Abstract Background Genes and gene products are frequently annotated with Gene Ontology concepts based on the evidence provided in genomics articles. Manually locating and curating information about a genomic entity from the biomedical literature requires vast amounts of human effort. Hence, there is clearly a need forautomated computational tools to annotate the genes and gene products with Gene Ontology concepts by computationally capturing the related knowledge embedded in textual data. Results In this article, we present an automated genomic entity annotation system, GEANN, which extracts information about the characteristics of genes and gene products in article abstracts from PubMed, and translates the discoveredknowledge into Gene Ontology (GO concepts, a widely-used standardized vocabulary of genomic traits. GEANN utilizes textual "extraction patterns", and a semantic matching framework to locate phrases matching to a pattern and produce Gene Ontology annotations for genes and gene products. In our experiments, GEANN has reached to the precision level of 78% at therecall level of 61%. On a select set of Gene Ontology concepts, GEANN either outperforms or is comparable to two other automated annotation studies. Use of WordNet for semantic pattern matching improves the precision and recall by 24% and 15%, respectively, and the improvement due to semantic pattern matching becomes more apparent as the Gene Ontology terms become more general. Conclusion GEANN is useful for two distinct purposes: (i automating the annotation of genomic entities with Gene Ontology concepts, and (ii providing existing annotations with additional "evidence articles" from the literature. The use of textual extraction patterns that are constructed based on the existing annotations achieve high precision. The semantic pattern matching framework provides a more flexible pattern matching scheme with respect to "exactmatching" with the advantage of locating approximate

  14. JGI Plant Genomics Gene Annotation Pipeline

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    Shu, Shengqiang; Rokhsar, Dan; Goodstein, David; Hayes, David; Mitros, Therese

    2014-07-14

    Plant genomes vary in size and are highly complex with a high amount of repeats, genome duplication and tandem duplication. Gene encodes a wealth of information useful in studying organism and it is critical to have high quality and stable gene annotation. Thanks to advancement of sequencing technology, many plant species genomes have been sequenced and transcriptomes are also sequenced. To use these vastly large amounts of sequence data to make gene annotation or re-annotation in a timely fashion, an automatic pipeline is needed. JGI plant genomics gene annotation pipeline, called integrated gene call (IGC), is our effort toward this aim with aid of a RNA-seq transcriptome assembly pipeline. It utilizes several gene predictors based on homolog peptides and transcript ORFs. See Methods for detail. Here we present genome annotation of JGI flagship green plants produced by this pipeline plus Arabidopsis and rice except for chlamy which is done by a third party. The genome annotations of these species and others are used in our gene family build pipeline and accessible via JGI Phytozome portal whose URL and front page snapshot are shown below.

  15. Evaluating Hierarchical Structure in Music Annotations.

    Science.gov (United States)

    McFee, Brian; Nieto, Oriol; Farbood, Morwaread M; Bello, Juan Pablo

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for "flat" descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  16. Evaluating Hierarchical Structure in Music Annotations

    Directory of Open Access Journals (Sweden)

    Brian McFee

    2017-08-01

    Full Text Available Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR, it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded several insights relevant to the study of music cognition. First, annotators tend to agree when structural boundaries are ambiguous. Second, this ambiguity seems to depend on musical features, time scale, and genre. Furthermore, it is possible to tune current annotation evaluation metrics to better align with these perceptual differences. However, previous work has not directly analyzed the effects of hierarchical structure because the existing methods for comparing structural annotations are designed for “flat” descriptions, and do not readily generalize to hierarchical annotations. In this paper, we extend and generalize previous work on the evaluation of hierarchical descriptions of musical structure. We derive an evaluation metric which can compare hierarchical annotations holistically across multiple levels. sing this metric, we investigate inter-annotator agreement on the multilevel annotations of two different music corpora, investigate the influence of acoustic properties on hierarchical annotations, and evaluate existing hierarchical segmentation algorithms against the distribution of inter-annotator agreement.

  17. Logical Gene Ontology Annotations (GOAL): exploring gene ontology annotations with OWL.

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    Jupp, Simon; Stevens, Robert; Hoehndorf, Robert

    2012-04-24

    Ontologies such as the Gene Ontology (GO) and their use in annotations make cross species comparisons of genes possible, along with a wide range of other analytical activities. The bio-ontologies community, in particular the Open Biomedical Ontologies (OBO) community, have provided many other ontologies and an increasingly large volume of annotations of gene products that can be exploited in query and analysis. As many annotations with different ontologies centre upon gene products, there is a possibility to explore gene products through multiple ontological perspectives at the same time. Questions could be asked that link a gene product's function, process, cellular location, phenotype and disease. Current tools, such as AmiGO, allow exploration of genes based on their GO annotations, but not through multiple ontological perspectives. In addition, the semantics of these ontology's representations should be able to, through automated reasoning, afford richer query opportunities of the gene product annotations than is currently possible. To do this multi-perspective, richer querying of gene product annotations, we have created the Logical Gene Ontology, or GOAL ontology, in OWL that combines the Gene Ontology, Human Disease Ontology and the Mammalian Phenotype Ontology, together with classes that represent the annotations with these ontologies for mouse gene products. Each mouse gene product is represented as a class, with the appropriate relationships to the GO aspects, phenotype and disease with which it has been annotated. We then use defined classes to query these protein classes through automated reasoning, and to build a complex hierarchy of gene products. We have presented this through a Web interface that allows arbitrary queries to be constructed and the results displayed. This standard use of OWL affords a rich interaction with Gene Ontology, Human Disease Ontology and Mammalian Phenotype Ontology annotations for the mouse, to give a fine partitioning of

  18. Evaluating Hierarchical Structure in Music Annotations

    OpenAIRE

    Brian McFee; Oriol Nieto; Morwaread M. Farbood; Juan Pablo Bello

    2017-01-01

    Music exhibits structure at multiple scales, ranging from motifs to large-scale functional components. When inferring the structure of a piece, different listeners may attend to different temporal scales, which can result in disagreements when they describe the same piece. In the field of music informatics research (MIR), it is common to use corpora annotated with structural boundaries at different levels. By quantifying disagreements between multiple annotators, previous research has yielded...

  19. Measuring semantic similarities by combining gene ontology annotations and gene co-function networks.

    Science.gov (United States)

    Peng, Jiajie; Uygun, Sahra; Kim, Taehyong; Wang, Yadong; Rhee, Seung Y; Chen, Jin

    2015-02-14

    Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms. We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstrate that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large Arabidopsis gene families such as cytochrome P450 monooxygenases to group the members functionally and show that this grouping could facilitate functional characterization of genes in these families. Using NETSIM as an example, we demonstrated that the performance of a semantic similarity measure could be significantly improved after incorporating genome-specific information. NETSIM incorporates both GO annotations and gene co-function network data as a priori knowledge in the model. Therefore, functional similarities of GO terms that are not explicitly encoded in GO but are relevant in a taxon-specific manner become measurable when GO annotations are limited. Supplementary information and software are available at http://www.msu.edu/~jinchen/NETSIM .

  20. Evaluating Functional Annotations of Enzymes Using the Gene Ontology.

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    Holliday, Gemma L; Davidson, Rebecca; Akiva, Eyal; Babbitt, Patricia C

    2017-01-01

    The Gene Ontology (GO) (Ashburner et al., Nat Genet 25(1):25-29, 2000) is a powerful tool in the informatics arsenal of methods for evaluating annotations in a protein dataset. From identifying the nearest well annotated homologue of a protein of interest to predicting where misannotation has occurred to knowing how confident you can be in the annotations assigned to those proteins is critical. In this chapter we explore what makes an enzyme unique and how we can use GO to infer aspects of protein function based on sequence similarity. These can range from identification of misannotation or other errors in a predicted function to accurate function prediction for an enzyme of entirely unknown function. Although GO annotation applies to any gene products, we focus here a describing our approach for hierarchical classification of enzymes in the Structure-Function Linkage Database (SFLD) (Akiva et al., Nucleic Acids Res 42(Database issue):D521-530, 2014) as a guide for informed utilisation of annotation transfer based on GO terms.

  1. A method for increasing expressivity of Gene Ontology annotations using a compositional approach.

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    Huntley, Rachael P; Harris, Midori A; Alam-Faruque, Yasmin; Blake, Judith A; Carbon, Seth; Dietze, Heiko; Dimmer, Emily C; Foulger, Rebecca E; Hill, David P; Khodiyar, Varsha K; Lock, Antonia; Lomax, Jane; Lovering, Ruth C; Mutowo-Meullenet, Prudence; Sawford, Tony; Van Auken, Kimberly; Wood, Valerie; Mungall, Christopher J

    2014-05-21

    The Gene Ontology project integrates data about the function of gene products across a diverse range of organisms, allowing the transfer of knowledge from model organisms to humans, and enabling computational analyses for interpretation of high-throughput experimental and clinical data. The core data structure is the annotation, an association between a gene product and a term from one of the three ontologies comprising the GO. Historically, it has not been possible to provide additional information about the context of a GO term, such as the target gene or the location of a molecular function. This has limited the specificity of knowledge that can be expressed by GO annotations. The GO Consortium has introduced annotation extensions that enable manually curated GO annotations to capture additional contextual details. Extensions represent effector-target relationships such as localization dependencies, substrates of protein modifiers and regulation targets of signaling pathways and transcription factors as well as spatial and temporal aspects of processes such as cell or tissue type or developmental stage. We describe the content and structure of annotation extensions, provide examples, and summarize the current usage of annotation extensions. The additional contextual information captured by annotation extensions improves the utility of functional annotation by representing dependencies between annotations to terms in the different ontologies of GO, external ontologies, or an organism's gene products. These enhanced annotations can also support sophisticated queries and reasoning, and will provide curated, directional links between many gene products to support pathway and network reconstruction.

  2. Structural annotation of Mycobacterium tuberculosis proteome.

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    Praveen Anand

    Full Text Available Of the ∼4000 ORFs identified through the genome sequence of Mycobacterium tuberculosis (TB H37Rv, experimentally determined structures are available for 312. Since knowledge of protein structures is essential to obtain a high-resolution understanding of the underlying biology, we seek to obtain a structural annotation for the genome, using computational methods. Structural models were obtained and validated for ∼2877 ORFs, covering ∼70% of the genome. Functional annotation of each protein was based on fold-based functional assignments and a novel binding site based ligand association. New algorithms for binding site detection and genome scale binding site comparison at the structural level, recently reported from the laboratory, were utilized. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides an opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses. The resource (http://proline.physics.iisc.ernet.in/Tbstructuralannotation, being one of the first to be based on structure-derived functional annotations at a genome scale, is expected to be useful for better understanding of TB and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well.

  3. Current challenges in genome annotation through structural biology and bioinformatics.

    Science.gov (United States)

    Furnham, Nicholas; de Beer, Tjaart A P; Thornton, Janet M

    2012-10-01

    With the huge volume in genomic sequences being generated from high-throughout sequencing projects the requirement for providing accurate and detailed annotations of gene products has never been greater. It is proving to be a huge challenge for computational biologists to use as much information as possible from experimental data to provide annotations for genome data of unknown function. A central component to this process is to use experimentally determined structures, which provide a means to detect homology that is not discernable from just the sequence and permit the consequences of genomic variation to be realized at the molecular level. In particular, structures also form the basis of many bioinformatics methods for improving the detailed functional annotations of enzymes in combination with similarities in sequence and chemistry. Copyright © 2012. Published by Elsevier Ltd.

  4. A robust data-driven approach for gene ontology annotation

    OpenAIRE

    2014-01-01

    Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For th...

  5. Construction of coffee transcriptome networks based on gene annotation semantics.

    Science.gov (United States)

    Castillo, Luis F; Galeano, Narmer; Isaza, Gustavo A; Gaitán, Alvaro

    2012-07-24

    Gene annotation is a process that encompasses multiple approaches on the analysis of nucleic acids or protein sequences in order to assign structural and functional characteristics to gene models. When thousands of gene models are being described in an organism genome, construction and visualization of gene networks impose novel challenges in the understanding of complex expression patterns and the generation of new knowledge in genomics research. In order to take advantage of accumulated text data after conventional gene sequence analysis, this work applied semantics in combination with visualization tools to build transcriptome networks from a set of coffee gene annotations. A set of selected coffee transcriptome sequences, chosen by the quality of the sequence comparison reported by Basic Local Alignment Search Tool (BLAST) and Interproscan, were filtered out by coverage, identity, length of the query, and e-values. Meanwhile, term descriptors for molecular biology and biochemistry were obtained along the Wordnet dictionary in order to construct a Resource Description Framework (RDF) using Ruby scripts and Methontology to find associations between concepts. Relationships between sequence annotations and semantic concepts were graphically represented through a total of 6845 oriented vectors, which were reduced to 745 non-redundant associations. A large gene network connecting transcripts by way of relational concepts was created where detailed connections remain to be validated for biological significance based on current biochemical and genetics frameworks. Besides reusing text information in the generation of gene connections and for data mining purposes, this tool development opens the possibility to visualize complex and abundant transcriptome data, and triggers the formulation of new hypotheses in metabolic pathways analysis.

  6. GIFtS: annotation landscape analysis with GeneCards

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    Dalah Irina

    2009-10-01

    Full Text Available Abstract Background Gene annotation is a pivotal component in computational genomics, encompassing prediction of gene function, expression analysis, and sequence scrutiny. Hence, quantitative measures of the annotation landscape constitute a pertinent bioinformatics tool. GeneCards® is a gene-centric compendium of rich annotative information for over 50,000 human gene entries, building upon 68 data sources, including Gene Ontology (GO, pathways, interactions, phenotypes, publications and many more. Results We present the GeneCards Inferred Functionality Score (GIFtS which allows a quantitative assessment of a gene's annotation status, by exploiting the unique wealth and diversity of GeneCards information. The GIFtS tool, linked from the GeneCards home page, facilitates browsing the human genome by searching for the annotation level of a specified gene, retrieving a list of genes within a specified range of GIFtS value, obtaining random genes with a specific GIFtS value, and experimenting with the GIFtS weighting algorithm for a variety of annotation categories. The bimodal shape of the GIFtS distribution suggests a division of the human gene repertoire into two main groups: the high-GIFtS peak consists almost entirely of protein-coding genes; the low-GIFtS peak consists of genes from all of the categories. Cluster analysis of GIFtS annotation vectors provides the classification of gene groups by detailed positioning in the annotation arena. GIFtS also provide measures which enable the evaluation of the databases that serve as GeneCards sources. An inverse correlation is found (for GIFtS>25 between the number of genes annotated by each source, and the average GIFtS value of genes associated with that source. Three typical source prototypes are revealed by their GIFtS distribution: genome-wide sources, sources comprising mainly highly annotated genes, and sources comprising mainly poorly annotated genes. The degree of accumulated knowledge for a

  7. Bioinformatics Assisted Gene Discovery and Annotation of Human Genome

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    As the sequencing stage of human genome project is near the end, the work has begun for discovering novel genes from genome sequences and annotating their biological functions. Here are reviewed current major bioinformatics tools and technologies available for large scale gene discovery and annotation from human genome sequences. Some ideas about possible future development are also provided.

  8. Ontology-Based Prediction and Prioritization of Gene Functional Annotations.

    Science.gov (United States)

    Chicco, Davide; Masseroli, Marco

    2016-01-01

    Genes and their protein products are essential molecular units of a living organism. The knowledge of their functions is key for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. The association of a gene or protein with its functions, described by controlled terms of biomolecular terminologies or ontologies, is named gene functional annotation. Very many and valuable gene annotations expressed through terminologies and ontologies are available. Nevertheless, they might include some erroneous information, since only a subset of annotations are reviewed by curators. Furthermore, they are incomplete by definition, given the rapidly evolving pace of biomolecular knowledge. In this scenario, computational methods that are able to quicken the annotation curation process and reliably suggest new annotations are very important. Here, we first propose a computational pipeline that uses different semantic and machine learning methods to predict novel ontology-based gene functional annotations; then, we introduce a new semantic prioritization rule to categorize the predicted annotations by their likelihood of being correct. Our tests and validations proved the effectiveness of our pipeline and prioritization of predicted annotations, by selecting as most likely manifold predicted annotations that were later confirmed.

  9. The GATO gene annotation tool for research laboratories

    Directory of Open Access Journals (Sweden)

    A. Fujita

    2005-11-01

    Full Text Available Large-scale genome projects have generated a rapidly increasing number of DNA sequences. Therefore, development of computational methods to rapidly analyze these sequences is essential for progress in genomic research. Here we present an automatic annotation system for preliminary analysis of DNA sequences. The gene annotation tool (GATO is a Bioinformatics pipeline designed to facilitate routine functional annotation and easy access to annotated genes. It was designed in view of the frequent need of genomic researchers to access data pertaining to a common set of genes. In the GATO system, annotation is generated by querying some of the Web-accessible resources and the information is stored in a local database, which keeps a record of all previous annotation results. GATO may be accessed from everywhere through the internet or may be run locally if a large number of sequences are going to be annotated. It is implemented in PHP and Perl and may be run on any suitable Web server. Usually, installation and application of annotation systems require experience and are time consuming, but GATO is simple and practical, allowing anyone with basic skills in informatics to access it without any special training. GATO can be downloaded at [http://mariwork.iq.usp.br/gato/]. Minimum computer free space required is 2 MB.

  10. How well are protein structures annotated in secondary databases?

    Science.gov (United States)

    Rother, Kristian; Michalsky, Elke; Leser, Ulf

    2005-09-01

    We investigated to what extent Protein Data Bank (PDB) entries are annotated with second-party information based on existing cross-references between PDB and 15 other databases. We report 2 interesting findings. First, there is a clear "annotation gap" for structures less than 7 years old for secondary databases that are manually curated. Second, the examined databases overlap with each other quite well, dividing the PDB into 2 well-annotated thirds and one poorly annotated third. Both observations should be taken into account in any study depending on the selection of protein structures by their annotation.

  11. microRNAs Databases: Developmental Methodologies, Structural and Functional Annotations.

    Science.gov (United States)

    Singh, Nagendra Kumar

    2017-09-01

    microRNA (miRNA) is an endogenous and evolutionary conserved non-coding RNA, involved in post-transcriptional process as gene repressor and mRNA cleavage through RNA-induced silencing complex (RISC) formation. In RISC, miRNA binds in complementary base pair with targeted mRNA along with Argonaut proteins complex, causes gene repression or endonucleolytic cleavage of mRNAs and results in many diseases and syndromes. After the discovery of miRNA lin-4 and let-7, subsequently large numbers of miRNAs were discovered by low-throughput and high-throughput experimental techniques along with computational process in various biological and metabolic processes. The miRNAs are important non-coding RNA for understanding the complex biological phenomena of organism because it controls the gene regulation. This paper reviews miRNA databases with structural and functional annotations developed by various researchers. These databases contain structural and functional information of animal, plant and virus miRNAs including miRNAs-associated diseases, stress resistance in plant, miRNAs take part in various biological processes, effect of miRNAs interaction on drugs and environment, effect of variance on miRNAs, miRNAs gene expression analysis, sequence of miRNAs, structure of miRNAs. This review focuses on the developmental methodology of miRNA databases such as computational tools and methods used for extraction of miRNAs annotation from different resources or through experiment. This study also discusses the efficiency of user interface design of every database along with current entry and annotations of miRNA (pathways, gene ontology, disease ontology, etc.). Here, an integrated schematic diagram of construction process for databases is also drawn along with tabular and graphical comparison of various types of entries in different databases. Aim of this paper is to present the importance of miRNAs-related resources at a single place.

  12. Missing genes in the annotation of prokaryotic genomes

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    Feng Wu-chun

    2010-03-01

    Full Text Available Abstract Background Protein-coding gene detection in prokaryotic genomes is considered a much simpler problem than in intron-containing eukaryotic genomes. However there have been reports that prokaryotic gene finder programs have problems with small genes (either over-predicting or under-predicting. Therefore the question arises as to whether current genome annotations have systematically missing, small genes. Results We have developed a high-performance computing methodology to investigate this problem. In this methodology we compare all ORFs larger than or equal to 33 aa from all fully-sequenced prokaryotic replicons. Based on that comparison, and using conservative criteria requiring a minimum taxonomic diversity between conserved ORFs in different genomes, we have discovered 1,153 candidate genes that are missing from current genome annotations. These missing genes are similar only to each other and do not have any strong similarity to gene sequences in public databases, with the implication that these ORFs belong to missing gene families. We also uncovered 38,895 intergenic ORFs, readily identified as putative genes by similarity to currently annotated genes (we call these absent annotations. The vast majority of the missing genes found are small (less than 100 aa. A comparison of select examples with GeneMark, EasyGene and Glimmer predictions yields evidence that some of these genes are escaping detection by these programs. Conclusions Prokaryotic gene finders and prokaryotic genome annotations require improvement for accurate prediction of small genes. The number of missing gene families found is likely a lower bound on the actual number, due to the conservative criteria used to determine whether an ORF corresponds to a real gene.

  13. Gene calling and bacterial genome annotation with BG7.

    Science.gov (United States)

    Tobes, Raquel; Pareja-Tobes, Pablo; Manrique, Marina; Pareja-Tobes, Eduardo; Kovach, Evdokim; Alekhin, Alexey; Pareja, Eduardo

    2015-01-01

    New massive sequencing technologies are providing many bacterial genome sequences from diverse taxa but a refined annotation of these genomes is crucial for obtaining scientific findings and new knowledge. Thus, bacterial genome annotation has emerged as a key point to investigate in bacteria. Any efficient tool designed specifically to annotate bacterial genomes sequenced with massively parallel technologies has to consider the specific features of bacterial genomes (absence of introns and scarcity of nonprotein-coding sequence) and of next-generation sequencing (NGS) technologies (presence of errors and not perfectly assembled genomes). These features make it convenient to focus on coding regions and, hence, on protein sequences that are the elements directly related with biological functions. In this chapter we describe how to annotate bacterial genomes with BG7, an open-source tool based on a protein-centered gene calling/annotation paradigm. BG7 is specifically designed for the annotation of bacterial genomes sequenced with NGS. This tool is sequence error tolerant maintaining their capabilities for the annotation of highly fragmented genomes or for annotating mixed sequences coming from several genomes (as those obtained through metagenomics samples). BG7 has been designed with scalability as a requirement, with a computing infrastructure completely based on cloud computing (Amazon Web Services).

  14. CvManGO, a method for leveraging computational predictions to improve literature-based Gene Ontology annotations.

    Science.gov (United States)

    Park, Julie; Costanzo, Maria C; Balakrishnan, Rama; Cherry, J Michael; Hong, Eurie L

    2012-01-01

    The set of annotations at the Saccharomyces Genome Database (SGD) that classifies the cellular function of S. cerevisiae gene products using Gene Ontology (GO) terms has become an important resource for facilitating experimental analysis. In addition to capturing and summarizing experimental results, the structured nature of GO annotations allows for functional comparison across organisms as well as propagation of functional predictions between related gene products. Due to their relevance to many areas of research, ensuring the accuracy and quality of these annotations is a priority at SGD. GO annotations are assigned either manually, by biocurators extracting experimental evidence from the scientific literature, or through automated methods that leverage computational algorithms to predict functional information. Here, we discuss the relationship between literature-based and computationally predicted GO annotations in SGD and extend a strategy whereby comparison of these two types of annotation identifies genes whose annotations need review. Our method, CvManGO (Computational versus Manual GO annotations), pairs literature-based GO annotations with computational GO predictions and evaluates the relationship of the two terms within GO, looking for instances of discrepancy. We found that this method will identify genes that require annotation updates, taking an important step towards finding ways to prioritize literature review. Additionally, we explored factors that may influence the effectiveness of CvManGO in identifying relevant gene targets to find in particular those genes that are missing literature-supported annotations, but our survey found that there are no immediately identifiable criteria by which one could enrich for these under-annotated genes. Finally, we discuss possible ways to improve this strategy, and the applicability of this method to other projects that use the GO for curation. DATABASE URL: http://www.yeastgenome.org.

  15. Gene coexpression network analysis as a source of functional annotation for rice genes.

    Directory of Open Access Journals (Sweden)

    Kevin L Childs

    Full Text Available With the existence of large publicly available plant gene expression data sets, many groups have undertaken data analyses to construct gene coexpression networks and functionally annotate genes. Often, a large compendium of unrelated or condition-independent expression data is used to construct gene networks. Condition-dependent expression experiments consisting of well-defined conditions/treatments have also been used to create coexpression networks to help examine particular biological processes. Gene networks derived from either condition-dependent or condition-independent data can be difficult to interpret if a large number of genes and connections are present. However, algorithms exist to identify modules of highly connected and biologically relevant genes within coexpression networks. In this study, we have used publicly available rice (Oryza sativa gene expression data to create gene coexpression networks using both condition-dependent and condition-independent data and have identified gene modules within these networks using the Weighted Gene Coexpression Network Analysis method. We compared the number of genes assigned to modules and the biological interpretability of gene coexpression modules to assess the utility of condition-dependent and condition-independent gene coexpression networks. For the purpose of providing functional annotation to rice genes, we found that gene modules identified by coexpression analysis of condition-dependent gene expression experiments to be more useful than gene modules identified by analysis of a condition-independent data set. We have incorporated our results into the MSU Rice Genome Annotation Project database as additional expression-based annotation for 13,537 genes, 2,980 of which lack a functional annotation description. These results provide two new types of functional annotation for our database. Genes in modules are now associated with groups of genes that constitute a collective functional

  16. Structural and Functional Annotation of Hypothetical Proteins of O139

    Directory of Open Access Journals (Sweden)

    Md. Saiful Islam

    2015-06-01

    Full Text Available In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera.

  17. Large-scale prokaryotic gene prediction and comparison to genome annotation

    DEFF Research Database (Denmark)

    Nielsen, Pernille; Krogh, Anders Stærmose

    2005-01-01

    Motivation: Prokaryotic genomes are sequenced and annotated at an increasing rate. The methods of annotation vary between sequencing groups. It makes genome comparison difficult and may lead to propagation of errors when questionable assignments are adapted from one genome to another. Genome...... genefinder EasyGene. Comparison of the GenBank and RefSeq annotations with the EasyGene predictions reveals that in some genomes up to 60% of the genes may have been annotated with a wrong start codon, especially in the GC-rich genomes. The fractional difference between annotated and predicted confirms......-annotated. These results are based on the difference between the number of annotated genes not found by EasyGene and the number of predicted genes that are not annotated in GenBank. We argue that the average performance of our standardized and fully automated method is slightly better than the annotation....

  18. HMM-Based Gene Annotation Methods

    Energy Technology Data Exchange (ETDEWEB)

    Haussler, David; Hughey, Richard; Karplus, Keven

    1999-09-20

    Development of new statistical methods and computational tools to identify genes in human genomic DNA, and to provide clues to their functions by identifying features such as transcription factor binding sites, tissue, specific expression and splicing patterns, and remove homologies at the protein level with genes of known function.

  19. Computational annotation of genes differentially expressed along olive fruit development

    Directory of Open Access Journals (Sweden)

    Martinelli Federico

    2009-10-01

    Full Text Available Abstract Background Olea europaea L. is a traditional tree crop of the Mediterranean basin with a worldwide economical high impact. Differently from other fruit tree species, little is known about the physiological and molecular basis of the olive fruit development and a few sequences of genes and gene products are available for olive in public databases. This study deals with the identification of large sets of differentially expressed genes in developing olive fruits and the subsequent computational annotation by means of different software. Results mRNA from fruits of the cv. Leccino sampled at three different stages [i.e., initial fruit set (stage 1, completed pit hardening (stage 2 and veraison (stage 3] was used for the identification of differentially expressed genes putatively involved in main processes along fruit development. Four subtractive hybridization libraries were constructed: forward and reverse between stage 1 and 2 (libraries A and B, and 2 and 3 (libraries C and D. All sequenced clones (1,132 in total were analyzed through BlastX against non-redundant NCBI databases and about 60% of them showed similarity to known proteins. A total of 89 out of 642 differentially expressed unique sequences was further investigated by Real-Time PCR, showing a validation of the SSH results as high as 69%. Library-specific cDNA repertories were annotated according to the three main vocabularies of the gene ontology (GO: cellular component, biological process and molecular function. BlastX analysis, GO terms mapping and annotation analysis were performed using the Blast2GO software, a research tool designed with the main purpose of enabling GO based data mining on sequence sets for which no GO annotation is yet available. Bioinformatic analysis pointed out a significantly different distribution of the annotated sequences for each GO category, when comparing the three fruit developmental stages. The olive fruit-specific transcriptome dataset was

  20. Automatic extraction of gene ontology annotation and its correlation with clusters in protein networks

    Directory of Open Access Journals (Sweden)

    Mazo Ilya

    2007-07-01

    Full Text Available Abstract Background Uncovering cellular roles of a protein is a task of tremendous importance and complexity that requires dedicated experimental work as well as often sophisticated data mining and processing tools. Protein functions, often referred to as its annotations, are believed to manifest themselves through topology of the networks of inter-proteins interactions. In particular, there is a growing body of evidence that proteins performing the same function are more likely to interact with each other than with proteins with other functions. However, since functional annotation and protein network topology are often studied separately, the direct relationship between them has not been comprehensively demonstrated. In addition to having the general biological significance, such demonstration would further validate the data extraction and processing methods used to compose protein annotation and protein-protein interactions datasets. Results We developed a method for automatic extraction of protein functional annotation from scientific text based on the Natural Language Processing (NLP technology. For the protein annotation extracted from the entire PubMed, we evaluated the precision and recall rates, and compared the performance of the automatic extraction technology to that of manual curation used in public Gene Ontology (GO annotation. In the second part of our presentation, we reported a large-scale investigation into the correspondence between communities in the literature-based protein networks and GO annotation groups of functionally related proteins. We found a comprehensive two-way match: proteins within biological annotation groups form significantly denser linked network clusters than expected by chance and, conversely, densely linked network communities exhibit a pronounced non-random overlap with GO groups. We also expanded the publicly available GO biological process annotation using the relations extracted by our NLP technology

  1. Structuring and presenting annotated media repositories

    NARCIS (Netherlands)

    Rutledge, L.; Ossenbruggen, J.R. van; Hardman, L.

    2004-01-01

    The Semantic Web envisions a Web that is both human readable and machine processible. In practice, however, there is still a large conceptual gap between annotated content repositories on the one hand, and coherent, human readable Web pages on the other. To bridge this conceptual gap, one needs to s

  2. Novel definition files for human GeneChips based on GeneAnnot

    Directory of Open Access Journals (Sweden)

    Ferrari Sergio

    2007-11-01

    Full Text Available Abstract Background Improvements in genome sequence annotation revealed discrepancies in the original probeset/gene assignment in Affymetrix microarray and the existence of differences between annotations and effective alignments of probes and transcription products. In the current generation of Affymetrix human GeneChips, most probesets include probes matching transcripts from more than one gene and probes which do not match any transcribed sequence. Results We developed a novel set of custom Chip Definition Files (CDF and the corresponding Bioconductor libraries for Affymetrix human GeneChips, based on the information contained in the GeneAnnot database. GeneAnnot-based CDFs are composed of unique custom-probesets, including only probes matching a single gene. Conclusion GeneAnnot-based custom CDFs solve the problem of a reliable reconstruction of expression levels and eliminate the existence of more than one probeset per gene, which often leads to discordant expression signals for the same transcript when gene differential expression is the focus of the analysis. GeneAnnot CDFs are freely distributed and fully compliant with Affymetrix standards and all available software for gene expression analysis. The CDF libraries are available from http://www.xlab.unimo.it/GA_CDF, along with supplementary information (CDF libraries, installation guidelines and R code, CDF statistics, and analysis results.

  3. KEGG as a reference resource for gene and protein annotation.

    Science.gov (United States)

    Kanehisa, Minoru; Sato, Yoko; Kawashima, Masayuki; Furumichi, Miho; Tanabe, Mao

    2016-01-04

    KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an integrated database resource for biological interpretation of genome sequences and other high-throughput data. Molecular functions of genes and proteins are associated with ortholog groups and stored in the KEGG Orthology (KO) database. The KEGG pathway maps, BRITE hierarchies and KEGG modules are developed as networks of KO nodes, representing high-level functions of the cell and the organism. Currently, more than 4000 complete genomes are annotated with KOs in the KEGG GENES database, which can be used as a reference data set for KO assignment and subsequent reconstruction of KEGG pathways and other molecular networks. As an annotation resource, the following improvements have been made. First, each KO record is re-examined and associated with protein sequence data used in experiments of functional characterization. Second, the GENES database now includes viruses, plasmids, and the addendum category for functionally characterized proteins that are not represented in complete genomes. Third, new automatic annotation servers, BlastKOALA and GhostKOALA, are made available utilizing the non-redundant pangenome data set generated from the GENES database. As a resource for translational bioinformatics, various data sets are created for antimicrobial resistance and drug interaction networks.

  4. A relation based measure of semantic similarity for Gene Ontology annotations

    Directory of Open Access Journals (Sweden)

    Gaudin Benoit

    2008-11-01

    Full Text Available Abstract Background Various measures of semantic similarity of terms in bio-ontologies such as the Gene Ontology (GO have been used to compare gene products. Such measures of similarity have been used to annotate uncharacterized gene products and group gene products into functional groups. There are various ways to measure semantic similarity, either using the topological structure of the ontology, the instances (gene products associated with terms or a mixture of both. We focus on an instance level definition of semantic similarity while using the information contained in the ontology, both in the graphical structure of the ontology and the semantics of relations between terms, to provide constraints on our instance level description. Semantic similarity of terms is extended to annotations by various approaches, either though aggregation operations such as min, max and average or through an extrapolative method. These approaches introduce assumptions about how semantic similarity of terms relates to the semantic similarity of annotations that do not necessarily reflect how terms relate to each other. Results We exploit the semantics of relations in the GO to construct an algorithm called SSA that provides the basis of a framework that naturally extends instance based methods of semantic similarity of terms, such as Resnik's measure, to describing annotations and not just terms. Our measure attempts to correctly interpret how terms combine via their relationships in the ontological hierarchy. SSA uses these relationships to identify the most specific common ancestors between terms. We outline the set of cases in which terms can combine and associate partial order constraints with each case that order the specificity of terms. These cases form the basis for the SSA algorithm. The set of associated constraints also provide a set of principles that any improvement on our method should seek to satisfy. Conclusion We derive a measure of semantic

  5. Cellular functions of genetically imprinted genes in human and mouse as annotated in the gene ontology.

    Science.gov (United States)

    Hamed, Mohamed; Ismael, Siba; Paulsen, Martina; Helms, Volkhard

    2012-01-01

    By analyzing the cellular functions of genetically imprinted genes as annotated in the Gene Ontology for human and mouse, we found that imprinted genes are often involved in developmental, transport and regulatory processes. In the human, paternally expressed genes are enriched in GO terms related to the development of organs and of anatomical structures. In the mouse, maternally expressed genes regulate cation transport as well as G-protein signaling processes. Furthermore, we investigated if imprinted genes are regulated by common transcription factors. We identified 25 TF families that showed an enrichment of binding sites in the set of imprinted genes in human and 40 TF families in mouse. In general, maternally and paternally expressed genes are not regulated by different transcription factors. The genes Nnat, Klf14, Blcap, Gnas and Ube3a contribute most to the enrichment of TF families. In the mouse, genes that are maternally expressed in placenta are enriched for AP1 binding sites. In the human, we found that these genes possessed binding sites for both, AP1 and SP1.

  6. Formal modeling of Gene Ontology annotation predictions based on factor graphs

    Science.gov (United States)

    Spetale, Flavio; Murillo, Javier; Tapia, Elizabeth; Arce, Débora; Ponce, Sergio; Bulacio, Pilar

    2016-04-01

    Gene Ontology (GO) is a hierarchical vocabulary for gene product annotation. Its synergy with machine learning classification methods has been widely used for the prediction of protein functions. Current classification methods rely on heuristic solutions to check the consistency with some aspects of the underlying GO structure. In this work we formalize the GO is-a relationship through predicate logic. Moreover, an ontology model based on Forney Factor Graph (FFG) is shown on a general fragment of Cellular Component GO.

  7. Information theory applied to the sparse gene ontology annotation network to predict novel gene function

    Science.gov (United States)

    Tao, Ying; Li, Jianrong

    2010-01-01

    Motivation Despite advances in the gene annotation process, the functions of a large portion of the gene products remain insufficiently characterized. In addition, the “in silico” prediction of novel Gene Ontology (GO) annotations for partially characterized gene functions or processes is highly dependent on reverse genetic or function genomics approaches. Results We propose a novel approach, Information Theory-based Semantic Similarity (ITSS), to automatically predict molecular functions of genes based on Gene Ontology annotations. We have demonstrated using a 10-fold cross-validation that the ITSS algorithm obtains prediction accuracies (Precision 97%, Recall 77%) comparable to other machine learning algorithms when applied to similarly dense annotated portions of the GO datasets. In addition, such method can generate highly accurate predictions in sparsely annotated portions of GO, in which previous algorithm failed to do so. As a result, our technique generates an order of magnitude more gene function predictions than previous methods. Further, this paper presents the first historical rollback validation for the predicted GO annotations, which may represent more realistic conditions for an evaluation than generally used cross-validations type of evaluations. By manually assessing a random sample of 100 predictions conducted in a historical roll-back evaluation, we estimate that a minimum precision of 51% (95% confidence interval: 43%–58%) can be achieved for the human GO Annotation file dated 2003. Availability The program is available on request. The 97,732 positive predictions of novel gene annotations from the 2005 GO Annotation dataset are available at http://phenos.bsd.uchicago.edu/mphenogo/prediction_result_2005.txt. PMID:17646340

  8. Predicting gene ontology annotations of orphan GWAS genes using protein-protein interactions.

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    Kuppuswamy, Usha; Ananthasubramanian, Seshan; Wang, Yanli; Balakrishnan, Narayanaswamy; Ganapathiraju, Madhavi K

    2014-04-03

    The number of genome-wide association studies (GWAS) has increased rapidly in the past couple of years, resulting in the identification of genes associated with different diseases. The next step in translating these findings into biomedically useful information is to find out the mechanism of the action of these genes. However, GWAS studies often implicate genes whose functions are currently unknown; for example, MYEOV, ANKLE1, TMEM45B and ORAOV1 are found to be associated with breast cancer, but their molecular function is unknown. We carried out Bayesian inference of Gene Ontology (GO) term annotations of genes by employing the directed acyclic graph structure of GO and the network of protein-protein interactions (PPIs). The approach is designed based on the fact that two proteins that interact biophysically would be in physical proximity of each other, would possess complementary molecular function, and play role in related biological processes. Predicted GO terms were ranked according to their relative association scores and the approach was evaluated quantitatively by plotting the precision versus recall values and F-scores (the harmonic mean of precision and recall) versus varying thresholds. Precisions of ~58% and ~ 40% for localization and functions respectively of proteins were determined at a threshold of ~30 (top 30 GO terms in the ranked list). Comparison with function prediction based on semantic similarity among nodes in an ontology and incorporation of those similarities in a k-nearest neighbor classifier confirmed that our results compared favorably. This approach was applied to predict the cellular component and molecular function GO terms of all human proteins that have interacting partners possessing at least one known GO annotation. The list of predictions is available at http://severus.dbmi.pitt.edu/engo/GOPRED.html. We present the algorithm, evaluations and the results of the computational predictions, especially for genes identified in

  9. Using deep RNA sequencing for the structural annotation of the Laccaria bicolor mycorrhizal transcriptome.

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    Peter E Larsen

    Full Text Available BACKGROUND: Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. METHODOLOGY: We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derived from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96% successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. CONCLUSIONS: 69% of expressed mycorrhizal JGI "best" gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene

  10. Using deep RNA sequencing for the structural annotation of the laccaria bicolor mycorrhizal transcriptome.

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, P. E.; Trivedi, G.; Sreedasyam, A.; Lu, V.; Podila, G. K.; Collart, F. R.; Biosciences Division; Univ. of Alabama

    2010-07-06

    Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derived from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. 69% of expressed mycorrhizal JGI 'best' gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided

  11. A collection of bioconductor methods to visualize gene-list annotations

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    Kibbe Warren A

    2010-01-01

    Full Text Available Abstract Background Gene-list annotations are critical for researchers to explore the complex relationships between genes and functionalities. Currently, the annotations of a gene list are usually summarized by a table or a barplot. As such, potentially biologically important complexities such as one gene belonging to multiple annotation categories are difficult to extract. We have devised explicit and efficient visualization methods that provide intuitive methods for interrogating the intrinsic connections between biological categories and genes. Findings We have constructed a data model and now present two novel methods in a Bioconductor package, "GeneAnswers", to simultaneously visualize genes, concepts (a.k.a. annotation categories, and concept-gene connections (a.k.a. annotations: the "Concept-and-Gene Network" and the "Concept-and-Gene Cross Tabulation". These methods have been tested and validated with microarray-derived gene lists. Conclusions These new visualization methods can effectively present annotations using Gene Ontology, Disease Ontology, or any other user-defined gene annotations that have been pre-associated with an organism's genome by human curation, automated pipelines, or a combination of the two. The gene-annotation data model and associated methods are available in the Bioconductor package called "GeneAnswers " described in this publication.

  12. A robust data-driven approach for gene ontology annotation.

    Science.gov (United States)

    Li, Yanpeng; Yu, Hong

    2014-01-01

    Gene ontology (GO) and GO annotation are important resources for biological information management and knowledge discovery, but the speed of manual annotation became a major bottleneck of database curation. BioCreative IV GO annotation task aims to evaluate the performance of system that automatically assigns GO terms to genes based on the narrative sentences in biomedical literature. This article presents our work in this task as well as the experimental results after the competition. For the evidence sentence extraction subtask, we built a binary classifier to identify evidence sentences using reference distance estimator (RDE), a recently proposed semi-supervised learning method that learns new features from around 10 million unlabeled sentences, achieving an F1 of 19.3% in exact match and 32.5% in relaxed match. In the post-submission experiment, we obtained 22.1% and 35.7% F1 performance by incorporating bigram features in RDE learning. In both development and test sets, RDE-based method achieved over 20% relative improvement on F1 and AUC performance against classical supervised learning methods, e.g. support vector machine and logistic regression. For the GO term prediction subtask, we developed an information retrieval-based method to retrieve the GO term most relevant to each evidence sentence using a ranking function that combined cosine similarity and the frequency of GO terms in documents, and a filtering method based on high-level GO classes. The best performance of our submitted runs was 7.8% F1 and 22.2% hierarchy F1. We found that the incorporation of frequency information and hierarchy filtering substantially improved the performance. In the post-submission evaluation, we obtained a 10.6% F1 using a simpler setting. Overall, the experimental analysis showed our approaches were robust in both the two tasks.

  13. Automatic annotation of protein motif function with Gene Ontology terms

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    Gopalakrishnan Vanathi

    2004-09-01

    Full Text Available Abstract Background Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, amuch needed and importanttask is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. Results This paperpresents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifsis viewed as both a binary classification and information retrieval problem, where PROSITE motifs are used as samples for mode training and functional prediction. The mutual information of a motif and aGO term association isfound to be a very useful feature. We take advantageof the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correctassociation. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. Conclusions In this research, different methods for automatic annotation of protein motifs have been investigated. Empirical result demonstrated that the methods have a great potential for detecting and augmenting information about thefunctions of newly discovered candidate protein motifs.

  14. Canine candidate genes for dilated cardiomyopathy: annotation of and polymorphic markers for 14 genes

    Directory of Open Access Journals (Sweden)

    van Oost Bernard A

    2007-10-01

    Full Text Available Abstract Background Dilated cardiomyopathy is a myocardial disease occurring in humans and domestic animals and is characterized by dilatation of the left ventricle, reduced systolic function and increased sphericity of the left ventricle. Dilated cardiomyopathy has been observed in several, mostly large and giant, dog breeds, such as the Dobermann and the Great Dane. A number of genes have been identified, which are associated with dilated cardiomyopathy in the human, mouse and hamster. These genes mainly encode structural proteins of the cardiac myocyte. Results We present the annotation of, and marker development for, 14 of these genes of the dog genome, i.e. α-cardiac actin, caveolin 1, cysteine-rich protein 3, desmin, lamin A/C, LIM-domain binding factor 3, myosin heavy polypeptide 7, phospholamban, sarcoglycan δ, titin cap, α-tropomyosin, troponin I, troponin T and vinculin. A total of 33 Single Nucleotide Polymorphisms were identified for these canine genes and 11 polymorphic microsatellite repeats were developed. Conclusion The presented polymorphisms provide a tool to investigate the role of the corresponding genes in canine Dilated Cardiomyopathy by linkage analysis or association studies.

  15. The use of multiple hierarchically independent gene ontology terms in gene function prediction and genome annotation

    NARCIS (Netherlands)

    Kourmpetis, Y.I.A.; Burgt, van der A.; Bink, M.C.A.M.; Braak, ter C.J.F.; Ham, van R.C.H.J.

    2007-01-01

    The Gene Ontology (GO) is a widely used controlled vocabulary for the description of gene function. In this study we quantify the usage of multiple and hierarchically independent GO terms in the curated genome annotations of seven well-studied species. In most genomes, significant proportions (6 -

  16. OAHG: an integrated resource for annotating human genes with multi-level ontologies

    Science.gov (United States)

    Cheng, Liang; Sun, Jie; Xu, Wanying; Dong, Lixiang; Hu, Yang; Zhou, Meng

    2016-01-01

    OAHG, an integrated resource, aims to establish a comprehensive functional annotation resource for human protein-coding genes (PCGs), miRNAs, and lncRNAs by multi-level ontologies involving Gene Ontology (GO), Disease Ontology (DO), and Human Phenotype Ontology (HPO). Many previous studies have focused on inferring putative properties and biological functions of PCGs and non-coding RNA genes from different perspectives. During the past several decades, a few of databases have been designed to annotate the functions of PCGs, miRNAs, and lncRNAs, respectively. A part of functional descriptions in these databases were mapped to standardize terminologies, such as GO, which could be helpful to do further analysis. Despite these developments, there is no comprehensive resource recording the function of these three important types of genes. The current version of OAHG, release 1.0 (Jun 2016), integrates three ontologies involving GO, DO, and HPO, six gene functional databases and two interaction databases. Currently, OAHG contains 1,434,694 entries involving 16,929 PCGs, 637 miRNAs, 193 lncRNAs, and 24,894 terms of ontologies. During the performance evaluation, OAHG shows the consistencies with existing gene interactions and the structure of ontology. For example, terms with more similar structure could be associated with more associated genes (Pearson correlation γ2 = 0.2428, p < 2.2e–16). PMID:27703231

  17. Annotation des structures discursives : l'expérience ANNODIS

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    Ho-Dac Lydia-Mai

    2014-07-01

    Full Text Available La ressource ANNODIS est un corpus diversifié de français écrit enrichi d'annotations concernant le niveau discursif. Son originalité réside dans sa mutualisation de deux approches complémentaires qui permettent, par leur oppositions et rapprochements, de poser un certain nombre de questions concernant l'annotation de structures discursives. cet article propose de revenir sur les enjeux principaux qui ont motivés les membres du projet ANNODIS : 1 stabiliser un certain nombre de définition linguistique de phénomènes discursives ciblées et 2 confronter aux données réelles une certaine modélisation de la construction de la cohérence discursive. Ce double objectif est révélateur des deux approches mises à l'épreuve dans l'expérience ANNODIS. Cet article revient sur les enjeux de cette ressource en terme à la fois de structures discursives et de campagne d'annotation. Un regard particulier sera porté sur la question du devenir des annotations, notamment dans un domaine encore peu stabilisé.

  18. Annotating the Function of the Human Genome with Gene Ontology and Disease Ontology.

    Science.gov (United States)

    Hu, Yang; Zhou, Wenyang; Ren, Jun; Dong, Lixiang; Wang, Yadong; Jin, Shuilin; Cheng, Liang

    2016-01-01

    Increasing evidences indicated that function annotation of human genome in molecular level and phenotype level is very important for systematic analysis of genes. In this study, we presented a framework named Gene2Function to annotate Gene Reference into Functions (GeneRIFs), in which each functional description of GeneRIFs could be annotated by a text mining tool Open Biomedical Annotator (OBA), and each Entrez gene could be mapped to Human Genome Organisation Gene Nomenclature Committee (HGNC) gene symbol. After annotating all the records about human genes of GeneRIFs, 288,869 associations between 13,148 mRNAs and 7,182 terms, 9,496 associations between 948 microRNAs and 533 terms, and 901 associations between 139 long noncoding RNAs (lncRNAs) and 297 terms were obtained as a comprehensive annotation resource of human genome. High consistency of term frequency of individual gene (Pearson correlation = 0.6401, p = 2.2e - 16) and gene frequency of individual term (Pearson correlation = 0.1298, p = 3.686e - 14) in GeneRIFs and GOA shows our annotation resource is very reliable.

  19. Structure and inference in annotated networks

    Science.gov (United States)

    Newman, M. E. J.; Clauset, Aaron

    2016-06-01

    For many networks of scientific interest we know both the connections of the network and information about the network nodes, such as the age or gender of individuals in a social network. Here we demonstrate how this `metadata' can be used to improve our understanding of network structure. We focus in particular on the problem of community detection in networks and develop a mathematically principled approach that combines a network and its metadata to detect communities more accurately than can be done with either alone. Crucially, the method does not assume that the metadata are correlated with the communities we are trying to find. Instead, the method learns whether a correlation exists and correctly uses or ignores the metadata depending on whether they contain useful information. We demonstrate our method on synthetic networks with known structure and on real-world networks, large and small, drawn from social, biological and technological domains.

  20. Gene expression and functional annotation of the human and mouse choroid plexus epithelium.

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    Sarah F Janssen

    Full Text Available BACKGROUND: The choroid plexus epithelium (CPE is a lobed neuro-epithelial structure that forms the outer blood-brain barrier. The CPE protrudes into the brain ventricles and produces the cerebrospinal fluid (CSF, which is crucial for brain homeostasis. Malfunction of the CPE is possibly implicated in disorders like Alzheimer disease, hydrocephalus or glaucoma. To study human genetic diseases and potential new therapies, mouse models are widely used. This requires a detailed knowledge of similarities and differences in gene expression and functional annotation between the species. The aim of this study is to analyze and compare gene expression and functional annotation of healthy human and mouse CPE. METHODS: We performed 44k Agilent microarray hybridizations with RNA derived from laser dissected healthy human and mouse CPE cells. We functionally annotated and compared the gene expression data of human and mouse CPE using the knowledge database Ingenuity. We searched for common and species specific gene expression patterns and function between human and mouse CPE. We also made a comparison with previously published CPE human and mouse gene expression data. RESULTS: Overall, the human and mouse CPE transcriptomes are very similar. Their major functionalities included epithelial junctions, transport, energy production, neuro-endocrine signaling, as well as immunological, neurological and hematological functions and disorders. The mouse CPE presented two additional functions not found in the human CPE: carbohydrate metabolism and a more extensive list of (neural developmental functions. We found three genes specifically expressed in the mouse CPE compared to human CPE, being ACE, PON1 and TRIM3 and no human specifically expressed CPE genes compared to mouse CPE. CONCLUSION: Human and mouse CPE transcriptomes are very similar, and display many common functionalities. Nonetheless, we also identified a few genes and pathways which suggest that the CPE

  1. Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger

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    Grigoriev Igor V

    2009-02-01

    Full Text Available Abstract Background Proteomic data is a potentially rich, but arguably unexploited, data source for genome annotation. Peptide identifications from tandem mass spectrometry provide prima facie evidence for gene predictions and can discriminate over a set of candidate gene models. Here we apply this to the recently sequenced Aspergillus niger fungal genome from the Joint Genome Institutes (JGI and another predicted protein set from another A.niger sequence. Tandem mass spectra (MS/MS were acquired from 1d gel electrophoresis bands and searched against all available gene models using Average Peptide Scoring (APS and reverse database searching to produce confident identifications at an acceptable false discovery rate (FDR. Results 405 identified peptide sequences were mapped to 214 different A.niger genomic loci to which 4093 predicted gene models clustered, 2872 of which contained the mapped peptides. Interestingly, 13 (6% of these loci either had no preferred predicted gene model or the genome annotators' chosen "best" model for that genomic locus was not found to be the most parsimonious match to the identified peptides. The peptides identified also boosted confidence in predicted gene structures spanning 54 introns from different gene models. Conclusion This work highlights the potential of integrating experimental proteomics data into genomic annotation pipelines much as expressed sequence tag (EST data has been. A comparison of the published genome from another strain of A.niger sequenced by DSM showed that a number of the gene models or proteins with proteomics evidence did not occur in both genomes, further highlighting the utility of the method.

  2. Combining evidence, biomedical literature and statistical dependence: new insights for functional annotation of gene sets

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    Burgun Anita

    2006-05-01

    Full Text Available Abstract Background Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence or text-mining of the published scientific literature (literature profiling. Results We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2 and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells. Conclusion The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions.

  3. Multi-label Image Annotation by Structural Grouping Sparsity

    Science.gov (United States)

    Han, Yahong; Wu, Fei; Zhuang, Yueting

    We can obtain high-dimensional heterogeneous features from real-world images on photo-sharing website, for an example Flickr. Those features are implemented to describe their various aspects of visual characteristics, such as color, texture and shape etc. The heterogeneous features are often over-complete to describe certain semantic. Therefore, the selection of limited discriminative features for certain semantics is hence crucial to make the image understanding more interpretable. This chapter introduces one approach for multi-label image annotation with a regularized penalty. We call it Multi-label Image Boosting by the selection of heterogeneous features with structural Grouping Sparsity (MtBGS). MtBGS induces a (structural) sparse selection model to identify subgroups of homogeneous features for predicting a certain label. Moreover, the correlations among multiple tags are utilized in MtBGS to boost the performance of multi-label annotation. Extensive experiments on public image datasets show that the proposed approach has better multi-label image annotation performance and leads to a quite interpretable model for image understanding.

  4. Expression profiling of hypothetical genes in Desulfovibrio vulgaris leads to improved functional annotation

    Energy Technology Data Exchange (ETDEWEB)

    Elias, Dwayne A.; Mukhopadhyay, Aindrila; Joachimiak, Marcin P.; Drury, Elliott C.; Redding, Alyssa M.; Yen, Huei-Che B.; Fields, Matthew W.; Hazen, Terry C.; Arkin, Adam P.; Keasling, Jay D.; Wall, Judy D.

    2008-10-27

    Hypothetical and conserved hypothetical genes account for>30percent of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved hypothetical (9.5percent) along with 887 hypothetical genes (24.4percent). Given the large fraction of the genome, it is plausible that some of these genes serve critical cellular roles. The study goals were to determine which genes were expressed and provide a more functionally based annotation. To accomplish this, expression profiles of 1234 hypothetical and conserved genes were used from transcriptomic datasets of 11 environmental stresses, complemented with shotgun LC-MS/MS and AMT tag proteomic data. Genes were divided into putatively polycistronic operons and those predicted to be monocistronic, then classified by basal expression levels and grouped according to changes in expression for one or multiple stresses. 1212 of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes. Except for the latter, monocistronic gene annotation was expanded using the above criteria along with matching Clusters of Orthologous Groups. Polycistronic genes were annotated in the same manner with inferences from their proximity to more confidently annotated genes. Two targeted deletion mutants were used as test cases to determine the relevance of the inferred functional annotations.

  5. Gene discovery in the hamster: a comparative genomics approach for gene annotation by sequencing of hamster testis cDNAs

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    Khan Shafiq A

    2003-06-01

    Full Text Available Abstract Background Complete genome annotation will likely be achieved through a combination of computer-based analysis of available genome sequences combined with direct experimental characterization of expressed regions of individual genomes. We have utilized a comparative genomics approach involving the sequencing of randomly selected hamster testis cDNAs to begin to identify genes not previously annotated on the human, mouse, rat and Fugu (pufferfish genomes. Results 735 distinct sequences were analyzed for their relatedness to known sequences in public databases. Eight of these sequences were derived from previously unidentified genes and expression of these genes in testis was confirmed by Northern blotting. The genomic locations of each sequence were mapped in human, mouse, rat and pufferfish, where applicable, and the structure of their cognate genes was derived using computer-based predictions, genomic comparisons and analysis of uncharacterized cDNA sequences from human and macaque. Conclusion The use of a comparative genomics approach resulted in the identification of eight cDNAs that correspond to previously uncharacterized genes in the human genome. The proteins encoded by these genes included a new member of the kinesin superfamily, a SET/MYND-domain protein, and six proteins for which no specific function could be predicted. Each gene was expressed primarily in testis, suggesting that they may play roles in the development and/or function of testicular cells.

  6. DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis

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    Baseler Michael W

    2007-11-01

    Full Text Available Abstract Background Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis. Description The DAVID Knowledgebase is built around the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of gene/protein identifiers from a variety of public genomic resources into DAVID gene clusters. The grouping of such identifiers improves the cross-reference capability, particularly across NCBI and UniProt systems, enabling more than 40 publicly available functional annotation sources to be comprehensively integrated and centralized by the DAVID gene clusters. The simple, pair-wise, text format files which make up the DAVID Knowledgebase are freely downloadable for various data analysis uses. In addition, a well organized web interface allows users to query different types of heterogeneous annotations in a high-throughput manner. Conclusion The DAVID Knowledgebase is designed to facilitate high throughput gene functional analysis. For a given gene list, it not only provides the quick accessibility to a wide range of heterogeneous annotation data in a centralized location, but also enriches the level of biological information for an individual gene. Moreover, the entire DAVID Knowledgebase is freely downloadable or searchable at http://david.abcc.ncifcrf.gov/knowledgebase/.

  7. Ab initio gene identification: prokaryote genome annotation with GeneScan and GLIMMER

    Indian Academy of Sciences (India)

    Gautam Aggarwal; Ramakrishna Ramaswamy

    2002-02-01

    We compare the annotation of three complete genomes using the ab initio methods of gene identification GeneScan and GLIMMER. The annotation given in GenBank, the standard against which these are compared, has been made using GeneMark. We find a number of novel genes which are predicted by both methods used here, as well as a number of genes that are predicted by GeneMark, but are not identified by either of the nonconsensus methods that we have used. The three organisms studied here are all prokaryotic species with fairly compact genomes. The Fourier measure forms the basis for an efficient non-consensus method for gene prediction, and the algorithm GeneScan exploits this measure. We have bench-marked this program as well as GLIMMER using 3 complete prokaryotic genomes. An effort has also been made to study the limitations of these techniques for complete genome analysis. GeneScan and GLIMMER are of comparable accuracy insofar as gene-identification is concerned, with sensitivities and specificities typically greater than 0.9. The number of false predictions (both positive and negative) is higher for GeneScan as compared to GLIMMER, but in a significant number of cases, similar results are provided by the two techniques. This suggests that there could be some as-yet unidentified additional genes in these three genomes, and also that some of the putative identifications made hitherto might require re-evaluation. All these cases are discussed in detail.

  8. Transcriptome assembly, gene annotation and tissue gene expression atlas of the rainbow trout.

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    Mohamed Salem

    Full Text Available Efforts to obtain a comprehensive genome sequence for rainbow trout are ongoing and will be complemented by transcriptome information that will enhance genome assembly and annotation. Previously, transcriptome reference sequences were reported using data from different sources. Although the previous work added a great wealth of sequences, a complete and well-annotated transcriptome is still needed. In addition, gene expression in different tissues was not completely addressed in the previous studies. In this study, non-normalized cDNA libraries were sequenced from 13 different tissues of a single doubled haploid rainbow trout from the same source used for the rainbow trout genome sequence. A total of ~1.167 billion paired-end reads were de novo assembled using the Trinity RNA-Seq assembler yielding 474,524 contigs > 500 base-pairs. Of them, 287,593 had homologies to the NCBI non-redundant protein database. The longest contig of each cluster was selected as a reference, yielding 44,990 representative contigs. A total of 4,146 contigs (9.2%, including 710 full-length sequences, did not match any mRNA sequences in the current rainbow trout genome reference. Mapping reads to the reference genome identified an additional 11,843 transcripts not annotated in the genome. A digital gene expression atlas revealed 7,678 housekeeping and 4,021 tissue-specific genes. Expression of about 16,000-32,000 genes (35-71% of the identified genes accounted for basic and specialized functions of each tissue. White muscle and stomach had the least complex transcriptomes, with high percentages of their total mRNA contributed by a small number of genes. Brain, testis and intestine, in contrast, had complex transcriptomes, with a large numbers of genes involved in their expression patterns. This study provides comprehensive de novo transcriptome information that is suitable for functional and comparative genomics studies in rainbow trout, including annotation of the

  9. Transcript annotation in FANTOM3: mouse gene catalog based on physical cDNAs.

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    Norihiro Maeda

    2006-04-01

    Full Text Available The international FANTOM consortium aims to produce a comprehensive picture of the mammalian transcriptome, based upon an extensive cDNA collection and functional annotation of full-length enriched cDNAs. The previous dataset, FANTOM2, comprised 60,770 full-length enriched cDNAs. Functional annotation revealed that this cDNA dataset contained only about half of the estimated number of mouse protein-coding genes, indicating that a number of cDNAs still remained to be collected and identified. To pursue the complete gene catalog that covers all predicted mouse genes, cloning and sequencing of full-length enriched cDNAs has been continued since FANTOM2. In FANTOM3, 42,031 newly isolated cDNAs were subjected to functional annotation, and the annotation of 4,347 FANTOM2 cDNAs was updated. To accomplish accurate functional annotation, we improved our automated annotation pipeline by introducing new coding sequence prediction programs and developed a Web-based annotation interface for simplifying the annotation procedures to reduce manual annotation errors. Automated coding sequence and function prediction was followed with manual curation and review by expert curators. A total of 102,801 full-length enriched mouse cDNAs were annotated. Out of 102,801 transcripts, 56,722 were functionally annotated as protein coding (including partial or truncated transcripts, providing to our knowledge the greatest current coverage of the mouse proteome by full-length cDNAs. The total number of distinct non-protein-coding transcripts increased to 34,030. The FANTOM3 annotation system, consisting of automated computational prediction, manual curation, and final expert curation, facilitated the comprehensive characterization of the mouse transcriptome, and could be applied to the transcriptomes of other species.

  10. An automated annotation tool for genomic DNA sequences using GeneScan and BLAST

    Indian Academy of Sciences (India)

    Andrew M. Lynn; Chakresh Kumar Jain; K. Kosalai; Pranjan Barman; Nupur Thakur; Harish Batra; Alok Bhattacharya

    2001-04-01

    Genomic sequence data are often available well before the annotated sequence is published. We present a method for analysis of genomic DNA to identify coding sequences using the GeneScan algorithm and characterize these resultant sequences by BLAST. The routines are used to develop a system for automated annotation of genome DNA sequences.

  11. Manual annotation and analysis of the defensin gene cluster in the C57BL/6J mouse reference genome

    Directory of Open Access Journals (Sweden)

    Dougan Gordon

    2009-12-01

    Full Text Available Abstract Background Host defense peptides are a critical component of the innate immune system. Human alpha- and beta-defensin genes are subject to copy number variation (CNV and historically the organization of mouse alpha-defensin genes has been poorly defined. Here we present the first full manual genomic annotation of the mouse defensin region on Chromosome 8 of the reference strain C57BL/6J, and the analysis of the orthologous regions of the human and rat genomes. Problems were identified with the reference assemblies of all three genomes. Defensins have been studied for over two decades and their naming has become a critical issue due to incorrect identification of defensin genes derived from different mouse strains and the duplicated nature of this region. Results The defensin gene cluster region on mouse Chromosome 8 A2 contains 98 gene loci: 53 are likely active defensin genes and 22 defensin pseudogenes. Several TATA box motifs were found for human and mouse defensin genes that likely impact gene expression. Three novel defensin genes belonging to the Cryptdin Related Sequences (CRS family were identified. All additional mouse defensin loci on Chromosomes 1, 2 and 14 were annotated and unusual splice variants identified. Comparison of the mouse alpha-defensins in the three main mouse reference gene sets Ensembl, Mouse Genome Informatics (MGI, and NCBI RefSeq reveals significant inconsistencies in annotation and nomenclature. We are collaborating with the Mouse Genome Nomenclature Committee (MGNC to establish a standardized naming scheme for alpha-defensins. Conclusions Prior to this analysis, there was no reliable reference gene set available for the mouse strain C57BL/6J defensin genes, demonstrating that manual intervention is still critical for the annotation of complex gene families and heavily duplicated regions. Accurate gene annotation is facilitated by the annotation of pseudogenes and regulatory elements. Manually curated gene

  12. FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression

    Directory of Open Access Journals (Sweden)

    Kolell Kevin J

    2004-12-01

    Full Text Available Abstract Background While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes. Results We describe a bioinformatics pipeline known as FunnyBase that has been used to store, annotate, and analyze 40,363 expressed sequence tags (ESTs from the heart and liver of the fish, Fundulus heteroclitus. Primary annotations based on sequence similarity are linked to networks of systematic annotation in Gene Ontology (GO and the Kyoto Encyclopedia of Genes and Genomes (KEGG and can be queried and computationally utilized in downstream analyses. Steps are taken to ensure that the annotation is self-consistent and that the structure of GO is used to identify higher level functions that may not be annotated directly. An integrated framework for cDNA library production, sequencing, quality control, expression data generation, and systems-level analysis is presented and utilized. In a case study, a set of genes, that had statistically significant regression between gene expression levels and environmental temperature along the Atlantic Coast, shows a statistically significant (P Conclusion The methods described have application for functional genomics studies, particularly among non-model organisms. The web interface for FunnyBase can be accessed at http://genomics.rsmas.miami.edu/funnybase/super_craw4/. Data and source code are available by request at jpaschall@bioinfobase.umkc.edu.

  13. NuChart: an R package to study gene spatial neighbourhoods with multi-omics annotations.

    Directory of Open Access Journals (Sweden)

    Ivan Merelli

    Full Text Available Long-range chromosomal associations between genomic regions, and their repositioning in the 3D space of the nucleus, are now considered to be key contributors to the regulation of gene expression and important links have been highlighted with other genomic features involved in DNA rearrangements. Recent Chromosome Conformation Capture (3C measurements performed with high throughput sequencing (Hi-C and molecular dynamics studies show that there is a large correlation between colocalization and coregulation of genes, but these important researches are hampered by the lack of biologists-friendly analysis and visualisation software. Here, we describe NuChart, an R package that allows the user to annotate and statistically analyse a list of input genes with information relying on Hi-C data, integrating knowledge about genomic features that are involved in the chromosome spatial organization. NuChart works directly with sequenced reads to identify the related Hi-C fragments, with the aim of creating gene-centric neighbourhood graphs on which multi-omics features can be mapped. Predictions about CTCF binding sites, isochores and cryptic Recombination Signal Sequences are provided directly with the package for mapping, although other annotation data in bed format can be used (such as methylation profiles and histone patterns. Gene expression data can be automatically retrieved and processed from the Gene Expression Omnibus and ArrayExpress repositories to highlight the expression profile of genes in the identified neighbourhood. Moreover, statistical inferences about the graph structure and correlations between its topology and multi-omics features can be performed using Exponential-family Random Graph Models. The Hi-C fragment visualisation provided by NuChart allows the comparisons of cells in different conditions, thus providing the possibility of novel biomarkers identification. NuChart is compliant with the Bioconductor standard and it is freely

  14. Automated update, revision, and quality control of the maize genome annotations using MAKER-P improves the B73 RefGen_v3 gene models and identifies new genes

    Science.gov (United States)

    The large size and relative complexity of many plant genomes make creation, quality control, and dissemination of high-quality gene structure annotations challenging. In response, we have developed MAKER-P, a fast and easy-to-use genome annotation engine for plants. Here, we report the use of MAKER-...

  15. Software Suite for Gene and Protein Annotation Prediction and Similarity Search.

    Science.gov (United States)

    Chicco, Davide; Masseroli, Marco

    2015-01-01

    In the computational biology community, machine learning algorithms are key instruments for many applications, including the prediction of gene-functions based upon the available biomolecular annotations. Additionally, they may also be employed to compute similarity between genes or proteins. Here, we describe and discuss a software suite we developed to implement and make publicly available some of such prediction methods and a computational technique based upon Latent Semantic Indexing (LSI), which leverages both inferred and available annotations to search for semantically similar genes. The suite consists of three components. BioAnnotationPredictor is a computational software module to predict new gene-functions based upon Singular Value Decomposition of available annotations. SimilBio is a Web module that leverages annotations available or predicted by BioAnnotationPredictor to discover similarities between genes via LSI. The suite includes also SemSim, a new Web service built upon these modules to allow accessing them programmatically. We integrated SemSim in the Bio Search Computing framework (http://www.bioinformatics.deib. polimi.it/bio-seco/seco/), where users can exploit the Search Computing technology to run multi-topic complex queries on multiple integrated Web services. Accordingly, researchers may obtain ranked answers involving the computation of the functional similarity between genes in support of biomedical knowledge discovery.

  16. Visual presentation as a welcome alternative to textual presentation of gene annotation information.

    Science.gov (United States)

    Desai, Jairav; Flatow, Jared M; Song, Jie; Zhu, Lihua J; Du, Pan; Huang, Chiang-Ching; Lu, Hui; Lin, Simon M; Kibbe, Warren A

    2010-01-01

    The functions of a gene are traditionally annotated textually using either free text (Gene Reference Into Function or GeneRIF) or controlled vocabularies (e.g., Gene Ontology or Disease Ontology). Inspired by the latest word cloud tools developed by the Information Visualization Group at IBM Research, we have prototyped a visual system for capturing gene annotations, which we named Gene Graph Into Function or GeneGIF. Fully developing the GeneGIF system would be a significant effort. To justify the necessity and to specify the design requirements of GeneGIF, we first surveyed the end-user preferences. From 53 responses, we found that a majority (64%, p 0.05) of the users favored visual presentation of information (GeneGIF) compared to textual (GeneRIF) information. The results of this study indicate that a visual presentation tool, such as GeneGIF, can complement standard textual presentation of gene annotations. Moreover, the survey participants provided many constructive comments that will specify the development of a phase-two project (http://128.248.174.241/) to visually annotate each gene in the human genome.

  17. Evaluation of clustering algorithms for gene expression data using gene ontology annotations

    Institute of Scientific and Technical Information of China (English)

    MA Ning; ZHANG Zheng-guo

    2012-01-01

    Background Clustering is a useful exploratory technique for interpreting gene expression data to reveal groups of genes sharing common functional attributes.Biologists frequently face the problem of choosing an appropriate algorithm.We aimed to provide a standalone,easily accessible and biologically oriented criterion for expression data clustering evaluation.Methods An external criterion utilizing annotation based similarities between genes is proposed in this work.Gene ontology information is employed as the annotation source.Comparisons among six widely used clustering algorithms over various types of gene expression data sets were carried out based on the criterion proposed.Results The rank of these algorithms given by the criterion coincides with our common knowledge.Single-linkage has significantly poorer performance,even worse than the random algorithm.Ward's method archives the best performance in most cases.Conclusions The criterion proposed has a strong ability to distinguish among different clustering algorithms with different distance measurements.It is also demonstrated that analyzing main contributors of the criterion may offer some guidelines in finding local compact clusters.As an addition,we suggest using Ward's algorithm for gene expression data analysis.

  18. goSTAG: gene ontology subtrees to tag and annotate genes within a set.

    Science.gov (United States)

    Bennett, Brian D; Bushel, Pierre R

    2017-01-01

    Over-representation analysis (ORA) detects enrichment of genes within biological categories. Gene Ontology (GO) domains are commonly used for gene/gene-product annotation. When ORA is employed, often times there are hundreds of statistically significant GO terms per gene set. Comparing enriched categories between a large number of analyses and identifying the term within the GO hierarchy with the most connections is challenging. Furthermore, ascertaining biological themes representative of the samples can be highly subjective from the interpretation of the enriched categories. We developed goSTAG for utilizing GO Subtrees to Tag and Annotate Genes that are part of a set. Given gene lists from microarray, RNA sequencing (RNA-Seq) or other genomic high-throughput technologies, goSTAG performs GO enrichment analysis and clusters the GO terms based on the p-values from the significance tests. GO subtrees are constructed for each cluster, and the term that has the most paths to the root within the subtree is used to tag and annotate the cluster as the biological theme. We tested goSTAG on a microarray gene expression data set of samples acquired from the bone marrow of rats exposed to cancer therapeutic drugs to determine whether the combination or the order of administration influenced bone marrow toxicity at the level of gene expression. Several clusters were labeled with GO biological processes (BPs) from the subtrees that are indicative of some of the prominent pathways modulated in bone marrow from animals treated with an oxaliplatin/topotecan combination. In particular, negative regulation of MAP kinase activity was the biological theme exclusively in the cluster associated with enrichment at 6 h after treatment with oxaliplatin followed by control. However, nucleoside triphosphate catabolic process was the GO BP labeled exclusively at 6 h after treatment with topotecan followed by control. goSTAG converts gene lists from genomic analyses into biological themes

  19. ArrayIDer: automated structural re-annotation pipeline for DNA microarrays

    Directory of Open Access Journals (Sweden)

    McCarthy Fiona M

    2009-01-01

    Full Text Available Abstract Background Systems biology modeling from microarray data requires the most contemporary structural and functional array annotation. However, microarray annotations, especially for non-commercial, non-traditional biomedical model organisms, are often dated. In addition, most microarray analysis tools do not readily accept EST clone names, which are abundantly represented on arrays. Manual re-annotation of microarrays is impracticable and so we developed a computational re-annotation tool (ArrayIDer to retrieve the most recent accession mapping files from public databases based on EST clone names or accessions and rapidly generate database accessions for entire microarrays. Results We utilized the Fred Hutchinson Cancer Research Centre 13K chicken cDNA array – a widely-used non-commercial chicken microarray – to demonstrate the principle that ArrayIDer could markedly improve annotation. We structurally re-annotated 55% of the entire array. Moreover, we decreased non-chicken functional annotations by 2 fold. One beneficial consequence of our re-annotation was to identify 290 pseudogenes, of which 66 were previously incorrectly annotated. Conclusion ArrayIDer allows rapid automated structural re-annotation of entire arrays and provides multiple accession types for use in subsequent functional analysis. This information is especially valuable for systems biology modeling in the non-traditional biomedical model organisms.

  20. A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences.

    Science.gov (United States)

    Othman, Razib M; Deris, Safaai; Illias, Rosli M

    2008-02-01

    A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. Then, the parallel genetic algorithm is employed to perform batch retrieval and to accelerate the search in large search space of the Gene Ontology graph. The genetic similarity algorithm is implemented in the Gene Ontology browser named basic UTMGO to overcome the weaknesses of the existing Gene Ontology browsers which use a conventional approach based on keyword matching. To show the applicability of the basic UTMGO, we extend its structure to develop a Gene Ontology -based protein sequence annotation tool named extended UTMGO. The objective of developing the extended UTMGO is to provide a simple and practical tool that is capable of producing better results and requires a reasonable amount of running time with low computing cost specifically for offline usage. The computational results and comparison with other related tools are presented to show the effectiveness of the proposed algorithm and tools.

  1. Annotation and Re-Sequencing of Genes from De Novo Transcriptome Assembly of Abies alba (Pinaceae

    Directory of Open Access Journals (Sweden)

    Anna M. Roschanski

    2013-01-01

    Full Text Available Premise of the study: We present a protocol for the annotation of transcriptome sequence data and the identification of candidate genes therein using the example of the nonmodel conifer Abies alba. Methods and Results: A normalized cDNA library was built from an A. alba seedling. The sequencing on a 454 platform yielded more than 1.5 million reads that were de novo assembled into 25 149 contigs. Two complementary approaches were applied to annotate gene fragments that code for (1 well-known proteins and (2 proteins that are potentially adaptively relevant. Primer development and testing yielded 88 amplicons that could successfully be resequenced from genomic DNA. Conclusions: The annotation workflow offers an efficient way to identify potential adaptively relevant genes from the large quantity of transcriptome sequence data. The primer set presented should be prioritized for single-nucleotide polymorphism detection in adaptively relevant genes in A. alba.

  2. High-performance web services for querying gene and variant annotation.

    Science.gov (United States)

    Xin, Jiwen; Mark, Adam; Afrasiabi, Cyrus; Tsueng, Ginger; Juchler, Moritz; Gopal, Nikhil; Stupp, Gregory S; Putman, Timothy E; Ainscough, Benjamin J; Griffith, Obi L; Torkamani, Ali; Whetzel, Patricia L; Mungall, Christopher J; Mooney, Sean D; Su, Andrew I; Wu, Chunlei

    2016-05-06

    Efficient tools for data management and integration are essential for many aspects of high-throughput biology. In particular, annotations of genes and human genetic variants are commonly used but highly fragmented across many resources. Here, we describe MyGene.info and MyVariant.info, high-performance web services for querying gene and variant annotation information. These web services are currently accessed more than three million times permonth. They also demonstrate a generalizable cloud-based model for organizing and querying biological annotation information. MyGene.info and MyVariant.info are provided as high-performance web services, accessible at http://mygene.info and http://myvariant.info . Both are offered free of charge to the research community.

  3. SpectroGene: A Tool for Proteogenomic Annotations Using Top-Down Spectra.

    Science.gov (United States)

    Kolmogorov, Mikhail; Liu, Xiaowen; Pevzner, Pavel A

    2016-01-01

    In the past decade, proteogenomics has emerged as a valuable technique that contributes to the state-of-the-art in genome annotation; however, previous proteogenomic studies were limited to bottom-up mass spectrometry and did not take advantage of top-down approaches. We show that top-down proteogenomics allows one to address the problems that remained beyond the reach of traditional bottom-up proteogenomics. In particular, we show that top-down proteogenomics leads to the discovery of previously unannotated genes even in extensively studied bacterial genomes and present SpectroGene, a software tool for genome annotation using top-down tandem mass spectra. We further show that top-down proteogenomics searches (against the six-frame translation of a genome) identify nearly all proteoforms found in traditional top-down proteomics searches (against the annotated proteome). SpectroGene is freely available at http://github.com/fenderglass/SpectroGene .

  4. Integrating multiple genome annotation databases improves the interpretation of microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Kennedy Breandan

    2010-01-01

    Full Text Available Abstract Background The Affymetrix GeneChip is a widely used gene expression profiling platform. Since the chips were originally designed, the genome databases and gene definitions have been considerably updated. Thus, more accurate interpretation of microarray data requires parallel updating of the specificity of GeneChip probes. We propose a new probe remapping protocol, using the zebrafish GeneChips as an example, by removing nonspecific probes, and grouping the probes into transcript level probe sets using an integrated zebrafish genome annotation. This genome annotation is based on combining transcript information from multiple databases. This new remapping protocol, especially the new genome annotation, is shown here to be an important factor in improving the interpretation of gene expression microarray data. Results Transcript data from the RefSeq, GenBank and Ensembl databases were downloaded from the UCSC genome browser, and integrated to generate a combined zebrafish genome annotation. Affymetrix probes were filtered and remapped according to the new annotation. The influence of transcript collection and gene definition methods was tested using two microarray data sets. Compared to remapping using a single database, this new remapping protocol results in up to 20% more probes being retained in the remapping, leading to approximately 1,000 more genes being detected. The differentially expressed gene lists are consequently increased by up to 30%. We are also able to detect up to three times more alternative splicing events. A small number of the bioinformatics predictions were confirmed using real-time PCR validation. Conclusions By combining gene definitions from multiple databases, it is possible to greatly increase the numbers of genes and splice variants that can be detected in microarray gene expression experiments.

  5. PANDA: pathway and annotation explorer for visualizing and interpreting gene-centric data.

    Science.gov (United States)

    Hart, Steven N; Moore, Raymond M; Zimmermann, Michael T; Oliver, Gavin R; Egan, Jan B; Bryce, Alan H; Kocher, Jean-Pierre A

    2015-01-01

    Objective. Bringing together genomics, transcriptomics, proteomics, and other -omics technologies is an important step towards developing highly personalized medicine. However, instrumentation has advances far beyond expectations and now we are able to generate data faster than it can be interpreted. Materials and Methods. We have developed PANDA (Pathway AND Annotation) Explorer, a visualization tool that integrates gene-level annotation in the context of biological pathways to help interpret complex data from disparate sources. PANDA is a web-based application that displays data in the context of well-studied pathways like KEGG, BioCarta, and PharmGKB. PANDA represents data/annotations as icons in the graph while maintaining the other data elements (i.e., other columns for the table of annotations). Custom pathways from underrepresented diseases can be imported when existing data sources are inadequate. PANDA also allows sharing annotations among collaborators. Results. In our first use case, we show how easy it is to view supplemental data from a manuscript in the context of a user's own data. Another use-case is provided describing how PANDA was leveraged to design a treatment strategy from the somatic variants found in the tumor of a patient with metastatic sarcomatoid renal cell carcinoma. Conclusion. PANDA facilitates the interpretation of gene-centric annotations by visually integrating this information with context of biological pathways. The application can be downloaded or used directly from our website: http://bioinformaticstools.mayo.edu/research/panda-viewer/.

  6. PANDA: pathway and annotation explorer for visualizing and interpreting gene-centric data

    Directory of Open Access Journals (Sweden)

    Steven N. Hart

    2015-05-01

    Full Text Available Objective. Bringing together genomics, transcriptomics, proteomics, and other -omics technologies is an important step towards developing highly personalized medicine. However, instrumentation has advances far beyond expectations and now we are able to generate data faster than it can be interpreted. Materials and Methods. We have developed PANDA (Pathway AND Annotation Explorer, a visualization tool that integrates gene-level annotation in the context of biological pathways to help interpret complex data from disparate sources. PANDA is a web-based application that displays data in the context of well-studied pathways like KEGG, BioCarta, and PharmGKB. PANDA represents data/annotations as icons in the graph while maintaining the other data elements (i.e., other columns for the table of annotations. Custom pathways from underrepresented diseases can be imported when existing data sources are inadequate. PANDA also allows sharing annotations among collaborators. Results. In our first use case, we show how easy it is to view supplemental data from a manuscript in the context of a user’s own data. Another use-case is provided describing how PANDA was leveraged to design a treatment strategy from the somatic variants found in the tumor of a patient with metastatic sarcomatoid renal cell carcinoma. Conclusion. PANDA facilitates the interpretation of gene-centric annotations by visually integrating this information with context of biological pathways. The application can be downloaded or used directly from our website: http://bioinformaticstools.mayo.edu/research/panda-viewer/.

  7. Functional annotation and identification of candidate disease genes by computational analysis of normal tissue gene expression data.

    Directory of Open Access Journals (Sweden)

    Laura Miozzi

    Full Text Available BACKGROUND: High-throughput gene expression data can predict gene function through the "guilt by association" principle: coexpressed genes are likely to be functionally associated. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed publicly available expression data on normal human tissues. The analysis is based on the integration of data obtained with two experimental platforms (microarrays and SAGE and of various measures of dissimilarity between expression profiles. The building blocks of the procedure are the Ranked Coexpression Groups (RCG, small sets of tightly coexpressed genes which are analyzed in terms of functional annotation. Functionally characterized RCGs are selected by means of the majority rule and used to predict new functional annotations. Functionally characterized RCGs are enriched in groups of genes associated to similar phenotypes. We exploit this fact to find new candidate disease genes for many OMIM phenotypes of unknown molecular origin. CONCLUSIONS/SIGNIFICANCE: We predict new functional annotations for many human genes, showing that the integration of different data sets and coexpression measures significantly improves the scope of the results. Combining gene expression data, functional annotation and known phenotype-gene associations we provide candidate genes for several genetic diseases of unknown molecular basis.

  8. Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data

    Directory of Open Access Journals (Sweden)

    Merchant Sabeeha S

    2011-07-01

    Full Text Available Abstract Background Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. Description The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of

  9. Guidelines for the functional annotation of microRNAs using the Gene Ontology.

    Science.gov (United States)

    Huntley, Rachael P; Sitnikov, Dmitry; Orlic-Milacic, Marija; Balakrishnan, Rama; D'Eustachio, Peter; Gillespie, Marc E; Howe, Doug; Kalea, Anastasia Z; Maegdefessel, Lars; Osumi-Sutherland, David; Petri, Victoria; Smith, Jennifer R; Van Auken, Kimberly; Wood, Valerie; Zampetaki, Anna; Mayr, Manuel; Lovering, Ruth C

    2016-05-01

    MicroRNA regulation of developmental and cellular processes is a relatively new field of study, and the available research data have not been organized to enable its inclusion in pathway and network analysis tools. The association of gene products with terms from the Gene Ontology is an effective method to analyze functional data, but until recently there has been no substantial effort dedicated to applying Gene Ontology terms to microRNAs. Consequently, when performing functional analysis of microRNA data sets, researchers have had to rely instead on the functional annotations associated with the genes encoding microRNA targets. In consultation with experts in the field of microRNA research, we have created comprehensive recommendations for the Gene Ontology curation of microRNAs. This curation manual will enable provision of a high-quality, reliable set of functional annotations for the advancement of microRNA research. Here we describe the key aspects of the work, including development of the Gene Ontology to represent this data, standards for describing the data, and guidelines to support curators making these annotations. The full microRNA curation guidelines are available on the GO Consortium wiki (http://wiki.geneontology.org/index.php/MicroRNA_GO_annotation_manual). © 2016 Huntley et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  10. In Silico Structural and Functional Annotation of Hypothetical Proteins of Vibrio cholerae O139

    Science.gov (United States)

    Islam, Md. Saiful; Shahik, Shah Md.; Sohel, Md.; Patwary, Noman I. A.

    2015-01-01

    In developing countries threat of cholera is a significant health concern whenever water purification and sewage disposal systems are inadequate. Vibrio cholerae is one of the responsible bacteria involved in cholera disease. The complete genome sequence of V. cholerae deciphers the presence of various genes and hypothetical proteins whose function are not yet understood. Hence analyzing and annotating the structure and function of hypothetical proteins is important for understanding the V. cholerae. V. cholerae O139 is the most common and pathogenic bacterial strain among various V. cholerae strains. In this study sequence of six hypothetical proteins of V. cholerae O139 has been annotated from NCBI. Various computational tools and databases have been used to determine domain family, protein-protein interaction, solubility of protein, ligand binding sites etc. The three dimensional structure of two proteins were modeled and their ligand binding sites were identified. We have found domains and families of only one protein. The analysis revealed that these proteins might have antibiotic resistance activity, DNA breaking-rejoining activity, integrase enzyme activity, restriction endonuclease, etc. Structural prediction of these proteins and detection of binding sites from this study would indicate a potential target aiding docking studies for therapeutic designing against cholera. PMID:26175663

  11. Lynx web services for annotations and systems analysis of multi-gene disorders.

    Science.gov (United States)

    Sulakhe, Dinanath; Taylor, Andrew; Balasubramanian, Sandhya; Feng, Bo; Xie, Bingqing; Börnigen, Daniela; Dave, Utpal J; Foster, Ian T; Gilliam, T Conrad; Maltsev, Natalia

    2014-07-01

    Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform.

  12. SelenoDB 2.0: annotation of selenoprotein genes in animals and their genetic diversity in humans.

    Science.gov (United States)

    Romagné, Frédéric; Santesmasses, Didac; White, Louise; Sarangi, Gaurab K; Mariotti, Marco; Hübler, Ron; Weihmann, Antje; Parra, Genís; Gladyshev, Vadim N; Guigó, Roderic; Castellano, Sergi

    2014-01-01

    SelenoDB (http://www.selenodb.org) aims to provide high-quality annotations of selenoprotein genes, proteins and SECIS elements. Selenoproteins are proteins that contain the amino acid selenocysteine (Sec) and the first release of the database included annotations for eight species. Since the release of SelenoDB 1.0 many new animal genomes have been sequenced. The annotations of selenoproteins in new genomes usually contain many errors in major databases. For this reason, we have now fully annotated selenoprotein genes in 58 animal genomes. We provide manually curated annotations for human selenoproteins, whereas we use an automatic annotation pipeline to annotate selenoprotein genes in other animal genomes. In addition, we annotate the homologous genes containing cysteine (Cys) instead of Sec. Finally, we have surveyed genetic variation in the annotated genes in humans. We use exon capture and resequencing approaches to identify single-nucleotide polymorphisms in more than 50 human populations around the world. We thus present a detailed view of the genetic divergence of Sec- and Cys-containing genes in animals and their diversity in humans. The addition of these datasets into the second release of the database provides a valuable resource for addressing medical and evolutionary questions in selenium biology.

  13. Gene fusions and gene duplications: relevance to genomic annotation and functional analysis

    Directory of Open Access Journals (Sweden)

    Riley Monica

    2005-03-01

    Full Text Available Abstract Background Escherichia coli a model organism provides information for annotation of other genomes. Our analysis of its genome has shown that proteins encoded by fused genes need special attention. Such composite (multimodular proteins consist of two or more components (modules encoding distinct functions. Multimodular proteins have been found to complicate both annotation and generation of sequence similar groups. Previous work overstated the number of multimodular proteins in E. coli. This work corrects the identification of modules by including sequence information from proteins in 50 sequenced microbial genomes. Results Multimodular E. coli K-12 proteins were identified from sequence similarities between their component modules and non-fused proteins in 50 genomes and from the literature. We found 109 multimodular proteins in E. coli containing either two or three modules. Most modules had standalone sequence relatives in other genomes. The separated modules together with all the single (un-fused proteins constitute the sum of all unimodular proteins of E. coli. Pairwise sequence relationships among all E. coli unimodular proteins generated 490 sequence similar, paralogous groups. Groups ranged in size from 92 to 2 members and had varying degrees of relatedness among their members. Some E. coli enzyme groups were compared to homologs in other bacterial genomes. Conclusion The deleterious effects of multimodular proteins on annotation and on the formation of groups of paralogs are emphasized. To improve annotation results, all multimodular proteins in an organism should be detected and when known each function should be connected with its location in the sequence of the protein. When transferring functions by sequence similarity, alignment locations must be noted, particularly when alignments cover only part of the sequences, in order to enable transfer of the correct function. Separating multimodular proteins into module units makes

  14. Pairagon+N-SCAN_EST: a model-based gene annotation pipeline

    DEFF Research Database (Denmark)

    Arumugam, Manimozhiyan; Wei, Chaochun; Brown, Randall H

    2006-01-01

    This paper describes Pairagon+N-SCAN_EST, a gene annotation pipeline that uses only native alignments. For each expressed sequence it chooses the best genomic alignment. Systems like ENSEMBL and ExoGean rely on trans alignments, in which expressed sequences are aligned to the genomic loci...

  15. Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval

    Directory of Open Access Journals (Sweden)

    Yuan Lei

    2012-05-01

    Full Text Available Abstract Background Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords. Results In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes. Conclusions We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.

  16. Metalloproteomics: High-Throughput Structural and Functional Annotation of Proteins in Structural Genomics

    Energy Technology Data Exchange (ETDEWEB)

    Shi,W.; Zhan, C.; Lgnatov, A.; Manjasetty, B.; Marinkovic, N.; Sullivan, M.; Huang, R.; Chance, M.; Li, H.; et al.

    2005-01-01

    A high-throughput method for measuring transition metal content based on quantitation of X-ray fluorescence signals was used to analyze 654 proteins selected as targets by the New York Structural GenomiX Research Consortium. Over 10% showed the presence of transition metal atoms in stoichiometric amounts; these totals as well as the abundance distribution are similar to those of the Protein Data Bank. Bioinformatics analysis of the identified metalloproteins in most cases supported the metalloprotein annotation; identification of the conserved metal binding motif was also shown to be useful in verifying structural models of the proteins. Metalloproteomics provides a rapid structural and functional annotation for these sequences and is shown to be {approx}95% accurate in predicting the presence or absence of stoichiometric metal content. The project's goal is to assay at least 1 member from each Pfam family; approximately 500 Pfam families have been characterized with respect to transition metal content so far.

  17. Treebank annotation with a wide-coverage head-driven phrase structure grammar

    OpenAIRE

    Schmidtke, Dag

    2004-01-01

    In this dissertation I investigate ways to extend the annotation of treebanks, or parsed corpora, by taking advantage of the rich and sophisticated grammatical analysis embodied in a modern, constraint-based wide-coverage grammar. As the underlying processing engine I implement a full typed feature structure inference and HPSG parsing system in C#. I develop a method for annotating a treebank with typed feature structure information with the use of the LmGO ERG grammar, an existing widecovera...

  18. Annotating novel genes by integrating synthetic lethals and genomic information

    Directory of Open Access Journals (Sweden)

    Faty Mahamadou

    2008-01-01

    Full Text Available Abstract Background Large scale screening for synthetic lethality serves as a common tool in yeast genetics to systematically search for genes that play a role in specific biological processes. Often the amounts of data resulting from a single large scale screen far exceed the capacities of experimental characterization of every identified target. Thus, there is need for computational tools that select promising candidate genes in order to reduce the number of follow-up experiments to a manageable size. Results We analyze synthetic lethality data for arp1 and jnm1, two spindle migration genes, in order to identify novel members in this process. To this end, we use an unsupervised statistical method that integrates additional information from biological data sources, such as gene expression, phenotypic profiling, RNA degradation and sequence similarity. Different from existing methods that require large amounts of synthetic lethal data, our method merely relies on synthetic lethality information from two single screens. Using a Multivariate Gaussian Mixture Model, we determine the best subset of features that assign the target genes to two groups. The approach identifies a small group of genes as candidates involved in spindle migration. Experimental testing confirms the majority of our candidates and we present she1 (YBL031W as a novel gene involved in spindle migration. We applied the statistical methodology also to TOR2 signaling as another example. Conclusion We demonstrate the general use of Multivariate Gaussian Mixture Modeling for selecting candidate genes for experimental characterization from synthetic lethality data sets. For the given example, integration of different data sources contributes to the identification of genetic interaction partners of arp1 and jnm1 that play a role in the same biological process.

  19. Assessing identity, redundancy and confounds in Gene Ontology annotations over time.

    Science.gov (United States)

    Gillis, Jesse; Pavlidis, Paul

    2013-02-15

    The Gene Ontology (GO) is heavily used in systems biology, but the potential for redundancy, confounds with other data sources and problems with stability over time have been little explored. We report that GO annotations are stable over short periods, with 3% of genes not being most semantically similar to themselves between monthly GO editions. However, we find that genes can alter their 'functional identity' over time, with 20% of genes not matching to themselves (by semantic similarity) after 2 years. We further find that annotation bias in GO, in which some genes are more characterized than others, has declined in yeast, but generally increased in humans. Finally, we discovered that many entries in protein interaction databases are owing to the same published reports that are used for GO annotations, with 66% of assessed GO groups exhibiting this confound. We provide a case study to illustrate how this information can be used in analyses of gene sets and networks. Data available at http://chibi.ubc.ca/assessGO.

  20. Meta4: a web application for sharing and annotating metagenomic gene predictions using web services.

    Science.gov (United States)

    Richardson, Emily J; Escalettes, Franck; Fotheringham, Ian; Wallace, Robert J; Watson, Mick

    2013-01-01

    Whole-genome shotgun metagenomics experiments produce DNA sequence data from entire ecosystems, and provide a huge amount of novel information. Gene discovery projects require up-to-date information about sequence homology and domain structure for millions of predicted proteins to be presented in a simple, easy-to-use system. There is a lack of simple, open, flexible tools that allow the rapid sharing of metagenomics datasets with collaborators in a format they can easily interrogate. We present Meta4, a flexible and extensible web application that can be used to share and annotate metagenomic gene predictions. Proteins and predicted domains are stored in a simple relational database, with a dynamic front-end which displays the results in an internet browser. Web services are used to provide up-to-date information about the proteins from homology searches against public databases. Information about Meta4 can be found on the project website, code is available on Github, a cloud image is available, and an example implementation can be seen at.

  1. The AnnoLite and AnnoLyze programs for comparative annotation of protein structures

    Directory of Open Access Journals (Sweden)

    Dopazo Joaquín

    2007-05-01

    Full Text Available Abstract Background Advances in structural biology, including structural genomics, have resulted in a rapid increase in the number of experimentally determined protein structures. However, about half of the structures deposited by the structural genomics consortia have little or no information about their biological function. Therefore, there is a need for tools for automatically and comprehensively annotating the function of protein structures. We aim to provide such tools by applying comparative protein structure annotation that relies on detectable relationships between protein structures to transfer functional annotations. Here we introduce two programs, AnnoLite and AnnoLyze, which use the structural alignments deposited in the DBAli database. Description AnnoLite predicts the SCOP, CATH, EC, InterPro, PfamA, and GO terms with an average sensitivity of ~90% and average precision of ~80%. AnnoLyze predicts ligand binding site and domain interaction patches with an average sensitivity of ~70% and average precision of ~30%, correctly localizing binding sites for small molecules in ~95% of its predictions. Conclusion The AnnoLite and AnnoLyze programs for comparative annotation of protein structures can reliably and automatically annotate new protein structures. The programs are fully accessible via the Internet as part of the DBAli suite of tools at http://salilab.org/DBAli/.

  2. Non-Structured Materials Science Data Sharing Based on Semantic Annotation

    Directory of Open Access Journals (Sweden)

    Changjun Hu

    2009-04-01

    Full Text Available The explosion of non-structured materials science data makes it urgent for materials researchers to resolve the problem of how to effectively share this information. Materials science image data is an important class of non-structured data. This paper proposes a semantic annotation method to resolve the problem of materials science image data sharing. This method is implemented by a four-layer architecture, which includes ontology building, semantic annotation, reasoning service, and application. We take metallographic image data as an example and build a metallographic image OWL-ontology. Users can accomplish semantic annotation of metallographic image according to the ontology. Reasoning service is provided in a data sharing application to demonstrate the effective sharing of materials science image data through adding semantic annotation.

  3. Enriching the annotation of Mycobacterium tuberculosis H37Rv proteome using remote homology detection approaches: insights into structure and function.

    Science.gov (United States)

    Ramakrishnan, Gayatri; Ochoa-Montaño, Bernardo; Raghavender, Upadhyayula S; Mudgal, Richa; Joshi, Adwait G; Chandra, Nagasuma R; Sowdhamini, Ramanathan; Blundell, Tom L; Srinivasan, Narayanaswamy

    2015-01-01

    The availability of the genome sequence of Mycobacterium tuberculosis H37Rv has encouraged determination of large numbers of protein structures and detailed definition of the biological information encoded therein; yet, the functions of many proteins in M. tuberculosis remain unknown. The emergence of multidrug resistant strains makes it a priority to exploit recent advances in homology recognition and structure prediction to re-analyse its gene products. Here we report the structural and functional characterization of gene products encoded in the M. tuberculosis genome, with the help of sensitive profile-based remote homology search and fold recognition algorithms resulting in an enhanced annotation of the proteome where 95% of the M. tuberculosis proteins were identified wholly or partly with information on structure or function. New information includes association of 244 proteins with 205 domain families and a separate set of new association of folds to 64 proteins. Extending structural information across uncharacterized protein families represented in the M. tuberculosis proteome, by determining superfamily relationships between families of known and unknown structures, has contributed to an enhancement in the knowledge of structural content. In retrospect, such superfamily relationships have facilitated recognition of probable structure and/or function for several uncharacterized protein families, eventually aiding recognition of probable functions for homologous proteins corresponding to such families. Gene products unique to mycobacteria for which no functions could be identified are 183. Of these 18 were determined to be M. tuberculosis specific. Such pathogen-specific proteins are speculated to harbour virulence factors required for pathogenesis. A re-annotated proteome of M. tuberculosis, with greater completeness of annotated proteins and domain assigned regions, provides a valuable basis for experimental endeavours designed to obtain a better

  4. Improving pan-genome annotation using whole genome multiple alignment

    Directory of Open Access Journals (Sweden)

    Salzberg Steven L

    2011-06-01

    Full Text Available Abstract Background Rapid annotation and comparisons of genomes from multiple isolates (pan-genomes is becoming commonplace due to advances in sequencing technology. Genome annotations can contain inconsistencies and errors that hinder comparative analysis even within a single species. Tools are needed to compare and improve annotation quality across sets of closely related genomes. Results We introduce a new tool, Mugsy-Annotator, that identifies orthologs and evaluates annotation quality in prokaryotic genomes using whole genome multiple alignment. Mugsy-Annotator identifies anomalies in annotated gene structures, including inconsistently located translation initiation sites and disrupted genes due to draft genome sequencing or pseudogenes. An evaluation of species pan-genomes using the tool indicates that such anomalies are common, especially at translation initiation sites. Mugsy-Annotator reports alternate annotations that improve consistency and are candidates for further review. Conclusions Whole genome multiple alignment can be used to efficiently identify orthologs and annotation problem areas in a bacterial pan-genome. Comparisons of annotated gene structures within a species may show more variation than is actually present in the genome, indicating errors in genome annotation. Our new tool Mugsy-Annotator assists re-annotation efforts by highlighting edits that improve annotation consistency.

  5. Proteomic detection of non-annotated protein-coding genes in Pseudomonas fluorescens Pf0-1.

    Science.gov (United States)

    Kim, Wook; Silby, Mark W; Purvine, Sam O; Nicoll, Julie S; Hixson, Kim K; Monroe, Matt; Nicora, Carrie D; Lipton, Mary S; Levy, Stuart B

    2009-12-24

    Genome sequences are annotated by computational prediction of coding sequences, followed by similarity searches such as BLAST, which provide a layer of possible functional information. While the existence of processes such as alternative splicing complicates matters for eukaryote genomes, the view of bacterial genomes as a linear series of closely spaced genes leads to the assumption that computational annotations that predict such arrangements completely describe the coding capacity of bacterial genomes. We undertook a proteomic study to identify proteins expressed by Pseudomonas fluorescens Pf0-1 from genes that were not predicted during the genome annotation. Mapping peptides to the Pf0-1 genome sequence identified sixteen non-annotated protein-coding regions, of which nine were antisense to predicted genes, six were intergenic, and one read in the same direction as an annotated gene but in a different frame. The expression of all but one of the newly discovered genes was verified by RT-PCR. Few clues as to the function of the new genes were gleaned from informatic analyses, but potential orthologs in other Pseudomonas genomes were identified for eight of the new genes. The 16 newly identified genes improve the quality of the Pf0-1 genome annotation, and the detection of antisense protein-coding genes indicates the under-appreciated complexity of bacterial genome organization.

  6. Proteomic detection of non-annotated protein-coding genes in Pseudomonas fluorescens Pf0-1.

    Directory of Open Access Journals (Sweden)

    Wook Kim

    Full Text Available Genome sequences are annotated by computational prediction of coding sequences, followed by similarity searches such as BLAST, which provide a layer of possible functional information. While the existence of processes such as alternative splicing complicates matters for eukaryote genomes, the view of bacterial genomes as a linear series of closely spaced genes leads to the assumption that computational annotations that predict such arrangements completely describe the coding capacity of bacterial genomes. We undertook a proteomic study to identify proteins expressed by Pseudomonas fluorescens Pf0-1 from genes that were not predicted during the genome annotation. Mapping peptides to the Pf0-1 genome sequence identified sixteen non-annotated protein-coding regions, of which nine were antisense to predicted genes, six were intergenic, and one read in the same direction as an annotated gene but in a different frame. The expression of all but one of the newly discovered genes was verified by RT-PCR. Few clues as to the function of the new genes were gleaned from informatic analyses, but potential orthologs in other Pseudomonas genomes were identified for eight of the new genes. The 16 newly identified genes improve the quality of the Pf0-1 genome annotation, and the detection of antisense protein-coding genes indicates the under-appreciated complexity of bacterial genome organization.

  7. Proteomic Detection of Non-Annotated Protein-Coding Genes in Pseudomonas fluorescens Pf0-1

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Wook; Silby, Mark W.; Purvine, Samuel O.; Nicoll, Julie S.; Hixson, Kim K.; Monroe, Matthew E.; Nicora, Carrie D.; Lipton, Mary S.; Levy, Stuart B.

    2009-12-24

    Genome sequences are annotated by computational prediction of coding sequences, followed by similarity searches such as BLAST, which provide a layer of (possible) functional information. While the existence of processes such as alternative splicing complicates matters for eukaryote genomes, the view of bacterial genomes as a linear series of closely spaced genes leads to the assumption that computational annotations which predict such arrangements completely describe the coding capacity of bacterial genomes. We undertook a proteomic study to identify proteins expressed by Pseudomonas fluorescens Pf0-1 from genes which were not predicted during the genome annotation. Mapping peptides to the Pf0-1 genome sequence identified sixteen non-annotated protein-coding regions, of which nine were antisense to predicted genes, six were intergenic, and one read in the same direction as an annotated gene but in a different frame. The expression of all but one of the newly discovered genes was verified by RT-PCR. Few clues as to the function of the new genes were gleaned from informatic analyses, but potential orthologues in other Pseudomonas genomes were identified for eight of the new genes. The 16 newly identified genes improve the quality of the Pf0-1 genome annotation, and the detection of antisense protein-coding genes indicates the under-appreciated complexity of bacterial genome organization.

  8. Functional annotation by identification of local surface similarities: a novel tool for structural genomics

    Directory of Open Access Journals (Sweden)

    Zanzoni Andreas

    2005-08-01

    Full Text Available Abstract Background Protein function is often dependent on subsets of solvent-exposed residues that may exist in a similar three-dimensional configuration in non homologous proteins thus having different order and/or spacing in the sequence. Hence, functional annotation by means of sequence or fold similarity is not adequate for such cases. Results We describe a method for the function-related annotation of protein structures by means of the detection of local structural similarity with a library of annotated functional sites. An automatic procedure was used to annotate the function of local surface regions. Next, we employed a sequence-independent algorithm to compare exhaustively these functional patches with a larger collection of protein surface cavities. After tuning and validating the algorithm on a dataset of well annotated structures, we applied it to a list of protein structures that are classified as being of unknown function in the Protein Data Bank. By this strategy, we were able to provide functional clues to proteins that do not show any significant sequence or global structural similarity with proteins in the current databases. Conclusion This method is able to spot structural similarities associated to function-related similarities, independently on sequence or fold resemblance, therefore is a valuable tool for the functional analysis of uncharacterized proteins. Results are available at http://cbm.bio.uniroma2.it/surface/structuralGenomics.html

  9. Genome, functional gene annotation, and nuclear transformation of the heterokont oleaginous alga Nannochloropsis oceanica CCMP1779.

    Directory of Open Access Journals (Sweden)

    Astrid Vieler

    Full Text Available Unicellular marine algae have promise for providing sustainable and scalable biofuel feedstocks, although no single species has emerged as a preferred organism. Moreover, adequate molecular and genetic resources prerequisite for the rational engineering of marine algal feedstocks are lacking for most candidate species. Heterokonts of the genus Nannochloropsis naturally have high cellular oil content and are already in use for industrial production of high-value lipid products. First success in applying reverse genetics by targeted gene replacement makes Nannochloropsis oceanica an attractive model to investigate the cell and molecular biology and biochemistry of this fascinating organism group. Here we present the assembly of the 28.7 Mb genome of N. oceanica CCMP1779. RNA sequencing data from nitrogen-replete and nitrogen-depleted growth conditions support a total of 11,973 genes, of which in addition to automatic annotation some were manually inspected to predict the biochemical repertoire for this organism. Among others, more than 100 genes putatively related to lipid metabolism, 114 predicted transcription factors, and 109 transcriptional regulators were annotated. Comparison of the N. oceanica CCMP1779 gene repertoire with the recently published N. gaditana genome identified 2,649 genes likely specific to N. oceanica CCMP1779. Many of these N. oceanica-specific genes have putative orthologs in other species or are supported by transcriptional evidence. However, because similarity-based annotations are limited, functions of most of these species-specific genes remain unknown. Aside from the genome sequence and its analysis, protocols for the transformation of N. oceanica CCMP1779 are provided. The availability of genomic and transcriptomic data for Nannochloropsis oceanica CCMP1779, along with efficient transformation protocols, provides a blueprint for future detailed gene functional analysis and genetic engineering of Nannochloropsis

  10. An Annotation Scheme for Reichenbach's Verbal Tense Structure

    CERN Document Server

    Derczynski, Leon

    2012-01-01

    In this paper we present RTMML, a markup language for the tenses of verbs and temporal relations between verbs. There is a richness to tense in language that is not fully captured by existing temporal annotation schemata. Following Reichenbach we present an analysis of tense in terms of abstract time points, with the aim of supporting automated processing of tense and temporal relations in language. This allows for precise reasoning about tense in documents, and the deduction of temporal relations between the times and verbal events in a discourse. We define the syntax of RTMML, and demonstrate the markup in a range of situations.

  11. New in protein structure and function annotation: hotspots, single nucleotide polymorphisms and the 'Deep Web'.

    Science.gov (United States)

    Bromberg, Yana; Yachdav, Guy; Ofran, Yanay; Schneider, Reinhard; Rost, Burkhard

    2009-05-01

    The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of approximately half of all known proteins; homology- and network-based inferences annotate some aspect of function for a similar fraction of the proteome. For most known protein sequences, however, there is detailed knowledge about neither their function nor their structure. Comprehensive efforts towards the expert curation of sequence annotations have failed to meet the demand of the rapidly increasing number of available sequences. Only the automated prediction of protein function in the absence of homology can close the gap between available sequences and annotations in the foreseeable future. This review focuses on two novel methods for automated annotation, and briefly presents an outlook on how modern web software may revolutionize the field of protein sequence annotation. First, predictions of protein binding sites and functional hotspots, and the evolution of these into the most successful type of prediction of protein function from sequence will be discussed. Second, a new tool, comprehensive in silico mutagenesis, which contributes important novel predictions of function and at the same time prepares for the onset of the next sequencing revolution, will be described. While these two new sub-fields of protein prediction represent the breakthroughs that have been achieved methodologically, it will then be argued that a different development might further change the way biomedical researchers benefit from annotations: modern web software can connect the worldwide web in any browser with the 'Deep Web' (ie, proprietary data resources). The availability of this direct connection, and the resulting access to a wealth of data, may impact drug discovery and development more than any existing method that contributes to protein annotation.

  12. Annotated genes and nonannotated genomes: cross-species use of Gene Ontology in ecology and evolution research.

    Science.gov (United States)

    Primmer, C R; Papakostas, S; Leder, E H; Davis, M J; Ragan, M A

    2013-06-01

    Recent advances in molecular technologies have opened up unprecedented opportunities for molecular ecologists to better understand the molecular basis of traits of ecological and evolutionary importance in almost any organism. Nevertheless, reliable and systematic inference of functionally relevant information from these masses of data remains challenging. The aim of this review is to highlight how the Gene Ontology (GO) database can be of use in resolving this challenge. The GO provides a largely species-neutral source of information on the molecular function, biological role and cellular location of tens of thousands of gene products. As it is designed to be species-neutral, the GO is well suited for cross-species use, meaning that, functional annotation derived from model organisms can be transferred to inferred orthologues in newly sequenced species. In other words, the GO can provide gene annotation information for species with nonannotated genomes. In this review, we describe the GO database, how functional information is linked with genes/gene products in model organisms, and how molecular ecologists can utilize this information to annotate their own data. Then, we outline various applications of GO for enhancing the understanding of molecular basis of traits in ecologically relevant species. We also highlight potential pitfalls, provide step-by-step recommendations for conducting a sound study in nonmodel organisms, suggest avenues for future research and outline a strategy for maximizing the benefits of a more ecological and evolutionary genomics-oriented ontology by ensuring its compatibility with the GO. © 2013 John Wiley & Sons Ltd.

  13. Identification of novel endogenous antisense transcripts by DNA microarray analysis targeting complementary strand of annotated genes

    Directory of Open Access Journals (Sweden)

    Kohama Chihiro

    2009-08-01

    Full Text Available Abstract Background Recent transcriptomic analyses in mammals have uncovered the widespread occurrence of endogenous antisense transcripts, termed natural antisense transcripts (NATs. NATs are transcribed from the opposite strand of the gene locus and are thought to control sense gene expression, but the mechanism of such regulation is as yet unknown. Although several thousand potential sense-antisense pairs have been identified in mammals, examples of functionally characterized NATs remain limited. To identify NAT candidates suitable for further functional analyses, we performed DNA microarray-based NAT screening using mouse adult normal tissues and mammary tumors to target not only the sense orientation but also the complementary strand of the annotated genes. Results First, we designed microarray probes to target the complementary strand of genes for which an antisense counterpart had been identified only in human public cDNA sources, but not in the mouse. We observed a prominent expression signal from 66.1% of 635 target genes, and 58 genes of these showed tissue-specific expression. Expression analyses of selected examples (Acaa1b and Aard confirmed their dynamic transcription in vivo. Although interspecies conservation of NAT expression was previously investigated by the presence of cDNA sources in both species, our results suggest that there are more examples of human-mouse conserved NATs that could not be identified by cDNA sources. We also designed probes to target the complementary strand of well-characterized genes, including oncogenes, and compared the expression of these genes between mammary cancerous tissues and non-pathological tissues. We found that antisense expression of 95 genes of 404 well-annotated genes was markedly altered in tumor tissue compared with that in normal tissue and that 19 of these genes also exhibited changes in sense gene expression. These results highlight the importance of NAT expression in the regulation

  14. Gene function prediction based on the Gene Ontology hierarchical structure.

    Science.gov (United States)

    Cheng, Liangxi; Lin, Hongfei; Hu, Yuncui; Wang, Jian; Yang, Zhihao

    2014-01-01

    The information of the Gene Ontology annotation is helpful in the explanation of life science phenomena, and can provide great support for the research of the biomedical field. The use of the Gene Ontology is gradually affecting the way people store and understand bioinformatic data. To facilitate the prediction of gene functions with the aid of text mining methods and existing resources, we transform it into a multi-label top-down classification problem and develop a method that uses the hierarchical relationships in the Gene Ontology structure to relieve the quantitative imbalance of positive and negative training samples. Meanwhile the method enhances the discriminating ability of classifiers by retaining and highlighting the key training samples. Additionally, the top-down classifier based on a tree structure takes the relationship of target classes into consideration and thus solves the incompatibility between the classification results and the Gene Ontology structure. Our experiment on the Gene Ontology annotation corpus achieves an F-value performance of 50.7% (precision: 52.7% recall: 48.9%). The experimental results demonstrate that when the size of training set is small, it can be expanded via topological propagation of associated documents between the parent and child nodes in the tree structure. The top-down classification model applies to the set of texts in an ontology structure or with a hierarchical relationship.

  15. Next-Generation Sequencing and the Crustacean Immune System: The Need for Alternatives in Immune Gene Annotation.

    Science.gov (United States)

    Clark, K F; Greenwood, Spencer J

    2016-12-01

    Next-generation sequencing has been a huge benefit to investigators studying non-model species. High-throughput gene expression studies, which were once restricted to animals with extensive genomic resources, can now be applied to any species. Transcriptomic studies using RNA-Seq can discover hundreds of thousands of transcripts from any species of interest. The power and limitation of these techniques is the sheer size of the dataset that is acquired. Parsing these large datasets is becoming easier as more bioinformatic tools are available for biologists without extensive computer programming expertise. Gene annotation and physiological pathway tools such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology enable the application of the vast amount of information acquired from model organisms to non-model species. While noble in nature, utilization of these tools can inadvertently misrepresent transcriptomic data from non-model species via annotation omission. Annotation followed by molecular pathway analysis highlights pathways that are disproportionately affected by disease, stress, or the physiological condition being examined. Problems occur when gene annotation procedures only recognizes a subset, often 50% or less, of the genes differently expressed from a non-model organisms. Annotated transcripts normally belong to highly conserved metabolic or regulatory genes that likely have a secondary or tertiary role, if any at all, in immunity. They appear to be disproportionately affected simply because conserved genes are most easily annotated. Evolutionarily induced specialization of physiological pathways is a driving force of adaptive evolution, but it results in genes that have diverged sufficiently to prevent their identification and annotation through conventional gene or protein databases. The purpose of this manuscript is to highlight some of the challenges faced when annotating crustacean immune genes by using an American lobster

  16. GoMapMan: integration, consolidation and visualization of plant gene annotations within the MapMan ontology.

    Science.gov (United States)

    Ramsak, Živa; Baebler, Špela; Rotter, Ana; Korbar, Matej; Mozetic, Igor; Usadel, Björn; Gruden, Kristina

    2014-01-01

    GoMapMan (http://www.gomapman.org) is an open web-accessible resource for gene functional annotations in the plant sciences. It was developed to facilitate improvement, consolidation and visualization of gene annotations across several plant species. GoMapMan is based on the MapMan ontology, organized in the form of a hierarchical tree of biological concepts, which describe gene functions. Currently, genes of the model species Arabidopsis and three crop species (potato, tomato and rice) are included. The main features of GoMapMan are (i) dynamic and interactive gene product annotation through various curation options; (ii) consolidation of gene annotations for different plant species through the integration of orthologue group information; (iii) traceability of gene ontology changes and annotations; (iv) integration of external knowledge about genes from different public resources; and (v) providing gathered information to high-throughput analysis tools via dynamically generated export files. All of the GoMapMan functionalities are openly available, with the restriction on the curation functions, which require prior registration to ensure traceability of the implemented changes.

  17. Integrative Annotation of 21,037 Human Genes Validated by Full-Length cDNA Clones

    Energy Technology Data Exchange (ETDEWEB)

    Imanishi, Tadashi; Itoh, Takeshi; Suzuki, Yutaka; O' Donovan, Claire; Fukuchi, Satoshi; Koyanagi, Kanako O.; Barrero, Roberto A.; Tamura, Takuro; Yamaguchi-Kabata, Yumi; Tanino, Motohiko; Yura, Kei; Miyazaki, Satoru; Ikeo, Kazuho; Homma, Keiichi; Kasprzyk, Arek; Nishikawa, Tetsuo; Hirakawa, Mika; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Ashurst, Jennifer; Jia, Libin; Nakao, Mitsuteru; Thomas, Michael A.; Mulder, Nicola; Karavidopoulou, Youla; Jin, Lihua; Kim, Sangsoo; Yasuda, Tomohiro; Lenhard, Boris; Eveno, Eric; Suzuki, Yoshiyuki; Yamasaki, Chisato; Takeda, Jun-ichi; Gough, Craig; Hilton, Phillip; Fujii, Yasuyuki; Sakai, Hiroaki; Tanaka, Susumu; Amid, Clara; Bellgard, Matthew; de Fatima Bonaldo, Maria; Bono Hidemasa; Bromberg, Susan K.; Brookes, Anthony J.; Bruford, Elspeth; Carninci Piero; Chelala, Claude; Couillault, Christine; de Souza, Sandro J.; Debily, Marie-Anne; Devignes, Marie-Dominique; Dubchak, Inna; Endo, Toshinori; Estreicher, Anne; Eyras, Eduardo; Fukami-Kobayashi, Kaoru; Gopinath, Gopal R.; Graudens, Esther; Hahn, Yoonsoo; Han, Michael; Han, Ze-Guang; Hanada, Kousuke; Hanaoka, Hideki; Harada, Erimi; Hashimoto, Katsuyuki; Hinz, Ursula; Hirai, Momoki; Hishiki, Teruyoshi; Hopkinson, Ian; Imbeaud, Sandrine; Inoko, Hidetoshi; Kanapin, Alexander; Kaneko, Yayoi; Kasukawa, Takeya; Kelso, Janet; Kersey, Paul; Kikuno Reiko; Kimura, Kouichi; Korn, Bernhard; Kuryshev, Vladimir; Makalowska, Izabela; Makino Takashi; Mano, Shuhei; Mariage-Samson, Regine; Mashima, Jun; Matsuda, Hideo; Mewes, Hans-Werner; Minoshima, Shinsei; Nagai, Keiichi; Nagasaki, Hideki; Nagata, Naoki; Nigam, Rajni; Ogasawara, Osamu; Ohara, Osamu; Ohtsubo, Masafumi; Okada, Norihiro; Okido, Toshihisa; Oota, Satoshi; Ota, Motonori; Ota, Toshio; Otsuki, Tetsuji; Piatier-Tonneau, Dominique; Poustka, Annemarie; Ren, Shuang-Xi; Saitou, Naruya; Sakai, Katsunaga; Sakamoto, Shigetaka; Sakate, Ryuichi; Schupp, Ingo; Servant, Florence; Sherry, Stephen; Shiba Rie; et al.

    2004-01-15

    The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4 percent of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5 percent of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for nonprotein-coding RNA

  18. Integrative annotation of 21,037 human genes validated by full-length cDNA clones.

    Directory of Open Access Journals (Sweden)

    Tadashi Imanishi

    2004-06-01

    Full Text Available The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/. It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs, identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA

  19. Rapid annotation of anonymous sequences from genome projects using semantic similarities and a weighting scheme in gene ontology.

    Directory of Open Access Journals (Sweden)

    Paolo Fontana

    Full Text Available BACKGROUND: Large-scale sequencing projects have now become routine lab practice and this has led to the development of a new generation of tools involving function prediction methods, bringing the latter back to the fore. The advent of Gene Ontology, with its structured vocabulary and paradigm, has provided computational biologists with an appropriate means for this task. METHODOLOGY: We present here a novel method called ARGOT (Annotation Retrieval of Gene Ontology Terms that is able to process quickly thousands of sequences for functional inference. The tool exploits for the first time an integrated approach which combines clustering of GO terms, based on their semantic similarities, with a weighting scheme which assesses retrieved hits sharing a certain number of biological features with the sequence to be annotated. These hits may be obtained by different methods and in this work we have based ARGOT processing on BLAST results. CONCLUSIONS: The extensive benchmark involved 10,000 protein sequences, the complete S. cerevisiae genome and a small subset of proteins for purposes of comparison with other available tools. The algorithm was proven to outperform existing methods and to be suitable for function prediction of single proteins due to its high degree of sensitivity, specificity and coverage.

  20. UniqTag: Content-Derived Unique and Stable Identifiers for Gene Annotation.

    Directory of Open Access Journals (Sweden)

    Shaun D Jackman

    Full Text Available When working on an ongoing genome sequencing and assembly project, it is rather inconvenient when gene identifiers change from one build of the assembly to the next. The gene labelling system described here, UniqTag, addresses this common challenge. UniqTag assigns a unique identifier to each gene that is a representative k-mer, a string of length k, selected from the sequence of that gene. Unlike serial numbers, these identifiers are stable between different assemblies and annotations of the same data without requiring that previous annotations be lifted over by sequence alignment. We assign UniqTag identifiers to ten builds of the Ensembl human genome spanning eight years to demonstrate this stability. The implementation of UniqTag in Ruby and an R package are available at https://github.com/sjackman/uniqtag sjackman/uniqtag. The R package is also available from CRAN: install.packages ("uniqtag". Supplementary material and code to reproduce it is available at https://github.com/sjackman/uniqtag-paper.

  1. UniqTag: Content-Derived Unique and Stable Identifiers for Gene Annotation

    Science.gov (United States)

    Jackman, Shaun D.; Bohlmann, Joerg; Birol, İnanç

    2015-01-01

    When working on an ongoing genome sequencing and assembly project, it is rather inconvenient when gene identifiers change from one build of the assembly to the next. The gene labelling system described here, UniqTag, addresses this common challenge. UniqTag assigns a unique identifier to each gene that is a representative k-mer, a string of length k, selected from the sequence of that gene. Unlike serial numbers, these identifiers are stable between different assemblies and annotations of the same data without requiring that previous annotations be lifted over by sequence alignment. We assign UniqTag identifiers to ten builds of the Ensembl human genome spanning eight years to demonstrate this stability. The implementation of UniqTag in Ruby and an R package are available at https://github.com/sjackman/uniqtag sjackman/uniqtag. The R package is also available from CRAN: install.packages ("uniqtag"). Supplementary material and code to reproduce it is available at https://github.com/sjackman/uniqtag-paper. PMID:26020645

  2. MODBASE: a database of annotated comparative protein structure models and associated resources

    OpenAIRE

    Pieper, Ursula; Eswar, Narayanan; Davis, Fred P.; Braberg, Hannes; Madhusudhan, M. S.; Rossi, Andrea; Marti-Renom, Marc; Karchin, Rachel; Webb, Ben M.; Eramian, David; Shen, Min-Yi; Kelly, Libusha; Melo, Francisco; Sali, Andrej

    2005-01-01

    MODBASE () is a database of annotated comparative protein structure models for all available protein sequences that can be matched to at least one known protein structure. The models are calculated by MODPIPE, an automated modeling pipeline that relies on MODELLER for fold assignment, sequence–structure alignment, model building and model assessment (). MODBASE is updated regularly to reflect the growth in protein sequence and structure databases, and improvements in the software for calculat...

  3. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.

    Science.gov (United States)

    Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane; Thomas, Paul D

    2017-01-04

    The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new 'hierarchical view' of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution.

  4. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements

    Science.gov (United States)

    Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane; Thomas, Paul D.

    2017-01-01

    The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new ‘hierarchical view’ of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution. PMID:27899595

  5. Statistical analysis of genomic protein family and domain controlled annotations for functional investigation of classified gene lists

    Directory of Open Access Journals (Sweden)

    Masseroli Marco

    2007-03-01

    Full Text Available Abstract Background The increasing protein family and domain based annotations constitute important information to understand protein functions and gain insight into relations among their codifying genes. To allow analyzing of gene proteomic annotations, we implemented novel modules within GFINDer, a Web system we previously developed that dynamically aggregates functional and phenotypic annotations of user-uploaded gene lists and allows performing their statistical analysis and mining. Results Exploiting protein information in Pfam and InterPro databanks, we developed and added in GFINDer original modules specifically devoted to the exploration and analysis of functional signatures of gene protein products. They allow annotating numerous user-classified nucleotide sequence identifiers with controlled information on related protein families, domains and functional sites, classifying them according to such protein annotation categories, and statistically analyzing the obtained classifications. In particular, when uploaded nucleotide sequence identifiers are subdivided in classes, the Statistics Protein Families&Domains module allows estimating relevance of Pfam or InterPro controlled annotations for the uploaded genes by highlighting protein signatures significantly more represented within user-defined classes of genes. In addition, the Logistic Regression module allows identifying protein functional signatures that better explain the considered gene classification. Conclusion Novel GFINDer modules provide genomic protein family and domain analyses supporting better functional interpretation of gene classes, for instance defined through statistical and clustering analyses of gene expression results from microarray experiments. They can hence help understanding fundamental biological processes and complex cellular mechanisms influenced by protein domain composition, and contribute to unveil new biomedical knowledge about the codifying genes.

  6. FragKB: structural and literature annotation resource of conserved peptide fragments and residues.

    Directory of Open Access Journals (Sweden)

    Ashish V Tendulkar

    Full Text Available BACKGROUND: FragKB (Fragment Knowledgebase is a repository of clusters of structurally similar fragments from proteins. Fragments are annotated with information at the level of sequence, structure and function, integrating biological descriptions derived from multiple existing resources and text mining. METHODOLOGY: FragKB contains approximately 400,000 conserved fragments from 4,800 representative proteins from PDB. Literature annotations are extracted from more than 1,700 articles and are available for over 12,000 fragments. The underlying systematic annotation workflow of FragKB ensures efficient update and maintenance of this database. The information in FragKB can be accessed through a web interface that facilitates sequence and structural visualization of fragments together with known literature information on the consequences of specific residue mutations and functional annotations of proteins and fragment clusters. FragKB is accessible online at http://ubio.bioinfo.cnio.es/biotools/fragkb/. SIGNIFICANCE: The information presented in FragKB can be used for modeling protein structures, for designing novel proteins and for functional characterization of related fragments. The current release is focused on functional characterization of proteins through inspection of conservation of the fragments.

  7. STANDARDIZATION AND STRUCTURAL ANNOTATION OF PUBLIC TOXICITY DATABASES: IMPROVING SAR CAPABILITIES AND LINKAGE TO 'OMICS DATA

    Science.gov (United States)

    Standardization and structural annotation of public toxicity databases: Improving SAR capabilities and linkage to 'omics data Ann M. Richard', ClarLynda Williams', Jamie Burch2'Nat Health & Environ Res Lab, US EPA, RTP, NC 27711; 2EPA/NC Central Univ Student COOP Trainee<...

  8. Annotation and classification of the bovine T cell receptor delta genes.

    Science.gov (United States)

    Herzig, Carolyn T A; Lefranc, Marie-Paule; Baldwin, Cynthia L

    2010-02-09

    gammadelta T cells differ from alphabeta T cells with regard to the types of antigen with which their T cell receptors interact; gammadelta T cell antigens are not necessarily peptides nor are they presented on MHC. Cattle are considered a "gammadelta T cell high" species indicating they have an increased proportion of gammadelta T cells in circulation relative to that in "gammadelta T cell low" species such as humans and mice. Prior to the onset of the studies described here, there was limited information regarding the genes that code for the T cell receptor delta chains of this gammadelta T cell high species. By annotating the bovine (Bos taurus) genome Btau_3.1 assembly the presence of 56 distinct T cell receptor delta (TRD) variable (V) genes were found, 52 of which belong to the TRDV1 subgroup and were co-mingled with the T cell receptor alpha variable (TRAV) genes. In addition, two genes belonging to the TRDV2 subgroup and single TRDV3 and TRDV4 genes were found. We confirmed the presence of five diversity (D) genes, three junctional (J) genes and a single constant (C) gene and describe the organization of the TRD locus. The TRDV4 gene is found downstream of the C gene and in an inverted orientation of transcription, consistent with its orthologs in humans and mice. cDNA evidence was assessed to validate expression of the variable genes and showed that one to five D genes could be incorporated into a single transcript. Finally, we grouped the bovine and ovine TRDV1 genes into sets based on their relatedness. The bovine genome contains a large and diverse repertoire of TRD genes when compared to the genomes of "gammadelta T cell low" species. This suggests that in cattle gammadelta T cells play a more important role in immune function since they would be predicted to bind a greater variety of antigens.

  9. On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

    Directory of Open Access Journals (Sweden)

    Julien Becker

    Full Text Available Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix together with the CSP (cysteine separation profile are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to

  10. ShrimpGPAT: a gene and protein annotation tool for knowledge sharing and gene discovery in shrimp.

    Science.gov (United States)

    Korshkari, Parpakron; Vaiwsri, Sirintra; Flegel, Timothy W; Ngamsuriyaroj, Sudsanguan; Sonthayanon, Burachai; Prachumwat, Anuphap

    2014-06-21

    Although captured and cultivated marine shrimp constitute highly important seafood in terms of both economic value and production quantity, biologists have little knowledge of the shrimp genome and this partly hinders their ability to improve shrimp aquaculture. To help improve this situation, the Shrimp Gene and Protein Annotation Tool (ShrimpGPAT) was conceived as a community-based annotation platform for the acquisition and updating of full-length complementary DNAs (cDNAs), Expressed Sequence Tags (ESTs), transcript contigs and protein sequences of penaeid shrimp and their decapod relatives and for in-silico functional annotation and sequence analysis. ShrimpGPAT currently holds quality-filtered, molecular sequences of 14 decapod species (~500,000 records for six penaeid shrimp and eight other decapods). The database predominantly comprises transcript sequences derived by both traditional EST Sanger sequencing and more recently by massive-parallel sequencing technologies. The analysis pipeline provides putative functions in terms of sequence homologs, gene ontologies and protein-protein interactions. Data retrieval can be conducted easily either by a keyword text search or by a sequence query via BLAST, and users can save records of interest for later investigation using tools such as multiple sequence alignment and BLAST searches against pre-defined databases. In addition, ShrimpGPAT provides space for community insights by allowing functional annotation with tags and comments on sequences. Community-contributed information will allow for continuous database enrichment, for improvement of functions and for other aspects of sequence analysis. ShrimpGPAT is a new, free and easily accessed service for the shrimp research community that provides a comprehensive and up-to-date database of quality-filtered decapod gene and protein sequences together with putative functional prediction and sequence analysis tools. An important feature is its community

  11. SARA: a server for function annotation of RNA structures.

    Science.gov (United States)

    Capriotti, Emidio; Marti-Renom, Marc A

    2009-07-01

    Recent interest in non-coding RNA transcripts has resulted in a rapid increase of deposited RNA structures in the Protein Data Bank. However, a characterization and functional classification of the RNA structure and function space have only been partially addressed. Here, we introduce the SARA program for pair-wise alignment of RNA structures as a web server for structure-based RNA function assignment. The SARA server relies on the SARA program, which aligns two RNA structures based on a unit-vector root-mean-square approach. The likely accuracy of the SARA alignments is assessed by three different P-values estimating the statistical significance of the sequence, secondary structure and tertiary structure identity scores, respectively. Our benchmarks, which relied on a set of 419 RNA structures with known SCOR structural class, indicate that at a negative logarithm of mean P-value higher or equal than 2.5, SARA can assign the correct or a similar SCOR class to 81.4% and 95.3% of the benchmark set, respectively. The SARA server is freely accessible via the World Wide Web at http://sgu.bioinfo.cipf.es/services/SARA/.

  12. Network Structure, Metadata, and the Prediction of Missing Nodes and Annotations

    Science.gov (United States)

    Hric, Darko; Peixoto, Tiago P.; Fortunato, Santo

    2016-07-01

    The empirical validation of community detection methods is often based on available annotations on the nodes that serve as putative indicators of the large-scale network structure. Most often, the suitability of the annotations as topological descriptors itself is not assessed, and without this it is not possible to ultimately distinguish between actual shortcomings of the community detection algorithms, on one hand, and the incompleteness, inaccuracy, or structured nature of the data annotations themselves, on the other. In this work, we present a principled method to access both aspects simultaneously. We construct a joint generative model for the data and metadata, and a nonparametric Bayesian framework to infer its parameters from annotated data sets. We assess the quality of the metadata not according to their direct alignment with the network communities, but rather in their capacity to predict the placement of edges in the network. We also show how this feature can be used to predict the connections to missing nodes when only the metadata are available, as well as predicting missing metadata. By investigating a wide range of data sets, we show that while there are seldom exact agreements between metadata tokens and the inferred data groups, the metadata are often informative of the network structure nevertheless, and can improve the prediction of missing nodes. This shows that the method uncovers meaningful patterns in both the data and metadata, without requiring or expecting a perfect agreement between the two.

  13. Maize microarray annotation database

    Directory of Open Access Journals (Sweden)

    Berger Dave K

    2011-10-01

    Full Text Available Abstract Background Microarray technology has matured over the past fifteen years into a cost-effective solution with established data analysis protocols for global gene expression profiling. The Agilent-016047 maize 44 K microarray was custom-designed from EST sequences, but only reporter sequences with EST accession numbers are publicly available. The following information is lacking: (a reporter - gene model match, (b number of reporters per gene model, (c potential for cross hybridization, (d sense/antisense orientation of reporters, (e position of reporter on B73 genome sequence (for eQTL studies, and (f functional annotations of genes represented by reporters. To address this, we developed a strategy to annotate the Agilent-016047 maize microarray, and built a publicly accessible annotation database. Description Genomic annotation of the 42,034 reporters on the Agilent-016047 maize microarray was based on BLASTN results of the 60-mer reporter sequences and their corresponding ESTs against the maize B73 RefGen v2 "Working Gene Set" (WGS predicted transcripts and the genome sequence. The agreement between the EST, WGS transcript and gDNA BLASTN results were used to assign the reporters into six genomic annotation groups. These annotation groups were: (i "annotation by sense gene model" (23,668 reporters, (ii "annotation by antisense gene model" (4,330; (iii "annotation by gDNA" without a WGS transcript hit (1,549; (iv "annotation by EST", in which case the EST from which the reporter was designed, but not the reporter itself, has a WGS transcript hit (3,390; (v "ambiguous annotation" (2,608; and (vi "inconclusive annotation" (6,489. Functional annotations of reporters were obtained by BLASTX and Blast2GO analysis of corresponding WGS transcripts against GenBank. The annotations are available in the Maize Microarray Annotation Database http://MaizeArrayAnnot.bi.up.ac.za/, as well as through a GBrowse annotation file that can be uploaded to

  14. Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

    Science.gov (United States)

    Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

    2013-10-01

    The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  15. WikiGenomes: an open web application for community consumption and curation of gene annotation data in Wikidata.

    Science.gov (United States)

    Putman, Tim E; Lelong, Sebastien; Burgstaller-Muehlbacher, Sebastian; Waagmeester, Andra; Diesh, Colin; Dunn, Nathan; Munoz-Torres, Monica; Stupp, Gregory S; Wu, Chunlei; Su, Andrew I; Good, Benjamin M

    2017-01-01

    With the advancement of genome-sequencing technologies, new genomes are being sequenced daily. Although these sequences are deposited in publicly available data warehouses, their functional and genomic annotations (beyond genes which are predicted automatically) mostly reside in the text of primary publications. Professional curators are hard at work extracting those annotations from the literature for the most studied organisms and depositing them in structured databases. However, the resources don't exist to fund the comprehensive curation of the thousands of newly sequenced organisms in this manner. Here, we describe WikiGenomes (wikigenomes.org), a web application that facilitates the consumption and curation of genomic data by the entire scientific community. WikiGenomes is based on Wikidata, an openly editable knowledge graph with the goal of aggregating published knowledge into a free and open database. WikiGenomes empowers the individual genomic researcher to contribute their expertise to the curation effort and integrates the knowledge into Wikidata, enabling it to be accessed by anyone without restriction. www.wikigenomes.org.

  16. NCBI prokaryotic genome annotation pipeline.

    Science.gov (United States)

    Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat; Chetvernin, Vyacheslav; Nawrocki, Eric P; Zaslavsky, Leonid; Lomsadze, Alexandre; Pruitt, Kim D; Borodovsky, Mark; Ostell, James

    2016-08-19

    Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/.

  17. p63 gene structure in the phylum mollusca.

    Science.gov (United States)

    Baričević, Ana; Štifanić, Mauro; Hamer, Bojan; Batel, Renato

    2015-08-01

    Roles of p53 family ancestor (p63) in the organisms' response to stressful environmental conditions (mainly pollution) have been studied among molluscs, especially in the genus Mytilus, within the last 15 years. Nevertheless, information about gene structure of this regulatory gene in molluscs is scarce. Here we report the first complete genomic structure of the p53 family orthologue in the mollusc Mediterranean mussel Mytilus galloprovincialis and confirm its similarity to vertebrate p63 gene. Our searches within the available molluscan genomes (Aplysia californica, Lottia gigantea, Crassostrea gigas and Biomphalaria glabrata), found only one p53 family member present in a single copy per haploid genome. Comparative analysis of those orthologues, additionally confirmed the conserved p63 gene structure. Conserved p63 gene structure can be a helpful tool to complement or/and revise gene annotations of any future p63 genomic sequence records in molluscs, but also in other animal phyla. Knowledge of the correct gene structure will enable better prediction of possible protein isoforms and their functions. Our analyses also pointed out possible mis-annotations of the p63 gene in sequenced molluscan genomes and stressed the value of manual inspection (based on alignments of cDNA and protein onto the genome sequence) for a reliable and complete gene annotation.

  18. RepeatsDB 2.0: improved annotation, classification, search and visualization of repeat protein structures

    Science.gov (United States)

    Paladin, Lisanna; Hirsh, Layla; Piovesan, Damiano; Andrade-Navarro, Miguel A.; Kajava, Andrey V.; Tosatto, Silvio C.E.

    2017-01-01

    RepeatsDB 2.0 (URL: http://repeatsdb.bio.unipd.it/) is an update of the database of annotated tandem repeat protein structures. Repeat proteins are a widespread class of non-globular proteins carrying heterogeneous functions involved in several diseases. Here we provide a new version of RepeatsDB with an improved classification schema including high quality annotations for ∼5400 protein structures. RepeatsDB 2.0 features information on start and end positions for the repeat regions and units for all entries. The extensive growth of repeat unit characterization was possible by applying the novel ReUPred annotation method over the entire Protein Data Bank, with data quality is guaranteed by an extensive manual validation for >60% of the entries. The updated web interface includes a new search engine for complex queries and a fully re-designed entry page for a better overview of structural data. It is now possible to compare unit positions, together with secondary structure, fold information and Pfam domains. Moreover, a new classification level has been introduced on top of the existing scheme as an independent layer for sequence similarity relationships at 40%, 60% and 90% identity. PMID:27899671

  19. BEACON: automated tool for Bacterial GEnome Annotation ComparisON

    KAUST Repository

    Kalkatawi, Manal Matoq Saeed

    2015-08-18

    Background Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs). Results The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACON’s utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27 %, while the number of genes without any function assignment is reduced. Conclusions We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/

  20. BEACON: automated tool for Bacterial GEnome Annotation ComparisON.

    Science.gov (United States)

    Kalkatawi, Manal; Alam, Intikhab; Bajic, Vladimir B

    2015-08-18

    Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs). The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACON's utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27%, while the number of genes without any function assignment is reduced. We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/ .

  1. A database of annotated promoters of genes associated with common respiratory and related diseases

    KAUST Repository

    Chowdhary, Rajesh

    2012-07-01

    Many genes have been implicated in the pathogenesis of common respiratory and related diseases (RRDs), yet the underlying mechanisms are largely unknown. Differential gene expression patterns in diseased and healthy individuals suggest that RRDs affect or are affected by modified transcription regulation programs. It is thus crucial to characterize implicated genes in terms of transcriptional regulation. For this purpose, we conducted a promoter analysis of genes associated with 11 common RRDs including allergic rhinitis, asthma, bronchiectasis, bronchiolitis, bronchitis, chronic obstructive pulmonary disease, cystic fibrosis, emphysema, eczema, psoriasis, and urticaria, many of which are thought to be genetically related. The objective of the present study was to obtain deeper insight into the transcriptional regulation of these disease-associated genes by annotating their promoter regions with transcription factors (TFs) and TF binding sites (TFBSs). We discovered many TFs that are significantly enriched in the target disease groups including associations that have been documented in the literature. We also identified a number of putative TFs/TFBSs that appear to be novel. The results of our analysis are provided in an online database that is freely accessible to researchers at http://www.respiratorygenomics.com. Promoter-associated TFBS information and related genomic features, such as histone modification sites, microsatellites, CpG islands, and SNPs, are graphically summarized in the database. Users can compare and contrast underlying mechanisms of specific RRDs relative to candidate genes, TFs, gene ontology terms, micro-RNAs, and biological pathways for the conduct of metaanalyses. This database represents a novel, useful resource for RRD researchers. Copyright © 2012 by the American Thoracic Society.

  2. Gene expression and functional annotation of the human ciliary body epithelia.

    Directory of Open Access Journals (Sweden)

    Sarah F Janssen

    Full Text Available PURPOSE: The ciliary body (CB of the human eye consists of the non-pigmented (NPE and pigmented (PE neuro-epithelia. We investigated the gene expression of NPE and PE, to shed light on the molecular mechanisms underlying the most important functions of the CB. We also developed molecular signatures for the NPE and PE and studied possible new clues for glaucoma. METHODS: We isolated NPE and PE cells from seven healthy human donor eyes using laser dissection microscopy. Next, we performed RNA isolation, amplification, labeling and hybridization against 44×k Agilent microarrays. For microarray conformations, we used a literature study, RT-PCRs, and immunohistochemical stainings. We analyzed the gene expression data with R and with the knowledge database Ingenuity. RESULTS: The gene expression profiles and functional annotations of the NPE and PE were highly similar. We found that the most important functionalities of the NPE and PE were related to developmental processes, neural nature of the tissue, endocrine and metabolic signaling, and immunological functions. In total 1576 genes differed statistically significantly between NPE and PE. From these genes, at least 3 were cell-specific for the NPE and 143 for the PE. Finally, we observed high expression in the (NPE of 35 genes previously implicated in molecular mechanisms related to glaucoma. CONCLUSION: Our gene expression analysis suggested that the NPE and PE of the CB were quite similar. Nonetheless, cell-type specific differences were found. The molecular machineries of the human NPE and PE are involved in a range of neuro-endocrinological, developmental and immunological functions, and perhaps glaucoma.

  3. IDconverter and IDClight: Conversion and annotation of gene and protein IDs

    Directory of Open Access Journals (Sweden)

    Díaz-Uriarte Ramón

    2007-01-01

    Full Text Available Abstract Background Researchers involved in the annotation of large numbers of gene, clone or protein identifiers are usually required to perform a one-by-one conversion for each identifier. When the field of research is one such as microarray experiments, this number may be around 30,000. Results To help researchers map accession numbers and identifiers among clones, genes, proteins and chromosomal positions, we have designed and developed IDconverter and IDClight. They are two user-friendly, freely available web server applications that also provide additional functional information by mapping the identifiers on to pathways, Gene Ontology terms, and literature references. Both tools are high-throughput oriented and include identifiers for the most common genomic databases. These tools have been compared to other similar tools, showing that they are among the fastest and the most up-to-date. Conclusion These tools provide a fast and intuitive way of enriching the information coming out of high-throughput experiments like microarrays. They can be valuable both to wet-lab researchers and to bioinformaticians.

  4. Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle.

    Science.gov (United States)

    Crispim, Aline Camporez; Kelly, Matthew John; Guimarães, Simone Eliza Facioni; Fonseca e Silva, Fabyano; Fortes, Marina Rufino Salinas; Wenceslau, Raphael Rocha; Moore, Stephen

    2015-01-01

    Understanding the genetic architecture of beef cattle growth cannot be limited simply to the genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the whole growth trajectory over time using a growth curve approach. For such an approach, the parameters that are used to describe growth curves were treated as phenotypes under a GWAS model. Data from 1,255 Brahman cattle that were weighed at birth, 6, 12, 15, 18, and 24 months of age were analyzed. Parameter estimates, such as mature weight (A) and maturity rate (K) from nonlinear models are utilized as substitutes for the original body weights for the GWAS analysis. We chose the best nonlinear model to describe the weight-age data, and the estimated parameters were used as phenotypes in a multi-trait GWAS. Our aims were to identify and characterize associated SNP markers to indicate SNP-derived candidate genes and annotate their function as related to growth processes in beef cattle. The Brody model presented the best goodness of fit, and the heritability values for the parameter estimates for mature weight (A) and maturity rate (K) were 0.23 and 0.32, respectively, proving that these traits can be a feasible alternative when the objective is to change the shape of growth curves within genetic improvement programs. The genetic correlation between A and K was -0.84, indicating that animals with lower mature body weights reached that weight at younger ages. One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively. The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1). Candidate

  5. Protein function annotation with Structurally Aligned Local Sites of Activity (SALSAs

    Directory of Open Access Journals (Sweden)

    Wang Zhouxi

    2013-02-01

    Full Text Available Abstract Background The prediction of biochemical function from the 3D structure of a protein has proved to be much more difficult than was originally foreseen. A reliable method to test the likelihood of putative annotations and to predict function from structure would add tremendous value to structural genomics data. We report on a new method, Structurally Aligned Local Sites of Activity (SALSA, for the prediction of biochemical function based on a local structural match at the predicted catalytic or binding site. Results Implementation of the SALSA method is described. For the structural genomics protein PY01515 (PDB ID 2aqw from Plasmodium yoelii, it is shown that the putative annotation, Orotidine 5'-monophosphate decarboxylase (OMPDC, is most likely correct. SALSA analysis of YP_001304206.1 (PDB ID 3h3l, a putative sugar hydrolase from Parabacteroides distasonis, shows that its active site does not bear close resemblance to any previously characterized member of its superfamily, the Concanavalin A-like lectins/glucanases. It is noted that three residues in the active site of the thermophilic beta-1,4-xylanase from Nonomuraea flexuosa (PDB ID 1m4w, Y78, E87, and E176, overlap with POOL-predicted residues of similar type, Y168, D153, and E232, in YP_001304206.1. The substrate recognition regions of the two proteins are rather different, suggesting that YP_001304206.1 is a new functional type within the superfamily. A structural genomics protein from Mycobacterium avium (PDB ID 3q1t has been reported to be an enoyl-CoA hydratase (ECH, but SALSA analysis shows a poor match between the predicted residues for the SG protein and those of known ECHs. A better local structural match is obtained with Anabaena beta-diketone hydrolase (ABDH, a known β-diketone hydrolase from Cyanobacterium anabaena (PDB ID 2j5s. This suggests that the reported ECH function of the SG protein is incorrect and that it is more likely a β-diketone hydrolase. Conclusions

  6. Annotation of gene function in citrus using gene expression information and co-expression networks

    OpenAIRE

    Wong, Darren CJ; Sweetman, Crystal; Ford, Christopher M.

    2014-01-01

    Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related bi...

  7. Annotation of gene function in citrus using gene expression information and co-expression networks

    OpenAIRE

    Wong, Darren CJ; Sweetman, Crystal; Ford, Christopher M.

    2014-01-01

    Background The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related bi...

  8. Annotation of gene function in citrus using gene expression information and co-expression networks.

    Science.gov (United States)

    Wong, Darren C J; Sweetman, Crystal; Ford, Christopher M

    2014-07-15

    The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world's most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a "guilt-by-association" principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed. We have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit. Integration of citrus gene co-expression networks, functional enrichment analysis and gene

  9. pathDIP: an annotated resource for known and predicted human gene-pathway associations and pathway enrichment analysis

    Science.gov (United States)

    Rahmati, Sara; Abovsky, Mark; Pastrello, Chiara; Jurisica, Igor

    2017-01-01

    Molecular pathway data are essential in current computational and systems biology research. While there are many primary and integrated pathway databases, several challenges remain, including low proteome coverage (57%), low overlap across different databases, unavailability of direct information about underlying physical connectivity of pathway members, and high fraction of protein-coding genes without any pathway annotations, i.e. ‘pathway orphans’. In order to address all these challenges, we developed pathDIP, which integrates data from 20 source pathway databases, ‘core pathways’, with physical protein–protein interactions to predict biologically relevant protein–pathway associations, referred to as ‘extended pathways’. Cross-validation determined 71% recovery rate of our predictions. Data integration and predictions increase coverage of pathway annotations for protein-coding genes to 86%, and provide novel annotations for 5732 pathway orphans. PathDIP (http://ophid.utoronto.ca/pathdip) annotates 17 070 protein-coding genes with 4678 pathways, and provides multiple query, analysis and output options. PMID:27899558

  10. Genome-wide Annotation, Identification, and Global Transcriptomic Analysis of Regulatory or Small RNA Gene Expression in Staphylococcus aureus

    Directory of Open Access Journals (Sweden)

    Ronan K. Carroll

    2016-02-01

    Full Text Available In Staphylococcus aureus, hundreds of small regulatory or small RNAs (sRNAs have been identified, yet this class of molecule remains poorly understood and severely understudied. sRNA genes are typically absent from genome annotation files, and as a consequence, their existence is often overlooked, particularly in global transcriptomic studies. To facilitate improved detection and analysis of sRNAs in S. aureus, we generated updated GenBank files for three commonly used S. aureus strains (MRSA252, NCTC 8325, and USA300, in which we added annotations for >260 previously identified sRNAs. These files, the first to include genome-wide annotation of sRNAs in S. aureus, were then used as a foundation to identify novel sRNAs in the community-associated methicillin-resistant strain USA300. This analysis led to the discovery of 39 previously unidentified sRNAs. Investigating the genomic loci of the newly identified sRNAs revealed a surprising degree of inconsistency in genome annotation in S. aureus, which may be hindering the analysis and functional exploration of these elements. Finally, using our newly created annotation files as a reference, we perform a global analysis of sRNA gene expression in S. aureus and demonstrate that the newly identified tsr25 is the most highly upregulated sRNA in human serum. This study provides an invaluable resource to the S. aureus research community in the form of our newly generated annotation files, while at the same time presenting the first examination of differential sRNA expression in pathophysiologically relevant conditions.

  11. Genome-wide annotation, expression profiling, and protein interaction studies of the core cell-cycle genes in Phalaenopsis aphrodite.

    Science.gov (United States)

    Lin, Hsiang-Yin; Chen, Jhun-Chen; Wei, Miao-Ju; Lien, Yi-Chen; Li, Huang-Hsien; Ko, Swee-Suak; Liu, Zin-Huang; Fang, Su-Chiung

    2014-01-01

    Orchidaceae is one of the most abundant and diverse families in the plant kingdom and its unique developmental patterns have drawn the attention of many evolutionary biologists. Particular areas of interest have included the co-evolution of pollinators and distinct floral structures, and symbiotic relationships with mycorrhizal flora. However, comprehensive studies to decipher the molecular basis of growth and development in orchids remain scarce. Cell proliferation governed by cell-cycle regulation is fundamental to growth and development of the plant body. We took advantage of recently released transcriptome information to systematically isolate and annotate the core cell-cycle regulators in the moth orchid Phalaenopsis aphrodite. Our data verified that Phalaenopsis cyclin-dependent kinase A (CDKA) is an evolutionarily conserved CDK. Expression profiling studies suggested that core cell-cycle genes functioning during the G1/S, S, and G2/M stages were preferentially enriched in the meristematic tissues that have high proliferation activity. In addition, subcellular localization and pairwise interaction analyses of various combinations of CDKs and cyclins, and of E2 promoter-binding factors and dimerization partners confirmed interactions of the functional units. Furthermore, our data showed that expression of the core cell-cycle genes was coordinately regulated during pollination-induced reproductive development. The data obtained establish a fundamental framework for study of the cell-cycle machinery in Phalaenopsis orchids.

  12. Meta4: a web-application for sharing and annotating metagenomic gene predictions using web-services

    Directory of Open Access Journals (Sweden)

    Emily J Richardson

    2013-09-01

    Full Text Available Whole-genome-shotgun (WGS metagenomics experiments produce DNA sequence data from entire ecosystems, and provide a huge amount of novel information. Gene discovery projects require up-to-date information about sequence homology and domain structure for millions of predicted proteins to be presented in a simple, easy-to-use system. There is a lack of simple, open, flexible tools that allow the rapid sharing of metagenomics datasets with collaborators in a format they can easily interrogate. We present Meta4, a flexible and extensible web-application that can be used to share and annotate metagenomic gene predictions. Proteins and predicted domains are stored in a simple relational database, with a dynamic front-end which displays the results in an internet browser. Web-services are used to provide up-to-date information about the proteins from homology searches against public databases. Information about Meta4 can be found on the project website (http://www.ark-genomics.org/bioinformatics/meta4, code is available on Github (https://github.com/mw55309/meta4, a cloud image is available, and an example implementation can be seen at http://www.ark-genomics.org/tools/meta4

  13. An Introduction to Genome Annotation.

    Science.gov (United States)

    Campbell, Michael S; Yandell, Mark

    2015-12-17

    Genome projects have evolved from large international undertakings to tractable endeavors for a single lab. Accurate genome annotation is critical for successful genomic, genetic, and molecular biology experiments. These annotations can be generated using a number of approaches and available software tools. This unit describes methods for genome annotation and a number of software tools commonly used in gene annotation.

  14. Comparative genomic analysis of the family Iridoviridae: re-annotating and defining the core set of iridovirus genes

    Directory of Open Access Journals (Sweden)

    Upton Chris

    2007-01-01

    Full Text Available Abstract Background Members of the family Iridoviridae can cause severe diseases resulting in significant economic and environmental losses. Very little is known about how iridoviruses cause disease in their host. In the present study, we describe the re-analysis of the Iridoviridae family of complex DNA viruses using a variety of comparative genomic tools to yield a greater consensus among the annotated sequences of its members. Results A series of genomic sequence comparisons were made among, and between the Ranavirus and Megalocytivirus genera in order to identify novel conserved ORFs. Of these two genera, the Megalocytivirus genomes required the greatest number of altered annotations. Prior to our re-analysis, the Megalocytivirus species orange-spotted grouper iridovirus and rock bream iridovirus shared 99% sequence identity, but only 82 out of 118 potential ORFs were annotated; in contrast, we predict that these species share an identical complement of genes. These annotation changes allowed the redefinition of the group of core genes shared by all iridoviruses. Seven new core genes were identified, bringing the total number to 26. Conclusion Our re-analysis of genomes within the Iridoviridae family provides a unifying framework to understand the biology of these viruses. Further re-defining the core set of iridovirus genes will continue to lead us to a better understanding of the phylogenetic relationships between individual iridoviruses as well as giving us a much deeper understanding of iridovirus replication. In addition, this analysis will provide a better framework for characterizing and annotating currently unclassified iridoviruses.

  15. Annotation and comparative analysis of the glycoside hydrolase genes in Brachypodium distachyon

    Energy Technology Data Exchange (ETDEWEB)

    Tyler, Ludmila [United States Department of Agriculture (USDA), Western Regional Research Center (WRRC), Albany; Bragg, Jennifer [United States Department of Agriculture (USDA), Western Regional Research Center (WRRC), Albany; Wu, Jiajie [United States Department of Agriculture (USDA), Western Regional Research Center (WRRC), Albany; Yang, Xiaohan [ORNL; Tuskan, Gerald A [ORNL; Vogel, John [United States Department of Agriculture (USDA), Western Regional Research Center (WRRC), Albany

    2010-01-01

    Background Glycoside hydrolases cleave the bond between a carbohydrate and another carbohydrate, a protein, lipid or other moiety. Genes encoding glycoside hydrolases are found in a wide range of organisms, from archea to animals, and are relatively abundant in plant genomes. In plants, these enzymes are involved in diverse processes, including starch metabolism, defense, and cell-wall remodeling. Glycoside hydrolase genes have been previously cataloged for Oryza sativa (rice), the model dicotyledonous plant Arabidopsis thaliana, and the fast-growing tree Populus trichocarpa (poplar). To improve our understanding of glycoside hydrolases in plants generally and in grasses specifically, we annotated the glycoside hydrolase genes in the grasses Brachypodium distachyon (an emerging monocotyledonous model) and Sorghum bicolor (sorghum). We then compared the glycoside hydrolases across species, both at the whole-genome level and at the level of individual glycoside hydrolase families. Results We identified 356 glycoside hydrolase genes in Brachypodium and 404 in sorghum. The corresponding proteins fell into the same 34 families that are represented in rice, Arabidopsis, and poplar, helping to define a glycoside hydrolase family profile which may be common to flowering plants. Examination of individual glycoside hydrolase familes (GH5, GH13, GH18, GH19, GH28, and GH51) revealed both similarities and distinctions between monocots and dicots, as well as between species. Shared evolutionary histories appear to be modified by lineage-specific expansions or deletions. Within families, the Brachypodium and sorghum proteins generally cluster with those from other monocots. Conclusions This work provides the foundation for further comparative and functional analyses of plant glycoside hydrolases. Defining the Brachypodium glycoside hydrolases sets the stage for Brachypodium to be a monocot model for investigations of these enzymes and their diverse roles in planta. Insights

  16. Warehousing re-annotated cancer genes for biomarker meta-analysis.

    Science.gov (United States)

    Orsini, M; Travaglione, A; Capobianco, E

    2013-07-01

    Translational research in cancer genomics assigns a fundamental role to bioinformatics in support of candidate gene prioritization with regard to both biomarker discovery and target identification for drug development. Efforts in both such directions rely on the existence and constant update of large repositories of gene expression data and omics records obtained from a variety of experiments. Users who interactively interrogate such repositories may have problems in retrieving sample fields that present limited associated information, due for instance to incomplete entries or sometimes unusable files. Cancer-specific data sources present similar problems. Given that source integration usually improves data quality, one of the objectives is keeping the computational complexity sufficiently low to allow an optimal assimilation and mining of all the information. In particular, the scope of integrating intraomics data can be to improve the exploration of gene co-expression landscapes, while the scope of integrating interomics sources can be that of establishing genotype-phenotype associations. Both integrations are relevant to cancer biomarker meta-analysis, as the proposed study demonstrates. Our approach is based on re-annotating cancer-specific data available at the EBI's ArrayExpress repository and building a data warehouse aimed to biomarker discovery and validation studies. Cancer genes are organized by tissue with biomedical and clinical evidences combined to increase reproducibility and consistency of results. For better comparative evaluation, multiple queries have been designed to efficiently address all types of experiments and platforms, and allow for retrieval of sample-related information, such as cell line, disease state and clinical aspects.

  17. Accurate protein structure annotation through competitive diffusion of enzymatic functions over a network of local evolutionary similarities.

    Directory of Open Access Journals (Sweden)

    Eric Venner

    Full Text Available High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks.

  18. Accurate protein structure annotation through competitive diffusion of enzymatic functions over a network of local evolutionary similarities.

    Science.gov (United States)

    Venner, Eric; Lisewski, Andreas Martin; Erdin, Serkan; Ward, R Matthew; Amin, Shivas R; Lichtarge, Olivier

    2010-12-13

    High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC) levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks.

  19. MuPIT interactive: webserver for mapping variant positions to annotated, interactive 3D structures.

    Science.gov (United States)

    Niknafs, Noushin; Kim, Dewey; Kim, Ryangguk; Diekhans, Mark; Ryan, Michael; Stenson, Peter D; Cooper, David N; Karchin, Rachel

    2013-11-01

    Mutation position imaging toolbox (MuPIT) interactive is a browser-based application for single-nucleotide variants (SNVs), which automatically maps the genomic coordinates of SNVs onto the coordinates of available three-dimensional (3D) protein structures. The application is designed for interactive browser-based visualization of the putative functional relevance of SNVs by biologists who are not necessarily experts either in bioinformatics or protein structure. Users may submit batches of several thousand SNVs and review all protein structures that cover the SNVs, including available functional annotations such as binding sites, mutagenesis experiments, and common polymorphisms. Multiple SNVs may be mapped onto each structure, enabling 3D visualization of SNV clusters and their relationship to functionally annotated positions. We illustrate the utility of MuPIT interactive in rationalizing the impact of selected polymorphisms in the PharmGKB database, somatic mutations identified in the Cancer Genome Atlas study of invasive breast carcinomas, and rare variants identified in the exome sequencing project. MuPIT interactive is freely available for non-profit use at http://mupit.icm.jhu.edu .

  20. MuPIT Interactive: Webserver for mapping variant positions to annotated, interactive 3D structures

    Science.gov (United States)

    Niknafs, Noushin; Kim, Dewey; Kim, Ryang Guk; Diekhans, Mark; Ryan, Michael; Stenson, Peter D.; Cooper, David N.; Karchin, Rachel

    2013-01-01

    Mutation Position Imaging Toolbox (MuPIT) Interactive is a browser-based application for single nucleotide variants (SNVs), which automatically maps the genomic coordinates of SNVs onto the coordinates of available three-dimensional protein structures. The application is designed for interactive browser-based visualization of the putative functional relevance of SNVs by biologists who are not necessarily experts either in bioinformatics or protein structure. Users may submit batches of several thousand SNVs and review all protein structures that cover the SNVs, including available functional annotations such as binding sites, mutagenesis experiments, and common polymorphisms. Multiple SNVs may be mapped onto each structure, enabling 3D visualization of SNV clusters and their relationship to functionally annotated positions. We illustrate the utility of MuPIT Interactive in rationalizing the impact of selected polymorphisms in the PharmGKB database, somatic mutations identified in the Cancer Genome Atlas study of invasive breast carcinomas, and rare variants identified in the Exome Sequencing Project. MuPIT Interactive is freely available for non-profit use at http://mupit.icm.jhu.edu. PMID:23793516

  1. Estimating gene gain and loss rates in the presence of error in genome assembly and annotation using CAFE 3.

    Science.gov (United States)

    Han, Mira V; Thomas, Gregg W C; Lugo-Martinez, Jose; Hahn, Matthew W

    2013-08-01

    Current sequencing methods produce large amounts of data, but genome assemblies constructed from these data are often fragmented and incomplete. Incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. This means that methods attempting to estimate rates of gene duplication and loss often will be misled by such errors and that rates of gene family evolution will be consistently overestimated. Here, we present a method that takes these errors into account, allowing one to accurately infer rates of gene gain and loss among genomes even with low assembly and annotation quality. The method is implemented in the newest version of the software package CAFE, along with several other novel features. We demonstrate the accuracy of the method with extensive simulations and reanalyze several previously published data sets. Our results show that errors in genome annotation do lead to higher inferred rates of gene gain and loss but that CAFE 3 sufficiently accounts for these errors to provide accurate estimates of important evolutionary parameters.

  2. MeSH key terms for validation and annotation of gene expression clusters

    Energy Technology Data Exchange (ETDEWEB)

    Rechtsteiner, A. (Andreas); Rocha, L. M. (Luis Mateus)

    2004-01-01

    Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert who had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes

  3. SAGExplore: a web server for unambiguous tag mapping in serial analysis of gene expression oriented to gene discovery and annotation.

    Science.gov (United States)

    Norambuena, Tomás; Malig, Rodrigo; Melo, Francisco

    2007-07-01

    We describe a web server for the accurate mapping of experimental tags in serial analysis of gene expression (SAGE). The core of the server relies on a database of genomic virtual tags built by a recently described method that attempts to reduce the amount of ambiguous assignments for those tags that are not unique in the genome. The method provides a complete annotation of potential virtual SAGE tags within a genome, along with an estimation of their confidence for experimental observation that ranks tags that present multiple matches in the genome. The output of the server consists of a table in HTML format that contains links to a graphic representation of the results and to some external servers and databases, facilitating the tasks of analysis of gene expression and gene discovery. Also, a table in tab delimited text format is produced, allowing the user to export the results into custom databases and software for further analysis. The current server version provides the most accurate and complete SAGE tag mapping source that is available for the yeast organism. In the near future, this server will also allow the accurate mapping of experimental SAGE-tags from other model organisms such as human, mouse, frog and fly. The server is freely available on the web at: http://dna.bio.puc.cl/SAGExplore.html.

  4. The Physalis peruviana leaf transcriptome: assembly, annotation and gene model prediction

    Directory of Open Access Journals (Sweden)

    Garzón-Martínez Gina A

    2012-04-01

    Full Text Available Abstract Background Physalis peruviana commonly known as Cape gooseberry is a member of the Solanaceae family that has an increasing popularity due to its nutritional and medicinal values. A broad range of genomic tools is available for other Solanaceae, including tomato and potato. However, limited genomic resources are currently available for Cape gooseberry. Results We report the generation of a total of 652,614 P. peruviana Expressed Sequence Tags (ESTs, using 454 GS FLX Titanium technology. ESTs, with an average length of 371 bp, were obtained from a normalized leaf cDNA library prepared using a Colombian commercial variety. De novo assembling was performed to generate a collection of 24,014 isotigs and 110,921 singletons, with an average length of 1,638 bp and 354 bp, respectively. Functional annotation was performed using NCBI’s BLAST tools and Blast2GO, which identified putative functions for 21,191 assembled sequences, including gene families involved in all the major biological processes and molecular functions as well as defense response and amino acid metabolism pathways. Gene model predictions in P. peruviana were obtained by using the genomes of Solanum lycopersicum (tomato and Solanum tuberosum (potato. We predict 9,436 P. peruviana sequences with multiple-exon models and conserved intron positions with respect to the potato and tomato genomes. Additionally, to study species diversity we developed 5,971 SSR markers from assembled ESTs. Conclusions We present the first comprehensive analysis of the Physalis peruviana leaf transcriptome, which will provide valuable resources for development of genetic tools in the species. Assembled transcripts with gene models could serve as potential candidates for marker discovery with a variety of applications including: functional diversity, conservation and improvement to increase productivity and fruit quality. P. peruviana was estimated to be phylogenetically branched out before the

  5. Recurrent use of evolutionary importance for functional annotation of proteins based on local structural similarity.

    Science.gov (United States)

    Kristensen, David M; Chen, Brian Y; Fofanov, Viacheslav Y; Ward, R Matthew; Lisewski, Andreas Martin; Kimmel, Marek; Kavraki, Lydia E; Lichtarge, Olivier

    2006-06-01

    The annotation of protein function has not kept pace with the exponential growth of raw sequence and structure data. An emerging solution to this problem is to identify 3D motifs or templates in protein structures that are necessary and sufficient determinants of function. Here, we demonstrate the recurrent use of evolutionary trace information to construct such 3D templates for enzymes, search for them in other structures, and distinguish true from spurious matches. Serine protease templates built from evolutionarily important residues distinguish between proteases and other proteins nearly as well as the classic Ser-His-Asp catalytic triad. In 53 enzymes spanning 33 distinct functions, an automated pipeline identifies functionally related proteins with an average positive predictive power of 62%, including correct matches to proteins with the same function but with low sequence identity (the average identity for some templates is only 17%). Although these template building, searching, and match classification strategies are not yet optimized, their sequential implementation demonstrates a functional annotation pipeline which does not require experimental information, but only local molecular mimicry among a small number of evolutionarily important residues.

  6. Structure and functional annotation of hypothetical proteins having putative Rubisco activase function from Vitis vinifera.

    Science.gov (United States)

    Kumar, Suresh

    2015-01-01

    Rubisco is a very large, complex and one of the most abundant proteins in the world and comprises up to 50% of all soluble protein in plants. The activity of Rubisco, the enzyme that catalyzes CO2 assimilation in photosynthesis, is regulated by Rubisco activase (Rca). In the present study, we searched for hypothetical protein of Vitis vinifera which has putative Rubisco activase function. The Arabidopsis and tobacco Rubisco activase protein sequences were used as seed sequences to search against Vitis vinifera in UniprotKB database. The selected hypothetical proteins of Vitis vinifera were subjected to sequence, structural and functional annotation. Subcellular localization predictions suggested it to be cytoplasmic protein. Homology modelling was used to define the three-dimensional (3D) structure of selected hypothetical proteins of Vitis vinifera. Template search revealed that all the hypothetical proteins share more than 80% sequence identity with structure of green-type Rubisco activase from tobacco, indicating proteins are evolutionary conserved. The homology modelling was generated using SWISS-MODEL. Several quality assessment and validation parameters computed indicated that homology models are reliable. Further, functional annotation through PFAM, CATH, SUPERFAMILY, CDART suggested that selected hypothetical proteins of Vitis vinifera contain ATPase family associated with various cellular activities (AAA) and belong to the AAA+ super family of ring-shaped P-loop containing nucleoside triphosphate hydrolases. This study will lead to research in the optimization of the functionality of Rubisco which has large implication in the improvement of plant productivity and resource use efficiency.

  7. Genome Wide Re-Annotation of Caldicellulosiruptor saccharolyticus with New Insights into Genes Involved in Biomass Degradation and Hydrogen Production.

    Directory of Open Access Journals (Sweden)

    Nupoor Chowdhary

    Full Text Available Caldicellulosiruptor saccharolyticus has proven itself to be an excellent candidate for biological hydrogen (H2 production, but still it has major drawbacks like sensitivity to high osmotic pressure and low volumetric H2 productivity, which should be considered before it can be used industrially. A whole genome re-annotation work has been carried out as an attempt to update the incomplete genome information that causes gap in the knowledge especially in the area of metabolic engineering, to improve the H2 producing capabilities of C. saccharolyticus. Whole genome re-annotation was performed through manual means for 2,682 Coding Sequences (CDSs. Bioinformatics tools based on sequence similarity, motif search, phylogenetic analysis and fold recognition were employed for re-annotation. Our methodology could successfully add functions for 409 hypothetical proteins (HPs, 46 proteins previously annotated as putative and assigned more accurate functions for the known protein sequences. Homology based gene annotation has been used as a standard method for assigning function to novel proteins, but over the past few years many non-homology based methods such as genomic context approaches for protein function prediction have been developed. Using non-homology based functional prediction methods, we were able to assign cellular processes or physical complexes for 249 hypothetical sequences. Our re-annotation pipeline highlights the addition of 231 new CDSs generated from MicroScope Platform, to the original genome with functional prediction for 49 of them. The re-annotation of HPs and new CDSs is stored in the relational database that is available on the MicroScope web-based platform. In parallel, a comparative genome analyses were performed among the members of genus Caldicellulosiruptor to understand the function and evolutionary processes. Further, with results from integrated re-annotation studies (homology and genomic context approach, we strongly

  8. Comprehensive annotation of bidirectional promoters identifies co-regulation among breast and ovarian cancer genes.

    Directory of Open Access Journals (Sweden)

    Mary Q Yang

    2007-04-01

    Full Text Available A "bidirectional gene pair" comprises two adjacent genes whose transcription start sites are neighboring and directed away from each other. The intervening regulatory region is called a "bidirectional promoter." These promoters are often associated with genes that function in DNA repair, with the potential to participate in the development of cancer. No connection between these gene pairs and cancer has been previously investigated. Using the database of spliced-expressed sequence tags (ESTs, we identified the most complete collection of human transcripts under the control of bidirectional promoters. A rigorous screen of the spliced EST data identified new bidirectional promoters, many of which functioned as alternative promoters or regulated novel transcripts. Additionally, we show a highly significant enrichment of bidirectional promoters in genes implicated in somatic cancer, including a substantial number of genes implicated in breast and ovarian cancers. The repeated use of this promoter structure in the human genome suggests it could regulate co-expression patterns among groups of genes. Using microarray expression data from 79 human tissues, we verify regulatory networks among genes controlled by bidirectional promoters. Subsets of these promoters contain similar combinations of transcription factor binding sites, including evolutionarily conserved ETS factor binding sites in ERBB2, FANCD2, and BRCA2. Interpreting the regulation of genes involved in co-expression networks, especially those involved in cancer, will be an important step toward defining molecular events that may contribute to disease.

  9. Re-annotation of the CAZy genes of Trichoderma reesei and transcription in the presence of lignocellulosic substrates

    Directory of Open Access Journals (Sweden)

    Häkkinen Mari

    2012-10-01

    Full Text Available Abstract Background Trichoderma reesei is a soft rot Ascomycota fungus utilised for industrial production of secreted enzymes, especially lignocellulose degrading enzymes. About 30 carbohydrate active enzymes (CAZymes of T. reesei have been biochemically characterised. Genome sequencing has revealed a large number of novel candidates for CAZymes, thus increasing the potential for identification of enzymes with novel activities and properties. Plenty of data exists on the carbon source dependent regulation of the characterised hydrolytic genes. However, information on the expression of the novel CAZyme genes, especially on complex biomass material, is very limited. Results In this study, the CAZyme gene content of the T. reesei genome was updated and the annotations of the genes refined using both computational and manual approaches. Phylogenetic analysis was done to assist the annotation and to identify functionally diversified CAZymes. The analyses identified 201 glycoside hydrolase genes, 22 carbohydrate esterase genes and five polysaccharide lyase genes. Updated or novel functional predictions were assigned to 44 genes, and the phylogenetic analysis indicated further functional diversification within enzyme families or groups of enzymes. GH3 β-glucosidases, GH27 α-galactosidases and GH18 chitinases were especially functionally diverse. The expression of the lignocellulose degrading enzyme system of T. reesei was studied by cultivating the fungus in the presence of different inducing substrates and by subjecting the cultures to transcriptional profiling. The substrates included both defined and complex lignocellulose related materials, such as pretreated bagasse, wheat straw, spruce, xylan, Avicel cellulose and sophorose. The analysis revealed co-regulated groups of CAZyme genes, such as genes induced in all the conditions studied and also genes induced preferentially by a certain set of substrates. Conclusions In this study, the CAZyme

  10. EuCAP, a Eukaryotic Community Annotation Package, and its application to the rice genome

    Directory of Open Access Journals (Sweden)

    Hamilton John P

    2007-10-01

    Full Text Available Abstract Background Despite the improvements of tools for automated annotation of genome sequences, manual curation at the structural and functional level can provide an increased level of refinement to genome annotation. The Institute for Genomic Research Rice Genome Annotation (hereafter named the Osa1 Genome Annotation is the product of an automated pipeline and, for this reason, will benefit from the input of biologists with expertise in rice and/or particular gene families. Leveraging knowledge from a dispersed community of scientists is a demonstrated way of improving a genome annotation. This requires tools that facilitate 1 the submission of gene annotation to an annotation project, 2 the review of the submitted models by project annotators, and 3 the incorporation of the submitted models in the ongoing annotation effort. Results We have developed the Eukaryotic Community Annotation Package (EuCAP, an annotation tool, and have applied it to the rice genome. The primary level of curation by community annotators (CA has been the annotation of gene families. Annotation can be submitted by email or through the EuCAP Web Tool. The CA models are aligned to the rice pseudomolecules and the coordinates of these alignments, along with functional annotation, are stored in the MySQL EuCAP Gene Model database. Web pages displaying the alignments of the CA models to the Osa1 Genome models are automatically generated from the EuCAP Gene Model database. The alignments are reviewed by the project annotators (PAs in the context of experimental evidence. Upon approval by the PAs, the CA models, along with the corresponding functional annotations, are integrated into the Osa1 Genome Annotation. The CA annotations, grouped by family, are displayed on the Community Annotation pages of the project website http://rice.tigr.org, as well as in the Community Annotation track of the Genome Browser. Conclusion We have applied EuCAP to rice. As of July 2007, the

  11. MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

    Science.gov (United States)

    Rappaport, Noa; Twik, Michal; Plaschkes, Inbar; Nudel, Ron; Iny Stein, Tsippi; Levitt, Jacob; Gershoni, Moran; Morrey, C. Paul; Safran, Marilyn; Lancet, Doron

    2017-01-01

    The MalaCards human disease database (http://www.malacards.org/) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ∼20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards’ affiliation with the GeneCards Suite of databases. MalaCards’ capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a ‘flat’ disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny. PMID:27899610

  12. MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search.

    Science.gov (United States)

    Rappaport, Noa; Twik, Michal; Plaschkes, Inbar; Nudel, Ron; Iny Stein, Tsippi; Levitt, Jacob; Gershoni, Moran; Morrey, C Paul; Safran, Marilyn; Lancet, Doron

    2017-01-04

    The MalaCards human disease database (http://www.malacards.org/) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ∼20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards' affiliation with the GeneCards Suite of databases. MalaCards' capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a 'flat' disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. Complete fold annotation of the human proteome using a novel structural feature space.

    Science.gov (United States)

    Middleton, Sarah A; Illuminati, Joseph; Kim, Junhyong

    2017-04-13

    Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this method by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families.

  14. JAFA: a protein function annotation meta-server

    DEFF Research Database (Denmark)

    Friedberg, Iddo; Harder, Tim; Godzik, Adam

    2006-01-01

    With the high number of sequences and structures streaming in from genomic projects, there is a need for more powerful and sophisticated annotation tools. Most problematic of the annotation efforts is predicting gene and protein function. Over the past few years there has been considerable progre...

  15. A computational approach for the annotation of hydrogen-bonded base interactions in crystallographic structures of the ribozymes

    Energy Technology Data Exchange (ETDEWEB)

    Hamdani, Hazrina Yusof, E-mail: hazrina@mfrlab.org [School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi (Malaysia); Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, Kepala Batas (Malaysia); Artymiuk, Peter J., E-mail: p.artymiuk@sheffield.ac.uk [Dept. of Molecular Biology and Biotechnology, Firth Court, University of Sheffield, S10 T2N Sheffield (United Kingdom); Firdaus-Raih, Mohd, E-mail: firdaus@mfrlab.org [School of Biosciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi (Malaysia)

    2015-09-25

    A fundamental understanding of the atomic level interactions in ribonucleic acid (RNA) and how they contribute towards RNA architecture is an important knowledge platform to develop through the discovery of motifs from simple arrangements base pairs, to more complex arrangements such as triples and larger patterns involving non-standard interactions. The network of hydrogen bond interactions is important in connecting bases to form potential tertiary motifs. Therefore, there is an urgent need for the development of automated methods for annotating RNA 3D structures based on hydrogen bond interactions. COnnection tables Graphs for Nucleic ACids (COGNAC) is automated annotation system using graph theoretical approaches that has been developed for the identification of RNA 3D motifs. This program searches for patterns in the unbroken networks of hydrogen bonds for RNA structures and capable of annotating base pairs and higher-order base interactions, which ranges from triples to sextuples. COGNAC was able to discover 22 out of 32 quadruples occurrences of the Haloarcula marismortui large ribosomal subunit (PDB ID: 1FFK) and two out of three occurrences of quintuple interaction reported by the non-canonical interactions in RNA (NCIR) database. These and several other interactions of interest will be discussed in this paper. These examples demonstrate that the COGNAC program can serve as an automated annotation system that can be used to annotate conserved base-base interactions and could be added as additional information to established RNA secondary structure prediction methods.

  16. Functional Annotation, Genome Organization and Phylogeny of the Grapevine (Vitis vinifera) Terpene Synthase Gene Family Based on Genome Assembly, FLcDNA Cloning, and Enzyme Assays

    Science.gov (United States)

    2010-01-01

    Background Terpenoids are among the most important constituents of grape flavour and wine bouquet, and serve as useful metabolite markers in viticulture and enology. Based on the initial 8-fold sequencing of a nearly homozygous Pinot noir inbred line, 89 putative terpenoid synthase genes (VvTPS) were predicted by in silico analysis of the grapevine (Vitis vinifera) genome assembly [1]. The finding of this very large VvTPS family, combined with the importance of terpenoid metabolism for the organoleptic properties of grapevine berries and finished wines, prompted a detailed examination of this gene family at the genomic level as well as an investigation into VvTPS biochemical functions. Results We present findings from the analysis of the up-dated 12-fold sequencing and assembly of the grapevine genome that place the number of predicted VvTPS genes at 69 putatively functional VvTPS, 20 partial VvTPS, and 63 VvTPS probable pseudogenes. Gene discovery and annotation included information about gene architecture and chromosomal location. A dense cluster of 45 VvTPS is localized on chromosome 18. Extensive FLcDNA cloning, gene synthesis, and protein expression enabled functional characterization of 39 VvTPS; this is the largest number of functionally characterized TPS for any species reported to date. Of these enzymes, 23 have unique functions and/or phylogenetic locations within the plant TPS gene family. Phylogenetic analyses of the TPS gene family showed that while most VvTPS form species-specific gene clusters, there are several examples of gene orthology with TPS of other plant species, representing perhaps more ancient VvTPS, which have maintained functions independent of speciation. Conclusions The highly expanded VvTPS gene family underpins the prominence of terpenoid metabolism in grapevine. We provide a detailed experimental functional annotation of 39 members of this important gene family in grapevine and comprehensive information about gene structure and

  17. Mapping and annotating obesity-related genes in pig and human genomes.

    Science.gov (United States)

    Martelli, Pier Luigi; Fontanesi, Luca; Piovesan, Damiano; Fariselli, Piero; Casadio, Rita

    2014-01-01

    Background. Obesity is a major health problem in both developed and emerging countries. Obesity is a complex disease whose etiology involves genetic factors in strong interplay with environmental determinants and lifestyle. The discovery of genetic factors and biological pathways underlying human obesity is hampered by the difficulty in controlling the genetic background of human cohorts. Animal models are then necessary to further dissect the genetics of obesity. Pig has emerged as one of the most attractive models, because of the similarity with humans in the mechanisms regulating the fat deposition. Results. We collected the genes related to obesity in humans and to fat deposition traits in pig. We localized them on both human and pig genomes, building a map useful to interpret comparative studies on obesity. We characterized the collected genes structurally and functionally with BAR+ and mapped them on KEGG pathways and on STRING protein interaction network. Conclusions. The collected set consists of 361 obesity related genes in human and pig genomes. All genes were mapped on the human genome, and 54 could not be localized on the pig genome (release 2012). Only for 3 human genes there is no counterpart in pig, confirming that this animal is a good model for human obesity studies. Obesity related genes are mostly involved in regulation and signaling processes/pathways and relevant connection emerges between obesity-related genes and diseases such as cancer and infectious diseases.

  18. Including Functional Annotations and Extending the Collection of Structural Classifications of Protein Loops (ArchDB

    Directory of Open Access Journals (Sweden)

    Antoni Hermoso

    2007-01-01

    Full Text Available Loops represent an important part of protein structures. The study of loop is critical for two main reasons: First, loops are often involved in protein function, stability and folding. Second, despite improvements in experimental and computational structure prediction methods, modeling the conformation of loops remains problematic. Here, we present a structural classification of loops, ArchDB, a mine of information with application in both mentioned fields: loop structure prediction and function prediction. ArchDB (http://sbi.imim.es/archdb is a database of classified protein loop motifs. The current database provides four different classification sets tailored for different purposes. ArchDB-40, a loop classification derived from SCOP40, well suited for modeling common loop motifs. Since features relevant to loop structure or function can be more easily determined on well-populated clusters, we have developed ArchDB-95, a loop classification derived from SCOP95. This new classification set shows a ∼40% increase in the number of subclasses, and a large 7-fold increase in the number of putative structure/function-related subclasses. We also present ArchDB-EC, a classification of loop motifs from enzymes, and ArchDB-KI, a manually annotated classification of loop motifs from kinases. Information about ligand contacts and PDB sites has been included in all classification sets. Improvements in our classification scheme are described, as well as several new database features, such as the ability to query by conserved annotations, sequence similarity, or uploading 3D coordinates of a protein. The lengths of classified loops range between 0 and 36 residues long. ArchDB offers an exhaustive sampling of loop structures. Functional information about loops and links with related biological databases are also provided. All this information and the possibility to browse/query the database through a web-server outline an useful tool with application in the

  19. A Method of Gene-Function Annotation Based on Variable Precision Rough Sets

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.

  20. PolySac3DB: an annotated data base of 3 dimensional structures of polysaccharides

    Directory of Open Access Journals (Sweden)

    Sarkar Anita

    2012-11-01

    Full Text Available Abstract Background Polysaccharides are ubiquitously present in the living world. Their structural versatility makes them important and interesting components in numerous biological and technological processes ranging from structural stabilization to a variety of immunologically important molecular recognition events. The knowledge of polysaccharide three-dimensional (3D structure is important in studying carbohydrate-mediated host-pathogen interactions, interactions with other bio-macromolecules, drug design and vaccine development as well as material science applications or production of bio-ethanol. Description PolySac3DB is an annotated database that contains the 3D structural information of 157 polysaccharide entries that have been collected from an extensive screening of scientific literature. They have been systematically organized using standard names in the field of carbohydrate research into 18 categories representing polysaccharide families. Structure-related information includes the saccharides making up the repeat unit(s and their glycosidic linkages, the expanded 3D representation of the repeat unit, unit cell dimensions and space group, helix type, diffraction diagram(s (when applicable, experimental and/or simulation methods used for structure description, link to the abstract of the publication, reference and the atomic coordinate files for visualization and download. The database is accompanied by a user-friendly graphical user interface (GUI. It features interactive displays of polysaccharide structures and customized search options for beginners and experts, respectively. The site also serves as an information portal for polysaccharide structure determination techniques. The web-interface also references external links where other carbohydrate-related resources are available. Conclusion PolySac3DB is established to maintain information on the detailed 3D structures of polysaccharides. All the data and features are available

  1. Epigenomic annotation of gene regulatory alterations during evolution of the primate brain

    NARCIS (Netherlands)

    Vermunt, Marit W; Tan, Sander C; Castelijns, Bas; Geeven, Geert; Reinink, Peter; de Bruijn, Ewart; Kondova, Ivanela; Persengiev, Stephan; Bontrop, Ronald; Cuppen, Edwin; de Laat, Wouter; Creyghton, Menno P

    Although genome sequencing has identified numerous noncoding alterations between primate species, which of those are regulatory and potentially relevant to the evolution of the human brain is unclear. Here we annotated cis-regulatory elements (CREs) in the human, rhesus macaque and chimpanzee

  2. Epigenomic annotation of gene regulatory alterations during evolution of the primate brain

    NARCIS (Netherlands)

    Vermunt, Marit W.; Tan, Sander C.; Castelijns, Bas; Geeven, Geert; Reinink, Peter; de Bruijn, Ewart; Kondova, Ivanela; Persengiev, Stephan; Bontrop, Ronald; Cuppen, Edwin|info:eu-repo/dai/nl/183050487; de laat, Wouter|info:eu-repo/dai/nl/169934497; Creyghton, Menno P.

    2016-01-01

    Although genome sequencing has identified numerous noncoding alterations between primate species, which of those are regulatory and potentially relevant to the evolution of the human brain is unclear. Here we annotated cis-regulatory elements (CREs) in the human, rhesus macaque and chimpanzee genome

  3. Annotated English

    CERN Document Server

    Hernandez-Orallo, Jose

    2010-01-01

    This document presents Annotated English, a system of diacritical symbols which turns English pronunciation into a precise and unambiguous process. The annotations are defined and located in such a way that the original English text is not altered (not even a letter), thus allowing for a consistent reading and learning of the English language with and without annotations. The annotations are based on a set of general rules that make the frequency of annotations not dramatically high. This makes the reader easily associate annotations with exceptions, and makes it possible to shape, internalise and consolidate some rules for the English language which otherwise are weakened by the enormous amount of exceptions in English pronunciation. The advantages of this annotation system are manifold. Any existing text can be annotated without a significant increase in size. This means that we can get an annotated version of any document or book with the same number of pages and fontsize. Since no letter is affected, the ...

  4. Annotation of the protein coding regions of the equine genome

    DEFF Research Database (Denmark)

    Hestand, Matthew S.; Kalbfleisch, Theodore S.; Coleman, Stephen J.

    2015-01-01

    Current gene annotation of the horse genome is largely derived from in silico predictions and cross-species alignments. Only a small number of genes are annotated based on equine EST and mRNA sequences. To expand the number of equine genes annotated from equine experimental evidence, we sequenced m...... and appear to be small errors in the equine reference genome, since they are also identified as homozygous variants by genomic DNA resequencing of the reference horse. Taken together, we provide a resource of equine mRNA structures and protein coding variants that will enhance equine and cross...

  5. Genome-wide profiling of 24 hr diel rhythmicity in the water flea, Daphnia pulex: network analysis reveals rhythmic gene expression and enhances functional gene annotation.

    Science.gov (United States)

    Rund, Samuel S C; Yoo, Boyoung; Alam, Camille; Green, Taryn; Stephens, Melissa T; Zeng, Erliang; George, Gary F; Sheppard, Aaron D; Duffield, Giles E; Milenković, Tijana; Pfrender, Michael E

    2016-08-18

    Marine and freshwater zooplankton exhibit daily rhythmic patterns of behavior and physiology which may be regulated directly by the light:dark (LD) cycle and/or a molecular circadian clock. One of the best-studied zooplankton taxa, the freshwater crustacean Daphnia, has a 24 h diel vertical migration (DVM) behavior whereby the organism travels up and down through the water column daily. DVM plays a critical role in resource tracking and the behavioral avoidance of predators and damaging ultraviolet radiation. However, there is little information at the transcriptional level linking the expression patterns of genes to the rhythmic physiology/behavior of Daphnia. Here we analyzed genome-wide temporal transcriptional patterns from Daphnia pulex collected over a 44 h time period under a 12:12 LD cycle (diel) conditions using a cosine-fitting algorithm. We used a comprehensive network modeling and analysis approach to identify novel co-regulated rhythmic genes that have similar network topological properties and functional annotations as rhythmic genes identified by the cosine-fitting analyses. Furthermore, we used the network approach to predict with high accuracy novel gene-function associations, thus enhancing current functional annotations available for genes in this ecologically relevant model species. Our results reveal that genes in many functional groupings exhibit 24 h rhythms in their expression patterns under diel conditions. We highlight the rhythmic expression of immunity, oxidative detoxification, and sensory process genes. We discuss differences in the chronobiology of D. pulex from other well-characterized terrestrial arthropods. This research adds to a growing body of literature suggesting the genetic mechanisms governing rhythmicity in crustaceans may be divergent from other arthropod lineages including insects. Lastly, these results highlight the power of using a network analysis approach to identify differential gene expression and provide novel

  6. Dynamic multimedia annotation tool

    Science.gov (United States)

    Pfund, Thomas; Marchand-Maillet, Stephane

    2001-12-01

    Annotating image collections is crucial for different multimedia applications. Not only this provides an alternative access to visual information but it is a critical step to perform the evaluation of content-based image retrieval systems. Annotation is a tedious task so that there is a real need for developing tools that lighten the work of annotators. The tool should be flexible and offer customization so as to make the annotator the most comfortable. It should also automate the most tasks as possible. In this paper, we present a still image annotation tool that has been developed with the aim of being flexible and adaptive. The principle is to create a set of dynamic web pages that are an interface to a SQL database. The keyword set is fixed and every image receives from concurrent annotators a set of keywords along with time stamps and annotator Ids. Each annotator has the possibility of going back and forth within the collection and its previous annotations. He is helped by a number of search services and customization options. An administrative section allows the supervisor to control the parameter of the annotation, including the keyword set, given via an XML structure. The architecture of the tool is made flexible so as to accommodate further options through its development.

  7. Annotation of gene promoters by integrative data-mining of ChIP-seq Pol-II enrichment data.

    Science.gov (United States)

    Gupta, Ravi; Wikramasinghe, Priyankara; Bhattacharyya, Anirban; Perez, Francisco A; Pal, Sharmistha; Davuluri, Ramana V

    2010-01-18

    Use of alternative gene promoters that drive widespread cell-type, tissue-type or developmental gene regulation in mammalian genomes is a common phenomenon. Chromatin immunoprecipitation methods coupled with DNA microarray (ChIP-chip) or massive parallel sequencing (ChIP-seq) are enabling genome-wide identification of active promoters in different cellular conditions using antibodies against Pol-II. However, these methods produce enrichment not only near the gene promoters but also inside the genes and other genomic regions due to the non-specificity of the antibodies used in ChIP. Further, the use of these methods is limited by their high cost and strong dependence on cellular type and context. We trained and tested different state-of-art ensemble and meta classification methods for identification of Pol-II enriched promoter and Pol-II enriched non-promoter sequences, each of length 500 bp. The classification models were trained and tested on a bench-mark dataset, using a set of 39 different feature variables that are based on chromatin modification signatures and various DNA sequence features. The best performing model was applied on seven published ChIP-seq Pol-II datasets to provide genome wide annotation of mouse gene promoters. We present a novel algorithm based on supervised learning methods to discriminate promoter associated Pol-II enrichment from enrichment elsewhere in the genome in ChIP-chip/seq profiles. We accumulated a dataset of 11,773 promoter and 46,167 non-promoter sequences, each of length 500 bp, generated from RNA Pol-II ChIP-seq data of five tissues (Brain, Kidney, Liver, Lung and Spleen). We evaluated the classification models in building the best predictor and found that Bagging and Random Forest based approaches give the best accuracy. We implemented the algorithm on seven different published ChIP-seq datasets to provide a comprehensive set of promoter annotations for both protein-coding and non-coding genes in the mouse genome. The

  8. Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources

    Directory of Open Access Journals (Sweden)

    van Hijum Sacha AFT

    2008-10-01

    Full Text Available Abstract Background Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict function on a large scale: genes exhibiting similar expression patterns are more likely to participate in shared biological processes. Results We developed Prosecutor, an application that enables researchers to rapidly infer gene function based on available gene expression data and functional annotations. Our parameter-free functional prediction method uses a sensitive algorithm to achieve a high association rate of linking genes with unknown function to annotated genes. Furthermore, Prosecutor utilizes additional biological information such as genomic context and known regulatory mechanisms that are specific for prokaryotes. We analyzed publicly available transcriptome data sets and used literature sources to validate putative functions suggested by Prosecutor. We supply the complete results of our analysis for 11 prokaryotic organisms on a dedicated website. Conclusion The Prosecutor software and supplementary datasets available at http://www.prosecutor.nl allow researchers working on any of the analyzed organisms to quickly identify the putative functions of their genes of interest. A de novo analysis allows new organisms to be studied.

  9. Supplementary Material for: BEACON: automated tool for Bacterial GEnome Annotation ComparisON

    KAUST Repository

    Kalkatawi, Manal Matoq Saeed

    2015-01-01

    Abstract Background Genome annotation is one way of summarizing the existing knowledge about genomic characteristics of an organism. There has been an increased interest during the last several decades in computer-based structural and functional genome annotation. Many methods for this purpose have been developed for eukaryotes and prokaryotes. Our study focuses on comparison of functional annotations of prokaryotic genomes. To the best of our knowledge there is no fully automated system for detailed comparison of functional genome annotations generated by different annotation methods (AMs). Results The presence of many AMs and development of new ones introduce needs to: a/ compare different annotations for a single genome, and b/ generate annotation by combining individual ones. To address these issues we developed an Automated Tool for Bacterial GEnome Annotation ComparisON (BEACON) that benefits both AM developers and annotation analysers. BEACON provides detailed comparison of gene function annotations of prokaryotic genomes obtained by different AMs and generates extended annotations through combination of individual ones. For the illustration of BEACONâ s utility, we provide a comparison analysis of multiple different annotations generated for four genomes and show on these examples that the extended annotation can increase the number of genes annotated by putative functions up to 27 %, while the number of genes without any function assignment is reduced. Conclusions We developed BEACON, a fast tool for an automated and a systematic comparison of different annotations of single genomes. The extended annotation assigns putative functions to many genes with unknown functions. BEACON is available under GNU General Public License version 3.0 and is accessible at: http://www.cbrc.kaust.edu.sa/BEACON/ .

  10. Ubiquitous Annotation Systems

    DEFF Research Database (Denmark)

    Hansen, Frank Allan

    2006-01-01

    Ubiquitous annotation systems allow users to annotate physical places, objects, and persons with digital information. Especially in the field of location based information systems much work has been done to implement adaptive and context-aware systems, but few efforts have focused on the general...... requirements for linking information to objects in both physical and digital space. This paper surveys annotation techniques from open hypermedia systems, Web based annotation systems, and mobile and augmented reality systems to illustrate different approaches to four central challenges ubiquitous annotation...... systems have to deal with: anchoring, structuring, presentation, and authoring. Through a number of examples each challenge is discussed and HyCon, a context-aware hypermedia framework developed at the University of Aarhus, Denmark, is used to illustrate an integrated approach to ubiquitous annotations...

  11. Heterogeneous data analysis for annotation of microRNAs and novel genome assembly

    NARCIS (Netherlands)

    Zhang, Yanju

    2011-01-01

    This thesis is the collection of four published papers demonstrating annotation of genes and microRNAs with the aid of bioinformatics, in particular using heterogeneous data integration. Gene annotation is the process of detecting the structure and biological function of the raw DNA sequences; while

  12. Discovery of germline-related genes in Cephalochordate amphioxus: A genome wide survey using genome annotation and transcriptome data.

    Science.gov (United States)

    Yue, Jia-Xing; Li, Kun-Lung; Yu, Jr-Kai

    2015-12-01

    The generation of germline cells is a critical process in the reproduction of multicellular organisms. Studies in animal models have identified a common repertoire of genes that play essential roles in primordial germ cell (PGC) formation. However, comparative studies also indicate that the timing and regulation of this core genetic program vary considerably in different animals, raising the intriguing questions regarding the evolution of PGC developmental mechanisms in metazoans. Cephalochordates (commonly called amphioxus or lancelets) represent one of the invertebrate chordate groups and can provide important information about the evolution of developmental mechanisms in the chordate lineage. In this study, we used genome and transcriptome data to identify germline-related genes in two distantly related cephalochordate species, Branchiostoma floridae and Asymmetron lucayanum. Branchiostoma and Asymmetron diverged more than 120 MYA, and the most conspicuous difference between them is their gonadal morphology. We used important germline developmental genes in several model animals to search the amphioxus genome and transcriptome dataset for conserved homologs. We also annotated the assembled transcriptome data using Gene Ontology (GO) terms to facilitate the discovery of putative genes associated with germ cell development and reproductive functions in amphioxus. We further confirmed the expression of 14 genes in developing oocytes or mature eggs using whole mount in situ hybridization, suggesting their potential functions in amphioxus germ cell development. The results of this global survey provide a useful resource for testing potential functions of candidate germline-related genes in cephalochordates and for investigating differences in gonad developmental mechanisms between Branchiostoma and Asymmetron species.

  13. Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research.

    Science.gov (United States)

    Köhler, Sebastian; Doelken, Sandra C; Ruef, Barbara J; Bauer, Sebastian; Washington, Nicole; Westerfield, Monte; Gkoutos, George; Schofield, Paul; Smedley, Damian; Lewis, Suzanna E; Robinson, Peter N; Mungall, Christopher J

    2013-01-01

    Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species. We have generated a cross-species phenotype ontology for human, mouse and zebrafish that contains classes from the Human Phenotype Ontology, Mammalian Phenotype Ontology, and generated classes for zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases. This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained from http://purl.obolibrary.org/obo/hp/uberpheno/.

  14. Ixodes scapularis tick serine proteinase inhibitor (serpin gene family; annotation and transcriptional analysis

    Directory of Open Access Journals (Sweden)

    Chalaire Katelyn C

    2009-05-01

    Full Text Available Abstract Background Serine proteinase inhibitors (Serpins are a large superfamily of structurally related, but functionally diverse proteins that control essential proteolytic pathways in most branches of life. Given their importance in the biology of many organisms, the concept that ticks might utilize serpins to evade host defenses and immunizing against or disrupting their functions as targets for tick control is an appealing option. Results A sequence homology search strategy has allowed us to identify at least 45 tick serpin genes in the Ixodes scapularis genome that are structurally segregated into 32 intronless and 13 intron-containing genes. Nine of the intron-containing serpins occur in a cluster of 11 genes that span 170 kb of DNA sequence. Based on consensus amino acid residues in the reactive center loop (RCL and signal peptide scanning, 93% are putatively inhibitory while 82% are putatively extracellular. Among the 11 different amino acid residues that are predicted at the P1 sites, 16 sequences possess basic amino acid (R/K residues. Temporal and spatial expression analyses revealed that 40 of the 45 serpins are differentially expressed in salivary glands (SG and/or midguts (MG of unfed and partially fed ticks. Ten of the 38 serpin genes were expressed from six to 24 hrs of feeding while six and fives genes each are predominantly or exclusively expressed in either MG and SG respectively. Conclusion Given the diversity among tick species, sizes of tick serpin families are likely to be variable. However this study provides insight on the potential sizes of serpin protein families in ticks. Ticks must overcome inflammation, complement activation and blood coagulation to complete feeding. Since these pathways are regulated by serpins that have basic residues at their P1 sites, we speculate that I. scapularis may utilize some of the serpins reported in this study to manipulate host defense. We have discussed our data in the context of

  15. Annotation of Ehux ESTs

    Energy Technology Data Exchange (ETDEWEB)

    Kuo, Alan; Grigoriev, Igor

    2009-06-12

    22 percent ESTs do no align with scaffolds. EST Pipeleine assembles 17126 consensi from the noaligned ESTs. Annotation Pipeline predicts 8564 ORFS on the consensi. Domain analysis of ORFs reveals missing genes. Cluster analysis reveals missing genes. Expression analysis reveals potential strain specific genes.

  16. Identiifcation of novel genes and optimization of annotated genes in foxtail millet by RNA-Seq technology%基于RNA-Seq技术的谷子新基因发掘及基因结构优化

    Institute of Scientific and Technical Information of China (English)

    穆彩琴; 张瑞娟; 屈聪玲; 韩渊怀; 王兴春; 杨致荣

    2016-01-01

    尽管谷子(Setaria italica)全基因组序列图谱已经公布,但其基因注释很不完善。为此,本文应用RNA-Seq技术开展了谷子新基因发掘和已注释基因结构优化工作。以‘晋谷21’谷子叶片为材料提取总RNA,构建测序文库并利用Illumina HiSeq 2500测序平台进行双端测序,最终获得37072949条高质量的干净读段(clean reads)。将其进一步与‘豫谷1号’谷子参考基因组进行序列比对,鉴定出614个新基因。在此基础上,利用COG、GO、KEGG、Swiss-Prot和NR等数据库对其进行了功能注释,获得了438个新基因的注释信息。此外,还优化了7175个已注释基因的结构,延伸了4330个基因的5′端和5362个基因的3′端。本研究旨在为后续谷子功能基因组学研究和其他生物基因组注释信息的完善提供有益的借鉴。%Although the reference genome of foxtail millet has been released, the gene annotation is not opti-mized. Therefore, we carried out the experiment for the identiifcation of novel genes and the structural optimi-zation of the annotated genes in foxtail millet by RNA sequencing (RNA-Seq) technology. The total RNA was isolated from the leaves of ‘Jingu 21’, and used for sequencing library construction. The library was paired-end sequenced using the Illumina HiSeq 2500 sequencing platform and, ifnally, 37 072 949 high quality clean reads were obtained. To identify novel genes and optimize the annotated gene structure, the clean reads were further aligned with ‘Yugu 1’ reference genome. A total of 614 novel genes were identiifed and 438 genes among them were annotated using COG, GO, KEGG, Swiss-Prot and NR databases. In addition, 7 175 gene structures were optimized, and 4 330 of 5′ ends and 5 362 of 3′ ends were extended. This study can provide useful references for future functional genomics research in foxtail millet and for optimization of the genome annotation in other related organisms.

  17. Annotated genetic linkage maps of Pinus pinaster Ait. from a Central Spain population using microsatellite and gene based markers

    Directory of Open Access Journals (Sweden)

    de Miguel Marina

    2012-10-01

    Full Text Available Abstract Background Pinus pinaster Ait. is a major resin producing species in Spain. Genetic linkage mapping can facilitate marker-assisted selection (MAS through the identification of Quantitative Trait Loci and selection of allelic variants of interest in breeding populations. In this study, we report annotated genetic linkage maps for two individuals (C14 and C15 belonging to a breeding program aiming to increase resin production. We use different types of DNA markers, including last-generation molecular markers. Results We obtained 13 and 14 linkage groups for C14 and C15 maps, respectively. A total of 211 and 215 markers were positioned on each map and estimated genome length was between 1,870 and 2,166 cM respectively, which represents near 65% of genome coverage. Comparative mapping with previously developed genetic linkage maps for P. pinaster based on about 60 common markers enabled aligning linkage groups to this reference map. The comparison of our annotated linkage maps and linkage maps reporting QTL information revealed 11 annotated SNPs in candidate genes that co-localized with previously reported QTLs for wood properties and water use efficiency. Conclusions This study provides genetic linkage maps from a Spanish population that shows high levels of genetic divergence with French populations from which segregating progenies have been previously mapped. These genetic maps will be of interest to construct a reliable consensus linkage map for the species. The importance of developing functional genetic linkage maps is highlighted, especially when working with breeding populations for its future application in MAS for traits of interest.

  18. Developmental gene discovery in a hemimetabolous insect: de novo assembly and annotation of a transcriptome for the cricket Gryllus bimaculatus.

    Directory of Open Access Journals (Sweden)

    Victor Zeng

    Full Text Available Most genomic resources available for insects represent the Holometabola, which are insects that undergo complete metamorphosis like beetles and flies. In contrast, the Hemimetabola (direct developing insects, representing the basal branches of the insect tree, have very few genomic resources. We have therefore created a large and publicly available transcriptome for the hemimetabolous insect Gryllus bimaculatus (cricket, a well-developed laboratory model organism whose potential for functional genetic experiments is currently limited by the absence of genomic resources. cDNA was prepared using mRNA obtained from adult ovaries containing all stages of oogenesis, and from embryo samples on each day of embryogenesis. Using 454 Titanium pyrosequencing, we sequenced over four million raw reads, and assembled them into 21,512 isotigs (predicted transcripts and 120,805 singletons with an average coverage per base pair of 51.3. We annotated the transcriptome manually for over 400 conserved genes involved in embryonic patterning, gametogenesis, and signaling pathways. BLAST comparison of the transcriptome against the NCBI non-redundant protein database (nr identified significant similarity to nr sequences for 55.5% of transcriptome sequences, and suggested that the transcriptome may contain 19,874 unique transcripts. For predicted transcripts without significant similarity to known sequences, we assessed their similarity to other orthopteran sequences, and determined that these transcripts contain recognizable protein domains, largely of unknown function. We created a searchable, web-based database to allow public access to all raw, assembled and annotated data. This database is to our knowledge the largest de novo assembled and annotated transcriptome resource available for any hemimetabolous insect. We therefore anticipate that these data will contribute significantly to more effective and higher-throughput deployment of molecular analysis tools in

  19. Algal functional annotation tool

    Energy Technology Data Exchange (ETDEWEB)

    Lopez, D. [UCLA; Casero, D. [UCLA; Cokus, S. J. [UCLA; Merchant, S. S. [UCLA; Pellegrini, M. [UCLA

    2012-07-01

    The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion.

  20. Annotation Of Novel And Conserved MicroRNA Genes In The Build 10 Sus scrofa Reference Genome And Determination Of Their Expression Levels In Ten Different Tissues

    DEFF Research Database (Denmark)

    Thomsen, Bo; Nielsen, Mathilde; Hedegaard, Jakob

    The DNA template used in the pig genome sequencing project was provided by a Duroc pig named TJ Tabasco. In an effort to annotate microRNA (miRNA) genes in the reference genome we have conducted deep sequencing to determine the miRNA transcriptomes in ten different tissues isolated from Pinky......, a genetically identical clone of TJ Tabasco. The purpose was to generate miRNA sequences that are highly homologous to the reference genome sequence, which along with computational prediction will improve confidence in the genomic annotation of miRNA genes. Based on homology searches of the sequence data...

  1. Annotated Gene and Proteome Data Support Recognition of Interconnections Between the Results of Different Experiments in Space Research

    Science.gov (United States)

    Bauer, Johann; Wehland, Markus; Pietsch, Jessica; Sickmann, Albert; Weber, Gerhard; Grimm, Daniela

    2016-06-01

    In a series of studies, human thyroid and endothelial cells exposed to real or simulated microgravity were analyzed in terms of changes in gene expression patterns or protein content. Due to the limitation of available cells in many space research experiments, comparative and control experiments had to be done in a serial manner. Therefore, detected genes or proteins were annotated with gene names and SwissProt numbers, in order to allow searches for interconnections between results obtained in different experiments by different methods. A crosscheck of several studies on the behavior of cytoskeletal genes and proteins suggested that clusters of cytoskeletal components change differently under the influence of microgravity and/or vibration in different cell types. The result that LOX and ISG15 gene expression were clearly altered during the Shenzhou-8 spaceflight mission could be estimated by comparison with the results of other experiments. The more than 100-fold down-regulation of LOX supports our hypothesis that the amount and stability of extracellular matrix have a great influence on the formation of three-dimensional aggregates under microgravity. The approximately 40-fold up-regulation of ISG15 cannot yet be explained in detail, but strongly suggests that ISGylation, an alternative form of posttranslational modification, plays a role in longterm cultures.

  2. Algal functional annotation tool

    Energy Technology Data Exchange (ETDEWEB)

    2012-07-12

    Abstract BACKGROUND: Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. DESCRIPTION: The Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes

  3. De novo assembly, gene annotation, and marker discovery in stored-product pest Liposcelis entomophila (Enderlein using transcriptome sequences.

    Directory of Open Access Journals (Sweden)

    Dan-Dan Wei

    Full Text Available BACKGROUND: As a major stored-product pest insect, Liposcelis entomophila has developed high levels of resistance to various insecticides in grain storage systems. However, the molecular mechanisms underlying resistance and environmental stress have not been characterized. To date, there is a lack of genomic information for this species. Therefore, studies aimed at profiling the L. entomophila transcriptome would provide a better understanding of the biological functions at the molecular levels. METHODOLOGY/PRINCIPAL FINDINGS: We applied Illumina sequencing technology to sequence the transcriptome of L. entomophila. A total of 54,406,328 clean reads were obtained and that de novo assembled into 54,220 unigenes, with an average length of 571 bp. Through a similarity search, 33,404 (61.61% unigenes were matched to known proteins in the NCBI non-redundant (Nr protein database. These unigenes were further functionally annotated with gene ontology (GO, cluster of orthologous groups of proteins (COG, and Kyoto Encyclopedia of Genes and Genomes (KEGG databases. A large number of genes potentially involved in insecticide resistance were manually curated, including 68 putative cytochrome P450 genes, 37 putative glutathione S-transferase (GST genes, 19 putative carboxyl/cholinesterase (CCE genes, and other 126 transcripts to contain target site sequences or encoding detoxification genes representing eight types of resistance enzymes. Furthermore, to gain insight into the molecular basis of the L. entomophila toward thermal stresses, 25 heat shock protein (Hsp genes were identified. In addition, 1,100 SSRs and 57,757 SNPs were detected and 231 pairs of SSR primes were designed for investigating the genetic diversity in future. CONCLUSIONS/SIGNIFICANCE: We developed a comprehensive transcriptomic database for L. entomophila. These sequences and putative molecular markers would further promote our understanding of the molecular mechanisms underlying

  4. Genomic organization, annotation, and ligand-receptor inferences of chicken chemokines and chemokine receptor genes based on comparative genomics

    Directory of Open Access Journals (Sweden)

    Sze Sing-Hoi

    2005-03-01

    Full Text Available Abstract Background Chemokines and their receptors play important roles in host defense, organogenesis, hematopoiesis, and neuronal communication. Forty-two chemokines and 19 cognate receptors have been found in the human genome. Prior to this report, only 11 chicken chemokines and 7 receptors had been reported. The objectives of this study were to systematically identify chicken chemokines and their cognate receptor genes in the chicken genome and to annotate these genes and ligand-receptor binding by a comparative genomics approach. Results Twenty-three chemokine and 14 chemokine receptor genes were identified in the chicken genome. All of the chicken chemokines contained a conserved CC, CXC, CX3C, or XC motif, whereas all the chemokine receptors had seven conserved transmembrane helices, four extracellular domains with a conserved cysteine, and a conserved DRYLAIV sequence in the second intracellular domain. The number of coding exons in these genes and the syntenies are highly conserved between human, mouse, and chicken although the amino acid sequence homologies are generally low between mammalian and chicken chemokines. Chicken genes were named with the systematic nomenclature used in humans and mice based on phylogeny, synteny, and sequence homology. Conclusion The independent nomenclature of chicken chemokines and chemokine receptors suggests that the chicken may have ligand-receptor pairings similar to mammals. All identified chicken chemokines and their cognate receptors were identified in the chicken genome except CCR9, whose ligand was not identified in this study. The organization of these genes suggests that there were a substantial number of these genes present before divergence between aves and mammals and more gene duplications of CC, CXC, CCR, and CXCR subfamilies in mammals than in aves after the divergence.

  5. Annotation of Differential Gene Expression in Small Yellow Follicles of a Broiler-Type Strain of Taiwan Country Chickens in Response to Acute Heat Stress.

    Science.gov (United States)

    Cheng, Chuen-Yu; Tu, Wei-Lin; Wang, Shih-Han; Tang, Pin-Chi; Chen, Chih-Feng; Chen, Hsin-Hsin; Lee, Yen-Pai; Chen, Shuen-Ei; Huang, San-Yuan

    2015-01-01

    This study investigated global gene expression in the small yellow follicles (6-8 mm diameter) of broiler-type B strain Taiwan country chickens (TCCs) in response to acute heat stress. Twelve 30-wk-old TCC hens were divided into four groups: control hens maintained at 25°C and hens subjected to 38°C acute heat stress for 2 h without recovery (H2R0), with 2-h recovery (H2R2), and with 6-h recovery (H2R6). Small yellow follicles were collected for RNA isolation and microarray analysis at the end of each time point. Results showed that 69, 51, and 76 genes were upregulated and 58, 15, 56 genes were downregulated after heat treatment of H2R0, H2R2, and H2R6, respectively, using a cutoff value of two-fold or higher. Gene ontology analysis revealed that these differentially expressed genes are associated with the biological processes of cell communication, developmental process, protein metabolic process, immune system process, and response to stimuli. Upregulation of heat shock protein 25, interleukin 6, metallopeptidase 1, and metalloproteinase 13, and downregulation of type II alpha 1 collagen, discoidin domain receptor tyrosine kinase 2, and Kruppel-like factor 2 suggested that acute heat stress induces proteolytic disintegration of the structural matrix and inflamed damage and adaptive responses of gene expression in the follicle cells. These suggestions were validated through gene expression, using quantitative real-time polymerase chain reaction. Functional annotation clarified that interleukin 6-related pathways play a critical role in regulating acute heat stress responses in the small yellow follicles of TCC hens.

  6. Genepi: a blackboard framework for genome annotation.

    Science.gov (United States)

    Descorps-Declère, Stéphane; Ziébelin, Danielle; Rechenmann, François; Viari, Alain

    2006-10-12

    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 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. 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.

  7. Genepi: a blackboard framework for genome annotation

    Directory of Open Access Journals (Sweden)

    Ziébelin Danielle

    2006-10-01

    Full Text Available Abstract 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.

  8. Functional genomics tools applied to plant metabolism: a survey on plant respiration, its connections and the annotation of complex gene functions

    Directory of Open Access Journals (Sweden)

    Wagner L. Araújo

    2012-09-01

    Full Text Available The application of post-genomic techniques in plant respiration studies has greatly improved our ability to assign functions to gene products. In addition it has also revealed previously unappreciated interactions between distal elements of metabolism. Such results have reinforced the need to consider plant respiratory metabolism as part of a complex network and making sense of such interactions will ultimately require the construction of predictive and mechanistic models. Transcriptomics, proteomics, metabolomics and the quantification of metabolic flux will be of great value in creating such models both by facilitating the annotation of complex gene function, determining their structure and by furnishing the quantitative data required to test them. In this review we highlight how these experimental approaches have contributed to our current understanding of plant respiratory metabolism and its interplay with associated process (e.g. photosynthesis, photorespiration and nitrogen metabolism. We also discuss how data from these techniques may be integrated, with the ultimate aim of identifying mechanisms that control and regulate plant respiration and discovering novel gene functions with potential biotechnological implications.

  9. Array2BIO: from microarray expression data to functional annotation of co-regulated genes

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    Rasley Amy

    2006-06-01

    Full Text Available Abstract Background There are several isolated tools for partial analysis of microarray expression data. To provide an integrative, easy-to-use and automated toolkit for the analysis of Affymetrix microarray expression data we have developed Array2BIO, an application that couples several analytical methods into a single web based utility. Results Array2BIO converts raw intensities into probe expression values, automatically maps those to genes, and subsequently identifies groups of co-expressed genes using two complementary approaches: (1 comparative analysis of signal versus control and (2 clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on Gene Ontology classification and KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods for quantifying expression levels, including Benjamini-Hochberg and Bonferroni multiple testing corrections. An automated interface with the ECR Browser provides evolutionary conservation analysis for the identified gene loci while the interconnection with Crème allows prediction of gene regulatory elements that underlie observed expression patterns. Conclusion We have developed Array2BIO – a web based tool for rapid comprehensive analysis of Affymetrix microarray expression data, which also allows users to link expression data to Dcode.org comparative genomics tools and integrates a system for translating co-expression data into mechanisms of gene co-regulation. Array2BIO is publicly available at http://array2bio.dcode.org.

  10. Analysis of antisense expression by whole genome tiling microarrays and siRNAs suggests mis-annotation of Arabidopsis orphan protein-coding genes.

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    Casey R Richardson

    Full Text Available BACKGROUND: MicroRNAs (miRNAs and trans-acting small-interfering RNAs (tasi-RNAs are small (20-22 nt long RNAs (smRNAs generated from hairpin secondary structures or antisense transcripts, respectively, that regulate gene expression by Watson-Crick pairing to a target mRNA and altering expression by mechanisms related to RNA interference. The high sequence homology of plant miRNAs to their targets has been the mainstay of miRNA prediction algorithms, which are limited in their predictive power for other kingdoms because miRNA complementarity is less conserved yet transitive processes (production of antisense smRNAs are active in eukaryotes. We hypothesize that antisense transcription and associated smRNAs are biomarkers which can be computationally modeled for gene discovery. PRINCIPAL FINDINGS: We explored rice (Oryza sativa sense and antisense gene expression in publicly available whole genome tiling array transcriptome data and sequenced smRNA libraries (as well as C. elegans and found evidence of transitivity of MIRNA genes similar to that found in Arabidopsis. Statistical analysis of antisense transcript abundances, presence of antisense ESTs, and association with smRNAs suggests several hundred Arabidopsis 'orphan' hypothetical genes are non-coding RNAs. Consistent with this hypothesis, we found novel Arabidopsis homologues of some MIRNA genes on the antisense strand of previously annotated protein-coding genes. A Support Vector Machine (SVM was applied using thermodynamic energy of binding plus novel expression features of sense/antisense transcription topology and siRNA abundances to build a prediction model of miRNA targets. The SVM when trained on targets could predict the "ancient" (deeply conserved class of validated Arabidopsis MIRNA genes with an accuracy of 84%, and 76% for "new" rapidly-evolving MIRNA genes. CONCLUSIONS: Antisense and smRNA expression features and computational methods may identify novel MIRNA genes and other non

  11. A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer

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    Leckie Christopher

    2010-09-01

    Full Text Available Abstract Background In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of interesting genes or biological pathways. However, in order to analyze the large number of noisy measurements in microarrays, effective and efficient bioinformatics techniques are needed to identify the associations between genes and relevant phenotypes. Moreover, systematic tests are needed to validate the statistical and biological significance of those discoveries. Results In this paper, we develop a robust and efficient method for exploratory analysis of microarray data, which produces a number of different orderings (rankings of both genes and samples (reflecting correlation among those genes and samples. The core algorithm is closely related to biclustering, and so we first compare its performance with several existing biclustering algorithms on two real datasets - gastric cancer and lymphoma datasets. We then show on the gastric cancer data that the sample orderings generated by our method are highly statistically significant with respect to the histological classification of samples by using the Jonckheere trend test, while the gene modules are biologically significant with respect to biological processes (from the Gene Ontology. In particular, some of the gene modules associated with biclusters are closely linked to gastric cancer tumorigenesis reported in previous literature, while others are potentially novel discoveries. Conclusion In conclusion, we have developed an effective and efficient method, Bi-Ordering Analysis, to detect informative patterns in gene expression microarrays by ranking genes and samples. In addition, a number of evaluation metrics were applied to assess both the statistical and biological significance of the resulting bi-orderings. The methodology was validated on gastric cancer and lymphoma datasets.

  12. A bi-ordering approach to linking gene expression with clinical annotations in gastric cancer.

    Science.gov (United States)

    Shi, Fan; Leckie, Christopher; MacIntyre, Geoff; Haviv, Izhak; Boussioutas, Alex; Kowalczyk, Adam

    2010-09-23

    In the study of cancer genomics, gene expression microarrays, which measure thousands of genes in a single assay, provide abundant information for the investigation of interesting genes or biological pathways. However, in order to analyze the large number of noisy measurements in microarrays, effective and efficient bioinformatics techniques are needed to identify the associations between genes and relevant phenotypes. Moreover, systematic tests are needed to validate the statistical and biological significance of those discoveries. In this paper, we develop a robust and efficient method for exploratory analysis of microarray data, which produces a number of different orderings (rankings) of both genes and samples (reflecting correlation among those genes and samples). The core algorithm is closely related to biclustering, and so we first compare its performance with several existing biclustering algorithms on two real datasets - gastric cancer and lymphoma datasets. We then show on the gastric cancer data that the sample orderings generated by our method are highly statistically significant with respect to the histological classification of samples by using the Jonckheere trend test, while the gene modules are biologically significant with respect to biological processes (from the Gene Ontology). In particular, some of the gene modules associated with biclusters are closely linked to gastric cancer tumorigenesis reported in previous literature, while others are potentially novel discoveries. In conclusion, we have developed an effective and efficient method, Bi-Ordering Analysis, to detect informative patterns in gene expression microarrays by ranking genes and samples. In addition, a number of evaluation metrics were applied to assess both the statistical and biological significance of the resulting bi-orderings. The methodology was validated on gastric cancer and lymphoma datasets.

  13. GeneViTo: Visualizing gene-product functional and structural features in genomic datasets

    Directory of Open Access Journals (Sweden)

    Promponas Vasilis J

    2003-10-01

    Full Text Available Abstract Background The availability of increasing amounts of sequence data from completely sequenced genomes boosts the development of new computational methods for automated genome annotation and comparative genomics. Therefore, there is a need for tools that facilitate the visualization of raw data and results produced by bioinformatics analysis, providing new means for interactive genome exploration. Visual inspection can be used as a basis to assess the quality of various analysis algorithms and to aid in-depth genomic studies. Results GeneViTo is a JAVA-based computer application that serves as a workbench for genome-wide analysis through visual interaction. The application deals with various experimental information concerning both DNA and protein sequences (derived from public sequence databases or proprietary data sources and meta-data obtained by various prediction algorithms, classification schemes or user-defined features. Interaction with a Graphical User Interface (GUI allows easy extraction of genomic and proteomic data referring to the sequence itself, sequence features, or general structural and functional features. Emphasis is laid on the potential comparison between annotation and prediction data in order to offer a supplement to the provided information, especially in cases of "poor" annotation, or an evaluation of available predictions. Moreover, desired information can be output in high quality JPEG image files for further elaboration and scientific use. A compilation of properly formatted GeneViTo input data for demonstration is available to interested readers for two completely sequenced prokaryotes, Chlamydia trachomatis and Methanococcus jannaschii. Conclusions GeneViTo offers an inspectional view of genomic functional elements, concerning data stemming both from database annotation and analysis tools for an overall analysis of existing genomes. The application is compatible with Linux or Windows ME-2000-XP operating

  14. An atlas of tissue-specific conserved coexpression for functional annotation and disease gene prediction.

    Science.gov (United States)

    Piro, Rosario Michael; Ala, Ugo; Molineris, Ivan; Grassi, Elena; Bracco, Chiara; Perego, Gian Paolo; Provero, Paolo; Di Cunto, Ferdinando

    2011-11-01

    Gene coexpression relationships that are phylogenetically conserved between human and mouse have been shown to provide important clues about gene function that can be efficiently used to identify promising candidate genes for human hereditary disorders. In the past, such approaches have considered mostly generic gene expression profiles that cover multiple tissues and organs. The individual genes of multicellular organisms, however, can participate in different transcriptional programs, operating at scales as different as single-cell types, tissues, organs, body regions or the entire organism. Therefore, systematic analysis of tissue-specific coexpression could be, in principle, a very powerful strategy to dissect those functional relationships among genes that emerge only in particular tissues or organs. In this report, we show that, in fact, conserved coexpression as determined from tissue-specific and condition-specific data sets can predict many functional relationships that are not detected by analyzing heterogeneous microarray data sets. More importantly, we find that, when combined with disease networks, the simultaneous use of both generic (multi-tissue) and tissue-specific conserved coexpression allows a more efficient prediction of human disease genes than the use of generic conserved coexpression alone. Using this strategy, we were able to identify high-probability candidates for 238 orphan disease loci. We provide proof of concept that this combined use of generic and tissue-specific conserved coexpression can be very useful to prioritize the mutational candidates obtained from deep-sequencing projects, even in the case of genetic disorders as heterogeneous as XLMR.

  15. The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4).

    Science.gov (United States)

    Huntemann, Marcel; Ivanova, Natalia N; Mavromatis, Konstantinos; Tripp, H James; Paez-Espino, David; Palaniappan, Krishnaveni; Szeto, Ernest; Pillay, Manoj; Chen, I-Min A; Pati, Amrita; Nielsen, Torben; Markowitz, Victor M; Kyrpides, Nikos C

    2015-01-01

    The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. Structural annotation is followed by assignment of protein product names and functions.

  16. PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

    Directory of Open Access Journals (Sweden)

    Liqi Li

    Full Text Available Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM in conjunction with integrated features from position-specific score matrix (PSSM, PROFEAT and Gene Ontology (GO. A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

  17. PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

    Science.gov (United States)

    Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

    2014-01-01

    Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

  18. The late-annotated small ORF LSO1 is a target gene of the iron regulon of Saccharomyces cerevisiae.

    Science.gov (United States)

    An, Xiuxiang; Zhang, Caiguo; Sclafani, Robert A; Seligman, Paul; Huang, Mingxia

    2015-12-01

    We have identified a new downstream target gene of the Aft1/2-regulated iron regulon in budding yeast Saccharomyces cerevisiae, the late-annotated small open reading frame LSO1. LSO1 transcript is among the most highly induced from a transcriptome analysis of a fet3-1 mutant grown in the presence of the iron chelator bathophenanthrolinedisulfonic acid. LSO1 has a paralog, LSO2, which is constitutively expressed and not affected by iron availability. In contrast, we find that the LSO1 promoter region contains three consensus binding sites for the Aft1/2 transcription factors and that an LSO1-lacZ reporter is highly induced under low-iron conditions in a Aft1-dependent manner. The expression patterns of the Lso1 and Lso2 proteins mirror those of their mRNAs. Both proteins are localized to the nucleus and cytoplasm, but become more cytoplasmic upon iron deprivation consistent with a role in iron transport. LSO1 and LSO2 appear to play overlapping roles in the cellular response to iron starvation since single lso1 and lso2 mutants are sensitive to iron deprivation and this sensitivity is exacerbated when both genes are deleted.

  19. An in silico Approach for Structural and Functional Annotation of Salmonella enterica serovar typhimurium Hypothetical Protein R_27

    Directory of Open Access Journals (Sweden)

    Arif Khan

    2016-03-01

    Full Text Available Typhoid fever is a major cause of illness in most developing countries, including Bangladesh. In quest of new potential drug against Typhoid fever, the current study was designed to elucidate structural and functional details of S. typhi hypothetical protein (HP R_27. HP R_27 has the primary amino acid sequences available only. The structural annotation was determined by ProtParam, SOPMA, and CELLO. The three-dimensional (3D structure of HP R_27 predicted through homology modeling by using Phyre2. The 3D structure then refined and verified by ModRefiner, PROCHECK, ERRAT, QMEAN. The functional annotation was also performed by InterProScan, SMART, Pfam, NCBI-CDD and found Phospholipase D-like and DNA repair activity. Multiple sequence alignment also supported the existence of PLD-like domain and DNA repair protein domain in the selected hypothetical protein sequences. Finally, the cavity of drug binding was also identified to assist further molecular docking study and potent inhibitor identification. This in silico approach can be further utilized in molecular drug design for other clinically significant pathogens.

  20. De novo assembly, gene annotation and marker development using Illumina paired-end transcriptome sequences in celery (Apium graveolens L..

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    Nan Fu

    Full Text Available BACKGROUND: Celery is an increasing popular vegetable species, but limited transcriptome and genomic data hinder the research to it. In addition, a lack of celery molecular markers limits the process of molecular genetic breeding. High-throughput transcriptome sequencing is an efficient method to generate a large transcriptome sequence dataset for gene discovery, molecular marker development and marker-assisted selection breeding. PRINCIPAL FINDINGS: Celery transcriptomes from four tissues were sequenced using Illumina paired-end sequencing technology. De novo assembling was performed to generate a collection of 42,280 unigenes (average length of 502.6 bp that represent the first transcriptome of the species. 78.43% and 48.93% of the unigenes had significant similarity with proteins in the National Center for Biotechnology Information (NCBI non-redundant protein database (Nr and Swiss-Prot database respectively, and 10,473 (24.77% unigenes were assigned to Clusters of Orthologous Groups (COG. 21,126 (49.97% unigenes harboring Interpro domains were annotated, in which 15,409 (36.45% were assigned to Gene Ontology(GO categories. Additionally, 7,478 unigenes were mapped onto 228 pathways using the Kyoto Encyclopedia of Genes and Genomes Pathway database (KEGG. Large numbers of simple sequence repeats (SSRs were indentified, and then the rate of successful amplication and polymorphism were investigated among 31 celery accessions. CONCLUSIONS: This study demonstrates the feasibility of generating a large scale of sequence information by Illumina paired-end sequencing and efficient assembling. Our results provide a valuable resource for celery research. The developed molecular markers are the foundation of further genetic linkage analysis and gene localization, and they will be essential to accelerate the process of breeding.

  1. Differential Gene Expression in the Otic Capsule and the Middle Ear-An Annotation of Bone-Related Signaling Genes

    DEFF Research Database (Denmark)

    Nielsen, Michelle C.; Martin-Bertelsen, Tomas; Friis, Morten;

    2015-01-01

    and stria vascularis) and the lining tissues from the middle ear of the rat. Data was analyzed with statistical bioinformatics tools. Gene expression levels of selected genes were validated using quantitative polymerase chain reaction. Results: A total of 413 genes were identified when young inner bulla...

  2. CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation

    Directory of Open Access Journals (Sweden)

    Li Gong-Hua

    2010-08-01

    Full Text Available Abstract Background The rapid development of structural genomics has resulted in many "unknown function" proteins being deposited in Protein Data Bank (PDB, thus, the functional prediction of these proteins has become a challenge for structural bioinformatics. Several sequence-based and structure-based methods have been developed to predict protein function, but these methods need to be improved further, such as, enhancing the accuracy, sensitivity, and the computational speed. Here, an accurate algorithm, the CMASA (Contact MAtrix based local Structural Alignment algorithm, has been developed to predict unknown functions of proteins based on the local protein structural similarity. This algorithm has been evaluated by building a test set including 164 enzyme families, and also been compared to other methods. Results The evaluation of CMASA shows that the CMASA is highly accurate (0.96, sensitive (0.86, and fast enough to be used in the large-scale functional annotation. Comparing to both sequence-based and global structure-based methods, not only the CMASA can find remote homologous proteins, but also can find the active site convergence. Comparing to other local structure comparison-based methods, the CMASA can obtain the better performance than both FFF (a method using geometry to predict protein function and SPASM (a local structure alignment method; and the CMASA is more sensitive than PINTS and is more accurate than JESS (both are local structure alignment methods. The CMASA was applied to annotate the enzyme catalytic sites of the non-redundant PDB, and at least 166 putative catalytic sites have been suggested, these sites can not be observed by the Catalytic Site Atlas (CSA. Conclusions The CMASA is an accurate algorithm for detecting local protein structural similarity, and it holds several advantages in predicting enzyme active sites. The CMASA can be used in large-scale enzyme active site annotation. The CMASA can be available by the

  3. Genomic sequence around butterfly wing development genes: annotation and comparative analysis.

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    Inês C Conceição

    Full Text Available BACKGROUND: Analysis of genomic sequence allows characterization of genome content and organization, and access beyond gene-coding regions for identification of functional elements. BAC libraries, where relatively large genomic regions are made readily available, are especially useful for species without a fully sequenced genome and can increase genomic coverage of phylogenetic and biological diversity. For example, no butterfly genome is yet available despite the unique genetic and biological properties of this group, such as diversified wing color patterns. The evolution and development of these patterns is being studied in a few target species, including Bicyclus anynana, where a whole-genome BAC library allows targeted access to large genomic regions. METHODOLOGY/PRINCIPAL FINDINGS: We characterize ∼1.3 Mb of genomic sequence around 11 selected genes expressed in B. anynana developing wings. Extensive manual curation of in silico predictions, also making use of a large dataset of expressed genes for this species, identified repetitive elements and protein coding sequence, and highlighted an expansion of Alcohol dehydrogenase genes. Comparative analysis with orthologous regions of the lepidopteran reference genome allowed assessment of conservation of fine-scale synteny (with detection of new inversions and translocations and of DNA sequence (with detection of high levels of conservation of non-coding regions around some, but not all, developmental genes. CONCLUSIONS: The general properties and organization of the available B. anynana genomic sequence are similar to the lepidopteran reference, despite the more than 140 MY divergence. Our results lay the groundwork for further studies of new interesting findings in relation to both coding and non-coding sequence: 1 the Alcohol dehydrogenase expansion with higher similarity between the five tandemly-repeated B. anynana paralogs than with the corresponding B. mori orthologs, and 2 the high

  4. Functional annotation of novel lineage-specific genes using co-expression and promoter analysis

    Directory of Open Access Journals (Sweden)

    Loor Juan J

    2010-03-01

    Full Text Available Abstract Background The diversity of placental architectures within and among mammalian orders is believed to be the result of adaptive evolution. Although, the genetic basis for these differences is unknown, some may arise from rapidly diverging and lineage-specific genes. Previously, we identified 91 novel lineage-specific transcripts (LSTs from a cow term-placenta cDNA library, which are excellent candidates for adaptive placental functions acquired by the ruminant lineage. The aim of the present study was to infer functions of previously uncharacterized lineage-specific genes (LSGs using co-expression, promoter, pathway and network analysis. Results Clusters of co-expressed genes preferentially expressed in liver, placenta and thymus were found using 49 previously uncharacterized LSTs as seeds. Over-represented composite transcription factor binding sites (TFBS in promoters of clustered LSGs and known genes were then identified computationally. Functions were inferred for nine previously uncharacterized LSGs using co-expression analysis and pathway analysis tools. Our results predict that these LSGs may function in cell signaling, glycerophospholipid/fatty acid metabolism, protein trafficking, regulatory processes in the nucleus, and processes that initiate parturition and immune system development. Conclusions The placenta is a rich source of lineage-specific genes that function in the adaptive evolution of placental architecture and functions. We have shown that co-expression, promoter, and gene network analyses are useful methods to infer functions of LSGs with heretofore unknown functions. Our results indicate that many LSGs are involved in cellular recognition and developmental processes. Furthermore, they provide guidance for experimental approaches to validate the functions of LSGs and to study their evolution.

  5. Functional annotation of novel lineage-specific genes using co-expression and promoter analysis.

    Science.gov (United States)

    Kumar, Charu G; Everts, Robin E; Loor, Juan J; Lewin, Harris A

    2010-03-09

    The diversity of placental architectures within and among mammalian orders is believed to be the result of adaptive evolution. Although, the genetic basis for these differences is unknown, some may arise from rapidly diverging and lineage-specific genes. Previously, we identified 91 novel lineage-specific transcripts (LSTs) from a cow term-placenta cDNA library, which are excellent candidates for adaptive placental functions acquired by the ruminant lineage. The aim of the present study was to infer functions of previously uncharacterized lineage-specific genes (LSGs) using co-expression, promoter, pathway and network analysis. Clusters of co-expressed genes preferentially expressed in liver, placenta and thymus were found using 49 previously uncharacterized LSTs as seeds. Over-represented composite transcription factor binding sites (TFBS) in promoters of clustered LSGs and known genes were then identified computationally. Functions were inferred for nine previously uncharacterized LSGs using co-expression analysis and pathway analysis tools. Our results predict that these LSGs may function in cell signaling, glycerophospholipid/fatty acid metabolism, protein trafficking, regulatory processes in the nucleus, and processes that initiate parturition and immune system development. The placenta is a rich source of lineage-specific genes that function in the adaptive evolution of placental architecture and functions. We have shown that co-expression, promoter, and gene network analyses are useful methods to infer functions of LSGs with heretofore unknown functions. Our results indicate that many LSGs are involved in cellular recognition and developmental processes. Furthermore, they provide guidance for experimental approaches to validate the functions of LSGs and to study their evolution.

  6. plantiSMASH: automated identification, annotation and expression analysis of plant biosynthetic gene clusters

    DEFF Research Database (Denmark)

    Kautsar, Satria A.; Suarez Duran, Hernando G.; Blin, Kai

    2017-01-01

    of predicted biosynthetic enzyme-coding genes, and facilitates comparative genomic analysis to study the evolutionary conservation of each cluster. Applied on 48 high-quality plant genomes, plantiSMASH identifies a rich diversity of candidate plant BGCs. These results will guide further experimental...... exploration of the nature and dynamics of gene clustering in plant metabolism. Moreover, spurred by the continuing decrease in costs of plant genome sequencing, they will allow genome mining technologies to be applied to plant natural product discovery. The plantiSMASH web server, precalculated results...

  7. Functional annotation of rare gene aberration drivers of pancreatic cancer | Office of Cancer Genomics

    Science.gov (United States)

    As we enter the era of precision medicine, characterization of cancer genomes will directly influence therapeutic decisions in the clinic. Here we describe a platform enabling functionalization of rare gene mutations through their high-throughput construction, molecular barcoding and delivery to cancer models for in vivo tumour driver screens. We apply these technologies to identify oncogenic drivers of pancreatic ductal adenocarcinoma (PDAC).

  8. Gene expression and functional annotation of human choroid plexus epithelium failure in Alzheimer's disease

    NARCIS (Netherlands)

    Bergen, Arthur A; Kaing, Sovann; Ten Brink, Jacoline B; Gorgels, Theo G; Janssen, Sarah F

    2015-01-01

    BACKGROUND: Alzheimer's disease (AD) is the most common form of dementia. AD has a multifactorial disease etiology and is currently untreatable. Multiple genes and molecular mechanisms have been implicated in AD, including ß-amyloid deposition in the brain, neurofibrillary tangle accumulation of

  9. Gene Expression and Functional Annotation of the Human Ciliary Body Epithelia

    NARCIS (Netherlands)

    S.F. Janssen (Sarah); T.G.M.F. Gorgels (Theo); K. Bossers (Koen); J.B. ten Brink (Jacoline); A.H.W. Essing (Anke); M.H. Nagtegaal (Marleen); P.J. van der Spek (Peter); N.M. Jansonius (Nomdo); A.A.B. Bergen (Arthur)

    2012-01-01

    textabstractPurpose: The ciliary body (CB) of the human eye consists of the non-pigmented (NPE) and pigmented (PE) neuro-epithelia. We investigated the gene expression of NPE and PE, to shed light on the molecular mechanisms underlying the most important functions of the CB. We also developed molecu

  10. Gene Expression and Functional Annotation of the Human Ciliary Body Epithelia

    NARCIS (Netherlands)

    Janssen, Sarah F.; Gorgels, Theo G. M. F.; Bossers, Koen; ten Brink, Jacoline B.; Essing, Anke H. W.; Nagtegaal, Martijn; van der Spek, Peter J.; Jansonius, Nomdo M.; Bergen, Arthur A. B.

    2012-01-01

    Purpose: The ciliary body (CB) of the human eye consists of the non-pigmented (NPE) and pigmented (PE) neuro-epithelia. We investigated the gene expression of NPE and PE, to shed light on the molecular mechanisms underlying the most important functions of the CB. We also developed molecular signatur

  11. Using Apollo to browse and edit genome annotations.

    Science.gov (United States)

    Misra, Sima; Harris, Nomi

    2006-01-01

    An annotation is any feature that can be tied to genomic sequence, such as an exon, transcript, promoter, or transposable element. As biological knowledge increases, annotations of different types need to be added and modified, and links to other sources of information need to be incorporated, to allow biologists to easily access all of the available sequence analysis data and design appropriate experiments. The Apollo genome browser and editor offers biologists these capabilities. Apollo can display many different types of computational evidence, such as alignments and similarities based on BLAST searches (UNITS 3.3 & 3.4), and enables biologists to utilize computational evidence to create and edit gene models and other genomic features, e.g., using experimental evidence to refine exon-intron structures predicted by gene prediction algorithms. This protocol describes simple ways to browse genome annotation data, as well as techniques for editing annotations and loading data from different sources.

  12. Characterization of transcriptome dynamics during watermelon fruit development: sequencing, assembly, annotation and gene expression profiles.

    Science.gov (United States)

    Guo, Shaogui; Liu, Jingan; Zheng, Yi; Huang, Mingyun; Zhang, Haiying; Gong, Guoyi; He, Hongju; Ren, Yi; Zhong, Silin; Fei, Zhangjun; Xu, Yong

    2011-09-21

    Cultivated watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus] is an important agriculture crop world-wide. The fruit of watermelon undergoes distinct stages of development with dramatic changes in its size, color, sweetness, texture and aroma. In order to better understand the genetic and molecular basis of these changes and significantly expand the watermelon transcript catalog, we have selected four critical stages of watermelon fruit development and used Roche/454 next-generation sequencing technology to generate a large expressed sequence tag (EST) dataset and a comprehensive transcriptome profile for watermelon fruit flesh tissues. We performed half Roche/454 GS-FLX run for each of the four watermelon fruit developmental stages (immature white, white-pink flesh, red flesh and over-ripe) and obtained 577,023 high quality ESTs with an average length of 302.8 bp. De novo assembly of these ESTs together with 11,786 watermelon ESTs collected from GenBank produced 75,068 unigenes with a total length of approximately 31.8 Mb. Overall 54.9% of the unigenes showed significant similarities to known sequences in GenBank non-redundant (nr) protein database and around two-thirds of them matched proteins of cucumber, the most closely-related species with a sequenced genome. The unigenes were further assigned with gene ontology (GO) terms and mapped to biochemical pathways. More than 5,000 SSRs were identified from the EST collection. Furthermore we carried out digital gene expression analysis of these ESTs and identified 3,023 genes that were differentially expressed during watermelon fruit development and ripening, which provided novel insights into watermelon fruit biology and a comprehensive resource of candidate genes for future functional analysis. We then generated profiles of several interesting metabolites that are important to fruit quality including pigmentation and sweetness. Integrative analysis of metabolite and digital gene expression

  13. Rapid high resolution genotyping of Francisella tularensis by whole genome sequence comparison of annotated genes ("MLST+".

    Directory of Open Access Journals (Sweden)

    Markus H Antwerpen

    Full Text Available The zoonotic disease tularemia is caused by the bacterium Francisella tularensis. This pathogen is considered as a category A select agent with potential to be misused in bioterrorism. Molecular typing based on DNA-sequence like canSNP-typing or MLVA has become the accepted standard for this organism. Due to the organism's highly clonal nature, the current typing methods have reached their limit of discrimination for classifying closely related subpopulations within the subspecies F. tularensis ssp. holarctica. We introduce a new gene-by-gene approach, MLST+, based on whole genome data of 15 sequenced F. tularensis ssp. holarctica strains and apply this approach to investigate an epidemic of lethal tularemia among non-human primates in two animal facilities in Germany. Due to the high resolution of MLST+ we are able to demonstrate that three independent clones of this highly infectious pathogen were responsible for these spatially and temporally restricted outbreaks.

  14. Developmental Stage Annotation of Drosophila Gene Expression Pattern Images via an Entire Solution Path for LDA.

    Science.gov (United States)

    Ye, Jieping; Chen, Jianhui; Janardan, Ravi; Kumar, Sudhir

    2008-03-01

    Gene expression in a developing embryo occurs in particular cells (spatial patterns) in a time-specific manner (temporal patterns), which leads to the differentiation of cell fates. Images of a Drosophila melanogaster embryo at a given developmental stage, showing a particular gene expression pattern revealed by a gene-specific probe, can be compared for spatial overlaps. The comparison is fundamentally important to formulating and testing gene interaction hypotheses. Expression pattern comparison is most biologically meaningful when images from a similar time point (developmental stage) are compared. In this paper, we present LdaPath, a novel formulation of Linear Discriminant Analysis (LDA) for automatic developmental stage range classification. It employs multivariate linear regression with the L(1)-norm penalty controlled by a regularization parameter for feature extraction and visualization. LdaPath computes an entire solution path for all values of regularization parameter with essentially the same computational cost as fitting one LDA model. Thus, it facilitates efficient model selection. It is based on the equivalence relationship between LDA and the least squares method for multi-class classifications. This equivalence relationship is established under a mild condition, which we show empirically to hold for many high-dimensional datasets, such as expression pattern images. Our experiments on a collection of 2705 expression pattern images show the effectiveness of the proposed algorithm. Results also show that the LDA model resulting from LdaPath is sparse, and irrelevant features may be removed. Thus, LdaPath provides a general framework for simultaneous feature selection and feature extraction.

  15. Automatic annotation of organellar genomes with DOGMA

    Energy Technology Data Exchange (ETDEWEB)

    Wyman, Stacia; Jansen, Robert K.; Boore, Jeffrey L.

    2004-06-01

    Dual Organellar GenoMe Annotator (DOGMA) automates the annotation of extra-nuclear organellar (chloroplast and animal mitochondrial) genomes. It is a web-based package that allows the use of comparative BLAST searches to identify and annotate genes in a genome. DOGMA presents a list of putative genes to the user in a graphical format for viewing and editing. Annotations are stored on our password-protected server. Complete annotations can be extracted for direct submission to GenBank. Furthermore, intergenic regions of specified length can be extracted, as well the nucleotide sequences and amino acid sequences of the genes.

  16. Gene-based and semantic structure of the Gene Ontology as a complex network

    Science.gov (United States)

    Coronnello, Claudia; Tumminello, Michele; Miccichè, Salvatore

    2016-09-01

    The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The Gene Ontology (GO) is constantly evolving over time. The information accumulated time-by-time and included in the GO is encoded in the definition of terms and in the setting up of semantic relations amongst terms. Here we investigate the Gene Ontology from a complex network perspective. We consider the semantic network of terms naturally associated with the semantic relationships provided by the Gene Ontology consortium. Moreover, the GO is a natural example of bipartite network of terms and genes. Here we are interested in studying the properties of the projected network of terms, i.e. a gene-based weighted network of GO terms, in which a link between any two terms is set if at least one gene is annotated in both terms. One aim of the present paper is to compare the structural properties of the semantic and the gene-based network. The relative importance of terms is very similar in the two networks, but the community structure changes. We show that in some cases GO terms that appear to be distinct from a semantic point of view are instead connected, and appear in the same community when considering their gene content. The identification of such gene-based communities of terms might therefore be the basis of a simple protocol aiming at improving the semantic structure of GO. Information about terms that share large gene content might also be important from a biomedical point of view, as it might reveal how genes over-expressed in a certain term also affect other biological processes, molecular functions and cellular components not directly linked according to GO semantics.

  17. ANOTACIÓN SEMÁNTICA DE IMÁGENES MÉDICAS Semantic Annotation of Medical Images

    Directory of Open Access Journals (Sweden)

    OSCAR CEBALLOS

    Full Text Available El uso de ontologías para facilitar la anotación semántica de imágenes médicas ha sido un enfoque ampliamente utilizado. Una limitación particular de este enfoque, es el reducido número de ontologías con un alto nivel de completitud, debido en parte, a la dificultad que representa su evolución. En este artículo se propone un método que facilita la evolución de ontologías a partir de las contribuciones hechas por expertos de dominio mediante el etiquetado social de imágenes médicas. El método guía el proceso colaborativo durante el descubrimiento del cambio. Adicionalmente, se presenta una herramienta construida sobre Web Protégé para dar soporte al método propuesto.The use of ontologies to facilitate semantic annotation of medical images has been a widely used approach. A particular limitation of this approach is the lack of ontologies with a high level of completeness, mainly because the problem that ontology evolution represent. This article proposes an approach that facilitates the evolution of ontologies from the contributions made by domain experts through social tagging of medical images. The method guides the collaborative process during the discovery of change. Additionally, we present a tool build on Web Protégé to support the proposed method.

  18. Transcriptional dynamics of the developing sweet cherry (Prunus avium L.) fruit: sequencing, annotation and expression profiling of exocarp-associated genes.

    Science.gov (United States)

    Alkio, Merianne; Jonas, Uwe; Declercq, Myriam; Van Nocker, Steven; Knoche, Moritz

    2014-01-01

    The exocarp, or skin, of fleshy fruit is a specialized tissue that protects the fruit, attracts seed dispersing fruit eaters, and has large economical relevance for fruit quality. Development of the exocarp involves regulated activities of many genes. This research analyzed global gene expression in the exocarp of developing sweet cherry (Prunus avium L., 'Regina'), a fruit crop species with little public genomic resources. A catalog of transcript models (contigs) representing expressed genes was constructed from de novo assembled short complementary DNA (cDNA) sequences generated from developing fruit between flowering and maturity at 14 time points. Expression levels in each sample were estimated for 34 695 contigs from numbers of reads mapping to each contig. Contigs were annotated functionally based on BLAST, gene ontology and InterProScan analyses. Coregulated genes were detected using partitional clustering of expression patterns. The results are discussed with emphasis on genes putatively involved in cuticle deposition, cell wall metabolism and sugar transport. The high temporal resolution of the expression patterns presented here reveals finely tuned developmental specialization of individual members of gene families. Moreover, the de novo assembled sweet cherry fruit transcriptome with 7760 full-length protein coding sequences and over 20 000 other, annotated cDNA sequences together with their developmental expression patterns is expected to accelerate molecular research on this important tree fruit crop.

  19. Scaling Out and Evaluation of OBSecAn, an Automated Section Annotator for Semi-Structured Clinical Documents, on a Large VA Clinical Corpus.

    Science.gov (United States)

    Tran, Le-Thuy T; Divita, Guy; Redd, Andrew; Carter, Marjorie E; Samore, Matthew; Gundlapalli, Adi V

    2015-01-01

    "Identifying and labeling" (annotating) sections improves the effectiveness of extracting information stored in the free text of clinical documents. OBSecAn, an automated ontology-based section annotator, was developed to identify and label sections of semi-structured clinical documents from the Department of Veterans Affairs (VA). In the first step, the algorithm reads and parses the document to obtain and store information regarding sections into a structure that supports the hierarchy of sections. The second stage detects and makes correction to errors in the parsed structure. The third stage produces the section annotation output using the final parsed tree. In this study, we present the OBSecAn method and its scale to a million document corpus and evaluate its performance in identifying family history sections. We identify high yield sections for this use case from note titles such as primary care and demonstrate a median rate of 99% in correctly identifying a family history section.

  20. Chromatin structure regulates gene conversion.

    Directory of Open Access Journals (Sweden)

    W Jason Cummings

    2007-10-01

    Full Text Available Homology-directed repair is a powerful mechanism for maintaining and altering genomic structure. We asked how chromatin structure contributes to the use of homologous sequences as donors for repair using the chicken B cell line DT40 as a model. In DT40, immunoglobulin genes undergo regulated sequence diversification by gene conversion templated by pseudogene donors. We found that the immunoglobulin Vlambda pseudogene array is characterized by histone modifications associated with active chromatin. We directly demonstrated the importance of chromatin structure for gene conversion, using a regulatable experimental system in which the heterochromatin protein HP1 (Drosophila melanogaster Su[var]205, expressed as a fusion to Escherichia coli lactose repressor, is tethered to polymerized lactose operators integrated within the pseudo-Vlambda donor array. Tethered HP1 diminished histone acetylation within the pseudo-Vlambda array, and altered the outcome of Vlambda diversification, so that nontemplated mutations rather than templated mutations predominated. Thus, chromatin structure regulates homology-directed repair. These results suggest that histone modifications may contribute to maintaining genomic stability by preventing recombination between repetitive sequences.

  1. PanViz: interactive visualization of the structure of functionally annotated pangenomes

    DEFF Research Database (Denmark)

    Pedersen, Thomas Lin; Nookaew, Intawat; Wayne Ussery, David

    2017-01-01

    with gene ontology based navigation of gene groups. Furthermore it allows for rich and complex visual querying of gene groups in the pangenome. PanViz visualizations require no external programs and are easily sharable, allowing for rapid pangenome analyses. PanViz is written entirely in Java......PanViz is a novel, interactive, visualization tool for pangenome analysis. PanViz allows visualization of changes in gene group (groups of similar genes across genomes) classification as different subsets of pangenomes are selected, as well as comparisons of individual genomes to pangenomes...

  2. PanViz: interactive visualization of the structure of functionally annotated pangenomes.

    Science.gov (United States)

    Pedersen, Thomas Lin; Nookaew, Intawat; Wayne Ussery, David; Månsson, Maria

    2017-01-05

    PanViz is a novel, interactive, visualization tool for pangenome analysis. PanViz allows visualization of changes in gene group (groups of similar genes across genomes) classification as different subsets of pangenomes are selected, as well as comparisons of individual genomes to pangenomes with gene ontology based navigation of gene groups. Furthermore it allows for rich and complex visual querying of gene groups in the pangenome. PanViz visualizations require no external programs and are easily sharable, allowing for rapid pangenome analyses.

  3. Automatic recognition of disorders, findings, pharmaceuticals and body structures from clinical text: an annotation and machine learning study.

    Science.gov (United States)

    Skeppstedt, Maria; Kvist, Maria; Nilsson, Gunnar H; Dalianis, Hercules

    2014-06-01

    Automatic recognition of clinical entities in the narrative text of health records is useful for constructing applications for documentation of patient care, as well as for secondary usage in the form of medical knowledge extraction. There are a number of named entity recognition studies on English clinical text, but less work has been carried out on clinical text in other languages. This study was performed on Swedish health records, and focused on four entities that are highly relevant for constructing a patient overview and for medical hypothesis generation, namely the entities: Disorder, Finding, Pharmaceutical Drug and Body Structure. The study had two aims: to explore how well named entity recognition methods previously applied to English clinical text perform on similar texts written in Swedish; and to evaluate whether it is meaningful to divide the more general category Medical Problem, which has been used in a number of previous studies, into the two more granular entities, Disorder and Finding. Clinical notes from a Swedish internal medicine emergency unit were annotated for the four selected entity categories, and the inter-annotator agreement between two pairs of annotators was measured, resulting in an average F-score of 0.79 for Disorder, 0.66 for Finding, 0.90 for Pharmaceutical Drug and 0.80 for Body Structure. A subset of the developed corpus was thereafter used for finding suitable features for training a conditional random fields model. Finally, a new model was trained on this subset, using the best features and settings, and its ability to generalise to held-out data was evaluated. This final model obtained an F-score of 0.81 for Disorder, 0.69 for Finding, 0.88 for Pharmaceutical Drug, 0.85 for Body Structure and 0.78 for the combined category Disorder+Finding. The obtained results, which are in line with or slightly lower than those for similar studies on English clinical text, many of them conducted using a larger training data set, show that

  4. The mammalian adult neurogenesis gene ontology (MANGO) provides a structural framework for published information on genes regulating adult hippocampal neurogenesis.

    Science.gov (United States)

    Overall, Rupert W; Paszkowski-Rogacz, Maciej; Kempermann, Gerd

    2012-01-01

    Adult hippocampal neurogenesis is not a single phenotype, but consists of a number of sub-processes, each of which is under complex genetic control. Interpretation of gene expression studies using existing resources often does not lead to results that address the interrelatedness of these processes. Formal structure, such as provided by ontologies, is essential in any field for comprehensive interpretation of existing knowledge but, until now, such a structure has been lacking for adult neurogenesis. We have created a resource with three components 1. A structured ontology describing the key stages in the development of adult hippocampal neural stem cells into functional granule cell neurons. 2. A comprehensive survey of the literature to annotate the results of all published reports on gene function in adult hippocampal neurogenesis (257 manuscripts covering 228 genes) to the appropriate terms in our ontology. 3. An easy-to-use searchable interface to the resulting database made freely available online. The manuscript presents an overview of the database highlighting global trends such as the current bias towards research on early proliferative stages, and an example gene set enrichment analysis. A limitation of the resource is the current scope of the literature which, however, is growing by around 100 publications per year. With the ontology and database in place, new findings can be rapidly annotated and regular updates of the database will be made publicly available. The resource we present allows relevant interpretation of gene expression screens in terms of defined stages of postnatal neuronal development. Annotation of genes by hand from the adult neurogenesis literature ensures the data are directly applicable to the system under study. We believe this approach could also serve as an example to other fields in a 'bottom-up' community effort complementing the already successful 'top-down' approach of the Gene Ontology.

  5. The mammalian adult neurogenesis gene ontology (MANGO provides a structural framework for published information on genes regulating adult hippocampal neurogenesis.

    Directory of Open Access Journals (Sweden)

    Rupert W Overall

    Full Text Available BACKGROUND: Adult hippocampal neurogenesis is not a single phenotype, but consists of a number of sub-processes, each of which is under complex genetic control. Interpretation of gene expression studies using existing resources often does not lead to results that address the interrelatedness of these processes. Formal structure, such as provided by ontologies, is essential in any field for comprehensive interpretation of existing knowledge but, until now, such a structure has been lacking for adult neurogenesis. METHODOLOGY/PRINCIPAL FINDINGS: We have created a resource with three components 1. A structured ontology describing the key stages in the development of adult hippocampal neural stem cells into functional granule cell neurons. 2. A comprehensive survey of the literature to annotate the results of all published reports on gene function in adult hippocampal neurogenesis (257 manuscripts covering 228 genes to the appropriate terms in our ontology. 3. An easy-to-use searchable interface to the resulting database made freely available online. The manuscript presents an overview of the database highlighting global trends such as the current bias towards research on early proliferative stages, and an example gene set enrichment analysis. A limitation of the resource is the current scope of the literature which, however, is growing by around 100 publications per year. With the ontology and database in place, new findings can be rapidly annotated and regular updates of the database will be made publicly available. CONCLUSIONS/SIGNIFICANCE: The resource we present allows relevant interpretation of gene expression screens in terms of defined stages of postnatal neuronal development. Annotation of genes by hand from the adult neurogenesis literature ensures the data are directly applicable to the system under study. We believe this approach could also serve as an example to other fields in a 'bottom-up' community effort complementing the already

  6. LeARN: a platform for detecting, clustering and annotating non-coding RNAs

    Directory of Open Access Journals (Sweden)

    Schiex Thomas

    2008-01-01

    Full Text Available Abstract Background In the last decade, sequencing projects have led to the development of a number of annotation systems dedicated to the structural and functional annotation of protein-coding genes. These annotation systems manage the annotation of the non-protein coding genes (ncRNAs in a very crude way, allowing neither the edition of the secondary structures nor the clustering of ncRNA genes into families which are crucial for appropriate annotation of these molecules. Results LeARN is a flexible software package which handles the complete process of ncRNA annotation by integrating the layers of automatic detection and human curation. Conclusion This software provides the infrastructure to deal properly with ncRNAs in the framework of any annotation project. It fills the gap between existing prediction software, that detect independent ncRNA occurrences, and public ncRNA repositories, that do not offer the flexibility and interactivity required for annotation projects. The software is freely available from the download section of the website http://bioinfo.genopole-toulouse.prd.fr/LeARN

  7. Functional annotations of diabetes nephropathy susceptibility loci through analysis of genome-wide renal gene expression in rat models of diabetes mellitus

    DEFF Research Database (Denmark)

    Hu, Yaomin; Kaisaki, Pamela J; Argoud, Karène

    2009-01-01

    of spontaneous (genetically determined) mild hyperglycaemia and insulin resistance (Goto-Kakizaki-GK) and experimentally induced severe hyperglycaemia (Wistar-Kyoto-WKY rats injected with streptozotocin [STZ]). RESULTS: Different patterns of transcription regulation in the two rat models of diabetes likely...... number of protein coding sequences of unknown function which can be considered as functional and, when they map to DN loci, positional candidates for DN. Further expression analysis of rat orthologs of human DN positional candidate genes provided functional annotations of known and novel genes...

  8. DFLAT: functional annotation for human development.

    Science.gov (United States)

    Wick, Heather C; Drabkin, Harold; Ngu, Huy; Sackman, Michael; Fournier, Craig; Haggett, Jessica; Blake, Judith A; Bianchi, Diana W; Slonim, Donna K

    2014-02-07

    Recent increases in genomic studies of the developing human fetus and neonate have led to a need for widespread characterization of the functional roles of genes at different developmental stages. The Gene Ontology (GO), a valuable and widely-used resource for characterizing gene function, offers perhaps the most suitable functional annotation system for this purpose. However, due in part to the difficulty of studying molecular genetic effects in humans, even the current collection of comprehensive GO annotations for human genes and gene products often lacks adequate developmental context for scientists wishing to study gene function in the human fetus. The Developmental FunctionaL Annotation at Tufts (DFLAT) project aims to improve the quality of analyses of fetal gene expression and regulation by curating human fetal gene functions using both manual and semi-automated GO procedures. Eligible annotations are then contributed to the GO database and included in GO releases of human data. DFLAT has produced a considerable body of functional annotation that we demonstrate provides valuable information about developmental genomics. A collection of gene sets (genes implicated in the same function or biological process), made by combining existing GO annotations with the 13,344 new DFLAT annotations, is available for use in novel analyses. Gene set analyses of expression in several data sets, including amniotic fluid RNA from fetuses with trisomies 21 and 18, umbilical cord blood, and blood from newborns with bronchopulmonary dysplasia, were conducted both with and without the DFLAT annotation. Functional analysis of expression data using the DFLAT annotation increases the number of implicated gene sets, reflecting the DFLAT's improved representation of current knowledge. Blinded literature review supports the validity of newly significant findings obtained with the DFLAT annotations. Newly implicated significant gene sets also suggest specific hypotheses for future

  9. Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome

    Directory of Open Access Journals (Sweden)

    McCarthy Fiona M

    2007-11-01

    Full Text Available Abstract Background The chicken genome was sequenced because of its phylogenetic position as a non-mammalian vertebrate, its use as a biomedical model especially to study embryology and development, its role as a source of human disease organisms and its importance as the major source of animal derived food protein. However, genomic sequence data is, in itself, of limited value; generally it is not equivalent to understanding biological function. The benefit of having a genome sequence is that it provides a basis for functional genomics. However, the sequence data currently available is poorly structurally and functionally annotated and many genes do not have standard nomenclature assigned. Results We analysed eight chicken tissues and improved the chicken genome structural annotation by providing experimental support for the in vivo expression of 7,809 computationally predicted proteins, including 30 chicken proteins that were only electronically predicted or hypothetical translations in human. To improve functional annotation (based on Gene Ontology, we mapped these identified proteins to their human and mouse orthologs and used this orthology to transfer Gene Ontology (GO functional annotations to the chicken proteins. The 8,213 orthology-based GO annotations that we produced represent an 8% increase in currently available chicken GO annotations. Orthologous chicken products were also assigned standardized nomenclature based on current chicken nomenclature guidelines. Conclusion We demonstrate the utility of high-throughput expression proteomics for rapid experimental structural annotation of a newly sequenced eukaryote genome. These experimentally-supported predicted proteins were further annotated by assigning the proteins with standardized nomenclature and functional annotation. This method is widely applicable to a diverse range of species. Moreover, information from one genome can be used to improve the annotation of other genomes and

  10. The Gene Ontology (GO) project in 2006

    National Research Council Canada - National Science Library

    2006-01-01

    The Gene Ontology (GO) project (http://www.geneontology.org) develops and uses a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://song.sourceforge.net...

  11. The Gene Ontology project in 2008

    National Research Council Canada - National Science Library

    The Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org...

  12. Functional annotation of rheumatoid arthritis and osteoarthritis associated genes by integrative genome-wide gene expression profiling analysis.

    Directory of Open Access Journals (Sweden)

    Zhan-Chun Li

    Full Text Available BACKGROUND: Rheumatoid arthritis (RA and osteoarthritis (OA are two major types of joint diseases that share multiple common symptoms. However, their pathological mechanism remains largely unknown. The aim of our study is to identify RA and OA related-genes and gain an insight into the underlying genetic basis of these diseases. METHODS: We collected 11 whole genome-wide expression profiling datasets from RA and OA cohorts and performed a meta-analysis to comprehensively investigate their expression signatures. This method can avoid some pitfalls of single dataset analyses. RESULTS AND CONCLUSION: We found that several biological pathways (i.e., the immunity, inflammation and apoptosis related pathways are commonly involved in the development of both RA and OA. Whereas several other pathways (i.e., vasopressin-related pathway, regulation of autophagy, endocytosis, calcium transport and endoplasmic reticulum stress related pathways present significant difference between RA and OA. This study provides novel insights into the molecular mechanisms underlying this disease, thereby aiding the diagnosis and treatment of the disease.

  13. A Uniform System For The Annotation Of Human microRNA Genes And The Evolution Of The Human microRNAome

    Science.gov (United States)

    Fromm, Bastian; Billipp, Tyler; Peck, Liam E.; Johansen, Morten; Tarver, James E.; King, Benjamin L.; Newcomb, James M.; Sempere, Lorenzo F.; Flatmark, Kjersti; Hovig, Eivind; Peterson, Kevin J.

    2016-01-01

    Although microRNAs (miRNAs) are among the most intensively studied molecules of the past 20 years, determining what is and what is not a miRNA has not been straightforward. Here, we present a uniform system for the annotation and nomenclature of miRNA genes. We show that fewer than a third of the 1,881 human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase entries, are robustly supported as miRNA genes. Furthermore, we show that the human repertoire of miRNAs has been shaped by periods of intense miRNA innovation, and that mature gene products show a very different tempo and mode of sequence evolution than star products. We establish a new open access database -- MirGeneDB (http://mirgenedb.org) -- to catalog this set of robustly supported miRNAs, which complements the efforts of miRBase, but differs from it by annotating the mature versus star products, and by imposing an evolutionary hierarchy upon this curated and consistently named repertoire. PMID:26473382

  14. A Uniform System for the Annotation of Vertebrate microRNA Genes and the Evolution of the Human microRNAome.

    Science.gov (United States)

    Fromm, Bastian; Billipp, Tyler; Peck, Liam E; Johansen, Morten; Tarver, James E; King, Benjamin L; Newcomb, James M; Sempere, Lorenzo F; Flatmark, Kjersti; Hovig, Eivind; Peterson, Kevin J

    2015-01-01

    Although microRNAs (miRNAs) are among the most intensively studied molecules of the past 20 years, determining what is and what is not a miRNA has not been straightforward. Here, we present a uniform system for the annotation and nomenclature of miRNA genes. We show that less than a third of the 1,881 human miRBase entries, and only approximately 16% of the 7,095 metazoan miRBase entries, are robustly supported as miRNA genes. Furthermore, we show that the human repertoire of miRNAs has been shaped by periods of intense miRNA innovation and that mature gene products show a very different tempo and mode of sequence evolution than star products. We establish a new open access database--MirGeneDB ( http://mirgenedb.org )--to catalog this set of miRNAs, which complements the efforts of miRBase but differs from it by annotating the mature versus star products and by imposing an evolutionary hierarchy upon this curated and consistently named repertoire.

  15. Promoter prediction and annotation of microbial genomes based on DNA sequence and structural responses to superhelical stress

    Directory of Open Access Journals (Sweden)

    Benham Craig J

    2006-05-01

    Full Text Available Abstract Background In our previous studies, we found that the sites in prokaryotic genomes which are most susceptible to duplex destabilization under the negative superhelical stresses that occur in vivo are statistically highly significantly associated with intergenic regions that are known or inferred to contain promoters. In this report we investigate how this structural property, either alone or together with other structural and sequence attributes, may be used to search prokaryotic genomes for promoters. Results We show that the propensity for stress-induced DNA duplex destabilization (SIDD is closely associated with specific promoter regions. The extent of destabilization in promoter-containing regions is found to be bimodally distributed. When compared with DNA curvature, deformability, thermostability or sequence motif scores within the -10 region, SIDD is found to be the most informative DNA property regarding promoter locations in the E. coli K12 genome. SIDD properties alone perform better at detecting promoter regions than other programs trained on this genome. Because this approach has a very low false positive rate, it can be used to predict with high confidence the subset of promoters that are strongly destabilized. When SIDD properties are combined with -10 motif scores in a linear classification function, they predict promoter regions with better than 80% accuracy. When these methods were tested with promoter and non-promoter sequences from Bacillus subtilis, they achieved similar or higher accuracies. We also present a strictly SIDD-based predictor for annotating promoter sequences in complete microbial genomes. Conclusion In this report we show that the propensity to undergo stress-induced duplex destabilization (SIDD is a distinctive structural attribute of many prokaryotic promoter sequences. We have developed methods to identify promoter sequences in prokaryotic genomes that use SIDD either as a sole predictor or in

  16. MADS-box gene evolution - structure and transcription patterns

    DEFF Research Database (Denmark)

    Johansen, Bo; Pedersen, Louise Buchholt; Skipper, Martin;

    2002-01-01

    Mads-box genes, ABC model, Evolution, Phylogeny, Transcription patterns, Gene structure, Conserved motifs......Mads-box genes, ABC model, Evolution, Phylogeny, Transcription patterns, Gene structure, Conserved motifs...

  17. Heterologous expression of plasmodial proteins for structural studies and functional annotation

    CSIR Research Space (South Africa)

    Birkholtz, LM

    2008-01-01

    Full Text Available of interest is cloned into a transfer vector, which is co-transfected with viral DNA into Spodoptera frugiperda (usually Sf9 or Sf21) insect cells. In a homologous recombination event, the foreign gene, under the control of a strong viral promoter...

  18. Metagenomic and metatranscriptomic analysis of microbial community structure and gene expression of activated sludge.

    Directory of Open Access Journals (Sweden)

    Ke Yu

    Full Text Available The present study applied both metagenomic and metatranscriptomic approaches to characterize microbial structure and gene expression of an activated sludge community from a municipal wastewater treatment plant in Hong Kong. DNA and cDNA were sequenced by Illumina Hi-seq2000 at a depth of 2.4 Gbp. Taxonomic analysis by MG-RAST showed bacteria were dominant in both DNA and cDNA datasets. The taxonomic profile obtained by BLAST against SILVA SSUref database and annotation by MEGAN showed that activated sludge was dominated by Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Verrucomicrobia phyla in both DNA and cDNA datasets. Global gene expression annotation based on KEGG metabolism pathway displayed slight disagreement between the DNA and cDNA datasets. Further gene expression annotation focusing on nitrogen removal revealed that denitrification-related genes sequences dominated in both DNA and cDNA datasets, while nitrifying genes were also expressed in relative high levels. Specially, ammonia monooxygenase and hydroxylamine oxidase demonstrated the high cDNA/DNA ratios in the present study, indicating strong nitrification activity. Enzyme subunits gene sequences annotation discovered that subunits of ammonia monooxygenase (amoA, amoB, amoC and hydroxylamine oxygenase had higher expression levels compared with subunits of the other enzymes genes. Taxonomic profiles of selected enzymes (ammonia monooxygenase and hydroxylamine oxygenase showed that ammonia-oxidizing bacteria present mainly belonged to Nitrosomonas and Nitrosospira species and no ammonia-oxidizing Archaea sequences were detected in both DNA and cDNA datasets.

  19. Annotation of the protein coding regions of the equine genome

    DEFF Research Database (Denmark)

    Hestand, Matthew S.; Kalbfleisch, Theodore S.; Coleman, Stephen J.;

    2015-01-01

    Current gene annotation of the horse genome is largely derived from in silico predictions and cross-species alignments. Only a small number of genes are annotated based on equine EST and mRNA sequences. To expand the number of equine genes annotated from equine experimental evidence, we sequenced...

  20. Collective dynamics of social annotation

    CERN Document Server

    Cattuto, Ciro; Baldassarri, Andrea; Schehr, G; Loreto, Vittorio

    2009-01-01

    The enormous increase of popularity and use of the WWW has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems, through which users annotate resources (such as web pages or digital photographs) with text keywords dubbed tags. Understanding the rich emerging structures resulting from the uncoordinated actions of users calls for an interdisciplinary effort. In particular concepts borrowed from statistical physics, such as random walks, and the complex networks framework, can effectively contribute to the mathematical modeling of social annotation systems. Here we show that the process of social annotation can be seen as a collective but uncoordinated exploration of an underlying semantic space, pictured as a graph, through a series of random walks. This modeling framework reproduces several aspects, so far unexplained, of social annotation, among which the peculiar growth of the size of the...

  1. Annotation, Phylogeny and Expression Analysis of the Nuclear Factor Y Gene Families in Common Bean (Phaseolus vulgaris

    Directory of Open Access Journals (Sweden)

    Carolina eRípodas

    2015-01-01

    Full Text Available In the past decade, plant nuclear factor Y (NF-Y genes have gained major interest due to their roles in many biological processes in plant development or adaptation to environmental conditions, particularly in the root nodule symbiosis established between legume plants and nitrogen fixing bacteria. NF-Ys are heterotrimeric transcriptional complexes composed of three subunits, NF-YA, NF-YB and NF-YC, which bind with high affinity and specificity to the CCAAT box, a cis element present in many eukaryotic promoters. In plants, NF-Y subunits consist of gene families with about ten members each. In this study, we have identified and characterized the NF-Y gene families of common bean (Phaseolus vulgaris, a grain legume of worldwide economical importance and the main source of dietary protein of developing countries. Expression analysis showed that some members of each family are up-regulated at early or late stages of the nitrogen fixing symbiotic interaction with its partner Rhizobium etli. We also showed that some genes are differentially accumulated in response to inoculation with high or less efficient R. etli strains, constituting excellent candidates to participate in the strain-specific response during symbiosis. Genes of the NF-YA family exhibit a highly structured intron-exon organization. Moreover, this family is characterized by the presence of upstream ORFs when introns in the 5' UTR are retained and miRNA target sites in their 3' UTR, suggesting that these genes might be subjected to a complex post-transcriptional regulation. Multiple protein alignments indicated the presence of highly conserved domains in each of the NF-Y families, presumably involved in subunit interactions and DNA binding. The analysis presented here constitutes a starting point to understand the regulation and biological function of individual members of the NF-Y families in different developmental processes in this grain legume.

  2. De novo cloning and annotation of genes associated with immunity, detoxification and energy metabolism from the fat body of the oriental fruit fly, Bactrocera dorsalis.

    Science.gov (United States)

    Yang, Wen-Jia; Yuan, Guo-Rui; Cong, Lin; Xie, Yi-Fei; Wang, Jin-Jun

    2014-01-01

    The oriental fruit fly, Bactrocera dorsalis, is a destructive pest in tropical and subtropical areas. In this study, we performed transcriptome-wide analysis of the fat body of B. dorsalis and obtained more than 59 million sequencing reads, which were assembled into 27,787 unigenes with an average length of 591 bp. Among them, 17,442 (62.8%) unigenes matched known proteins in the NCBI database. The assembled sequences were further annotated with gene ontology, cluster of orthologous group terms, and Kyoto encyclopedia of genes and genomes. In depth analysis was performed to identify genes putatively involved in immunity, detoxification, and energy metabolism. Many new genes were identified including serpins, peptidoglycan recognition proteins and defensins, which were potentially linked to immune defense. Many detoxification genes were identified, including cytochrome P450s, glutathione S-transferases and ATP-binding cassette (ABC) transporters. Many new transcripts possibly involved in energy metabolism, including fatty acid desaturases, lipases, alpha amylases, and trehalose-6-phosphate synthases, were identified. Moreover, we randomly selected some genes to examine their expression patterns in different tissues by quantitative real-time PCR, which indicated that some genes exhibited fat body-specific expression in B. dorsalis. The identification of a numerous transcripts in the fat body of B. dorsalis laid the foundation for future studies on the functions of these genes.

  3. De novo cloning and annotation of genes associated with immunity, detoxification and energy metabolism from the fat body of the oriental fruit fly, Bactrocera dorsalis.

    Directory of Open Access Journals (Sweden)

    Wen-Jia Yang

    Full Text Available The oriental fruit fly, Bactrocera dorsalis, is a destructive pest in tropical and subtropical areas. In this study, we performed transcriptome-wide analysis of the fat body of B. dorsalis and obtained more than 59 million sequencing reads, which were assembled into 27,787 unigenes with an average length of 591 bp. Among them, 17,442 (62.8% unigenes matched known proteins in the NCBI database. The assembled sequences were further annotated with gene ontology, cluster of orthologous group terms, and Kyoto encyclopedia of genes and genomes. In depth analysis was performed to identify genes putatively involved in immunity, detoxification, and energy metabolism. Many new genes were identified including serpins, peptidoglycan recognition proteins and defensins, which were potentially linked to immune defense. Many detoxification genes were identified, including cytochrome P450s, glutathione S-transferases and ATP-binding cassette (ABC transporters. Many new transcripts possibly involved in energy metabolism, including fatty acid desaturases, lipases, alpha amylases, and trehalose-6-phosphate synthases, were identified. Moreover, we randomly selected some genes to examine their expression patterns in different tissues by quantitative real-time PCR, which indicated that some genes exhibited fat body-specific expression in B. dorsalis. The identification of a numerous transcripts in the fat body of B. dorsalis laid the foundation for future studies on the functions of these genes.

  4. De novo assembly and annotation of the transcriptome of the agricultural weed Ipomoea purpurea uncovers gene expression changes associated with herbicide resistance.

    Science.gov (United States)

    Leslie, Trent; Baucom, Regina S

    2014-08-25

    Human-mediated selection can lead to rapid evolution in very short time scales, and the evolution of herbicide resistance in agricultural weeds is an excellent example of this phenomenon. The common morning glory, Ipomoea purpurea, is resistant to the herbicide glyphosate, but genetic investigations of this trait have been hampered by the lack of genomic resources for this species. Here, we present the annotated transcriptome of the common morning glory, Ipomoea purpurea, along with an examination of whole genome expression profiling to assess potential gene expression differences between three artificially selected herbicide resistant lines and three susceptible lines. The assembled Ipomoea transcriptome reported in this work contains 65,459 assembled transcripts, ~28,000 of which were functionally annotated by assignment to Gene Ontology categories. Our RNA-seq survey using this reference transcriptome identified 19 differentially expressed genes associated with resistance-one of which, a cytochrome P450, belongs to a large plant family of genes involved in xenobiotic detoxification. The differentially expressed genes also broadly implicated receptor-like kinases, which were down-regulated in the resistant lines, and other growth and defense genes, which were up-regulated in resistant lines. Interestingly, the target of glyphosate-EPSP synthase-was not overexpressed in the resistant Ipomoea lines as in other glyphosate resistant weeds. Overall, this work identifies potential candidate resistance loci for future investigations and dramatically increases genomic resources for this species. The assembled transcriptome presented herein will also provide a valuable resource to the Ipomoea community, as well as to those interested in utilizing the close relationship between the Convolvulaceae and the Solanaceae for phylogenetic and comparative genomics examinations.

  5. NewGOA: predicting new GO annotations of proteins by bi-random walks on a hybrid graph.

    Science.gov (United States)

    Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhao, Yingwen

    2017-06-15

    A remaining key challenge of modern biology is annotating the functional roles of proteins. Various computational models have been proposed for this challenge. Most of them assume the annotations of annotated proteins are complete. But in fact, many of them are incomplete. We proposed a method called NewGOA to predict new Gene Ontology (GO) annotations for incompletely annotated proteins and for completely un-annotated ones. NewGOA employs a hybrid graph, composed of two types of nodes (proteins and GO terms), to encode interactions between proteins, hierarchical relationships between terms and available annotations of proteins. To account for structural difference between the terms subgraph and the proteins subgraph, NewGOA applies a bi-random walks algorithm, which executes asynchronous random walks on the hybrid graph, to predict new GO annotations of proteins. Experimental study on archived GO annotations of two model species (H. Sapiens and S. cerevisiae) shows that NewGOA can more accurately and efficiently predict new annotations of proteins than other related methods. Experimental results also indicate the bi-random walks can explore and further exploit the structural difference between terms subgraph and proteins subgraph. The supplementary files and codes of NewGOA are available at: http://mlda.swu.edu.cn/codes.php?name=NewGO.

  6. Whole genome shotgun sequencing of Brassica oleracea and its application to gene discovery and annotation in Arabidopsis

    OpenAIRE

    Ayele, Mulu; Haas, Brian J.; Kumar, Nikhil; Wu, Hank; Xiao, Yongli; Van Aken, Susan; Utterback, Teresa R.; WORTMAN, Jennifer R.; White, Owen R.; Town, Christopher D

    2005-01-01

    Through comparative studies of the model organism Arabidopsis thaliana and its close relative Brassica oleracea, we have identified conserved regions that represent potentially functional sequences overlooked by previous Arabidopsis genome annotation methods. A total of 454,274 whole genome shotgun sequences covering 283 Mb (0.44×) of the estimated 650 Mb Brassica genome were searched against the Arabidopsis genome, and conserved Arabidopsis genome sequences (CAGSs) were identified. Of these ...

  7. Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo

    Directory of Open Access Journals (Sweden)

    Waterston Robert H

    2010-02-01

    Full Text Available Abstract Background Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tracking the expression of individual C. elegans genes was developed that collects image samples of a developing embryo by 3-D time lapse microscopy. In this protocol, a program called StarryNite performs the automatic recognition of fluorescently labeled cells and traces their lineage. However, due to the amount of noise present in the data and due to the challenges introduced by increasing number of cells in later stages of development, this program is not error free. In the current version, the error correction (i.e., editing is performed manually using a graphical interface tool named AceTree, which is specifically developed for this task. For a single experiment, this manual annotation task takes several hours. Results In this paper, we reduce the time required to correct errors made by StarryNite. We target one of the most frequent error types (movements annotated as divisions and train a support vector machine (SVM classifier to decide whether a division call made by StarryNite is correct or not. We show, via cross-validation experiments on several benchmark data sets, that the SVM successfully identifies this type of error significantly. A new version of StarryNite that includes the trained SVM classifier is available at http://starrynite.sourceforge.net. Conclusions We demonstrate the utility of a machine learning approach to error annotation for StarryNite. In the process, we also provide some general methodologies for developing and validating a classifier with respect to a given pattern recognition task.

  8. Comparative genomic mapping of the bovine Fragile Histidine Triad (FHIT tumour suppressor gene: characterization of a 2 Mb BAC contig covering the locus, complete annotation of the gene, analysis of cDNA and of physiological expression profiles

    Directory of Open Access Journals (Sweden)

    Boussaha Mekki

    2006-05-01

    Full Text Available Abstract Background The Fragile Histidine Triad gene (FHIT is an oncosuppressor implicated in many human cancers, including vesical tumors. FHIT is frequently hit by deletions caused by fragility at FRA3B, the most active of human common fragile sites, where FHIT lays. Vesical tumors affect also cattle, including animals grazing in the wild on bracken fern; compounds released by the fern are known to induce chromosome fragility and may trigger cancer with the interplay of latent Papilloma virus. Results The bovine FHIT was characterized by assembling a contig of 78 BACs. Sequence tags were designed on human exons and introns and used directly to select bovine BACs, or compared with sequence data in the bovine genome database or in the trace archive of the bovine genome sequencing project, and adapted before use. FHIT is split in ten exons like in man, with exons 5 to 9 coding for a 149 amino acids protein. VISTA global alignments between bovine genomic contigs retrieved from the bovine genome database and the human FHIT region were performed. Conservation was extremely high over a 2 Mb region spanning the whole FHIT locus, including the size of introns. Thus, the bovine FHIT covers about 1.6 Mb compared to 1.5 Mb in man. Expression was analyzed by RT-PCR and Northern blot, and was found to be ubiquitous. Four cDNA isoforms were isolated and sequenced, that originate from an alternative usage of three variants of exon 4, revealing a size very close to the major human FHIT cDNAs. Conclusion A comparative genomic approach allowed to assemble a contig of 78 BACs and to completely annotate a 1.6 Mb region spanning the bovine FHIT gene. The findings confirmed the very high level of conservation between human and bovine genomes and the importance of comparative mapping to speed the annotation process of the recently sequenced bovine genome. The detailed knowledge of the genomic FHIT region will allow to study the role of FHIT in bovine cancerogenesis

  9. Re-annotation and re-analysis of the Campylobacter jejuni NCTC11168 genome sequence

    Directory of Open Access Journals (Sweden)

    Dorrell Nick

    2007-06-01

    Full Text Available Abstract Background Campylobacter jejuni is the leading bacterial cause of human gastroenteritis in the developed world. To improve our understanding of this important human pathogen, the C. jejuni NCTC11168 genome was sequenced and published in 2000. The original annotation was a milestone in Campylobacter research, but is outdated. We now describe the complete re-annotation and re-analysis of the C. jejuni NCTC11168 genome using current database information, novel tools and annotation techniques not used during the original annotation. Results Re-annotation was carried out using sequence database searches such as FASTA, along with programs such as TMHMM for additional support. The re-annotation also utilises sequence data from additional Campylobacter strains and species not available during the original annotation. Re-annotation was accompanied by a full literature search that was incorporated into the updated EMBL file [EMBL: AL111168]. The C. jejuni NCTC11168 re-annotation reduced the total number of coding sequences from 1654 to 1643, of which 90.0% have additional information regarding the identification of new motifs and/or relevant literature. Re-annotation has led to 18.2% of coding sequence product functions being revised. Conclusions Major updates were made to genes involved in the biosynthesis of important surface structures such as lipooligosaccharide, capsule and both O- and N-linked glycosylation. This re-annotation will be a key resource for Campylobacter research and will also provide a prototype for the re-annotation and re-interpretation of other bacterial genomes.

  10. The identification and functional annotation of RNA structures conserved in vertebrates

    DEFF Research Database (Denmark)

    Seemann, Ernst Stefan; Mirza, Aashiq Hussain; Hansen, Claus

    2017-01-01

    -based, rather than sequence-based, alignments. After careful correction for sequence identity and GC content, we predict ~516k human genomic regions containing CRSs. We find that a substantial fraction of human-mouse CRS regions (i) co-localize consistently with binding sites of the same RNA binding proteins...... (RBPs) or (ii) are transcribed in corresponding tissues. Additionally, a CaptureSeq experiment revealed expression of many of our CRS regions in human fetal brain, including 662 novel ones. For selected human and mouse candidate pairs, qRT-PCR and in vitro RNA structure probing supported both shared...

  11. Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting.

    Science.gov (United States)

    Torres, José Salavert; Damian Segrelles Quilis, J; Espert, Ignacio Blanquer; García, Vicente Hernandez

    2012-12-01

    An important effort has been invested on improving the image diagnosis process in different medical areas using information technologies. The field of medical imaging involves two main data types: medical imaging and reports. Developments based on the DICOM standard have demonstrated to be a convenient and widespread solution among the medical community. The main objective of this work is to design a Web application prototype that will be able to improve diagnosis and follow-on of breast cancer patients. It is based on TRENCADIS middleware, which provides a knowledge-oriented storage model composed by federated repositories of DICOM image studies and DICOM-SR medical reports. The full structure and contents of the diagnosis reports are used as metadata for indexing images. The TRENCADIS infrastructure takes full advantage of Grid technologies by deploying multi-resource grid services that enable multiple views (reports schemes) of the knowledge database. The paper presents a real deployment of such Web application prototype in the Dr. Peset Hospital providing radiologists with a tool to create, store and search diagnostic reports based on breast cancer explorations (mammography, magnetic resonance, ultrasound, pre-surgery biopsy and post-surgery biopsy), improving support for diagnostics decisions. A technical details for use cases (outlining enhanced multi-resource grid services communication and processing steps) and interactions between actors and the deployed prototype are described. As a result, information is more structured, the logic is clearer, network messages have been reduced and, in general, the system is more resistant to failures.

  12. Taxonomic precision of different hypervariable regions of 16S rRNA gene and annotation methods for functional bacterial groups in biological wastewater treatment.

    Directory of Open Access Journals (Sweden)

    Feng Guo

    Full Text Available High throughput sequencing of 16S rRNA gene leads us into a deeper understanding on bacterial diversity for complex environmental samples, but introduces blurring due to the relatively low taxonomic capability of short read. For wastewater treatment plant, only those functional bacterial genera categorized as nutrient remediators, bulk/foaming species, and potential pathogens are significant to biological wastewater treatment and environmental impacts. Precise taxonomic assignment of these bacteria at least at genus level is important for microbial ecological research and routine wastewater treatment monitoring. Therefore, the focus of this study was to evaluate the taxonomic precisions of different ribosomal RNA (rRNA gene hypervariable regions generated from a mix activated sludge sample. In addition, three commonly used classification methods including RDP Classifier, BLAST-based best-hit annotation, and the lowest common ancestor annotation by MEGAN were evaluated by comparing their consistency. Under an unsupervised way, analysis of consistency among different classification methods suggests there are no hypervariable regions with good taxonomic coverage for all genera. Taxonomic assignment based on certain regions of the 16S rRNA genes, e.g. the V1&V2 regions - provide fairly consistent taxonomic assignment for a relatively wide range of genera. Hence, it is recommended to use these regions for studying functional groups in activated sludge. Moreover, the inconsistency among methods also demonstrated that a specific method might not be suitable for identification of some bacterial genera using certain 16S rRNA gene regions. As a general rule, drawing conclusions based only on one sequencing region and one classification method should be avoided due to the potential false negative results.

  13. Structure and sequence based functional annotation of Zika virus NS2b protein: Computational insights.

    Science.gov (United States)

    Aguilera-Pesantes, Daniel; Méndez, Miguel A

    2017-02-08

    While Zika virus (ZIKV) outbreaks are a growing concern for global health, a deep understanding about the virus is lacking. Here we report a contribution to the basic science on the virus- a detailed computational analysis of the non structural protein NS2b. This protein acts as a cofactor for the NS3 protease (NS3Pro) domain that is important on the viral life cycle, and is an interesting target for drug development. We found that ZIKV NS2b cofactor is highly similar to other virus within the Flavivirus genus, especially to West Nile Virus, suggesting that it is completely necessary for the protease complex activity. Furthermore, the ZIKV NS2b has an important role to the function and stability of the ZIKV NS3 protease domain even when presents a low conservation score. In addition, ZIKV NS2b is mostly rigid, which could imply a non dynamic nature in substrate recognition. Finally, by performing a computational alanine scanning mutagenesis, we found that residues Gly 52 and Asp 83 in the NS2b could be important in substrate recognition.

  14. Structure of the murine Thy-1 gene

    NARCIS (Netherlands)

    V. Giguere; K-I. Isobe; F.G. Grosveld (Frank)

    1985-01-01

    textabstractWe have cloned the murine Thy-1.1 (AKR) and Thy-1.2 (Balb/c) genes. The complete exon/intron structure and the nucleotide sequence of the Thy-1.2 gene was determined. The gene contains four exons and three intervening sequences. The complete transcriptional unit gives rise to a tissue an

  15. Automated pipeline for atlas-based annotation of gene expresssion patterns: application to postnatal day 7 mouse brain

    Energy Technology Data Exchange (ETDEWEB)

    Carson, James P.; Ju, Tao; Bello, Musodiq; Thaller, Christina; Warren, Joe; Kakadiaris, Ioannis; Chiu, Wah; Eichele, Gregor

    2010-02-01

    Abstract As bio-medical images and volumes are being collected at an increasing speed, there is a growing demand for efficient means to organize spatial information for comparative analysis. In many scenarios, such as determining gene expression patterns by in situ hybridization, the images are collected from multiple subjects over a common anatomical region, such as the brain. A fundamental challenge in comparing spatial data from different images is how to account for the shape variations among subjects, which makes direct image-to-image comparison meaningless. In this paper, we describe subdivision meshes as a geometric means to efficiently organize 2D images and 3D volumes collected from different subjects for comparison. The key advantages of a subdivision mesh for this purpose are its light-weight geometric structure and its explicit modeling of anatomical boundaries, which enable efficient and accurate registration. The multi-resolution structure of a subdivision mesh also allows development of fast comparison algorithms among registered images and volumes.

  16. Manual annotation, transcriptional analysis, and protein expression studies reveal novel genes in the agl cluster responsible for N glycosylation in the halophilic archaeon Haloferax volcanii.

    Science.gov (United States)

    Yurist-Doutsch, Sophie; Eichler, Jerry

    2009-05-01

    While Eukarya, Bacteria, and Archaea are all capable of protein N glycosylation, the archaeal version of this posttranslational modification is the least understood. To redress this imbalance, recent studies of the halophilic archaeon Haloferax volcanii have identified a gene cluster encoding the Agl proteins involved in the assembly and attachment of a pentasaccharide to select Asn residues of the surface layer glycoprotein in this species. However, because the automated tools used for rapid annotation of genome sequences, including that of H. volcanii, are not always accurate, a reannotation of the agl cluster was undertaken in order to discover genes not previously recognized. In the present report, reanalysis of the gene cluster that includes aglB, aglE, aglF, aglG, aglI, and aglJ, which are known components of the H. volcanii protein N-glycosylation machinery, was undertaken. Using computer-based tools or visual inspection, together with transcriptional analysis and protein expression approaches, genes encoding AglP, AglQ, and AglR are now described.

  17. Transcriptome sequencing and annotation of the microalgae Dunaliella tertiolecta: Pathway description and gene discovery for production of next-generation biofuels

    Directory of Open Access Journals (Sweden)

    Bibby Kyle

    2011-03-01

    Full Text Available Abstract Background Biodiesel or ethanol derived from lipids or starch produced by microalgae may overcome many of the sustainability challenges previously ascribed to petroleum-based fuels and first generation plant-based biofuels. The paucity of microalgae genome sequences, however, limits gene-based biofuel feedstock optimization studies. Here we describe the sequencing and de novo transcriptome assembly for the non-model microalgae species, Dunaliella tertiolecta, and identify pathways and genes of importance related to biofuel production. Results Next generation DNA pyrosequencing technology applied to D. tertiolecta transcripts produced 1,363,336 high quality reads with an average length of 400 bases. Following quality and size trimming, ~ 45% of the high quality reads were assembled into 33,307 isotigs with a 31-fold coverage and 376,482 singletons. Assembled sequences and singletons were subjected to BLAST similarity searches and annotated with Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG orthology (KO identifiers. These analyses identified the majority of lipid and starch biosynthesis and catabolism pathways in D. tertiolecta. Conclusions The construction of metabolic pathways involved in the biosynthesis and catabolism of fatty acids, triacylglycrols, and starch in D. tertiolecta as well as the assembled transcriptome provide a foundation for the molecular genetics and functional genomics required to direct metabolic engineering efforts that seek to enhance the quantity and character of microalgae-based biofuel feedstock.

  18. Transcriptome sequencing and annotation of the microalgae Dunaliella tertiolecta: Pathway description and gene discovery for production of next-generation biofuels

    Science.gov (United States)

    2011-01-01

    Background Biodiesel or ethanol derived from lipids or starch produced by microalgae may overcome many of the sustainability challenges previously ascribed to petroleum-based fuels and first generation plant-based biofuels. The paucity of microalgae genome sequences, however, limits gene-based biofuel feedstock optimization studies. Here we describe the sequencing and de novo transcriptome assembly for the non-model microalgae species, Dunaliella tertiolecta, and identify pathways and genes of importance related to biofuel production. Results Next generation DNA pyrosequencing technology applied to D. tertiolecta transcripts produced 1,363,336 high quality reads with an average length of 400 bases. Following quality and size trimming, ~ 45% of the high quality reads were assembled into 33,307 isotigs with a 31-fold coverage and 376,482 singletons. Assembled sequences and singletons were subjected to BLAST similarity searches and annotated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) orthology (KO) identifiers. These analyses identified the majority of lipid and starch biosynthesis and catabolism pathways in D. tertiolecta. Conclusions The construction of metabolic pathways involved in the biosynthesis and catabolism of fatty acids, triacylglycrols, and starch in D. tertiolecta as well as the assembled transcriptome provide a foundation for the molecular genetics and functional genomics required to direct metabolic engineering efforts that seek to enhance the quantity and character of microalgae-based biofuel feedstock. PMID:21401935

  19. Facilitating functional annotation of chicken microarray data

    Directory of Open Access Journals (Sweden)

    Gresham Cathy R

    2009-10-01

    Full Text Available Abstract Background Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO. However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information. Results We have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM tool to help researchers to quickly retrieve corresponding functional information for their dataset. Conclusion Results from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and

  20. Gene Structures, Evolution and Transcriptional Profiling of the WRKY Gene Family in Castor Bean (Ricinus communis L..

    Directory of Open Access Journals (Sweden)

    Zhi Zou

    Full Text Available WRKY proteins comprise one of the largest transcription factor families in plants and form key regulators of many plant processes. This study presents the characterization of 58 WRKY genes from the castor bean (Ricinus communis L., Euphorbiaceae genome. Compared with the automatic genome annotation, one more WRKY-encoding locus was identified and 20 out of the 57 predicted gene models were manually corrected. All RcWRKY genes were shown to contain at least one intron in their coding sequences. According to the structural features of the present WRKY domains, the identified RcWRKY genes were assigned to three previously defined groups (I-III. Although castor bean underwent no recent whole-genome duplication event like physic nut (Jatropha curcas L., Euphorbiaceae, comparative genomics analysis indicated that one gene loss, one intron loss and one recent proximal duplication occurred in the RcWRKY gene family. The expression of all 58 RcWRKY genes was supported by ESTs and/or RNA sequencing reads derived from roots, leaves, flowers, seeds and endosperms. Further global expression profiles with RNA sequencing data revealed diverse expression patterns among various tissues. Results obtained from this study not only provide valuable information for future functional analysis and utilization of the castor bean WRKY genes, but also provide a useful reference to investigate the gene family expansion and evolution in Euphorbiaceus plants.

  1. Gene Structures, Evolution and Transcriptional Profiling of the WRKY Gene Family in Castor Bean (Ricinus communis L.).

    Science.gov (United States)

    Zou, Zhi; Yang, Lifu; Wang, Danhua; Huang, Qixing; Mo, Yeyong; Xie, Guishui

    2016-01-01

    WRKY proteins comprise one of the largest transcription factor families in plants and form key regulators of many plant processes. This study presents the characterization of 58 WRKY genes from the castor bean (Ricinus communis L., Euphorbiaceae) genome. Compared with the automatic genome annotation, one more WRKY-encoding locus was identified and 20 out of the 57 predicted gene models were manually corrected. All RcWRKY genes were shown to contain at least one intron in their coding sequences. According to the structural features of the present WRKY domains, the identified RcWRKY genes were assigned to three previously defined groups (I-III). Although castor bean underwent no recent whole-genome duplication event like physic nut (Jatropha curcas L., Euphorbiaceae), comparative genomics analysis indicated that one gene loss, one intron loss and one recent proximal duplication occurred in the RcWRKY gene family. The expression of all 58 RcWRKY genes was supported by ESTs and/or RNA sequencing reads derived from roots, leaves, flowers, seeds and endosperms. Further global expression profiles with RNA sequencing data revealed diverse expression patterns among various tissues. Results obtained from this study not only provide valuable information for future functional analysis and utilization of the castor bean WRKY genes, but also provide a useful reference to investigate the gene family expansion and evolution in Euphorbiaceus plants.

  2. A transcriptomic analysis of striped catfish (Pangasianodon hypophthalmus) in response to salinity adaptation: De novo assembly, gene annotation and marker discovery.

    Science.gov (United States)

    Thanh, Nguyen Minh; Jung, Hyungtaek; Lyons, Russell E; Chand, Vincent; Tuan, Nguyen Viet; Thu, Vo Thi Minh; Mather, Peter

    2014-06-01

    The striped catfish (Pangasianodon hypophthalmus) culture industry in the Mekong Delta in Vietnam has developed rapidly over the past decade. The culture industry now however, faces some significant challenges, especially related to climate change impacts notably from predicted extensive saltwater intrusion into many low topographical coastal provinces across the Mekong Delta. This problem highlights a need for development of culture stocks that can tolerate more saline culture environments as a response to expansion of saline water-intruded land. While a traditional artificial selection program can potentially address this need, understanding the genomic basis of salinity tolerance can assist development of more productive culture lines. The current study applied a transcriptomic approach using Ion PGM technology to generate expressed sequence tag (EST) resources from the intestine and swim bladder from striped catfish reared at a salinity level of 9ppt which showed best growth performance. Total sequence data generated was 467.8Mbp, consisting of 4,116,424 reads with an average length of 112bp. De novo assembly was employed that generated 51,188 contigs, and allowed identification of 16,116 putative genes based on the GenBank non-redundant database. GO annotation, KEGG pathway mapping, and functional annotation of the EST sequences recovered with a wide diversity of biological functions and processes. In addition, more than 11,600 simple sequence repeats were also detected. This is the first comprehensive analysis of a striped catfish transcriptome, and provides a valuable genomic resource for future selective breeding programs and functional or evolutionary studies of genes that influence salinity tolerance in this important culture species.

  3. The standard operating procedure of the DOE-JGI Metagenome Annotation Pipeline (MAP v.4).

    Science.gov (United States)

    Huntemann, Marcel; Ivanova, Natalia N; Mavromatis, Konstantinos; Tripp, H James; Paez-Espino, David; Tennessen, Kristin; Palaniappan, Krishnaveni; Szeto, Ernest; Pillay, Manoj; Chen, I-Min A; Pati, Amrita; Nielsen, Torben; Markowitz, Victor M; Kyrpides, Nikos C

    2016-01-01

    The DOE-JGI Metagenome Annotation Pipeline (MAP v.4) performs structural and functional annotation for metagenomic sequences that are submitted to the Integrated Microbial Genomes with Microbiomes (IMG/M) system for comparative analysis. The pipeline runs on nucleotide sequences provided via the IMG submission site. Users must first define their analysis projects in GOLD and then submit the associated sequence datasets consisting of scaffolds/contigs with optional coverage information and/or unassembled reads in fasta and fastq file formats. The MAP processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNAs, as well as CRISPR elements. Structural annotation is followed by functional annotation including assignment of protein product names and connection to various protein family databases.

  4. Annotation of a hybrid partial genome of the coffee rust (Hemileia vastatrix) contributes to the gene repertoire catalog of the Pucciniales.

    Science.gov (United States)

    Cristancho, Marco A; Botero-Rozo, David Octavio; Giraldo, William; Tabima, Javier; Riaño-Pachón, Diego Mauricio; Escobar, Carolina; Rozo, Yomara; Rivera, Luis F; Durán, Andrés; Restrepo, Silvia; Eilam, Tamar; Anikster, Yehoshua; Gaitán, Alvaro L

    2014-01-01

    Coffee leaf rust caused by the fungus Hemileia vastatrix is the most damaging disease to coffee worldwide. The pathogen has recently appeared in multiple outbreaks in coffee producing countries resulting in significant yield losses and increases in costs related to its control. New races/isolates are constantly emerging as evidenced by the presence of the fungus in plants that were previously resistant. Genomic studies are opening new avenues for the study of the evolution of pathogens, the detailed description of plant-pathogen interactions and the development of molecular techniques for the identification of individual isolates. For this purpose we sequenced 8 different H. vastatrix isolates using NGS technologies and gathered partial genome assemblies due to the large repetitive content in the coffee rust hybrid genome; 74.4% of the assembled contigs harbor repetitive sequences. A hybrid assembly of 333 Mb was built based on the 8 isolates; this assembly was used for subsequent analyses. Analysis of the conserved gene space showed that the hybrid H. vastatrix genome, though highly fragmented, had a satisfactory level of completion with 91.94% of core protein-coding orthologous genes present. RNA-Seq from urediniospores was used to guide the de novo annotation of the H. vastatrix gene complement. In total, 14,445 genes organized in 3921 families were uncovered; a considerable proportion of the predicted proteins (73.8%) were homologous to other Pucciniales species genomes. Several gene families related to the fungal lifestyle were identified, particularly 483 predicted secreted proteins that represent candidate effector genes and will provide interesting hints to decipher virulence in the coffee rust fungus. The genome sequence of Hva will serve as a template to understand the molecular mechanisms used by this fungus to attack the coffee plant, to study the diversity of this species and for the development of molecular markers to distinguish races/isolates.

  5. Annotation of a hybrid partial genome of the Coffee Rust (Hemileia vastatrix contributes to the gene repertoire catalogue of the Pucciniales

    Directory of Open Access Journals (Sweden)

    Marco Aurelio Cristancho

    2014-10-01

    Full Text Available Coffee leaf rust caused by the fungus Hemileia vastatrix is the most damaging disease to coffee worldwide. The pathogen has recently appeared in multiple outbreaks in coffee producing countries resulting in significant yield losses and increases in costs related to its control. New races/isolates are constantly emerging as evidenced by the presence of the fungus in plants that were previously resistant. Genomic studies are opening new avenues for the study of the evolution of pathogens, the detailed description of plant-pathogen interactions and the development of molecular techniques for the identification of individual isolates. For this purpose we sequenced 8 different H. vastatrix isolates using NGS technologies and gathered partial genome assemblies due to the large repetitive content in the coffee rust hybrid genome; 74.4% of the assembled contigs harbor repetitive sequences. A hybrid assembly of 333Mb was built based on the 8 isolates; this assembly was used for subsequent analyses.Analysis of the conserved gene space showed that the hybrid H. vastatrix genome, though highly fragmented, had a satisfactory level of completion with 91.94% of core protein-coding orthologous genes present. RNA-Seq from urediniospores was used to guide the de novo annotation of the H. vastatrix gene complement. In total, 14,445 genes organized in 3,921 families were uncovered; a considerable proportion of the predicted proteins (73.8% were homologous to other Pucciniales species genomes. Several gene families related to the fungal lifestyle were identified, particularly 483 predicted secreted proteins that represent candidate effector genes and will provide interesting hints to decipher virulence in the coffee rust fungus. The genome sequence of Hva will serve as a template to understand the molecular mechanisms used by this fungus to attack the coffee plant, to study the diversity of this species and for the development of molecular markers to distinguish

  6. Computer-Based Annotation of Putative AraC/XylS-Family Transcription Factors of Known Structure but Unknown Function

    Directory of Open Access Journals (Sweden)

    Andreas Schüller

    2012-01-01

    Full Text Available Currently, about 20 crystal structures per day are released and deposited in the Protein Data Bank. A significant fraction of these structures is produced by research groups associated with the structural genomics consortium. The biological function of many of these proteins is generally unknown or not validated by experiment. Therefore, a growing need for functional prediction of protein structures has emerged. Here we present an integrated bioinformatics method that combines sequence-based relationships and three-dimensional (3D structural similarity of transcriptional regulators with computer prediction of their cognate DNA binding sequences. We applied this method to the AraC/XylS family of transcription factors, which is a large family of transcriptional regulators found in many bacteria controlling the expression of genes involved in diverse biological functions. Three putative new members of this family with known 3D structure but unknown function were identified for which a probable functional classification is provided. Our bioinformatics analyses suggest that they could be involved in plant cell wall degradation (Lin2118 protein from Listeria innocua, PDB code 3oou, symbiotic nitrogen fixation (protein from Chromobacterium violaceum, PDB code 3oio, and either metabolism of plant-derived biomass or nitrogen fixation (protein from Rhodopseudomonas palustris, PDB code 3mn2.

  7. Collective dynamics of social annotation.

    Science.gov (United States)

    Cattuto, Ciro; Barrat, Alain; Baldassarri, Andrea; Schehr, Gregory; Loreto, Vittorio

    2009-06-30

    The enormous increase of popularity and use of the worldwide web has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems, through which users annotate resources (such as web pages or digital photographs) with keywords known as "tags." Understanding the rich emergent structures resulting from the uncoordinated actions of users calls for an interdisciplinary effort. In particular concepts borrowed from statistical physics, such as random walks (RWs), and complex networks theory, can effectively contribute to the mathematical modeling of social annotation systems. Here, we show that the process of social annotation can be seen as a collective but uncoordinated exploration of an underlying semantic space, pictured as a graph, through a series of RWs. This modeling framework reproduces several aspects, thus far unexplained, of social annotation, among which are the peculiar growth of the size of the vocabulary used by the community and its complex network structure that represents an externalization of semantic structures grounded in cognition and that are typically hard to access.

  8. An atlas of bovine gene expression reveals novel distinctive tissue characteristics and evidence for improving genome annotation

    Science.gov (United States)

    Background A comprehensive transcriptome survey, or gene atlas, provides information essential for a complete understanding of the genomic biology of an organism. We present an atlas of RNA abundance for 92 adult, juvenile and fetal cattle tissues and three cattle cell lines. Results The Bovine Gene...

  9. Quantifying Variability of Manual Annotation in Cryo-Electron Tomograms.

    Science.gov (United States)

    Hecksel, Corey W; Darrow, Michele C; Dai, Wei; Galaz-Montoya, Jesús G; Chin, Jessica A; Mitchell, Patrick G; Chen, Shurui; Jakana, Jemba; Schmid, Michael F; Chiu, Wah

    2016-06-01

    Although acknowledged to be variable and subjective, manual annotation of cryo-electron tomography data is commonly used to answer structural questions and to create a "ground truth" for evaluation of automated segmentation algorithms. Validation of such annotation is lacking, but is critical for understanding the reproducibility of manual annotations. Here, we used voxel-based similarity scores for a variety of specimens, ranging in complexity and segmented by several annotators, to quantify the variation among their annotations. In addition, we have identified procedures for merging annotations to reduce variability, thereby increasing the reliability of manual annotation. Based on our analyses, we find that it is necessary to combine multiple manual annotations to increase the confidence level for answering structural questions. We also make recommendations to guide algorithm development for automated annotation of features of interest.

  10. Objective-guided image annotation.

    Science.gov (United States)

    Mao, Qi; Tsang, Ivor Wai-Hung; Gao, Shenghua

    2013-04-01

    Automatic image annotation, which is usually formulated as a multi-label classification problem, is one of the major tools used to enhance the semantic understanding of web images. Many multimedia applications (e.g., tag-based image retrieval) can greatly benefit from image annotation. However, the insufficient performance of image annotation methods prevents these applications from being practical. On the other hand, specific measures are usually designed to evaluate how well one annotation method performs for a specific objective or application, but most image annotation methods do not consider optimization of these measures, so that they are inevitably trapped into suboptimal performance of these objective-specific measures. To address this issue, we first summarize a variety of objective-guided performance measures under a unified representation. Our analysis reveals that macro-averaging measures are very sensitive to infrequent keywords, and hamming measure is easily affected by skewed distributions. We then propose a unified multi-label learning framework, which directly optimizes a variety of objective-specific measures of multi-label learning tasks. Specifically, we first present a multilayer hierarchical structure of learning hypotheses for multi-label problems based on which a variety of loss functions with respect to objective-guided measures are defined. And then, we formulate these loss functions as relaxed surrogate functions and optimize them by structural SVMs. According to the analysis of various measures and the high time complexity of optimizing micro-averaging measures, in this paper, we focus on example-based measures that are tailor-made for image annotation tasks but are seldom explored in the literature. Experiments show consistency with the formal analysis on two widely used multi-label datasets, and demonstrate the superior performance of our proposed method over state-of-the-art baseline methods in terms of example-based measures on four

  11. WebScipio: An online tool for the determination of gene structures using protein sequences

    Directory of Open Access Journals (Sweden)

    Waack Stephan

    2008-09-01

    Full Text Available Abstract Background Obtaining the gene structure for a given protein encoding gene is an important step in many analyses. A software suited for this task should be readily accessible, accurate, easy to handle and should provide the user with a coherent representation of the most probable gene structure. It should be rigorous enough to optimise features on the level of single bases and at the same time flexible enough to allow for cross-species searches. Results WebScipio, a web interface to the Scipio software, allows a user to obtain the corresponding coding sequence structure of a here given a query protein sequence that belongs to an already assembled eukaryotic genome. The resulting gene structure is presented in various human readable formats like a schematic representation, and a detailed alignment of the query and the target sequence highlighting any discrepancies. WebScipio can also be used to identify and characterise the gene structures of homologs in related organisms. In addition, it offers a web service for integration with other programs. Conclusion WebScipio is a tool that allows users to get a high-quality gene structure prediction from a protein query. It offers more than 250 eukaryotic genomes that can be searched and produces predictions that are close to what can be achieved by manual annotation, for in-species and cross-species searches alike. WebScipio is freely accessible at http://www.webscipio.org.

  12. Global transcript structure resolution of high gene density genomes through multi-platform data integration.

    Science.gov (United States)

    O'Grady, Tina; Wang, Xia; Höner Zu Bentrup, Kerstin; Baddoo, Melody; Concha, Monica; Flemington, Erik K

    2016-10-14

    Annotation of herpesvirus genomes has traditionally been undertaken through the detection of open reading frames and other genomic motifs, supplemented with sequencing of individual cDNAs. Second generation sequencing and high-density microarray studies have revealed vastly greater herpesvirus transcriptome complexity than is captured by existing annotation. The pervasive nature of overlapping transcription throughout herpesvirus genomes, however, poses substantial problems in resolving transcript structures using these methods alone. We present an approach that combines the unique attributes of Pacific Biosciences Iso-Seq long-read, Illumina short-read and deepCAGE (Cap Analysis of Gene Expression) sequencing to globally resolve polyadenylated isoform structures in replicating Epstein-Barr virus (EBV). Our method, Transcriptome Resolution through Integration of Multi-platform Data (TRIMD), identifies nearly 300 novel EBV transcripts, quadrupling the size of the annotated viral transcriptome. These findings illustrate an array of mechanisms through which EBV achieves functional diversity in its relatively small, compact genome including programmed alternative splicing (e.g. across the IR1 repeats), alternative promoter usage by LMP2 and other latency-associated transcripts, intergenic splicing at the BZLF2 locus, and antisense transcription and pervasive readthrough transcription throughout the genome.

  13. Sequencing, De Novo Assembly, and Annotation of the Transcriptome of the Endangered Freshwater Pearl Bivalve, Cristaria plicata, Provides Novel Insights into Functional Genes and Marker Discovery.

    Directory of Open Access Journals (Sweden)

    Bharat Bhusan Patnaik

    Full Text Available The freshwater mussel Cristaria plicata (Bivalvia: Eulamellibranchia: Unionidae, is an economically important species in molluscan aquaculture due to its use in pearl farming. The species have been listed as endangered in South Korea due to the loss of natural habitats caused by anthropogenic activities. The decreasing population and a lack of genomic information on the species is concerning for environmentalists and conservationists. In this study, we conducted a de novo transcriptome sequencing and annotation analysis of C. plicata using Illumina HiSeq 2500 next-generation sequencing (NGS technology, the Trinity assembler, and bioinformatics databases to prepare a sustainable resource for the identification of candidate genes involved in immunity, defense, and reproduction.The C. plicata transcriptome analysis included a total of 286,152,584 raw reads and 281,322,837 clean reads. The de novo assembly identified a total of 453,931 contigs and 374,794 non-redundant unigenes with average lengths of 731.2 and 737.1 bp, respectively. Furthermore, 100% coverage of C. plicata mitochondrial genes within two unigenes supported the quality of the assembler. In total, 84,274 unigenes showed homology to entries in at least one database, and 23,246 unigenes were allocated to one or more Gene Ontology (GO terms. The most prominent GO biological process, cellular component, and molecular function categories (level 2 were cellular process, membrane, and binding, respectively. A total of 4,776 unigenes were mapped to 123 biological pathways in the KEGG database. Based on the GO terms and KEGG annotation, the unigenes were suggested to be involved in immunity, stress responses, sex-determination, and reproduction. A total of 17,251 cDNA simple sequence repeats (cSSRs were identified from 61,141 unigenes (size of >1 kb with the most abundant being dinucleotide repeats.This dataset represents the first transcriptome analysis of the endangered mollusc, C. plicata

  14. BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments.

    Science.gov (United States)

    Al-Shahrour, Fátima; Minguez, Pablo; Vaquerizas, Juan M; Conde, Lucía; Dopazo, Joaquín

    2005-07-01

    We present Babelomics, a complete suite of web tools for the functional analysis of groups of genes in high-throughput experiments, which includes the use of information on Gene Ontology terms, interpro motifs, KEGG pathways, Swiss-Prot keywords, analysis of predicted transcription factor binding sites, chromosomal positions and presence in tissues with determined histological characteristics, through five integrated modules: FatiGO (fast assignment and transference of information), FatiWise, transcription factor association test, GenomeGO and tissues mining tool, respectively. Additionally, another module, FatiScan, provides a new procedure that integrates biological information in combination with experimental results in order to find groups of genes with modest but coordinate significant differential behaviour. FatiScan is highly sensitive and is capable of finding significant asymmetries in the distribution of genes of common function across a list of ordered genes even if these asymmetries were not extreme. The strong multiple-testing nature of the contrasts made by the tools is taken into account. All the tools are integrated in the gene expression analysis package GEPAS. Babelomics is the natural evolution of our tool FatiGO (which analysed almost 22,000 experiments during the last year) to include more sources on information and new modes of using it. Babelomics can be found at http://www.babelomics.org.

  15. Annotation Method (AM): SE22_AM1 [Metabolonote[Archive

    Lifescience Database Archive (English)

    Full Text Available ether with predicted molecular formulae and putative structures, were provided as metabolite annotations. Comparison with public data...bases was performed. A grading system was introduced to describe the evidence supporting the annotations. ...

  16. Functional genomics and structural biology in the definition of gene function.

    Science.gov (United States)

    Hrmova, Maria; Fincher, Geoffrey B

    2009-01-01

    By mid-2007, the three-dimensional (3D) structures of some 45,000 proteins have been solved, over a period where the linear structures of millions of genes have been defined. Technical challenges associated with X-ray crystallography are being overcome and high-throughput methods both for crystallization of proteins and for solving their 3D structures are under development. The question arises as to how structural biology can be integrated with and adds value to functional genomics programs. Structural biology will assist in the definition of gene function through the identification of the likely function of the protein products of genes. The 3D information allows protein sequences predicted from DNA sequences to be classified into broad groups, according to the overall 'fold', or 3D shape, of the protein. Structural information can be used to predict the preferred substrate of a protein, and thereby greatly enhance the accurate annotation of the corresponding gene. Furthermore, it will enable the effects of amino acid substitutions in enzymes to be better understood with respect to enzyme function and could thereby provide insights into natural variation in genes. If the molecular basis of transcription factor-DNA interactions were defined through precise 3D knowledge of the protein-DNA binding site, it would be possible to predict the effects of base substitutions within the motif on the specificity and/or kinetics of binding. In this chapter, we present specific examples of how structural biology can provide valuable information for functional genomics programs.

  17. De novo assembly, functional annotation and comparative analysis of Withania somnifera leaf and root transcriptomes to identify putative genes involved in the withanolides biosynthesis.

    Science.gov (United States)

    Gupta, Parul; Goel, Ridhi; Pathak, Sumya; Srivastava, Apeksha; Singh, Surya Pratap; Sangwan, Rajender Singh; Asif, Mehar Hasan; Trivedi, Prabodh Kumar

    2013-01-01

    Withania somnifera is one of the most valuable medicinal plants used in Ayurvedic and other indigenous medicine systems due to bioactive molecules known as withanolides. As genomic information regarding this plant is very limited, little information is available about biosynthesis of withanolides. To facilitate the basic understanding about the withanolide biosynthesis pathways, we performed transcriptome sequencing for Withania leaf (101L) and root (101R) which specifically synthesize withaferin A and withanolide A, respectively. Pyrosequencing yielded 8,34,068 and 7,21,755 reads which got assembled into 89,548 and 1,14,814 unique sequences from 101L and 101R, respectively. A total of 47,885 (101L) and 54,123 (101R) could be annotated using TAIR10, NR, tomato and potato databases. Gene Ontology and KEGG analyses provided a detailed view of all the enzymes involved in withanolide backbone synthesis. Our analysis identified members of cytochrome P450, glycosyltransferase and methyltransferase gene families with unique presence or differential expression in leaf and root and might be involved in synthesis of tissue-specific withanolides. We also detected simple sequence repeats (SSRs) in transcriptome data for use in future genetic studies. Comprehensive sequence resource developed for Withania, in this study, will help to elucidate biosynthetic pathway for tissue-specific synthesis of secondary plant products in non-model plant organisms as well as will be helpful in developing strategies for enhanced biosynthesis of withanolides through biotechnological approaches.

  18. De novo assembly, functional annotation and comparative analysis of Withania somnifera leaf and root transcriptomes to identify putative genes involved in the withanolides biosynthesis.

    Directory of Open Access Journals (Sweden)

    Parul Gupta

    Full Text Available Withania somnifera is one of the most valuable medicinal plants used in Ayurvedic and other indigenous medicine systems due to bioactive molecules known as withanolides. As genomic information regarding this plant is very limited, little information is available about biosynthesis of withanolides. To facilitate the basic understanding about the withanolide biosynthesis pathways, we performed transcriptome sequencing for Withania leaf (101L and root (101R which specifically synthesize withaferin A and withanolide A, respectively. Pyrosequencing yielded 8,34,068 and 7,21,755 reads which got assembled into 89,548 and 1,14,814 unique sequences from 101L and 101R, respectively. A total of 47,885 (101L and 54,123 (101R could be annotated using TAIR10, NR, tomato and potato databases. Gene Ontology and KEGG analyses provided a detailed view of all the enzymes involved in withanolide backbone synthesis. Our analysis identified members of cytochrome P450, glycosyltransferase and methyltransferase gene families with unique presence or differential expression in leaf and root and might be involved in synthesis of tissue-specific withanolides. We also detected simple sequence repeats (SSRs in transcriptome data for use in future genetic studies. Comprehensive sequence resource developed for Withania, in this study, will help to elucidate biosynthetic pathway for tissue-specific synthesis of secondary plant products in non-model plant organisms as well as will be helpful in developing strategies for enhanced biosynthesis of withanolides through biotechnological approaches.

  19. Gene finding with a hidden Markov model of genome structure and evolution

    DEFF Research Database (Denmark)

    Pedersen, Jakob Skou; Hein, Jotun

    2003-01-01

    annotation. The modelling of evolution by the existing comparative gene finders leaves room for improvement. Results: A probabilistic model of both genome structure and evolution is designed. This type of model is called an Evolutionary Hidden Markov Model (EHMM), being composed of an HMM and a set of region......Motivation: A growing number of genomes are sequenced. The differences in evolutionary pattern between functional regions can thus be observed genome-wide in a whole set of organisms. The diverse evolutionary pattern of different functional regions can be exploited in the process of genomic...

  20. Towards a Library of Standard Operating Procedures (SOPs) for (meta)genomic annotation

    Energy Technology Data Exchange (ETDEWEB)

    Kyrpides, Nikos; Angiuoli, Samuel V.; Cochrane, Guy; Field, Dawn; Garrity, George; Gussman, Aaron; Kodira, Chinnappa D.; Klimke, William; Kyrpides, Nikos; Madupu, Ramana; Markowitz, Victor; Tatusova, Tatiana; Thomson, Nick; White, Owen

    2008-04-01

    Genome annotations describe the features of genomes and accompany sequences in genome databases. The methodologies used to generate genome annotation are diverse and typically vary amongst groups. Descriptions of the annotation procedure are helpful in interpreting genome annotation data. Standard Operating Procedures (SOPs) for genome annotation describe the processes that generate genome annotations. Some groups are currently documenting procedures but standards are lacking for structure and content of annotation SOPs. In addition, there is no central repository to store and disseminate procedures and protocols for genome annotation. We highlight the importance of SOPs for genome annotation and endorse a central online repository of SOPs.

  1. Towards a Library of Standard Operating Procedures (SOPs) for (meta)genomic annotation

    Energy Technology Data Exchange (ETDEWEB)

    Kyrpides, Nikos; Angiuoli, Samuel V.; Cochrane, Guy; Field, Dawn; Garrity, George; Gussman, Aaron; Kodira, Chinnappa D.; Klimke, William; Kyrpides, Nikos; Madupu, Ramana; Markowitz, Victor; Tatusova, Tatiana; Thomson, Nick; White, Owen

    2008-04-01

    Genome annotations describe the features of genomes and accompany sequences in genome databases. The methodologies used to generate genome annotation are diverse and typically vary amongst groups. Descriptions of the annotation procedure are helpful in interpreting genome annotation data. Standard Operating Procedures (SOPs) for genome annotation describe the processes that generate genome annotations. Some groups are currently documenting procedures but standards are lacking for structure and content of annotation SOPs. In addition, there is no central repository to store and disseminate procedures and protocols for genome annotation. We highlight the importance of SOPs for genome annotation and endorse a central online repository of SOPs.

  2. xGDBvm: A Web GUI-Driven Workflow for Annotating Eukaryotic Genomes in the Cloud.

    Science.gov (United States)

    Duvick, Jon; Standage, Daniel S; Merchant, Nirav; Brendel, Volker P

    2016-04-01

    Genome-wide annotation of gene structure requires the integration of numerous computational steps. Currently, annotation is arguably best accomplished through collaboration of bioinformatics and domain experts, with broad community involvement. However, such a collaborative approach is not scalable at today's pace of sequence generation. To address this problem, we developed the xGDBvm software, which uses an intuitive graphical user interface to access a number of common genome analysis and gene structure tools, preconfigured in a self-contained virtual machine image. Once their virtual machine instance is deployed through iPlant's Atmosphere cloud services, users access the xGDBvm workflow via a unified Web interface to manage inputs, set program parameters, configure links to high-performance computing (HPC) resources, view and manage output, apply analysis and editing tools, or access contextual help. The xGDBvm workflow will mask the genome, compute spliced alignments from transcript and/or protein inputs (locally or on a remote HPC cluster), predict gene structures and gene structure quality, and display output in a public or private genome browser complete with accessory tools. Problematic gene predictions are flagged and can be reannotated using the integrated yrGATE annotation tool. xGDBvm can also be configured to append or replace existing data or load precomputed data. Multiple genomes can be annotated and displayed, and outputs can be archived for sharing or backup. xGDBvm can be adapted to a variety of use cases including de novo genome annotation, reannotation, comparison of different annotations, and training or teaching.

  3. Augmented annotation and orthologue analysis for Oryctolagus cuniculus: Better Bunny

    National Research Council Canada - National Science Library

    Craig, Douglas B; Kannan, Sujatha; Dombkowski, Alan A

    2012-01-01

    .... Using data extracted from several public bioinformatics repositories we created Better Bunny, a database and query tool that extensively augments the available functional annotation for rabbit genes...

  4. Chicken rRNA Gene Cluster Structure.

    Directory of Open Access Journals (Sweden)

    Alexander G Dyomin

    Full Text Available Ribosomal RNA (rRNA genes, whose activity results in nucleolus formation, constitute an extremely important part of genome. Despite the extensive exploration into avian genomes, no complete description of avian rRNA gene primary structure has been offered so far. We publish a complete chicken rRNA gene cluster sequence here, including 5'ETS (1836 bp, 18S rRNA gene (1823 bp, ITS1 (2530 bp, 5.8S rRNA gene (157 bp, ITS2 (733 bp, 28S rRNA gene (4441 bp and 3'ETS (343 bp. The rRNA gene cluster sequence of 11863 bp was assembled from raw reads and deposited to GenBank under KT445934 accession number. The assembly was validated through in situ fluorescent hybridization analysis on chicken metaphase chromosomes using computed and synthesized specific probes, as well as through the reference assembly against de novo assembled rRNA gene cluster sequence using sequenced fragments of BAC-clone containing chicken NOR (nucleolus organizer region. The results have confirmed the chicken rRNA gene cluster validity.

  5. Concept annotation in the CRAFT corpus

    Directory of Open Access Journals (Sweden)

    Bada Michael

    2012-07-01

    Full Text Available Abstract Background Manually annotated corpora are critical for the training and evaluation of automated methods to identify concepts in biomedical text. Results This paper presents the concept annotations of the Colorado Richly Annotated Full-Text (CRAFT Corpus, a collection of 97 full-length, open-access biomedical journal articles that have been annotated both semantically and syntactically to serve as a research resource for the biomedical natural-language-processing (NLP community. CRAFT identifies all mentions of nearly all concepts from nine prominent biomedical ontologies and terminologies: the Cell Type Ontology, the Chemical Entities of Biological Interest ontology, the NCBI Taxonomy, the Protein Ontology, the Sequence Ontology, the entries of the Entrez Gene database, and the three subontologies of the Gene Ontology. The first public release includes the annotations for 67 of the 97 articles, reserving two sets of 15 articles for future text-mining competitions (after which these too will be released. Concept annotations were created based on a single set of guidelines, which has enabled us to achieve consistently high interannotator agreement. Conclusions As the initial 67-article release contains more than 560,000 tokens (and the full set more than 790,000 tokens, our corpus is among the largest gold-standard annotated biomedical corpora. Unlike most others, the journal articles that comprise the corpus are drawn from diverse biomedical disciplines and are marked up in their entirety. Additionally, with a concept-annotation count of nearly 100,000 in the 67-article subset (and more than 140,000 in the full collection, the scale of conceptual markup is also among the largest of comparable corpora. The concept annotations of the CRAFT Corpus have the potential to significantly advance biomedical text mining by providing a high-quality gold standard for NLP systems. The corpus, annotation guidelines, and other associated resources are

  6. D-galactose catabolism in Penicillium chrysogenum: Expression analysis of the structural genes of the Leloir pathway.

    Science.gov (United States)

    Jónás, Ágota; Fekete, Erzsébet; Németh, Zoltán; Flipphi, Michel; Karaffa, Levente

    2016-09-01

    In this study, we analyzed the expression of the structural genes encoding the five enzymes comprising the Leloir pathway of D-galactose catabolism in the industrial cell factory Penicillium chrysogenum on various carbon sources. The genome of P. chrysogenum contains a putative galactokinase gene at the annotated locus Pc13g10140, the product of which shows strong structural similarity to yeast galactokinase that was expressed on lactose and D-galactose only. The expression profile of the galactose-1-phosphate uridylyl transferase gene at annotated locus Pc15g00140 was essentially similar to that of galactokinase. This is in contrast to the results from other fungi such as Aspergillus nidulans, Trichoderma reesei and A. niger, where the ortholog galactokinase and galactose-1-phosphate uridylyl transferase genes were constitutively expressed. As for the UDP-galactose-4-epimerase encoding gene, five candidates were identified. We could not detect Pc16g12790, Pc21g12170 and Pc20g06140 expression on any of the carbon sources tested, while for the other two loci (Pc21g10370 and Pc18g01080) transcripts were clearly observed under all tested conditions. Like the 4-epimerase specified at locus Pc21g10370, the other two structural Leloir pathway genes - UDP-glucose pyrophosphorylase (Pc21g12790) and phosphoglucomutase (Pc18g01390) - were expressed constitutively at high levels as can be expected from their indispensable function in fungal cell wall formation.

  7. Comparisons of Graph-structure Clustering Methods for Gene Expression Data

    Institute of Scientific and Technical Information of China (English)

    Zhuo FANG; Lei LIU; Jiong YANG; Qing-Ming LUO; Yi-Xue LI

    2006-01-01

    Although many numerical clustering algorithms have been applied to gene expression data analysis, the essential step is still biological interpretation by manual inspection. The correlation between genetic co-regulation and affiliation to a common biological process is what biologists expect. Here, we introduce some clustering algorithms that are based on graph structure constituted by biological knowledge. After applying a widely used dataset, we compared the result clusters of two of these algorithms in terms of the homogeneity of clusters and coherence of annotation and matching ratio. The results show that the clusters of knowledge-guided analysis are the kernel parts of the clusters of Gene Ontology (GO)-Cluster software, which contains the genes that are most expression correlative and most consistent with biological functions. Moreover, knowledge-guided analysis seems much more applicable than GO-Cluster in a larger dataset.

  8. TEnest 2.0: computational annotation and visualization of nested transposable elements.

    Science.gov (United States)

    Kronmiller, Brent A; Wise, Roger P

    2013-01-01

    Grass genomes harbor a diverse and complex content of repeated sequences. Most of these repeats occur as abundant transposable elements (TEs), which present unique challenges to sequence, assemble, and annotate genomes. Multiple copies of Long Terminal Repeat (LTR) retrotransposons can hinder sequence assembly and also cause problems with gene annotation. TEs can also contain protein-encoding genes, the ancient remnants of which can mislead gene identification software if not correctly masked. Hence, accurate assembly is crucial for gene annotation. We present TEnest v2.0. TEnest computationally annotates and chronologically displays nested transposable elements. Utilizing organism-specific TE databases as a reference for reconstructing degraded TEs to their ancestral state, annotation of repeats is accomplished by iterative sequence alignment. Subsequently, an output consisting of a graphical display of the chronological nesting structure and coordinate positions of all TE insertions is the result. Both linux command line and Web versions of the TEnest software are available at www.wiselab.org and www.plantgdb.org/tool/, respectively.

  9. Annotation of mammalian primary microRNAs

    Directory of Open Access Journals (Sweden)

    Enright Anton J

    2008-11-01

    Full Text Available Abstract Background MicroRNAs (miRNAs are important regulators of gene expression and have been implicated in development, differentiation and pathogenesis. Hundreds of miRNAs have been discovered in mammalian genomes. Approximately 50% of mammalian miRNAs are expressed from introns of protein-coding genes; the primary transcript (pri-miRNA is therefore assumed to be the host transcript. However, very little is known about the structure of pri-miRNAs expressed from intergenic regions. Here we annotate transcript boundaries of miRNAs in human, mouse and rat genomes using various transcription features. The 5' end of the pri-miRNA is predicted from transcription start sites, CpG islands and 5' CAGE tags mapped in the upstream flanking region surrounding the precursor miRNA (pre-miRNA. The 3' end of the pri-miRNA is predicted based on the mapping of polyA signals, and supported by cDNA/EST and ditags data. The predicted pri-miRNAs are also analyzed for promoter and insulator-associated regulatory regions. Results We define sets of conserved and non-conserved human, mouse and rat pre-miRNAs using bidirectional BLAST and synteny analysis. Transcription features in their flanking regions are used to demarcate the 5' and 3' boundaries of the pri-miRNAs. The lengths and boundaries of primary transcripts are highly conserved between orthologous miRNAs. A significant fraction of pri-miRNAs have lengths between 1 and 10 kb, with very few introns. We annotate a total of 59 pri-miRNA structures, which include 82 pre-miRNAs. 36 pri-miRNAs are conserved in all 3 species. In total, 18 of the confidently annotated transcripts express more than one pre-miRNA. The upstream regions of 54% of the predicted pri-miRNAs are found to be associated with promoter and insulator regulatory sequences. Conclusion Little is known about the primary transcripts of intergenic miRNAs. Using comparative data, we are able to identify the boundaries of a significant proportion of

  10. Structure, expression and functions of MTA genes.

    Science.gov (United States)

    Kumar, Rakesh; Wang, Rui-An

    2016-05-15

    Metastatic associated proteins (MTA) are integrators of upstream regulatory signals with the ability to act as master coregulators for modifying gene transcriptional activity. The MTA family includes three genes and multiple alternatively spliced variants. The MTA proteins neither have their own enzymatic activity nor have been shown to directly interact with DNA. However, MTA proteins interact with a variety of chromatin remodeling factors and complexes with enzymatic activities for modulating the plasticity of nucleosomes, leading to the repression or derepression of target genes or other extra-nuclear and nucleosome remodeling and histone deacetylase (NuRD)-complex independent activities. The functions of MTA family members are driven by the steady state levels and subcellular localization of MTA proteins, the dynamic nature of modifying signals and enzymes, the structural features and post-translational modification of protein domains, interactions with binding proteins, and the nature of the engaged and resulting features of nucleosomes in the proximity of target genes. In general, MTA1 and MTA2 are the most upregulated genes in human cancer and correlate well with aggressive phenotypes, therapeutic resistance, poor prognosis and ultimately, unfavorable survival of cancer patients. Here we will discuss the structure, expression and functions of the MTA family of genes in the context of cancer cells.

  11. Application of comprehensive NMR-based analysis strategy in annotation, isolation and structure elucidation of low molecular weight metabolites of Ricinus communis seeds.

    Science.gov (United States)

    Vučković, Ivan; Rapinoja, Marja-Leena; Vaismaa, Matti; Vanninen, Paula; Koskela, Harri

    2016-01-01

    Powder-like extract of Ricinus communis seeds contain a toxic protein, ricin, which has a history of military, criminal and terroristic use. As the detection of ricin in this "terrorist powder" is difficult and time-consuming, related low mass metabolites have been suggested to be useful for screening as biomarkers of ricin. To apply a comprehensive NMR-based analysis strategy for annotation, isolation and structure elucidation of low molecular weight plant metabolites of Ricinus communis seeds. The seed extract was prepared with a well-known acetone extraction approach. The common metabolites were annotated from seed extract dissolved in acidic solution using (1)H NMR spectroscopy with spectrum library comparison and standard addition, whereas unconfirmed metabolites were identified using multi-step off-line HPLC-DAD-NMR approach. In addition to the common plant metabolites, two previously unreported compounds, 1,3-digalactoinositol and ricinyl-alanine, were identified with support of MS analyses. The applied comprehensive NMR-based analysis strategy provided identification of the prominent low molecular weight metabolites with high confidence. Copyright © 2015 John Wiley & Sons, Ltd.

  12. Annotation and retrieval in protein interaction databases

    Science.gov (United States)

    Cannataro, Mario; Hiram Guzzi, Pietro; Veltri, Pierangelo

    2014-06-01

    Biological databases have been developed with a special focus on the efficient retrieval of single records or the efficient computation of specialized bioinformatics algorithms against the overall database, such as in sequence alignment. The continuos production of biological knowledge spread on several biological databases and ontologies, such as Gene Ontology, and the availability of efficient techniques to handle such knowledge, such as annotation and semantic similarity measures, enable the development on novel bioinformatics applications that explicitly use and integrate such knowledge. After introducing the annotation process and the main semantic similarity measures, this paper shows how annotations and semantic similarity can be exploited to improve the extraction and analysis of biologically relevant data from protein interaction databases. As case studies, the paper presents two novel software tools, OntoPIN and CytoSeVis, both based on the use of Gene Ontology annotations, for the advanced querying of protein interaction databases and for the enhanced visualization of protein interaction networks.

  13. Systematic analysis of human kinase genes: a large number of genes and alternative splicing events result in functional and structural diversity

    Science.gov (United States)

    Milanesi, Luciano; Petrillo, Mauro; Sepe, Leandra; Boccia, Angelo; D'Agostino, Nunzio; Passamano, Myriam; Di Nardo, Salvatore; Tasco, Gianluca; Casadio, Rita; Paolella, Giovanni

    2005-01-01

    Background Protein kinases are a well defined family of proteins, characterized by the presence of a common kinase catalytic domain and playing a significant role in many important cellular processes, such as proliferation, maintenance of cell shape, apoptosys. In many members of the family, additional non-kinase domains contribute further specialization, resulting in subcellular localization, protein binding and regulation of activity, among others. About 500 genes encode members of the kinase family in the human genome, and although many of them represent well known genes, a larger number of genes code for proteins of more recent identification, or for unknown proteins identified as kinase only after computational studies. Results A systematic in silico study performed on the human genome, led to the identification of 5 genes, on chromosome 1, 11, 13, 15 and 16 respectively, and 1 pseudogene on chromosome X; some of these genes are reported as kinases from NCBI but are absent in other databases, such as KinBase. Comparative analysis of 483 gene regions and subsequent computational analysis, aimed at identifying unannotated exons, indicates that a large number of kinase may code for alternately spliced forms or be incorrectly annotated. An InterProScan automated analysis was perfomed to study domain distribution and combination in the various families. At the same time, other structural features were also added to the annotation process, including the putative presence of transmembrane alpha helices, and the cystein propensity to participate into a disulfide bridge. Conclusion The predicted human kinome was extended by identifiying both additional genes and potential splice variants, resulting in a varied panorama where functionality may be searched at the gene and protein level. Structural analysis of kinase proteins domains as defined in multiple sources together with transmembrane alpha helices and signal peptide prediction provides hints to function assignment

  14. Linking human diseases to animal models using ontology-based phenotype annotation.

    Directory of Open Access Journals (Sweden)

    Nicole L Washington

    2009-11-01

    Full Text Available Scientists and clinicians who study genetic alterations and disease have traditionally described phenotypes in natural language. The considerable variation in these free-text descriptions has posed a hindrance to the important task of identifying candidate genes and models for human diseases and indicates the need for a computationally tractable method to mine data resources for mutant phenotypes. In this study, we tested the hypothesis that ontological annotation of disease phenotypes will facilitate the discovery of new genotype-phenotype relationships within and across species. To describe phenotypes using ontologies, we used an Entity-Quality (EQ methodology, wherein the affected entity (E and how it is affected (Q are recorded using terms from a variety of ontologies. Using this EQ method, we annotated the phenotypes of 11 gene-linked human diseases described in Online Mendelian Inheritance in Man (OMIM. These human annotations were loaded into our Ontology-Based Database (OBD along with other ontology-based phenotype descriptions of mutants from various model organism databases. Phenotypes recorded with this EQ method can be computationally compared based on the hierarchy of terms in the ontologies and the frequency of annotation. We utilized four similarity metrics to compare phenotypes and developed an ontology of homologous and analogous anatomical structures to compare phenotypes between species. Using these tools, we demonstrate that we can identify, through the similarity of the recorded phenotypes, other alleles of the same gene, other members of a signaling pathway, and orthologous genes and pathway members across species. We conclude that EQ-based annotation of phenotypes, in conjunction with a cross-species ontology, and a variety of similarity metrics can identify biologically meaningful similarities between genes by comparing phenotypes alone. This annotation and search method provides a novel and efficient means to identify

  15. Prosecutor : parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources

    NARCIS (Netherlands)

    Blom, E.J.; Breitling, R.; Hofstede, K.J.; Roerdink, J.B.T.M.; van Hijum, S.A F T; Kuipers, O.P.

    2008-01-01

    Background: Despite a plethora of functional genomic efforts, the function of many genes in sequenced genomes remains unknown. The increasing amount of microarray data for many species allows employing the guilt-by-association principle to predict function on a large scale: genes exhibiting similar

  16. Amplification and characterization of eukaryotic structural genes.

    Science.gov (United States)

    Maniatis, T; Efstratiadis, A; Sim, G K; Kafatos, F

    1978-05-01

    An approach to the study of eukaryotic structural genes which are differentially expressed during development is described. This approach involves the isolation and amplification of mRNA sequences by in vitro conversion of mRNA to double-stranded cDNA followed by molecular cloning in bacterial plasmids. This procedure provides highly specific hybridization probes that can be used to identify genes and their contiguous DNA sequences in genomic DNA, and to detect specific RNA transcripts during development. The nature of the method allows the isolation of individual mRNA sequences from a complex population of molecules at different stages of development.

  17. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

  18. ATLAS (Automatic Tool for Local Assembly Structures) - A Comprehensive Infrastructure for Assembly, Annotation, and Genomic Binning of Metagenomic and Metaranscripomic Data

    Energy Technology Data Exchange (ETDEWEB)

    White, Richard A.; Brown, Joseph M.; Colby, Sean M.; Overall, Christopher C.; Lee, Joon-Yong; Zucker, Jeremy D.; Glaesemann, Kurt R.; Jansson, Georg C.; Jansson, Janet K.

    2017-03-02

    ATLAS (Automatic Tool for Local Assembly Structures) is a comprehensive multiomics data analysis pipeline that is massively parallel and scalable. ATLAS contains a modular analysis pipeline for assembly, annotation, quantification and genome binning of metagenomics and metatranscriptomics data and a framework for reference metaproteomic database construction. ATLAS transforms raw sequence data into functional and taxonomic data at the microbial population level and provides genome-centric resolution through genome binning. ATLAS provides robust taxonomy based on majority voting of protein coding open reading frames rolled-up at the contig level using modified lowest common ancestor (LCA) analysis. ATLAS provides robust taxonomy based on majority voting of protein coding open reading frames rolled-up at the contig level using modified lowest common ancestor (LCA) analysis. ATLAS is user-friendly, easy install through bioconda maintained as open-source on GitHub, and is implemented in Snakemake for modular customizable workflows.

  19. 小鼠舌肌发育相关基因的功能聚类分析%Functional annotation clustering of genes in mouse tongue myogenesis

    Institute of Scientific and Technical Information of China (English)

    丛蔚; 刘波; 蒋玉玲; 肖晶

    2015-01-01

    目的:研究小鼠舌肌发育的分子调控机制。方法:取胚胎第13.25天(E13.25)及 E15.5小鼠舌组织。应用 Affy-metrix Mouse GeneChip,对胎鼠舌发育过程中的差异基因进行筛选。应用 DAVID 网络分析工具对基因进行功能和聚类分析。结果:基因功能和聚类分析表明,在 E13.25高表达的基因主要与细胞周期相关因子(Exo1、Gsk3B、Kif20b、Skp2)和细胞粘附因子(Neo1、lama1)等相关。在 E15.5高表达的基因主要与细胞骨架(titin、Hspb7)相关。结论:小鼠舌组织增殖和特化与细胞周期和细胞粘附基因相关,舌组织分化和成熟主要与细胞骨架相关。%Objective:To gain insight into the molecular mechanisms associated with mouse tongue myogenesis.Methods:Different genes in the tongue at mouse embryonic day 13.25 (E13.25)and 15.5 was investigated using Affymetrix Mouse GeneChip.Using the twice significance of difference as the standard,the molecular mechanisms of tongue development were studied and several molecules re-lated were identified by DAVID functional annotation clustering analysis.Results:Genes of higher expression level at E13.25 were re-lated to cell cycle and cell adhesion,of whom Exo1 ,Gsk3B,Kif20b,Skp2 (cell cycle related factors)and Neo1 and lama1 (cell adhe-sion factors)were activated.While genes of higher expression level at E15.5 were related to cytoskeleton,such as titin and Hspb7. Conclusions:The proliferation and determination of tongue were related with gene clusters of cell cycle and cell adhesion,and,differen-tiation and maturation of tongue were relevant to gene cluster of cytoskeleton.It had highlighted potential cascades and important candi-dates for further investigation on the genetic mechanism and clinical therapy of tongue related diseases.

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

    Directory of Open Access Journals (Sweden)

    Upton Chris

    2006-06-01

    Full Text Available Abstract 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

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

    Science.gov (United States)

    Tcherepanov, Vasily; Ehlers, Angelika; Upton, Chris

    2006-06-13

    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. 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. 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

  2. Short interspersed nuclear elements (SINEs) are abundant in Solanaceae and have a family-specific impact on gene structure and genome organization.

    Science.gov (United States)

    Seibt, Kathrin M; Wenke, Torsten; Muders, Katja; Truberg, Bernd; Schmidt, Thomas

    2016-05-01

    Short interspersed nuclear elements (SINEs) are highly abundant non-autonomous retrotransposons that are widespread in plants. They are short in size, non-coding, show high sequence diversity, and are therefore mostly not or not correctly annotated in plant genome sequences. Hence, comparative studies on genomic SINE populations are rare. To explore the structural organization and impact of SINEs, we comparatively investigated the genome sequences of the Solanaceae species potato (Solanum tuberosum), tomato (Solanum lycopersicum), wild tomato (Solanum pennellii), and two pepper cultivars (Capsicum annuum). Based on 8.5 Gbp sequence data, we annotated 82 983 SINE copies belonging to 10 families and subfamilies on a base pair level. Solanaceae SINEs are dispersed over all chromosomes with enrichments in distal regions. Depending on the genome assemblies and gene predictions, 30% of all SINE copies are associated with genes, particularly frequent in introns and untranslated regions (UTRs). The close association with genes is family specific. More than 10% of all genes annotated in the Solanaceae species investigated contain at least one SINE insertion, and we found genes harbouring up to 16 SINE copies. We demonstrate the involvement of SINEs in gene and genome evolution including the donation of splice sites, start and stop codons and exons to genes, enlargement of introns and UTRs, generation of tandem-like duplications and transduction of adjacent sequence regions. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

  3. Biosynthesis of Akaeolide and Lorneic Acids and Annotation of Type I Polyketide Synthase Gene Clusters in the Genome of Streptomyces sp. NPS554

    Directory of Open Access Journals (Sweden)

    Tao Zhou

    2015-01-01

    Full Text Available The incorporation pattern of biosynthetic precursors into two structurally unique polyketides, akaeolide and lorneic acid A, was elucidated by feeding experiments with 13C-labeled precursors. In addition, the draft genome sequence of the producer, Streptomyces sp. NPS554, was performed and the biosynthetic gene clusters for these polyketides were identified. The putative gene clusters contain all the polyketide synthase (PKS domains necessary for assembly of the carbon skeletons. Combined with the 13C-labeling results, gene function prediction enabled us to propose biosynthetic pathways involving unusual carbon-carbon bond formation reactions. Genome analysis also indicated the presence of at least ten orphan type I PKS gene clusters that might be responsible for the production of new polyketides.

  4. Teaching and Learning Communities through Online Annotation

    Science.gov (United States)

    van der Pluijm, B.

    2016-12-01

    What do colleagues do with your assigned textbook? What they say or think about the material? Want students to be more engaged in their learning experience? If so, online materials that complement standard lecture format provide new opportunity through managed, online group annotation that leverages the ubiquity of internet access, while personalizing learning. The concept is illustrated with the new online textbook "Processes in Structural Geology and Tectonics", by Ben van der Pluijm and Stephen Marshak, which offers a platform for sharing of experiences, supplementary materials and approaches, including readings, mathematical applications, exercises, challenge questions, quizzes, alternative explanations, and more. The annotation framework used is Hypothes.is, which offers a free, open platform markup environment for annotation of websites and PDF postings. The annotations can be public, grouped or individualized, as desired, including export access and download of annotations. A teacher group, hosted by a moderator/owner, limits access to members of a user group of teachers, so that its members can use, copy or transcribe annotations for their own lesson material. Likewise, an instructor can host a student group that encourages sharing of observations, questions and answers among students and instructor. Also, the instructor can create one or more closed groups that offers study help and hints to students. Options galore, all of which aim to engage students and to promote greater responsibility for their learning experience. Beyond new capacity, the ability to analyze student annotation supports individual learners and their needs. For example, student notes can be analyzed for key phrases and concepts, and identify misunderstandings, omissions and problems. Also, example annotations can be shared to enhance notetaking skills and to help with studying. Lastly, online annotation allows active application to lecture posted slides, supporting real-time notetaking

  5. Annotating Coloured Petri Nets

    DEFF Research Database (Denmark)

    Lindstrøm, Bo; Wells, Lisa Marie

    2002-01-01

    Coloured Petri nets (CP-nets) can be used for several fundamentally different purposes like functional analysis, performance analysis, and visualisation. To be able to use the corresponding tool extensions and libraries it is sometimes necessary to include extra auxiliary information in the CP-ne...... a certain use of the CP-net. We define the semantics of annotations by describing a translation from a CP-net and the corresponding annotation layers to another CP-net where the annotations are an integrated part of the CP-net....... a method which makes it possible to associate auxiliary information, called annotations, with tokens without modifying the colour sets of the CP-net. Annotations are pieces of information that are not essential for determining the behaviour of the system being modelled, but are rather added to support...

  6. Correction of the Caulobacter crescentus NA1000 genome annotation.

    Directory of Open Access Journals (Sweden)

    Bert Ely

    Full Text Available Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.

  7. Correction of the Caulobacter crescentus NA1000 genome annotation.

    Science.gov (United States)

    Ely, Bert; Scott, LaTia Etheredge

    2014-01-01

    Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.

  8. A pipeline for automated annotation of yeast genome sequences by a conserved-synteny approach

    Directory of Open Access Journals (Sweden)

    Proux-Wéra Estelle

    2012-09-01

    Full Text Available Abstract Background Yeasts are a model system for exploring eukaryotic genome evolution. Next-generation sequencing technologies are poised to vastly increase the number of yeast genome sequences, both from resequencing projects (population studies and from de novo sequencing projects (new species. However, the annotation of genomes presents a major bottleneck for de novo projects, because it still relies on a process that is largely manual. Results Here we present the Yeast Genome Annotation Pipeline (YGAP, an automated system designed specifically for new yeast genome sequences lacking transcriptome data. YGAP does automatic de novo annotation, exploiting homology and synteny information from other yeast species stored in the Yeast Gene Order Browser (YGOB database. The basic premises underlying YGAP's approach are that data from other species already tells us what genes we should expect to find in any particular genomic region and that we should also expect that orthologous genes are likely to have similar intron/exon structures. Additionally, it is able to detect probable frameshift sequencing errors and can propose corrections for them. YGAP searches intelligently for introns, and detects tRNA genes and Ty-like elements. Conclusions In tests on Saccharomyces cerevisiae and on the genomes of Naumovozyma castellii and Tetrapisispora blattae newly sequenced with Roche-454 technology, YGAP outperformed another popular annotation program (AUGUSTUS. For S. cerevisiae and N. castellii, 91-93% of YGAP's predicted gene structures were identical to those in previous manually curated gene sets. YGAP has been implemented as a webserver with a user-friendly interface at http://wolfe.gen.tcd.ie/annotation.

  9. Dictionary-driven protein annotation.

    Science.gov (United States)

    Rigoutsos, Isidore; Huynh, Tien; Floratos, Aris; Parida, Laxmi; Platt, Daniel

    2002-09-01

    Computational methods seeking to automatically determine the properties (functional, structural, physicochemical, etc.) of a protein directly from the sequence have long been the focus of numerous research groups. With the advent of advanced sequencing methods and systems, the number of amino acid sequences that are being deposited in the public databases has been increasing steadily. This has in turn generated a renewed demand for automated approaches that can annotate individual sequences and complete genomes quickly, exhaustively and objectively. In this paper, we present one such approach that is centered around and exploits the Bio-Dictionary, a collection of amino acid patterns that completely covers the natural sequence space and can capture functional and structural signals that have been reused during evolution, within and across protein families. Our annotation approach also makes use of a weighted, position-specific scoring scheme that is unaffected by the over-representation of well-conserved proteins and protein fragments in the databases used. For a given query sequence, the method permits one to determine, in a single pass, the following: local and global similarities between the query and any protein already present in a public database; the likeness of the query to all available archaeal/ bacterial/eukaryotic/viral sequences in the database as a function of amino acid position within the query; the character of secondary structure of the query as a function of amino acid position within the query; the cytoplasmic, transmembrane or extracellular behavior of the query; the nature and position of binding domains, active sites, post-translationally modified sites, signal peptides, etc. In terms of performance, the proposed method is exhaustive, objective and allows for the rapid annotation of individual sequences and full genomes. Annotation examples are presented and discussed in Results, including individual queries and complete genomes that were

  10. Omics data management and annotation.

    Science.gov (United States)

    Harel, Arye; Dalah, Irina; Pietrokovski, Shmuel; Safran, Marilyn; Lancet, Doron

    2011-01-01

    Technological Omics breakthroughs, including next generation sequencing, bring avalanches of data which need to undergo effective data management to ensure integrity, security, and maximal knowledge-gleaning. Data management system requirements include flexible input formats, diverse data entry mechanisms and views, user friendliness, attention to standards, hardware and software platform definition, as well as robustness. Relevant solutions elaborated by the scientific community include Laboratory Information Management Systems (LIMS) and standardization protocols facilitating data sharing and managing. In project planning, special consideration has to be made when choosing relevant Omics annotation sources, since many of them overlap and require sophisticated integration heuristics. The data modeling step defines and categorizes the data into objects (e.g., genes, articles, disorders) and creates an application flow. A data storage/warehouse mechanism must be selected, such as file-based systems and relational databases, the latter typically used for larger projects. Omics project life cycle considerations must include the definition and deployment of new versions, incorporating either full or partial updates. Finally, quality assurance (QA) procedures must validate data and feature integrity, as well as system performance expectations. We illustrate these data management principles with examples from the life cycle of the GeneCards Omics project (http://www.genecards.org), a comprehensive, widely used compendium of annotative information about human genes. For example, the GeneCards infrastructure has recently been changed from text files to a relational database, enabling better organization and views of the growing data. Omics data handling benefits from the wealth of Web-based information, the vast amount of public domain software, increasingly affordable hardware, and effective use of data management and annotation principles as outlined in this chapter.

  11. Collaborative annotation of 3D crystallographic models.

    Science.gov (United States)

    Hunter, J; Henderson, M; Khan, I

    2007-01-01

    This paper describes the AnnoCryst system-a tool that was designed to enable authenticated collaborators to share online discussions about 3D crystallographic structures through the asynchronous attachment, storage, and retrieval of annotations. Annotations are personal comments, interpretations, questions, assessments, or references that can be attached to files, data, digital objects, or Web pages. The AnnoCryst system enables annotations to be attached to 3D crystallographic models retrieved from either private local repositories (e.g., Fedora) or public online databases (e.g., Protein Data Bank or Inorganic Crystal Structure Database) via a Web browser. The system uses the Jmol plugin for viewing and manipulating the 3D crystal structures but extends Jmol by providing an additional interface through which annotations can be created, attached, stored, searched, browsed, and retrieved. The annotations are stored on a standardized Web annotation server (Annotea), which has been extended to support 3D macromolecular structures. Finally, the system is embedded within a security framework that is capable of authenticating users and restricting access only to trusted colleagues.

  12. GoPipe:批量序列的Gene Ontology注释和统计分析%GoPipe: Streamlined Gene Ontology Annotation for Batch Anonymous Sequences With Statistics

    Institute of Scientific and Technical Information of China (English)

    陈作舟; 薛成海; 朱晟; 周丰丰; XUEFENG BRUCE LING; 刘国平; 陈良标

    2005-01-01

    随着后基因组时代的到来,批量的测序,特别是EST的测序,逐渐成为普通实验室的日常工作.这些新的序列往往需要进行批量的Gene Ontology(GO)的注释及随后的统计分析.但是目前除了Goblet以外,并没有软件适合对未知序列进行批量的GO注释,而GoBlet因为具有上载量的限制,以及仅仅利用BLAST作为预测工具,所以仍有许多不足之处.开发了一个软件包GoPipe,通过整合BLAST和InterProScan的结果来进行序列注释,并提供了进一步作统计比较的工具.主程序接收任意个BLAST和InterProScan的结果文件,并依次进行文本分析、数据整合、去除冗余、统计分析和显示等工作.还提供了统计的工具来比较不同输入对GO的分布来挖掘生物学意义.另外,在交集工作模式下,程序取InterProScan和BLAST结果的交集,在测试数据集中,其精确度达到99.1%,这大大超过了InterProScan本身对GO预测的精确度,而敏感度只是稍微下降.较高的精确度、较快的速度和较大的灵活性使它成为对未知序列进行批量Gene Ontology注释的理想的工具.上述软件包可以在网站(http://gopipe.fishgenome.org/)免费获得或者与作者联系获取.%Accelerated availability of new sequences, especially ESTs, calls for computational methods to link sequences with Gene Ontology (GO) terms in a batch mode. There is currently no program for such purpose except Goblet, an online tool which uses BLAST to interpret query sequence with proper GO terms, but has a restriction of upload sequence files less than 100 kilobytes in size. GoPipe is a standalone package that integrates BLAST and InterProScan results to obtain Gene Ontology annotation with built-in statistical options. GoPipe takes any number of BLAST and/or InterProScan output files simultaneously and launches jobs sequentially to perform parsing, data integration, redundancy removal, GO distributions calculation and graphic display. A very

  13. A task-based approach for Gene Ontology evaluation.

    Science.gov (United States)

    Clarke, Erik L; Loguercio, Salvatore; Good, Benjamin M; Su, Andrew I

    2013-04-15

    The Gene Ontology and its associated annotations are critical tools for interpreting lists of genes. Here, we introduce a method for evaluating the Gene Ontology annotations and structure based on the impact they have on gene set enrichment analysis, along with an example implementation. This task-based approach yields quantitative assessments grounded in experimental data and anchored tightly to the primary use of the annotations. Applied to specific areas of biological interest, our framework allowed us to understand the progress of annotation and structural ontology changes from 2004 to 2012. Our framework was also able to determine that the quality of annotations and structure in the area under test have been improving in their ability to recall underlying biological traits. Furthermore, we were able to distinguish between the impact of changes to the annotation sets and ontology structure. Our framework and implementation lay the groundwork for a powerful tool in evaluating the usefulness of the Gene Ontology. We demonstrate both the flexibility and the power of this approach in evaluating the current and past state of the Gene Ontology as well as its applicability in developing new methods for creating gene annotations.

  14. Genetic control of functional traits related to photosynthesis and water use efficiency in Pinus pinaster Ait. drought response: integration of genome annotation, allele association and QTL detection for candidate gene identification.

    Science.gov (United States)

    de Miguel, Marina; Cabezas, José-Antonio; de María, Nuria; Sánchez-Gómez, David; Guevara, María-Ángeles; Vélez, María-Dolores; Sáez-Laguna, Enrique; Díaz, Luis-Manuel; Mancha, Jose-Antonio; Barbero, María-Carmen; Collada, Carmen; Díaz-Sala, Carmen; Aranda, Ismael; Cervera, María-Teresa

    2014-06-12

    Understanding molecular mechanisms that control photosynthesis and water use efficiency in response to drought is crucial for plant species from dry areas. This study aimed to identify QTL for these traits in a Mediterranean conifer and tested their stability under drought. High density linkage maps for Pinus pinaster were used in the detection of QTL for photosynthesis and water use efficiency at three water irrigation regimes. A total of 28 significant and 27 suggestive QTL were found. QTL detected for photochemical traits accounted for the higher percentage of phenotypic variance. Functional annotation of genes within the QTL suggested 58 candidate genes for the analyzed traits. Allele association analysis in selected candidate genes showed three SNPs located in a MYB transcription factor that were significantly associated with efficiency of energy capture by open PSII reaction centers and specific leaf area. The integration of QTL mapping of functional traits, genome annotation and allele association yielded several candidate genes involved with molecular control of photosynthesis and water use efficiency in response to drought in a conifer species. The results obtained highlight the importance of maintaining the integrity of the photochemical machinery in P. pinaster drought response.

  15. Personnalisation de Syst\\`emes OLAP Annot\\'es

    CERN Document Server

    Jerbi, Houssem; Ravat, Franck; Teste, Olivier

    2010-01-01

    This paper deals with personalization of annotated OLAP systems. Data constellation is extended to support annotations and user preferences. Annotations reflect the decision-maker experience whereas user preferences enable users to focus on the most interesting data. User preferences allow annotated contextual recommendations helping the decision-maker during his/her multidimensional navigations.

  16. The Mycoplasma hominis vaa gene displays a mosaic gene structure

    DEFF Research Database (Denmark)

    Boesen, Thomas; Emmersen, Jeppe M. G.; Jensen, Lise T.;

    1998-01-01

    Mycoplasma hominis contains a variable adherence-associated (vaa) gene. To classify variants of the vaa genes, we examined 42 M. hominis isolated by PCR, DNA sequencing and immunoblotting. This uncovered the existence of five gene categories. Comparison of the gene types revealed a modular compos...

  17. New statistical Methods of Genome-Scale Data Analysis in Life Science - Applications to enterobacterial Diagnostics, Meta-Analysis of Arabidopsis thaliana Gene Expression and functional Sequence Annotation

    OpenAIRE

    Friedrich, Torben

    2009-01-01

    Recent progresses and developments in molecular biology provide a wealth of new but insufficiently characterised data. This fund comprises amongst others biological data of genomic DNA, protein sequences, 3-dimensional protein structures as well as profiles of gene expression. In the present work, this information is used to develop new methods for the characterisation and classification of organisms and whole groups of organisms as well as to enhance the automated gain and transfer of inform...

  18. The physics of DNA and the annotation of the Plasmodium falciparum genome.

    Science.gov (United States)

    Yeramian, E

    2000-09-19

    A gene identification procedure is formulated, based on large-scale structural analyses of genomic sequences. The structural property is the physical - thermal - stability of the DNA double-helix, as described by the classical helix-coil model. The analyses are detailed for the Plasmodium falciparum genome, which represents one of the most difficult cases for the gene identification problem (notably because of the extreme AT-richness of the genome). In this genome, the coding domains (either uninterrupted genes or exons in split genes) are accurately identified as regions of high thermal stability. The conclusion is based on the study of the available cloned genes, of which 17 examples are described in detail. These examples demonstrate that the physical criterion is valid for the detection of coding regions whose lengths extend from a few base pairs up to several thousand base pairs. Accordingly, the structural analyses can provide a powerful and convenient tool for the identification of complex genes in the P. falciparum genome. The limits of such a scheme are discussed. The gene identification procedure is applied to the completely sequenced chromosomes (2 and 3), and the results are compared with the database annotations. The structural analyses suggest more or less extensive revision to the annotations, and also allow new putative genes to be identified in the chromosome sequences. Several examples of such new genes are described in detail.

  19. SigmoID: a user-friendly tool for improving bacterial genome annotation through analysis of transcription control signals.

    Science.gov (United States)

    Nikolaichik, Yevgeny; Damienikan, Aliaksandr U

    2016-01-01

    The majority of bacterial genome annotations are currently automated and based on a 'gene by gene' approach. Regulatory signals and operon structures are rarely taken into account which often results in incomplete and even incorrect gene function assignments. Here we present SigmoID, a cross-platform (OS X, Linux and Windows) open-source application aiming at simplifying the identification of transcription regulatory sites (promoters, transcription factor binding sites and terminators) in bacterial genomes and providing assistance in correcting annotations in accordance with regulatory information. SigmoID combines a user-friendly graphical interface to well known command line tools with a genome browser for visualising regulatory elements in genomic context. Integrated access to online databases with regulatory information (RegPrecise and RegulonDB) and web-based search engines speeds up genome analysis and simplifies correction of genome annotation. We demonstrate some features of SigmoID by constructing a series of regulatory protein binding site profiles for two groups of bacteria: Soft Rot Enterobacteriaceae (Pectobacterium and Dickeya spp.) and Pseudomonas spp. Furthermore, we inferred over 900 transcription factor binding sites and alternative sigma factor promoters in the annotated genome of Pectobacterium atrosepticum. These regulatory signals control putative transcription units covering about 40% of the P. atrosepticum chromosome. Reviewing the annotation in cases where it didn't fit with regulatory information allowed us to correct product and gene names for over 300 loci.

  20. Secondary structure and feature of mitochondrial tRNA genes of the Ussurian tube-nosed bat Murina ussuriensis (Chiroptera: Vespertilionidae

    Directory of Open Access Journals (Sweden)

    Kwang Bae Yoon

    2015-09-01

    Full Text Available The complete mitogenome (NC_021119 of the Ussurian tube-nosed bat Murina ussuriensis (Chiroptera: Vespertilionidae was annotated and characterized in our recent publication (http://www.ncbi.nlm.nih.gov/nuccore/NC_021119. Here we provide additional information on methods in detail for obtaining the complete sequence of M. ussuriensis mitogenome. In addition, we describe characteristics of 22 tRNA genes and secondary structure and feature of 22 tRNAs of M. ussuriensis mitogenome.

  1. Sequencing, annotation and comparative analysis of nine BACs of giant panda (Ailuropoda melanoleuca).

    Science.gov (United States)

    Zheng, Yang; Cai, Jing; Li, JianWen; Li, Bo; Lin, RunMao; Tian, Feng; Wang, XiaoLing; Wang, Jun

    2010-01-01

    A 10-fold BAC library for giant panda was constructed and nine BACs were selected to generate finish sequences. These BACs could be used as a validation resource for the de novo assembly accuracy of the whole genome shotgun sequencing reads of giant panda newly generated by the Illumina GA sequencing technology. Complete sanger sequencing, assembly, annotation and comparative analysis were carried out on the selected BACs of a joint length 878 kb. Homologue search and de novo prediction methods were used to annotate genes and repeats. Twelve protein coding genes were predicted, seven of which could be functionally annotated. The seven genes have an average gene size of about 41 kb, an average coding size of about 1.2 kb and an average exon number of 6 per gene. Besides, seven tRNA genes were found. About 27 percent of the BAC sequence is composed of repeats. A phylogenetic tree was constructed using neighbor-join algorithm across five species, including giant panda, human, dog, cat and mouse, which reconfirms dog as the most related species to giant panda. Our results provide detailed sequence and structure information for new genes and repeats of giant panda, which will be helpful for further studies on the giant panda.

  2. Sequencing,annotation and comparative analysis of nine BACs of the giant panda(Ailuropoda melanoleuca)

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A 10-fold BAC library for the giant panda was constructed and nine BACs were selected to generate finish sequences.These BACs could be used as a validation resource for the de novo assembly accuracy of the whole genome shotgun sequencing reads of the giant panda newly generated by Illumina GA sequencing technology.Complete Sanger sequencing,assembly,annotation and comparative analysis were carried out on the selected BACs of a joint length 878 kb.Homologue search and de novo prediction methods were used to annotate genes and repeats.Twelve protein coding genes were predicted,seven of which could be functionally annotated.The seven genes have an average gene size of about 41 kb,an average coding size of about 1.2 kb and an average exon number of 6 per gene.Besides,seven tRNA genes were found.About 27 percent of the BAC sequence is composed of repeats.A phylogenetic tree was constructed using a neighbor-join algorithm across five species,including the giant panda,human,dog,cat and mouse,which reconfirms dog as the most closely related species to the giant panda.Our results provide detailed sequence and structure information for new genes and repeats of the giant panda,which will be helpful for further studies about the giant panda.

  3. A Plasmodium falciparum FcB1-schizont-EST collection providing clues to schizont specific gene structure and polymorphism

    Directory of Open Access Journals (Sweden)

    Charneau Sébastien

    2009-05-01

    Full Text Available Abstract Background The Plasmodium falciparum genome (3D7 strain published in 2002, revealed ~5,400 genes, mostly based on in silico predictions. Experimental data is therefore required for structural and functional assessments of P. falciparum genes and expression, and polymorphic data are further necessary to exploit genomic information to further qualify therapeutic target candidates. Here, we undertook a large scale analysis of a P. falciparum FcB1-schizont-EST library previously constructed by suppression subtractive hybridization (SSH to study genes expressed during merozoite morphogenesis, with the aim of: 1 obtaining an exhaustive collection of schizont specific ESTs, 2 experimentally validating or correcting P. falciparum gene models and 3 pinpointing genes displaying protein polymorphism between the FcB1 and 3D7 strains. Results A total of 22,125 clones randomly picked from the SSH library were sequenced, yielding 21,805 usable ESTs that were then clustered on the P. falciparum genome. This allowed identification of 243 protein coding genes, including 121 previously annotated as hypothetical. Statistical analysis of GO terms, when available, indicated significant enrichment in genes involved in "entry into host-cells" and "actin cytoskeleton". Although most ESTs do not span full-length gene reading frames, detailed sequence comparison of FcB1-ESTs versus 3D7 genomic sequences allowed the confirmation of exon/intron boundaries in 29 genes, the detection of new boundaries in 14 genes and identification of protein polymorphism for 21 genes. In addition, a large number of non-protein coding ESTs were identified, mainly matching with the two A-type rRNA units (on chromosomes 5 and 7 and to a lower extent, two atypical rRNA loci (on chromosomes 1 and 8, TARE subtelomeric regions (several chromosomes and the recently described telomerase RNA gene (chromosome 9. Conclusion This FcB1-schizont-EST analysis confirmed the actual expression of 243

  4. NoisyGOA: Noisy GO annotations prediction using taxonomic and semantic similarity.

    Science.gov (United States)

    Lu, Chang; Wang, Jun; Zhang, Zili; Yang, Pengyi; Yu, Guoxian

    2016-12-01

    Gene Ontology (GO) provides GO annotations (GOA) that associate gene products with GO terms that summarize their cellular, molecular and functional aspects in the context of biological pathways. GO Consortium (GOC) resorts to various quality assurances to ensure the correctness of annotations. Due to resources limitations, only a small portion of annotations are manually added/checked by GO curators, and a large portion of available annotations are computationally inferred. While computationally inferred annotations provide greater coverage of known genes, they may also introduce annotation errors (noise) that could mislead the interpretation of the gene functions and their roles in cellular and biological processes. In this paper, we investigate how to identify noisy annotations, a rarely addressed problem, and propose a novel approach called NoisyGOA. NoisyGOA first measures taxonomic similarity between ontological terms using the GO hierarchy and semantic similarity between genes. Next, it leverages the taxonomic similarity and semantic similarity to predict noisy annotations. We compare NoisyGOA with other alternative methods on identifying noisy annotations under different simulated cases of noisy annotations, and on archived GO annotations. NoisyGOA achieved higher accuracy than other alternative methods in comparison. These results demonstrated both taxonomic similarity and semantic similarity contribute to the identification of noisy annotations. Our study shows that annotation errors are predictable and removing noisy annotations improves the performance of gene function prediction. This study can prompt the community to study methods for removing inaccurate annotations, a critical step for annotating gene and pathway functions. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. pdb-care (PDB CArbohydrate REsidue check: a program to support annotation of complex carbohydrate structures in PDB files

    Directory of Open Access Journals (Sweden)

    von der Lieth Claus-W

    2004-06-01

    Full Text Available Abstract Background Carbohydrates are involved in a variety of fundamental biological processes and pathological situations. They therefore have a large pharmaceutical and diagnostic potential. Knowledge of the 3D structure of glycans is a prerequisite for a complete understanding of their biological functions. The largest source of biomolecular 3D structures is the Protein Data Bank. However, about 30% of all 1663 PDB entries (version September 2003 containing carbohydrates comprise errors in glycan description. Unfortunately, no software is currently available which aligns the 3D information with the reported assignments. It is the aim of this work to fill this gap. Results The pdb-care program http://www.glycosciences.de/tools/pdb-care/ is able to identify and assign carbohydrate structures using only atom types and their 3D atom coordinates given in PDB-files. Looking up a translation table where systematic names and the respective PDB residue codes are listed, both assignments are compared and inconsistencies are reported. Additionally, the reliability of reported and calculated connectivities for molecules listed within the HETATOM records is checked and unusual values are reported. Conclusion Frequent use of pdb-care will help to improve the quality of carbohydrate data contained in the PDB. Automatic assignment of carbohydrate structures contained in PDB entries will enable the cross-linking of glycobiology resources with genomic and proteomic data collections.

  6. NoGOA: predicting noisy GO annotations using evidences and sparse representation.

    Science.gov (United States)

    Yu, Guoxian; Lu, Chang; Wang, Jun

    2017-07-21

    Gene Ontology (GO) is a community effort to represent functional features of gene products. GO annotations (GOA) provide functional associations between GO terms and gene products. Due to resources limitation, only a small portion of annotations are manually checked by curators, and the others are electronically inferred. Although quality control techniques have been applied to ensure the quality of annotations, the community consistently report that there are still considerable noisy (or incorrect) annotations. Given the wide application of annotations, however, how to identify noisy annotations is an important but yet seldom studied open problem. We introduce a novel approach called NoGOA to predict noisy annotations. NoGOA applies sparse representation on the gene-term association matrix to reduce the impact of noisy annotations, and takes advantage of sparse representation coefficients to measure the semantic similarity between genes. Secondly, it preliminarily predicts noisy annotations of a gene based on aggregated votes from semantic neighborhood genes of that gene. Next, NoGOA estimates the ratio of noisy annotations for each evidence code based on direct annotations in GOA files archived on different periods, and then weights entries of the association matrix via estimated ratios and propagates weights to ancestors of direct annotations using GO hierarchy. Finally, it integrates evidence-weighted association matrix and aggregated votes to predict noisy annotations. Experiments on archived GOA files of six model species (H. sapiens, A. thaliana, S. cerevisiae, G. gallus, B. Taurus and M. musculus) demonstrate that NoGOA achieves significantly better results than other related methods and removing noisy annotations improves the performance of gene function prediction. The comparative study justifies the effectiveness of integrating evidence codes with sparse representation for predicting noisy GO annotations. Codes and datasets are available at http://mlda.swu.edu.cn/codes.php?name=NoGOA .

  7. High-throughput proteogenomics of Ruegeria pomeroyi: seeding a better genomic annotation for the whole marine Roseobacter clade

    Directory of Open Access Journals (Sweden)

    Christie-Oleza Joseph A

    2012-02-01

    Full Text Available Abstract Background The structural and functional annotation of genomes is now heavily based on data obtained using automated pipeline systems. The key for an accurate structural annotation consists of blending similarities between closely related genomes with biochemical evidence of the genome interpretation. In this work we applied high-throughput proteogenomics to Ruegeria pomeroyi, a member of the Roseobacter clade, an abundant group of marine bacteria, as a seed for the annotation of the whole clade. Results A large dataset of peptides from R. pomeroyi was obtained after searching over 1.1 million MS/MS spectra against a six-frame translated genome database. We identified 2006 polypeptides, of which thirty-four were encoded by open reading frames (ORFs that had not previously been annotated. From the pool of 'one-hit-wonders', i.e. those ORFs specified by only one peptide detected by tandem mass spectrometry, we could confirm the probable existence of five additional new genes after proving that the corresponding RNAs were transcribed. We also identified the most-N-terminal peptide of 486 polypeptides, of which sixty-four had originally been wrongly annotated. Conclusions By extending these re-annotations to the other thirty-six Roseobacter isolates sequenced to date (twenty different genera, we propose the correction of the assigned start codons of 1082 homologous genes in the clade. In addition, we also report the presence of novel genes within operons encoding determinants of the important tricarboxylic acid cycle, a feature that seems to be characteristic of some Roseobacter genomes. The detection of their corresponding products in large amounts raises the question of their function. Their discoveries point to a possible theory for protein evolution that will rely on high expression of orphans in bacteria: their putative poor efficiency could be counterbalanced by a higher level of expression. Our proteogenomic analysis will increase

  8. Distribution, structure and diversity of “bacterial” genes encoding two-component proteins in the Euryarchaeota

    Directory of Open Access Journals (Sweden)

    Mark K. Ashby

    2006-01-01

    Full Text Available The publicly available annotated archaeal genome sequences (23 complete and three partial annotations, October 2005 were searched for the presence of potential two-component open reading frames (ORFs using gene category lists and BLASTP. A total of 489 potential two-component genes were identified from the gene category lists and BLASTP. Two-component genes were found in 14 of the 21 Euryarchaeal sequences (October 2005 and in neither the Crenarchaeota nor the Nanoarchaeota. A total of 20 predicted protein domains were identified in the putative two-component ORFs that, in addition to the histidine kinase and receiver domains, also includes sensor and signalling domains. The detailed structure of these putative proteins is shown, as is the distribution of each class of two-component genes in each species. Potential members of orthologous groups have been identified, as have any potential operons containing two or more two-component genes. The number of two-component genes in those Euryarchaeal species which have them seems to be linked more to lifestyle and habitat than to genome complexity, with most examples being found in Methanospirillum hungatei, Haloarcula marismortui, Methanococcoides burtonii and the mesophilic Methanosarcinales group. The large numbers of two-component genes in these species may reflect a greater requirement for internal regulation. Phylogenetic analysis of orthologous groups of five different protein classes, three probably involved in regulating taxis, suggests that most of these ORFs have been inherited vertically from an ancestral Euryarchaeal species and point to a limited number of key horizontal gene transfer events.

  9. Semantic annotation of mutable data.

    Science.gov (United States)

    Morris, Robert A; Dou, Lei; Hanken, James; Kelly, Maureen; Lowery, David B; Ludäscher, Bertram; Macklin, James A; Morris, Paul J

    2013-01-01

    Electronic annotation of scientific data is very similar to annotation of documents. Both types of annotation amplify the original object, add related knowledge to it, and dispute or support assertions in it. In each case, annotation is a framework for discourse about the original object, and, in each case, an annotation needs to clearly identify its scope and its own terminology. However, electronic annotation of data differs from annotation of documents: the content of the annotations, including expectations and supporting evidence, is more often shared among members of networks. Any consequent actions taken by the holders of the annotated data could be shared as well. But even those current annotation systems that admit data as their subject often make it difficult or impossible to annotate at fine-enough granularity to use the results in this way for data quality control. We address these kinds of issues by offering simple extensions to an existing annotation ontology and describe how the results support an interest-based distribution of annotations. We are using the result to design and deploy a platform that supports annotation services overlaid on networks of distributed data, with particular application to data quality control. Our initial instance supports a set of natural science collection metadata services. An important application is the support for data quality control and provision of missing data. A previous proof of concept demonstrated such use based on data annotations modeled with XML-Schema.

  10. Evolutionary interrogation of human biology in well-annotated genomic framework of rhesus macaque.

    Science.gov (United States)

    Zhang, Shi-Jian; Liu, Chu-Jun; Yu, Peng; Zhong, Xiaoming; Chen, Jia-Yu; Yang, Xinzhuang; Peng, Jiguang; Yan, Shouyu; Wang, Chenqu; Zhu, Xiaotong; Xiong, Jingwei; Zhang, Yong E; Tan, Bertrand Chin-Ming; Li, Chuan-Yun

    2014-05-01

    With genome sequence and composition highly analogous to human, rhesus macaque represents a unique reference for evolutionary studies of human biology. Here, we developed a comprehensive genomic framework of rhesus macaque, the RhesusBase2, for evolutionary interrogation of human genes and the associated regulations. A total of 1,667 next-generation sequencing (NGS) data sets were processed, integrated, and evaluated, generating 51.2 million new functional annotation records. With extensive NGS annotations, RhesusBase2 refined the fine-scale structures in 30% of the macaque Ensembl transcripts, reporting an accurate, up-to-date set of macaque gene models. On the basis of these annotations and accurate macaque gene models, we further developed an NGS-oriented Molecular Evolution Gateway to access and visualize macaque annotations in reference to human orthologous genes and associated regulations (www.rhesusbase.org/molEvo). We highlighted the application of this well-annotated genomic framework in generating hypothetical link of human-biased regulations to human-specific traits, by using mechanistic characterization of the DIEXF gene as an example that provides novel clues to the understanding of digestive system reduction in human evolution. On a global scale, we also identified a catalog of 9,295 human-biased regulatory events, which may represent novel elements that have a substantial impact on shaping human transcriptome and possibly underpin recent human phenotypic evolution. Taken together, we provide an NGS data-driven, information-rich framework that will broadly benefit genomics research in general and serves as an important resource for in-depth evolutionary studies of human biology.

  11. Automated analysis and annotation of basketball video

    Science.gov (United States)

    Saur, Drew D.; Tan, Yap-Peng; Kulkarni, Sanjeev R.; Ramadge, Peter J.

    1997-01-01

    Automated analysis and annotation of video sequences are important for digital video libraries, content-based video browsing and data mining projects. A successful video annotation system should provide users with useful video content summary in a reasonable processing time. Given the wide variety of video genres available today, automatically extracting meaningful video content for annotation still remains hard by using current available techniques. However, a wide range video has inherent structure such that some prior knowledge about the video content can be exploited to improve our understanding of the high-level video semantic content. In this paper, we develop tools and techniques for analyzing structured video by using the low-level information available directly from MPEG compressed video. Being able to work directly in the video compressed domain can greatly reduce the processing time and enhance storage efficiency. As a testbed, we have developed a basketball annotation system which combines the low-level information extracted from MPEG stream with the prior knowledge of basketball video structure to provide high level content analysis, annotation and browsing for events such as wide- angle and close-up views, fast breaks, steals, potential shots, number of possessions and possession times. We expect our approach can also be extended to structured video in other domains.

  12. MEETING: Chlamydomonas Annotation Jamboree - October 2003

    Energy Technology Data Exchange (ETDEWEB)

    Grossman, Arthur R

    2007-04-13

    Shotgun sequencing of the nuclear genome of Chlamydomonas reinhardtii (Chlamydomonas throughout) was performed at an approximate 10X coverage by JGI. Roughly half of the genome is now contained on 26 scaffolds, all of which are at least 1.6 Mb, and the coverage of the genome is ~95%. There are now over 200,000 cDNA sequence reads that we have generated as part of the Chlamydomonas genome project (Grossman, 2003; Shrager et al., 2003; Grossman et al. 2007; Merchant et al., 2007); other sequences have also been generated by the Kasuza sequence group (Asamizu et al., 1999; Asamizu et al., 2000) or individual laboratories that have focused on specific genes. Shrager et al. (2003) placed the reads into distinct contigs (an assemblage of reads with overlapping nucleotide sequences), and contigs that group together as part of the same genes have been designated ACEs (assembly of contigs generated from EST information). All of the reads have also been mapped to the Chlamydomonas nuclear genome and the cDNAs and their corresponding genomic sequences have been reassembled, and the resulting assemblage is called an ACEG (an Assembly of contiguous EST sequences supported by genomic sequence) (Jain et al., 2007). Most of the unique genes or ACEGs are also represented by gene models that have been generated by the Joint Genome Institute (JGI, Walnut Creek, CA). These gene models have been placed onto the DNA scaffolds and are presented as a track on the Chlamydomonas genome browser associated with the genome portal (http://genome.jgi-psf.org/Chlre3/Chlre3.home.html). Ultimately, the meeting grant awarded by DOE has helped enormously in the development of an annotation pipeline (a set of guidelines used in the annotation of genes) and resulted in high quality annotation of over 4,000 genes; the annotators were from both Europe and the USA. Some of the people who led the annotation initiative were Arthur Grossman, Olivier Vallon, and Sabeeha Merchant (with many individual

  13. Superfamily assignments for the yeast proteome through integration of structure prediction with the gene ontology.

    Directory of Open Access Journals (Sweden)

    Lars Malmström

    2007-04-01

    Full Text Available Saccharomyces cerevisiae is one of the best-studied model organisms, yet the three-dimensional structure and molecular function of many yeast proteins remain unknown. Yeast proteins were parsed into 14,934 domains, and those lacking sequence similarity to proteins of known structure were folded using the Rosetta de novo structure prediction method on the World Community Grid. This structural data was integrated with process, component, and function annotations from the Saccharomyces Genome Database to assign yeast protein domains to SCOP superfamilies using a simple Bayesian approach. We have predicted the structure of 3,338 putative domains and assigned SCOP superfamily annotations to 581 of them. We have also assigned structural annotations to 7,094 predicted domains based on fold recognition and homology modeling methods. The domain predictions and structural information are available in an online database at http://rd.plos.org/10.1371_journal.pbio.0050076_01.

  14. SigmoID: a user-friendly tool for improving bacterial genome annotation through analysis of transcription control signals

    Directory of Open Access Journals (Sweden)

    Yevgeny Nikolaichik

    2016-05-01

    Full Text Available The majority of bacterial genome annotations are currently automated and based on a ‘gene by gene’ approach. Regulatory signals and operon structures are rarely taken into account which often results in incomplete and even incorrect gene function assignments. Here we present SigmoID, a cross-platform (OS X, Linux and Windows open-source application aiming at simplifying the identification of transcription regulatory sites (promoters, transcription factor binding sites and terminators in bacterial genomes and providing assistance in correcting annotations in accordance with regulatory information. SigmoID combines a user-friendly graphical interface to well known command line tools with a genome browser for visualising regulatory elements in genomic context. Integrated access to online databases with regulatory information (RegPrecise and RegulonDB and web-based search engines speeds up genome analysis and simplifies correction of genome annotation. We demonstrate some features of SigmoID by constructing a series of regulatory protein binding site profiles for two groups of bacteria: Soft Rot Enterobacteriaceae (Pectobacterium and Dickeya spp. and Pseudomonas spp. Furthermore, we inferred over 900 transcription factor binding sites and alternative sigma factor promoters in the annotated genome of Pectobacterium atrosepticum. These regulatory signals control putative transcription units covering about 40% of the P. atrosepticum chromosome. Reviewing the annotation in cases where it didn’t fit with regulatory information allowed us to correct product and gene names for over 300 loci.

  15. Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research [v1; ref status: indexed, http://f1000r.es/p5

    Directory of Open Access Journals (Sweden)

    Sebastian Köhler

    2013-02-01

    Full Text Available Phenotype analyses, e.g. investigating metabolic processes, tissue formation, or organism behavior, are an important element of most biological and medical research activities. Biomedical researchers are making increased use of ontological standards and methods to capture the results of such analyses, with one focus being the comparison and analysis of phenotype information between species. We have generated a cross-species phenotype ontology for human, mouse and zebra fish that contains zebrafish phenotypes. We also provide up-to-date annotation data connecting human genes to phenotype classes from the generated ontology. We have included the data generation pipeline into our continuous integration system ensuring stable and up-to-date releases. This article describes the data generation process and is intended to help interested researchers access both the phenotype annotation data and the associated cross-species phenotype ontology. The resource described here can be used in sophisticated semantic similarity and gene set enrichment analyses for phenotype data across species. The stable releases of this resource can be obtained from http://purl.obolibrary.org/obo/hp/uberpheno/.

  16. Determining Semantically Related Significant Genes.

    Science.gov (United States)

    Taha, Kamal

    2014-01-01

    GO relation embodies some aspects of existence dependency. If GO term xis existence-dependent on GO term y, the presence of y implies the presence of x. Therefore, the genes annotated with the function of the GO term y are usually functionally and semantically related to the genes annotated with the function of the GO term x. A large number of gene set enrichment analysis methods have been developed in recent years for analyzing gene sets enrichment. However, most of these methods overlook the structural dependencies between GO terms in GO graph by not considering the concept of existence dependency. We propose in this paper a biological search engine called RSGSearch that identifies enriched sets of genes annotated with different functions using the concept of existence dependency. We observe that GO term xcannot be existence-dependent on GO term y, if x- and y- have the same specificity (biological characteristics). After encoding into a numeric format the contributions of GO terms annotating target genes to the semantics of their lowest common ancestors (LCAs), RSGSearch uses microarray experiment to identify the most significant LCA that annotates the result genes. We evaluated RSGSearch experimentally and compared it with five gene set enrichment systems. Results showed marked improvement.

  17. Bovine Genome Database: supporting community annotation and analysis of the Bos taurus genome

    Directory of Open Access Journals (Sweden)

    Childs Kevin L

    2010-11-01

    Full Text Available Abstract Background A goal of the Bovine Genome Database (BGD; http://BovineGenome.org has been to support the Bovine Genome Sequencing and Analysis Consortium (BGSAC in the annotation and analysis of the bovine genome. We were faced with several challenges, including the need to maintain consistent quality despite diversity in annotation expertise in the research community, the need to maintain consistent data formats, and the need to minimize the potential duplication of annotation effort. With new sequencing technologies allowing many more eukaryotic genomes to be sequenced, the demand for collaborative annotation is likely to increase. Here we present our approach, challenges and solutions facilitating a large distributed annotation project. Results and Discussion BGD has provided annotation tools that supported 147 members of the BGSAC in contributing 3,871 gene models over a fifteen-week period, and these annotations have been integrated into the bovine Official Gene Set. Our approach has been to provide an annotation system, which includes a BLAST site, multiple genome browsers, an annotation portal, and the Apollo Annotation Editor configured to connect directly to our Chado database. In addition to implementing and integrating components of the annotation system, we have performed computational analyses to create gene evidence tracks and a consensus gene set, which can be viewed on individual gene pages at BGD. Conclusions We have provided annotation tools that alleviate challenges associated with distributed annotation. Our system provides a consistent set of data to all annotators and eliminates the need for annotators to format data. Involving the bovine research community in genome annotation has allowed us to leverage expertise in various areas of bovine biology to provide biological insight into the genome sequence.

  18. A highly conserved gene island of three genes on chromosome 3B of hexaploid wheat: diverse gene function and genomic structure maintained in a tightly linked block

    Directory of Open Access Journals (Sweden)

    Ma Wujun

    2010-05-01

    Full Text Available Abstract Background The complexity of the wheat genome has resulted from waves of retrotransposable element insertions. Gene deletions and disruptions generated by the fast replacement of repetitive elements in wheat have resulted in disruption of colinearity at a micro (sub-megabase level among the cereals. In view of genomic changes that are possible within a given time span, conservation of genes between species tends to imply an important functional or regional constraint that does not permit a change in genomic structure. The ctg1034 contig completed in this paper was initially studied because it was assigned to the Sr2 resistance locus region, but detailed mapping studies subsequently assigned it to the long arm of 3B and revealed its unusual features. Results BAC shotgun sequencing of the hexaploid wheat (Triticum aestivum cv. Chinese Spring genome has been used to assemble a group of 15 wheat BACs from the chromosome 3B physical map FPC contig ctg1034 into a 783,553 bp genomic sequence. This ctg1034 sequence was annotated for biological features such as genes and transposable elements. A three-gene island was identified among >80% repetitive DNA sequence. Using bioinformatics analysis there were no observable similarity in their gene functions. The ctg1034 gene island also displayed complete conservation of gene order and orientation with syntenic gene islands found in publicly available genome sequences of Brachypodium distachyon, Oryza sativa, Sorghum bicolor and Zea mays, even though the intergenic space and introns were divergent. Conclusion We propose that ctg1034 is located within the heterochromatic C-band region of deletion bin 3BL7 based on the identification of heterochromatic tandem repeats and presence of significant matches to chromodomain-containing gypsy LTR retrotransposable elements. We also speculate that this location, among other highly repetitive sequences, may account for the relative stability in gene order and

  19. Software for computing and annotating genomic ranges.

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    Michael Lawrence

    Full Text Available We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

  20. Assembly, Annotation, and Analysis of Multiple Mycorrhizal Fungal Genomes

    Energy Technology Data Exchange (ETDEWEB)

    Initiative Consortium, Mycorrhizal Genomics; Kuo, Alan; Grigoriev, Igor; Kohler, Annegret; Martin, Francis

    2013-03-08

    Mycorrhizal fungi play critical roles in host plant health, soil community structure and chemistry, and carbon and nutrient cycling, all areas of intense interest to the US Dept. of Energy (DOE) Joint Genome Institute (JGI). To this end we are building on our earlier sequencing of the Laccaria bicolor genome by partnering with INRA-Nancy and the mycorrhizal research community in the MGI to sequence and analyze dozens of mycorrhizal genomes of all Basidiomycota and Ascomycota orders and multiple ecological types (ericoid, orchid, and ectomycorrhizal). JGI has developed and deployed high-throughput sequencing techniques, and Assembly, RNASeq, and Annotation Pipelines. In 2012 alone we sequenced, assembled, and annotated 12 draft or improved genomes of mycorrhizae, and predicted ~;;232831 genes and ~;;15011 multigene families, All of this data is publicly available on JGI MycoCosm (http://jgi.doe.gov/fungi/), which provides access to both the genome data and tools with which to analyze the data. Preliminary comparisons of the current total of 14 public mycorrhizal genomes suggest that 1) short secreted proteins potentially involved in symbiosis are more enriched in some orders than in others amongst the mycorrhizal Agaricomycetes, 2) there are wide ranges of numbers of genes involved in certain functional categories, such as signal transduction and post-translational modification, and 3) novel gene families are specific to some ecological types.

  1. FSim: A Novel Functional Similarity Search Algorithm and Tool for Discovering Functionally Related Gene Products

    Directory of Open Access Journals (Sweden)

    Qiang Hu

    2014-01-01

    Full Text Available Background. During the analysis of genomics data, it is often required to quantify the functional similarity of genes and their products based on the annotation information from gene ontology (GO with hierarchical structure. A flexible and user-friendly way to estimate the functional similarity of genes utilizing GO annotation is therefore highly desired. Results. We proposed a novel algorithm using a level coefficient-weighted model to measure the functional similarity of gene products based on multiple ontologies of hierarchical GO annotations. The performance of our algorithm was evaluated and found to be superior to the other tested methods. We implemented the proposed algorithm in a software package, FSim, based on R statistical and computing environment. It can be used to discover functionally related genes for a given gene, group of genes, or set of function terms. Conclusions. FSim is a flexible tool to analyze functional gene groups based on the GO annotation databases.

  2. AmiGO: online access to ontology and annotation data

    Energy Technology Data Exchange (ETDEWEB)

    Carbon, Seth; Ireland, Amelia; Mungall, Christopher J.; Shu, ShengQiang; Marshall, Brad; Lewis, Suzanna

    2009-01-15

    AmiGO is a web application that allows users to query, browse, and visualize ontologies and related gene product annotation (association) data. AmiGO can be used online at the Gene Ontology (GO) website to access the data provided by the GO Consortium; it can also be downloaded and installed to browse local ontologies and annotations. AmiGO is free open source software developed and maintained by the GO Consortium.

  3. AmiGO: online access to ontology and annotation data

    Energy Technology Data Exchange (ETDEWEB)

    Carbon, Seth; Ireland, Amelia; Mungall, Christopher J.; Shu, ShengQiang; Marshall, Brad; Lewis, Suzanna

    2009-01-15

    AmiGO is a web application that allows users to query, browse, and visualize ontologies and related gene product annotation (association) data. AmiGO can be used online at the Gene Ontology (GO) website to access the data provided by the GO Consortium; it can also be downloaded and installed to browse local ontologies and annotations. AmiGO is free open source software developed and maintained by the GO Consortium.

  4. Cheating. An Annotated Bibliography.

    Science.gov (United States)

    Wildemuth, Barbara M., Comp.

    This 89-item, annotated bibliography was compiled to provide access to research and discussions of cheating and, specifically, cheating on tests. It is not limited to any educational level, nor is it confined to any specific curriculum area. Two data bases were searched by computer, and a library search was conducted. A computer search of the…

  5. Collaborative Movie Annotation

    Science.gov (United States)

    Zad, Damon Daylamani; Agius, Harry

    In this paper, we focus on metadata for self-created movies like those found on YouTube and Google Video, the duration of which are increasing in line with falling upload restrictions. While simple tags may have been sufficient for most purposes for traditionally very short video footage that contains a relatively small amount of semantic content, this is not the case for movies of longer duration which embody more intricate semantics. Creating metadata is a time-consuming process that takes a great deal of individual effort; however, this effort can be greatly reduced by harnessing the power of Web 2.0 communities to create, update and maintain it. Consequently, we consider the annotation of movies within Web 2.0 environments, such that users create and share that metadata collaboratively and propose an architecture for collaborative movie annotation. This architecture arises from the results of an empirical experiment where metadata creation tools, YouTube and an MPEG-7 modelling tool, were used by users to create movie metadata. The next section discusses related work in the areas of collaborative retrieval and tagging. Then, we describe the experiments that were undertaken on a sample of 50 users. Next, the results are presented which provide some insight into how users interact with existing tools and systems for annotating movies. Based on these results, the paper then develops an architecture for collaborative movie annotation.

  6. Annotated Bibliography. First Edition.

    Science.gov (United States)

    Haring, Norris G.

    An annotated bibliography which presents approximately 300 references from 1951 to 1973 on the education of severely/profoundly handicapped persons. Citations are grouped alphabetically by author's name within the following categories: characteristics and treatment, gross motor development, sensory and motor development, physical therapy for the…

  7. Annotation of Regular Polysemy

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector

    Regular polysemy has received a lot of attention from the theory of lexical semantics and from computational linguistics. However, there is no consensus on how to represent the sense of underspecified examples at the token level, namely when annotating or disambiguating senses of metonymic words...

  8. Annotated bibliography traceability

    NARCIS (Netherlands)

    Narain, G.

    2006-01-01

    This annotated bibliography contains summaries of articles and chapters of books, which are relevant to traceability. After each summary there is a part about the relevancy of the paper for the LEI project. The aim of the LEI-project is to gain insight in several aspects of traceability in order to

  9. Annotation: The Savant Syndrome

    Science.gov (United States)

    Heaton, Pamela; Wallace, Gregory L.

    2004-01-01

    Background: Whilst interest has focused on the origin and nature of the savant syndrome for over a century, it is only within the past two decades that empirical group studies have been carried out. Methods: The following annotation briefly reviews relevant research and also attempts to address outstanding issues in this research area.…

  10. The RAST Server: Rapid Annotations using Subsystems Technology

    Directory of Open Access Journals (Sweden)

    Overbeek Ross A

    2008-02-01

    Full Text Available Abstract Background The number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them. Description We describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment. The service normally makes the annotated genome available within 12–24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service. Conclusion By providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes.

  11. Solving the Problem: Genome Annotation Standards before the Data Deluge

    Science.gov (United States)

    Klimke, William; O'Donovan, Claire; White, Owen; Brister, J. Rodney; Clark, Karen; Fedorov, Boris; Mizrachi, Ilene; Pruitt, Kim D.; Tatusova, Tatiana

    2011-01-01

    The promise of genome sequencing was that the vast undiscovered country would be mapped out by comparison of the multitude of sequences available and would aid researchers in deciphering the role of each gene in every organism. Researchers recognize that there is a need for high quality data. However, different annotation procedures, numerous databases, and a diminishing percentage of experimentally determined gene functions have resulted in a spectrum of annotation quality. NCBI in collaboration with sequencing centers, archival databases, and researchers, has developed the first international annotation standards, a fundamental step in ensuring that high quality complete prokaryotic genomes are available as gold standard references. Highlights include the development of annotation assessment tools, community acceptance of protein naming standards, comparison of annotation resources to provide consistent annotation, and improved tracking of the evidence used to generate a particular annotation. The development of a set of minimal standards, including the requirement for annotated complete prokaryotic genomes to contain a full set of ribosomal RNAs, transfer RNAs, and proteins encoding core conserved functions, is an historic milestone. The use of these standards in existing genomes and future submissions will increase the quality of databases, enabling researchers to make accurate biological discoveries. PMID:22180819

  12. Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development

    Directory of Open Access Journals (Sweden)

    Mungall Christopher J

    2010-10-01

    Full Text Available Abstract Background The Gene Ontology project supports categorization of gene products according to their location of action, the molecular functions that they carry out, and the processes that they are involved in. Although the ontologies are intentionally developed to be taxon neutral, and to cover all species, there are inherent taxon specificities in some branches. For example, the process 'lactation' is specific to mammals and the location 'mitochondrion' is specific to eukaryotes. The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation. Results We have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology. We have also developed an inference system that can be used to check for violations of these constraints in annotations. Using the constraints in conjunction with the inference system, we have detected and removed errors in annotations and improved the structure of the ontology. Conclusions Detection of inconsistencies in taxon-specificity enables gradual improvement of the ontologies, the annotations, and the formalized constraints. This is progressively improving the quality of our data. The full system is available for download, and new constraints or proposed changes to constraints can be submitted online at https://sourceforge.net/tracker/?atid=605890&group_id=36855.

  13. Structural and Operational Complexity of the Geobacter Sulfurreducens Genome

    Energy Technology Data Exchange (ETDEWEB)

    Qiu, Yu; Cho, Byung-Kwan; Park, Young S.; Lovley, Derek R.; Palsson, Bernhard O.; Zengler, Karsten

    2010-06-30

    Prokaryotic genomes can be annotated based on their structural, operational, and functional properties. These annotations provide the pivotal scaffold for understanding cellular functions on a genome-scale, such as metabolism and transcriptional regulation. Here, we describe a systems approach to simultaneously determine the structural and operational annotation of the Geobacter sulfurreducens genome. Integration of proteomics, transcriptomics, RNA polymerase, and sigma factor-binding information with deep-sequencing-based analysis of primary 59-end transcripts allowed for a most precise annotation. The structural annotation is comprised of numerous previously undetected genes, noncoding RNAs, prevalent leaderless mRNA transcripts, and antisense transcripts. When compared with other prokaryotes, we found that the number of antisense transcripts reversely correlated with genome size. The operational annotation consists of 1453 operons, 22% of which have multiple transcription start sites that use different RNA polymerase holoenzymes. Several operons with multiple transcription start sites encoded genes with essential functions, giving insight into the regulatory complexity of the genome. The experimentally determined structural and operational annotations can be combined with functional annotation, yielding a new three-level annotation that greatly expands our understanding of prokaryotic genomes.

  14. Semantator: semantic annotator for converting biomedical text to linked data.

    Science.gov (United States)

    Tao, Cui; Song, Dezhao; Sharma, Deepak; Chute, Christopher G

    2013-10-01

    More than 80% of biomedical data is embedded in plain text. The unstructured nature of these text-based documents makes it challenging to easily browse and query the data of interest in them. One approach to facilitate browsing and querying biomedical text is to convert the plain text to a linked web of data, i.e., converting data originally in free text to structured formats with defined meta-level semantics. In this paper, we introduce Semantator (Semantic Annotator), a semantic-web-based environment for annotating data of interest in biomedical documents, browsing and querying the annotated data, and interactively refining annotation results if needed. Through Semantator, information of interest can be either annotated manually or semi-automatically using plug-in information extraction tools. The annotated results will be stored in RDF and can be queried using the SPARQL query language. In addition, semantic reasoners can be directly applied to the annotated data for consistency checking and knowledge inference. Semantator has been released online and was used by the biomedical ontology community who provided positive feedbacks. Our evaluation results indicated that (1) Semantator can perform the annotation functionalities as designed; (2) Semantator can be adopted in real applications in clinical and transactional research; and (3) the annotated results using Semantator can be easily used in Semantic-web-based reasoning tools for further inference.

  15. Automatic medical X-ray image classification using annotation.

    Science.gov (United States)

    Zare, Mohammad Reza; Mueen, Ahmed; Seng, Woo Chaw

    2014-02-01

    The demand for automatically classification of medical X-ray images is rising faster than ever. In this paper, an approach is presented to gain high accuracy rate for those classes of medical database with high ratio of intraclass variability and interclass similarities. The classification framework was constructed via annotation using the following three techniques: annotation by binary classification, annotation by probabilistic latent semantic analysis, and annotation using top similar images. Next, final annotation was constructed by applying ranking similarity on annotated keywords made by each technique. The final annotation keywords were then divided into three levels according to the body region, specific bone structure in body region as well as imaging direction. Different weights were given to each level of the keywords; they are then used to calculate the weightage for each category of medical images based on their ground truth annotation. The weightage computed from the generated annotation of query image was compared with the weightage of each category of medical images, and then the query image would be assigned to the category with closest weightage to the query image. The average accuracy rate reported is 87.5 %.

  16. GSV Annotated Bibliography

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, Randy S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Pope, Paul A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Jiang, Ming [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Trucano, Timothy G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Aragon, Cecilia R. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ni, Kevin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Wei, Thomas [Argonne National Lab. (ANL), Argonne, IL (United States); Chilton, Lawrence K. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Bakel, Alan [Argonne National Lab. (ANL), Argonne, IL (United States)

    2011-06-14

    The following annotated bibliography was developed as part of the Geospatial Algorithm Veri cation and Validation (GSV) project for the Simulation, Algorithms and Modeling program of NA-22. Veri cation and Validation of geospatial image analysis algorithms covers a wide range of technologies. Papers in the bibliography are thus organized into the following ve topic areas: Image processing and analysis, usability and validation of geospatial image analysis algorithms, image distance measures, scene modeling and image rendering, and transportation simulation models.

  17. Filtering "genic" open reading frames from genomic DNA samples for advanced annotation

    Directory of Open Access Journals (Sweden)

    Sblattero Daniele

    2011-06-01

    Full Text Available Abstract Background In order to carry out experimental gene annotation, DNA encoding open reading frames (ORFs derived from real genes (termed "genic" in the correct frame is required. When genes are correctly assigned, isolation of genic DNA for functional annotation can be carried out by PCR. However, not all genes are correctly assigned, and even when correctly assigned, gene products are often incorrectly folded when expressed in heterologous hosts. This is a problem that can sometimes be overcome by the expression of protein fragments encoding domains, rather than full-length proteins. One possible method to isolate DNA encoding such domains would to "filter" complex DNA (cDNA libraries, genomic and metagenomic DNA for gene fragments that confer a selectable phenotype relying on correct folding, with all such domains present in a complex DNA sample, termed the “domainome”. Results In this paper we discuss the preparation of diverse genic ORF libraries from randomly fragmented genomic DNA using ß-lactamase to filter out the open reading frames. By cloning DNA fragments between leader sequences and the mature ß-lactamase gene, colonies can be selected for resistance to ampicillin, conferred by correct folding of the lactamase gene. Our experiments demonstrate that the majority of surviving colonies contain genic open reading frames, suggesting that ß-lactamase is acting as a selectable folding reporter. Furthermore, different leaders (Sec, TAT and SRP, normally translocating different protein classes, filter different genic fragment subsets, indicating that their use increases the fraction of the “domainone” that is accessible. Conclusions The availability of ORF libraries, obtained with the filtering method described here, combined with screening methods such as phage display and protein-protein interaction studies, or with protein structure determination projects, can lead to the identification and structural determination of

  18. Large-scale annotation of small-molecule libraries using public databases.

    Science.gov (United States)

    Zhou, Yingyao; Zhou, Bin; Chen, Kaisheng; Yan, S Frank; King, Frederick J; Jiang, Shumei; Winzeler, Elizabeth A

    2007-01-01

    While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.

  19. Annotation and analysis of a large cuticular protein family with the R&R Consensus in Anopheles gambiae

    Directory of Open Access Journals (Sweden)

    He Ningjia

    2008-01-01

    Full Text Available Abstract Background The most abundant family of insect cuticular proteins, the CPR family, is recognized by the R&R Consensus, a domain of about 64 amino acids that binds to chitin and is present throughout arthropods. Several species have now been shown to have more than 100 CPR genes, inviting speculation as to the functional importance of this large number and diversity. Results We have identified 156 genes in Anopheles gambiae that code for putative cuticular proteins in this CPR family, over 1% of the total number of predicted genes in this species. Annotation was verified using several criteria including identification of TATA boxes, INRs, and DPEs plus support from proteomic and gene expression analyses. Two previously recognized CPR classes, RR-1 and RR-2, form separate, well-supported clades with the exception of a small set of genes with long branches whose relationships are poorly resolved. Several of these outliers have clear orthologs in other species. Although both clades are under purifying selection, the RR-1 variant of the R&R Consensus is evolving at twice the rate of the RR-2 variant and is structurally more labile. In contrast, the regions flanking the R&R Consensus have diversified in amino-acid composition to a much greater extent in RR-2 genes compared with RR-1 genes. Many genes are found in compact tandem arrays that may include similar or dissimilar genes but always include just one of the two classes. Tandem arrays of RR-2 genes frequently contain subsets of genes coding for highly similar proteins (sequence clusters. Properties of the proteins indicated that each cluster may serve a distinct function in the cuticle. Conclusion The complete annotation of this large gene family provides insight on the mechanisms of gene family evolution and clues about the need for so many CPR genes. These data also should assist annotation of other Anopheles genes.

  20. The structure and expression of the human neuroligin-3 gene.

    Science.gov (United States)

    Philibert, R A; Winfield, S L; Sandhu, H K; Martin, B M; Ginns, E I

    2000-04-04

    The neuroligins are a family of proteins that are thought to mediate cell to cell interactions between neurons. During the sequencing at an Xq13 locus associated with a mental retardation syndrome in some studies, we discovered a portion of the human orthologue of the rat neuroligin-3 gene. We now report the structure and the expression of that gene. The gene spans approximately 30kb and contains eight exons. Unlike the rat gene, it codes for at least two mRNAs and at least one of which is expressed outside the CNS. Interestingly, the putative promoter for the gene overlaps the last exon of the neighboring HOPA gene and is located less than 1kb from an OPA element in which a polymorphism associated with mental retardation is found. These findings suggest a possible role for the neuroligin gene in mental retardation and that the role of the gene in humans may differ from its role in rats.

  1. Improving the Caenorhabditis elegans genome annotation using machine learning.

    Directory of Open Access Journals (Sweden)

    Gunnar Rätsch

    2007-02-01

    Full Text Available For modern biology, precise genome annotations are of prime importance, as they allow the accurate definition of genic regions. We employ state-of-the-art machine learning methods to assay and improve the accuracy of the genome annotation of the nematode Caenorhabditis elegans. The proposed machine learning system is trained to recognize exons and introns on the unspliced mRNA, utilizing recent advances in support vector machines and label sequence learning. In 87% (coding and untranslated regions and 95% (coding regions only of all genes tested in several out-of-sample evaluations, our method correctly identified all exons and introns. Notably, only 37% and 50%, respectively, of the presently unconfirmed genes in the C. elegans genome annotation agree with our predictions, thus we hypothesize that a sizable fraction of those genes are not correctly annotated. A retrospective evaluation of the Wormbase WS120 annotation [] of C. elegans reveals that splice form predictions on unconfirmed genes in WS120 are inaccurate in about 18% of the considered cases, while our predictions deviate from the truth only in 10%-13%. We experimentally analyzed 20 controversial genes on which our system and the annotation disagree, confirming the superiority of our predictions. While our method correctly predicted 75% of those cases, the standard annotation was never completely correct. The accuracy of our system is further corroborated by a comparison with two other recently proposed systems that can be used for splice form prediction: SNAP and ExonHunter. We conclude that the genome annotation of C. elegans and other organisms can be greatly enhanced using modern machine learning technology.

  2. The DOE-JGI Standard Operating Procedure for the Annotations of the Microbial Genomes

    Energy Technology Data Exchange (ETDEWEB)

    Mavromatis, Konstantinos; Ivanova, Natalia; Chen, I-Min A.; Szeto, Ernest; Markowitz, Victor; Kyrpides, Nikos C.

    2009-05-20

    The DOE-JGI Microbial Annotation Pipeline (DOE-JGI MAP) supports gene prediction and/or functional annotation of microbial genomes towards comparative analysis with the Integrated Microbial Genome (IMG) system. DOE-JGI MAP annotation is applied on nucleotide sequence datasets included in the IMG-ER (Expert Review) version of IMG via the IMG ER submission site. Users can submit the sequence datasets consisting of one or more contigs in a multi-fasta file. DOE-JGI MAP annotation includes prediction of protein coding and RNA genes, as well as repeats and assignment of product names to these genes.

  3. Transcriptional dynamics of the developing sweet cherry (Prunus avium L.) fruit: sequencing, annotation and expression profiling of exocarp-associated genes

    OpenAIRE

    Merianne Alkio; Uwe Jonas; Myriam Declercq; Steven van Nocker; Moritz Knoche

    2014-01-01

    The exocarp, or skin, of fleshy fruit is a specialized tissue that protects the fruit, attracts seed dispersing fruit eaters, and has large economical relevance for fruit quality. Development of the exocarp involves regulated activities of many genes. This research analyzed global gene expression in the exocarp of developing sweet cherry (Prunus avium L., ‘Regina’), a fruit crop species with little public genomic resources. A catalog of transcript models (contigs) representing expressed genes...

  4. IntelliGO: a new vector-based semantic similarity measure including annotation origin

    Directory of Open Access Journals (Sweden)

    Devignes Marie-Dominique

    2010-12-01

    Full Text Available Abstract Background The Gene Ontology (GO is a well known controlled vocabulary describing the biological process, molecular function and cellular component aspects of gene annotation. It has become a widely used knowledge source in bioinformatics for annotating genes and measuring their semantic similarity. These measures generally involve the GO graph structure, the information content of GO aspects, or a combination of both. However, only a few of the semantic similarity measures described so far can handle GO annotations differently according to their origin (i.e. their evidence codes. Results We present here a new semantic similarity measure called IntelliGO which integrates several complementary properties in a novel vector space model. The coefficients associated with each GO term that annotates a given gene or protein include its information content as well as a customized value for each type of GO evidence code. The generalized cosine similarity measure, used for calculating the dot product between two vectors, has been rigorously adapted to the context of the GO graph. The IntelliGO similarity measure is tested on two benchmark datasets consisting of KEGG pathways and Pfam domains grouped as clans, considering the GO biological process and molecular function terms, respectively, for a total of 683 yeast and human genes and involving more than 67,900 pair-wise comparisons. The ability of the IntelliGO similarity measure to express the biological cohesion of sets of genes compares favourably to four existing similarity measures. For inter-set comparison, it consistently discriminates between distinct sets of genes. Furthermore, the IntelliGO similarity measure allows the influence of weights assigned to evidence codes to be checked. Finally, the results obtained with a complementary reference technique give intermediate but correct correlation values with the sequence similarity, Pfam, and Enzyme classifications when compared to

  5. Statistical mechanics of ontology based annotations

    CERN Document Server

    Hoyle, David C

    2016-01-01

    We present a statistical mechanical theory of the process of annotating an object with terms selected from an ontology. The term selection process is formulated as an ideal lattice gas model, but in a highly structured inhomogeneous field. The model enables us to explain patterns recently observed in real-world annotation data sets, in terms of the underlying graph structure of the ontology. By relating the external field strengths to the information content of each node in the ontology graph, the statistical mechanical model also allows us to propose a number of practical metrics for assessing the quality of both the ontology, and the annotations that arise from its use. Using the statistical mechanical formalism we also study an ensemble of ontologies of differing size and complexity; an analysis not readily performed using real data alone. Focusing on regular tree ontology graphs we uncover a rich set of scaling laws describing the growth in the optimal ontology size as the number of objects being annotate...

  6. Annotation of Regular Polysemy

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector

    Regular polysemy has received a lot of attention from the theory of lexical semantics and from computational linguistics. However, there is no consensus on how to represent the sense of underspecified examples at the token level, namely when annotating or disambiguating senses of metonymic words...... like “London” (Location/Organization) or “cup” (Container/Content). The goal of this dissertation is to assess whether metonymic sense underspecification justifies incorporating a third sense into our sense inventories, thereby treating the underspecified sense as independent from the literal...

  7. Comparative genomics of the relationship between gene structure and expression

    NARCIS (Netherlands)

    Ren, X.

    2006-01-01

    The relationship between the structure of genes and their expression is a relatively new aspect of genome organization and regulation. With more genome sequences and expression data becoming available, bioinformatics approaches can help the further elucidation of the relationships between gene struc

  8. Structure and in vitro transcription of human globin genes.

    Science.gov (United States)

    Proudfoot, N J; Shander, M H; Manley, J L; Gefter, M L; Maniatis, T

    1980-09-19

    The alpha-like and beta-like subunits of human hemoglobin are encoded by a small family of genes that are differentially expressed during development. Through the use of molecular cloning procedures, each member of this gene family has been isolated and extensively characterized. Although the alpha-like and beta-like globin genes are located on different chromosomes, both sets of genes are arranged in closely linked clusters. In both clusters, each of the genes is transcribed from the same DNA strand, and the genes are arranged in the order of their expressions during development. Structural comparisons of immediately adjacent genes within each cluster have provided evidence for the occurrence of gene duplication and correction during evolution and have led to the discovery of pseudogenes, genes that have acquired numerous mutations that prevent their normal expression. Recently, in vivo and in vitro systems for studying the expression of cloned eukaryotic genes have been developed as a means of identifying DNA sequences that are necessary for normal gene function. This article describes the application of an in vitro transcription procedure to the study of human globin gene expression.

  9. Modeling Three-Dimensional Chromosome Structures Using Gene Expression Data.

    Science.gov (United States)

    Xiao, Guanghua; Wang, Xinlei; Khodursky, Arkady B

    2011-03-01

    Recent genomic studies have shown that significant chromosomal spatial correlation exists in gene expression of many organisms. Interestingly, coexpression has been observed among genes separated by a fixed interval in specific regions of a chromosome chain, which is likely caused by three-dimensional (3D) chromosome folding structures. Modeling such spatial correlation explicitly may lead to essential understandings of 3D chromosome structures and their roles in transcriptional regulation. In this paper, we explore chromosomal spatial correlation induced by 3D chromosome structures, and propose a hierarchical Bayesian method based on helical structures to formally model and incorporate the correlation into the analysis of gene expression microarray data. It is the first study to quantify and infer 3D chromosome structures in vivo using expression microarrays. Simulation studies show computing feasibility of the proposed method and that, under the assumption of helical chromosome structures, it can lead to precise estimation of structural parameters and gene expression levels. Real data applications demonstrate an intriguing biological phenomenon that functionally associated genes, which are far apart along the chromosome chain, are brought into physical proximity by chromosomal folding in 3D space to facilitate their coexpression. It leads to important biological insight into relationship between chromosome structure and function.

  10. Suppression subtractive hybridization (SSH) combined with bioinformatics method: an integrated functional annotation approach for analysis of differentially expressed immune-genes in insects.

    Science.gov (United States)

    Badapanda, Chandan

    2013-01-01

    The suppression subtractive hybridization (SSH) approach, a PCR based approach which amplifies differentially expressed cDNAs (complementary DNAs), while simultaneously suppressing amplification of common cDNAs, was employed to identify immuneinducible genes in insects. This technique has been used as a suitable tool for experimental identification of novel genes in eukaryotes as well as prokaryotes; whose genomes have been sequenced, or the species whose genomes have yet to be sequenced. In this article, I have proposed a method for in silico functional characterization of immune-inducible genes from insects. Apart from immune-inducible genes from insects, this method can be applied for the analysis of genes from other species, starting from bacteria to plants and animals. This article is provided with a background of SSH-based method taking specific examples from innate immune-inducible genes in insects, and subsequently a bioinformatics pipeline is proposed for functional characterization of newly sequenced genes. The proposed workflow presented here, can also be applied for any newly sequenced species generated from Next Generation Sequencing (NGS) platforms.

  11. Predicting word sense annotation agreement

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector; Johannsen, Anders Trærup; Lopez de Lacalle, Oier

    2015-01-01

    High agreement is a common objective when annotating data for word senses. However, a number of factors make perfect agreement impossible, e.g. the limitations of the sense inventories, the difficulty of the examples or the interpretation preferences of the annotations. Estimating potential...... agreement is thus a relevant task to supplement the evaluation of sense annotations. In this article we propose two methods to predict agreement on word-annotation instances. We experiment with a continuous representation and a three-way discretization of observed agreement. In spite of the difficulty...

  12. MITOS: improved de novo metazoan mitochondrial genome annotation.

    Science.gov (United States)

    Bernt, Matthias; Donath, Alexander; Jühling, Frank; Externbrink, Fabian; Florentz, Catherine; Fritzsch, Guido; Pütz, Joern; Middendorf, Martin; Stadler, Peter F

    2013-11-01

    About 2000 completely sequenced mitochondrial genomes are available from the NCBI RefSeq data base together with manually curated annotations of their protein-coding genes, rRNAs, and tRNAs. This annotation information, which has accumulated over two decades, has been obtained with a diverse set of computational tools and annotation strategies. Despite all efforts of manual curation it is still plagued by misassignments of reading directions, erroneous gene names, and missing as well as false positive annotations in particular for the RNA genes. Taken together, this causes substantial problems for fully automatic pipelines that aim to use these data comprehensively for studies of animal phylogenetics and the molecular evolution of mitogenomes. The MITOS pipeline is designed to compute a consistent de novo annotation of the mitogenomic sequences. We show that the results of MITOS match RefSeq and MitoZoa in terms of annotation coverage and quality. At the same time we avoid biases, inconsistencies of nomenclature, and typos originating from manual curation strategies. The MITOS pipeline is accessible online at http://mitos.bioinf.uni-leipzig.de. Copyright © 2012 Elsevier Inc. All rights reserved.

  13. Phylogenetic molecular function annotation

    Science.gov (United States)

    Engelhardt, Barbara E.; Jordan, Michael I.; Repo, Susanna T.; Brenner, Steven E.

    2009-07-01

    It is now easier to discover thousands of protein sequences in a new microbial genome than it is to biochemically characterize the specific activity of a single protein of unknown function. The molecular functions of protein sequences have typically been predicted using homology-based computational methods, which rely on the principle that homologous proteins share a similar function. However, some protein families include groups of proteins with different molecular functions. A phylogenetic approach for predicting molecular function (sometimes called "phylogenomics") is an effective means to predict protein molecular function. These methods incorporate functional evidence from all members of a family that have functional characterizations using the evolutionary history of the protein family to make robust predictions for the uncharacterized proteins. However, they are often difficult to apply on a genome-wide scale because of the time-consuming step of reconstructing the phylogenies of each protein to be annotated. Our automated approach for function annotation using phylogeny, the SIFTER (Statistical Inference of Function Through Evolutionary Relationships) methodology, uses a statistical graphical model to compute the probabilities of molecular functions for unannotated proteins. Our benchmark tests showed that SIFTER provides accurate functional predictions on various protein families, outperforming other available methods.

  14. Structure and Function of Cytochrome P-450 Genes

    Science.gov (United States)

    1988-01-25

    UNIT Bolling Air Force Base, D.C. 20332 ELEMENT NO. NO. NO. ACCESSION NO. 61102F 2312 A5 11. TITLE (Include Security Clasification ) Structure and...chromatin structure of these genes and to characterize nuclear proteins that bind to the genes. Accesion For hRIS A-RA&I d OVIrC TAB LISUrc’t,:oimnc...nuclear proteins that bind to the genes. ........ .. A. RESEARCH OBJECTIVES The overall goal and the specific aims of this project remain the same as

  15. Graph-based sequence annotation using a data integration approach.

    Science.gov (United States)

    Pesch, Robert; Lysenko, Artem; Hindle, Matthew; Hassani-Pak, Keywan; Thiele, Ralf; Rawlings, Christopher; Köhler, Jacob; Taubert, Jan

    2008-08-25

    The automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara-Cyc) which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation. The methods and algorithms presented in this publication are an integral part of the ONDEX system which is freely available from http://ondex.sf.net/.

  16. Combined evidence annotation of transposable elements in genome sequences.

    Directory of Open Access Journals (Sweden)

    Hadi Quesneville

    2005-07-01

    Full Text Available Transposable elements (TEs are mobile, repetitive sequences that make up significant fractions of metazoan genomes. Despite their near ubiquity and importance in genome and chromosome biology, most efforts to annotate TEs in genome sequences rely on the results of a single computational program, RepeatMasker. In contrast, recent advances in gene annotation indicate that high-quality gene models can be produced from combining multiple independent sources of computational evidence. To elevate the quality of TE annotations to a level comparable to that of gene models, we have developed a combined evidence-model TE annotation pipeline, analogous to systems used for gene annotation, by integrating results from multiple homology-based and de novo TE identification methods. As proof of principle, we have annotated "TE models" in Drosophila melanogaster Release 4 genomic sequences using the combined computational evidence derived from RepeatMasker, BLASTER, TBLASTX, all-by-all BLASTN, RECON, TE-HMM and the previous Release 3.1 annotation. Our system is designed for use with the Apollo genome annotation tool, allowing automatic results to be curated manually to produce reliable annotations. The euchromatic TE fraction of D. melanogaster is now estimated at 5.3% (cf. 3.86% in Release 3.1, and we found a substantially higher number of TEs (n = 6,013 than previously identified (n = 1,572. Most of the new TEs derive from small fragments of a few hundred nucleotides long and highly abundant families not previously annotated (e.g., INE-1. We also estimated that 518 TE copies (8.6% are inserted into at least one other TE, forming a nest of elements. The pipeline allows rapid and thorough annotation of even the most complex TE models, including highly deleted and/or nested elements such as those often found in heterochromatic sequences. Our pipeline can be easily adapted to other genome sequences, such as those of the D. melanogaster heterochromatin or other

  17. Increased complexity of gene structure and base composition in vertebrates

    Institute of Scientific and Technical Information of China (English)

    Ying Wu; Huizhong Yuan; Shengjun Tan; Jian-Qun Chen; Dacheng Tian; Haiwang Yang

    2011-01-01

    How the structure and base composition of genes changed with the evolution of vertebrates remains a puzzling question. Here we analyzed 895 orthologous protein-coding genes in six multicellular animals: human, chicken, zebrafish, sea squirt, fruit fly, and worm. Our analyses reveal that many gene regions, particularly intron and 3' UTR, gradually expanded throughout the evolution of vertebrates from their invertebrate ancestors, and that the number of exons per gene increased. Studies based on all protein-coding genes in each genome provide consistent results.We also find that GC-content increased in many gene regions (especially 5' UTR) in the evolution of endotherms, except in coding-exons.Analysis of individual genomes shows that 3′ UTR demonstrated stronger length and CC-content correlation with intron than 5' UTR, and gene with large intron in all six species demonstrated relatively similar GC-content. Our data indicates a great increase in complexity in vertebrate genes and we propose that the requirement for morphological and functional changes is probably the driving force behind the evolution of structure and base composition complexity in multicellular animal genes.

  18. Challenges in Whole-Genome Annotation of Pyrosequenced Eukaryotic Genomes

    Energy Technology Data Exchange (ETDEWEB)

    Kuo, Alan; Grigoriev, Igor

    2009-04-17

    Pyrosequencing technologies such as 454/Roche and Solexa/Illumina vastly lower the cost of nucleotide sequencing compared to the traditional Sanger method, and thus promise to greatly expand the number of sequenced eukaryotic genomes. However, the new technologies also bring new challenges such as shorter reads and new kinds and higher rates of sequencing errors, which complicate genome assembly and gene prediction. At JGI we are deploying 454 technology for the sequencing and assembly of ever-larger eukaryotic genomes. Here we describe our first whole-genome annotation of a purely 454-sequenced fungal genome that is larger than a yeast (>30 Mbp). The pezizomycotine (filamentous ascomycote) Aspergillus carbonarius belongs to the Aspergillus section Nigri species complex, members of which are significant as platforms for bioenergy and bioindustrial technology, as members of soil microbial communities and players in the global carbon cycle, and as agricultural toxigens. Application of a modified version of the standard JGI Annotation Pipeline has so far predicted ~;;10k genes. ~;;12percent of these preliminary annotations suffer a potential frameshift error, which is somewhat higher than the ~;;9percent rate in the Sanger-sequenced and conventionally assembled and annotated genome of fellow Aspergillus section Nigri member A. niger. Also,>90percent of A. niger genes have potential homologs in the A. carbonarius preliminary annotation. Weconclude, and with further annotation and comparative analysis expect to confirm, that 454 sequencing strategies provide a promising substrate for annotation of modestly sized eukaryotic genomes. We will also present results of annotation of a number of other pyrosequenced fungal genomes of bioenergy interest.

  19. Automating Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

    2006-01-22

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  20. Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob; Hohimer, Ryan E.; White, Amanda M.

    2006-06-06

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  1. Applied bioinformatics: Genome annotation and transcriptome analysis

    DEFF Research Database (Denmark)

    Gupta, Vikas

    and dhurrin, which have not previously been characterized in blueberries. There are more than 44,500 spider species with distinct habitats and unique characteristics. Spiders are masters of producing silk webs to catch prey and using venom to neutralize. The exploration of the genetics behind these properties...... japonicus (Lotus), Vaccinium corymbosum (blueberry), Stegodyphus mimosarum (spider) and Trifolium occidentale (clover). From a bioinformatics data analysis perspective, my work can be divided into three parts; genome annotation, small RNA, and gene expression analysis. Lotus is a legume of significant...... has just started. We have assembled and annotated the first two spider genomes to facilitate our understanding of spiders at the molecular level. The need for analyzing the large and increasing amount of sequencing data has increased the demand for efficient, user friendly, and broadly applicable...

  2. Annotation in Digital Scholarly Editions

    NARCIS (Netherlands)

    Boot, P.; Haentjens Dekker, R.

    2016-01-01

    Annotation in digital scholarly editions (of historical documents, literary works, letters, etc.) has long been recognized as an important desideratum, but has also proven to be an elusive ideal. In so far as annotation functionality is available, it is usually developed for a single edition and

  3. Mesotext. Framing and exploring annotations

    NARCIS (Netherlands)

    Boot, P.; Boot, P.; Stronks, E.

    2007-01-01

    From the introduction: Annotation is an important item on the wish list for digital scholarly tools. It is one of John Unsworth’s primitives of scholarship (Unsworth 2000). Especially in linguistics,a number of tools have been developed that facilitate the creation of annotations to source material

  4. Mesotext. Framing and exploring annotations

    NARCIS (Netherlands)

    Boot, P.; Boot, P.; Stronks, E.

    2007-01-01

    From the introduction: Annotation is an important item on the wish list for digital scholarly tools. It is one of John Unsworth’s primitives of scholarship (Unsworth 2000). Especially in linguistics,a number of tools have been developed that facilitate the creation of annotations to source material

  5. Structural determination of Streptococcus pneumoniae repeat units in serotype 41A and 41F capsular polysaccharides to probe gene functions in the corresponding capsular biosynthetic loci.

    Science.gov (United States)

    Petersen, Bent O; Skovsted, Ian C; Paulsen, Berit Smestad; Redondo, Antonio R; Meier, Sebastian

    2014-12-05

    We report the repeating unit structures of the native capsular polysaccharides of Streptococcus pneumoniae serotypes 41A and 41F. Structural determinations yielded six carbohydrate units in the doubly branched repeating unit to give the following structure for serotype 41A: The structure determinations were motivated (1) by an ambition to help close the remaining gaps in S. pneumoniae capsular polysaccharide structures, and (2) by the attempt to derive functional annotations of carbohydrate active enzymes in the biosynthesis of bacterial polysaccharides from the determined structures. An activity present in 41F but not 41A is identified as an acetyltransferase acting on the rhamnopyranosyl sidechain E. The genes encoding the formation of the six glycosidic bonds in serogroup 41 were determined from the capsular polysaccharide structures of serotype 41A, 41F, and genetically related serotypes, in conjunction with corresponding genomic information and computational homology searches. In combination with complementary information, NMR spectroscopy considerably simplifies the functional annotation of carbohydrate active enzymes in the biosynthesis of bacterial polysaccharides.

  6. Genomic analyses with biofilter 2.0: knowledge driven filtering, annotation, and model development

    National Research Council Canada - National Science Library

    Pendergrass, Sarah A; Frase, Alex; Wallace, John; Wolfe, Daniel; Katiyar, Neerja; Moore, Carrie; Ritchie, Marylyn D

    2013-01-01

    .... We have now extensively revised and updated the multi-purpose software tool Biofilter that allows researchers to annotate and/or filter data as well as generate gene-gene interaction models based...

  7. Efficient assembly and annotation of the transcriptome of catfish by RNA-Seq analysis of a doubled haploid homozygote

    Directory of Open Access Journals (Sweden)

    Liu Shikai

    2012-11-01

    Full Text Available Abstract Background Upon the completion of whole genome sequencing, thorough genome annotation that associates genome sequences with biological meanings is essential. Genome annotation depends on the availability of transcript information as well as orthology information. In teleost fish, genome annotation is seriously hindered by genome duplication. Because of gene duplications, one cannot establish orthologies simply by homology comparisons. Rather intense phylogenetic analysis or structural analysis of orthologies is required for the identification of genes. To conduct phylogenetic analysis and orthology analysis, full-length transcripts are essential. Generation of large numbers of full-length transcripts using traditional transcript sequencing is very difficult and extremely costly. Results In this work, we took advantage of a doubled haploid catfish, which has two sets of identical chromosomes and in theory there should be no allelic variations. As such, transcript sequences generated from next-generation sequencing can be favorably assembled into full-length transcripts. Deep sequencing of the doubled haploid channel catfish transcriptome was performed using Illumina HiSeq 2000 platform, yielding over 300 million high-quality trimmed reads totaling 27 Gbp. Assembly of these reads generated 370,798 non-redundant transcript-derived contigs. Functional annotation of the assembly allowed identification of 25,144 unique protein-encoding genes. A total of 2,659 unique genes were identified as putative duplicated genes in the catfish genome because the assembly of the corresponding transcripts harbored PSVs or MSVs (in the form of pseudo-SNPs in the assembly. Of the 25,144 contigs with unique protein hits, around 20,000 contigs matched 50% length of reference proteins, and over 14,000 transcripts were identified as full-length with complete open reading frames. The characterization of consensus sequences surrounding start codon and the stop

  8. An analysis on the entity annotations in biological corpora.

    Science.gov (United States)

    Neves, Mariana

    2014-01-01

    Collection of documents annotated with semantic entities and relationships are crucial resources to support development and evaluation of text mining solutions for the biomedical domain. Here I present an overview of 36 corpora and show an analysis on the semantic annotations they contain. Annotations for entity types were classified into six semantic groups and an overview on the semantic entities which can be found in each corpus is shown. Results show that while some semantic entities, such as genes, proteins and chemicals are consistently annotated in many collections, corpora available for diseases, variations and mutations are still few, in spite of their importance in the biological domain.

  9. dcGOR: an R package for analysing ontologies and protein domain annotations.

    Directory of Open Access Journals (Sweden)

    Hai Fang

    2014-10-01

    Full Text Available I introduce an open-source R package 'dcGOR' to provide the bioinformatics community with the ease to analyse ontologies and protein domain annotations, particularly those in the dcGO database. The dcGO is a comprehensive resource for protein domain annotations using a panel of ontologies including Gene Ontology. Although increasing in popularity, this database needs statistical and graphical support to meet its full potential. Moreover, there are no bioinformatics tools specifically designed for domain ontology analysis. As an add-on package built in the R software environment, dcGOR offers a basic infrastructure with great flexibility and functionality. It implements new data structure to represent domains, ontologies, annotations, and all analytical outputs as well. For each ontology, it provides various mining facilities, including: (i domain-based enrichment analysis and visualisation; (ii construction of a domain (semantic similarity network according to ontology annotations; and (iii significance analysis for estimating a contact (statistical significance network. To reduce runtime, most analyses support high-performance parallel computing. Taking as inputs a list of protein domains of interest, the package is able to easily carry out in-depth analyses in terms of functional, phenotypic and diseased relevance, and network-level understanding. More importantly, dcGOR is designed to allow users to import and analyse their own ontologies and annotations on domains (taken from SCOP, Pfam and InterPro and RNAs (from Rfam as well. The package is freely available at CRAN for easy installation, and also at GitHub for version control. The dedicated website with reproducible demos can be found at http://supfam.org/dcGOR.

  10. dcGOR: an R package for analysing ontologies and protein domain annotations.

    Science.gov (United States)

    Fang, Hai

    2014-10-01

    I introduce an open-source R package 'dcGOR' to provide the bioinformatics community with the ease to analyse ontologies and protein domain annotations, particularly those in the dcGO database. The dcGO is a comprehensive resource for protein domain annotations using a panel of ontologies including Gene Ontology. Although increasing in popularity, this database needs statistical and graphical support to meet its full potential. Moreover, there are no bioinformatics tools specifically designed for domain ontology analysis. As an add-on package built in the R software environment, dcGOR offers a basic infrastructure with great flexibility and functionality. It implements new data structure to represent domains, ontologies, annotations, and all analytical outputs as well. For each ontology, it provides various mining facilities, including: (i) domain-based enrichment analysis and visualisation; (ii) construction of a domain (semantic similarity) network according to ontology annotations; and (iii) significance analysis for estimating a contact (statistical significance) network. To reduce runtime, most analyses support high-performance parallel computing. Taking as inputs a list of protein domains of interest, the package is able to easily carry out in-depth analyses in terms of functional, phenotypic and diseased relevance, and network-level understanding. More importantly, dcGOR is designed to allow users to import and analyse their own ontologies and annotations on domains (taken from SCOP, Pfam and InterPro) and RNAs (from Rfam) as well. The package is freely available at CRAN for easy installation, and also at GitHub for version control. The dedicated website with reproducible demos can be found at http://supfam.org/dcGOR.

  11. Semantic annotation of biological concepts interplaying microbial cellular responses

    Directory of Open Access Journals (Sweden)

    Carreira Rafael

    2011-11-01

    Full Text Available Abstract Background Automated extraction systems have become a time saving necessity in Systems Biology. Considerable human effort is needed to model, analyse and simulate biological networks. Thus, one of the challenges posed to Biomedical Text Mining tools is that of learning to recognise a wide variety of biological concepts with different functional roles to assist in these processes. Results Here, we present a novel corpus concerning the integrated cellular responses to nutrient starvation in the model-organism Escherichia coli. Our corpus is a unique resource in that it annotates biomedical concepts that play a functional role in expression, regulation and metabolism. Namely, it includes annotations for genetic information carriers (genes and DNA, RNA molecules, proteins (transcription factors, enzymes and transporters, small metabolites, physiological states and laboratory techniques. The corpus consists of 130 full-text papers with a total of 59043 annotations for 3649 different biomedical concepts; the two dominant classes are genes (highest number of unique concepts and compounds (most frequently annotated concepts, whereas other important cellular concepts such as proteins account for no more than 10% of the annotated concepts. Conclusions To the best of our knowledge, a corpus that details such a wide range of biological concepts has never been presented to the text mining community. The inter-annotator agreement statistics provide evidence of the importance of a consolidated background when dealing with such complex descriptions, the ambiguities naturally arising from the terminology and their impact for modelling purposes. Availability is granted for the full-text corpora of 130 freely accessible documents, the annotation scheme and the annotation guidelines. Also, we include a corpus of 340 abstracts.

  12. Structural basis of eukaryotic gene transcription.

    Science.gov (United States)

    Boeger, Hinrich; Bushnell, David A; Davis, Ralph; Griesenbeck, Joachim; Lorch, Yahli; Strattan, J Seth; Westover, Kenneth D; Kornberg, Roger D

    2005-02-07

    An RNA polymerase II promoter has been isolated in transcriptionally activated and repressed states. Topological and nuclease digestion analyses have revealed a dynamic equilibrium between nucleosome removal and reassembly upon transcriptional activation, and have further shown that nucleosomes are removed by eviction of histone octamers rather than by sliding. The promoter, once exposed, assembles with RNA polymerase II, general transcription factors, and Mediator in a approximately 3 MDa transcription initiation complex. X-ray crystallography has revealed the structure of RNA polymerase II, in the act of transcription, at atomic resolution. Extension of this analysis has shown how nucleotides undergo selection, polymerization, and eventual release from the transcribing complex. X-ray and electron crystallography have led to a picture of the entire transcription initiation complex, elucidating the mechanisms of promoter recognition, DNA unwinding, abortive initiation, and promoter escape.

  13. CATH FunFHMMer web server: protein functional annotations using functional family assignments.

    Science.gov (United States)

    Das, Sayoni; Sillitoe, Ian; Lee, David; Lees, Jonathan G; Dawson, Natalie L; Ward, John; Orengo, Christine A

    2015-07-01

    The widening function annotation gap in protein databases and the increasing number and diversity of the proteins being sequenced presents new challenges to protein function prediction methods. Multidomain proteins complicate the protein sequence-structure-function relationship further as new combinations of domains can expand the functional repertoire, creating new proteins and functions. Here, we present the FunFHMMer web server, which provides Gene Ontology (GO) annotations for query protein sequences based on the functional classification of the domain-based CATH-Gene3D resource. Our server also provides valuable information for the prediction of functional sites. The predictive power of FunFHMMer has been validated on a set of 95 proteins where FunFHMMer performs better than BLAST, Pfam and CDD. Recent validation by an independent international competition ranks FunFHMMer as one of the top function prediction methods in predicting GO annotations for both the Biological Process and Molecular Function Ontology. The FunFHMMer web server is available at http://www.cathdb.info/search/by_funfhmmer.

  14. FREQUENT STRUCTURE ALTERATIONS OF p53 GENE IN NASOPHARYNGEAL CARCINOMA

    Institute of Scientific and Technical Information of China (English)

    龙江斌; 区宝祥; 梁启万; 李辉梅

    1998-01-01

    By southern hybridization with 1.8 kb cDNA probe,a high freqnency (40.5%) of structural abnormality of p 53 gene was observed in primary nasopharyngeal carcinoma (NPC) biopsies. The regioas of exons 1 to 4 of the gene were examined by poiymerase chain reaction-single strand conformation polymorphism, no point nmtation was found. Because very low rate of point mutation had been reported in exons 5 to 8,we considered that structural ahnormality in the region of exons 1 to 8 of the gene might be uncommon in NPC. The speetrophotometer scaaning analysis of outoradiograms and rehybridization investigation of nitrocellulose filter with exon 11 probe indicated that most of structure aberrations we observed might be rearrangement occurring in exon ll.

  15. Comparison of concept recognizers for building the Open Biomedical Annotator

    Science.gov (United States)

    Shah, Nigam H; Bhatia, Nipun; Jonquet, Clement; Rubin, Daniel; Chiang, Annie P; Musen, Mark A

    2009-01-01

    The National Center for Biomedical Ontology (NCBO) is developing a system for automated, ontology-based access to online biomedical resources (Shah NH, et al.: Ontology-driven indexing of public datasets for translational bioinformatics. BMC Bioinformatics 2009, 10(Suppl 2):S1). The system's indexing workflow processes the text metadata of diverse resources such as datasets from GEO and ArrayExpress to annotate and index them with concepts from appropriate ontologies. This indexing requires the use of a concept-recognition tool to identify ontology concepts in the resource's textual metadata. In this paper, we present a comparison of two concept recognizers – NLM's MetaMap and the University of Michigan's Mgrep. We utilize a number of data sources and dictionaries to evaluate the concept recognizers in terms of precision, recall, speed of execution, scalability and customizability. Our evaluations demonstrate that Mgrep has a clear edge over MetaMap for large-scale service oriented applications. Based on our analysis we also suggest areas of potential improvements for Mgrep. We have subsequently used Mgrep to build the Open Biomedical Annotator service. The Annotator service has access to a large dictionary of biomedical terms derived from the United Medical Language System (UMLS) and NCBO ontologies. The Annotator also leverages the hierarchical structure of the ontologies and their mappings to expand annotations. The Annotator service is available to the community as a REST Web service for creating ontology-based annotations of their data. PMID:19761568

  16. Semantator: Annotating Clinical Narratives with Semantic Web Ontologies

    OpenAIRE

    Song, Dezhao; Chute, Christopher G; Tao, Cui

    2012-01-01

    To facilitate clinical research, clinical data needs to be stored in a machine processable and understandable way. Manual annotating clinical data is time consuming. Automatic approaches (e.g., Natural Language Processing systems) have been adopted to convert such data into structured formats; however, the quality of such automatically extracted data may not always be satisfying. In this paper, we propose Semantator, a semi-automatic tool for document annotation with Semantic Web ontologies. ...

  17. Genes for the Major Structural Components of Thermotogales Species' Togas Revealed by Proteomic and Evolutionary Analyses of OmpA and OmpB Homologs

    Energy Technology Data Exchange (ETDEWEB)

    Petrus, Amanda K. [Univ. of Connecticut, Storrs, CT (United States); Swithers, Kristen S. [Univ. of Connecticut, Storrs, CT (United States); Ranjit, Chaman R. [Univ. of Connecticut, Storrs, CT (United States); Wu, Si [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Brewer, Heather M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gogarten, J. Peter [Univ. of Connecticut, Storrs, CT (United States); Pasa-Tolic, Ljiljana [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Noll, Kenneth M. [Univ. of Connecticut, Storrs, CT (United States)

    2012-06-29

    The unifying structural characteristic of members of the bacterial order Thermotogales is an unusual cell envelope that includes a loose-fitting sheath around each cell, often called a toga. Only two toga-associated structural proteins have been identified in Thermotoga maritima: the anchor protein OmpA1 (previously termed Ompα) and the porin OmpB (previously termed Ompβ). The gene encoding OmpA (ompA1) was assigned in the genome sequence to TM0477, but because no peptide sequence was available for OmpB, its gene (ompB) was not annotated. Here we identify the ompB gene as TM0476, determined by LC/MS/MS analysis of the native OmpB protein purified from T. maritima cells. The purified OmpB had β-sheet secondary structure as determined by circular dichroism. Analysis of the sequence of ompB product shows it has porin characteristics including a carboxy terminus anchoring motif and a porin-specific amino acid composition. Orthologs of ompB were found in the genomes of some, but not all, Thermotogales. Those without orthologs have putative analogs. Phylogenetic analyses of OmpA1 revealed that each species of the Thermotogales has one to three OmpA homologs. T. maritima has two OmpA homologs, encoded by ompA1(TM0477) and ompA2 (TM1729), both of which were found in the toga protein-enriched cell extracts. These annotations of the genes encoding toga structural proteins will guide future examinations of the structure and function of this unusual lineage-defining cell sheath.

  18. Comparative Omics-Driven Genome Annotation Refinement: Application across Yersiniae

    Energy Technology Data Exchange (ETDEWEB)

    Rutledge, Alexandra C.; Jones, Marcus B.; Chauhan, Sadhana; Purvine, Samuel O.; Sanford, James; Monroe, Matthew E.; Brewer, Heather M.; Payne, Samuel H.; Ansong, Charles; Frank, Bryan C.; Smith, Richard D.; Peterson, Scott; Motin, Vladimir L.; Adkins, Joshua N.

    2012-03-27

    Genome sequencing continues to be a rapidly evolving technology, yet most downstream aspects of genome annotation pipelines remain relatively stable or are even being abandoned. To date, the perceived value of manual curation for genome annotations is not offset by the real cost and time associated with the process. In order to balance the large number of sequences generated, the annotation process is now performed almost exclusively in an automated fashion for most genome sequencing projects. One possible way to reduce errors inherent to automated computational annotations is to apply data from 'omics' measurements (i.e. transcriptional and proteomic) to the un-annotated genome with a proteogenomic-based approach. This approach does require additional experimental and bioinformatics methods to include omics technologies; however, the approach is readily automatable and can benefit from rapid developments occurring in those research domains as well. The annotation process can be improved by experimental validation of transcription and translation and aid in the discovery of annotation errors. Here the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species, as is becoming common in sequencing efforts. Transcriptomic and proteomic data derived from three highly similar pathogenic Yersiniae (Y. pestis CO92, Y. pestis pestoides F, and Y. pseudotuberculosis PB1/+) was used to demonstrate a comprehensive comparative omic-based annotation methodology. Peptide and oligo measurements experimentally validated the expression of nearly 40% of each strain's predicted proteome and revealed the identification of 28 novel and 68 previously incorrect protein-coding sequences (e.g., observed frameshifts, extended start sites, and translated pseudogenes) within the three current Yersinia genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent

  19. GLANET: genomic loci annotation and enrichment tool.

    Science.gov (United States)

    Otlu, Burçak; Firtina, Can; Keles, Sündüz; Tastan, Oznur

    2017-09-15

    Genomic studies identify genomic loci representing genetic variations, transcription factor (TF) occupancy, or histone modification through next generation sequencing (NGS) technologies. Interpreting these loci requires evaluating them with known genomic and epigenomic annotations. We present GLANET as a comprehensive annotation and enrichment analysis tool which implements a sampling-based enrichment test that accounts for GC content and/or mappability biases, jointly or separately. GLANET annotates and performs enrichment analysis on these loci with a rich library. We introduce and perform novel data-driven computational experiments for assessing the power and Type-I error of its enrichment procedure which show that GLANET has attained high statistical power and well-controlled Type-I error rate. As a key feature, users can easily extend its library with new gene sets and genomic intervals. Other key features include assessment of impact of single nucleotide variants (SNPs) on TF binding sites and regulation based pathway enrichment analysis. GLANET can be run using its GUI or on command line. GLANET's source code is available at https://github.com/burcakotlu/GLANET . Tutorials are provided at https://glanet.readthedocs.org . burcak@ceng.metu.edu.tr or oznur.tastan@cs.bilkent.edu.tr. Supplementary data are available at Bioinformatics online.

  20. Jannovar: a java library for exome annotation.

    Science.gov (United States)

    Jäger, Marten; Wang, Kai; Bauer, Sebastian; Smedley, Damian; Krawitz, Peter; Robinson, Peter N

    2014-05-01

    Transcript-based annotation and pedigree analysis are two basic steps in the computational analysis of whole-exome sequencing experiments in genetic diagnostics and disease-gene discovery projects. Here, we present Jannovar, a stand-alone Java application as well as a Java library designed to be used in larger software frameworks for exome and genome analysis. Jannovar uses an interval tree to identify all transcripts affected by a given variant, and provides Human Genome Variation Society-compliant annotations both for variants affecting coding sequences and splice junctions as well as untranslated regions and noncoding RNA transcripts. Jannovar can also perform family-based pedigree analysis with Variant Call Format (VCF) files with data from members of a family segregating a Mendelian disorder. Using a desktop computer, Jannovar requires a few seconds to annotate a typical VCF file with exome data. Jannovar is freely available under the BSD2 license. Source code as well as the Java application and library file can be downloaded from http://compbio.charite.de (with tutorial) and https://github.com/charite/jannovar. © 2014 WILEY PERIODICALS, INC.

  1. Sentiment Analysis of Document Based on Annotation

    CERN Document Server

    Shukla, Archana

    2011-01-01

    I present a tool which tells the quality of document or its usefulness based on annotations. Annotation may include comments, notes, observation, highlights, underline, explanation, question or help etc. comments are used for evaluative purpose while others are used for summarization or for expansion also. Further these comments may be on another annotation. Such annotations are referred as meta-annotation. All annotation may not get equal weightage. My tool considered highlights, underline as well as comments to infer the collective sentiment of annotators. Collective sentiments of annotators are classified as positive, negative, objectivity. My tool computes collective sentiment of annotations in two manners. It counts all the annotation present on the documents as well as it also computes sentiment scores of all annotation which includes comments to obtain the collective sentiments about the document or to judge the quality of document. I demonstrate the use of tool on research paper.

  2. Comparison of muscle transcriptome between pigs with divergent meat quality phenotypes identifies genes related to muscle metabolism and structure.

    Directory of Open Access Journals (Sweden)

    Marie Damon

    Full Text Available BACKGROUND: Meat quality depends on physiological processes taking place in muscle tissue, which could involve a large pattern of genes associated with both muscle structural and metabolic features. Understanding the biological phenomena underlying muscle phenotype at slaughter is necessary to uncover meat quality development. Therefore, a muscle transcriptome analysis was undertaken to compare gene expression profiles between two highly contrasted pig breeds, Large White (LW and Basque (B, reared in two different housing systems themselves influencing meat quality. LW is the most predominant breed used in pig industry, which exhibits standard meat quality attributes. B is an indigenous breed with low lean meat and high fat contents, high meat quality characteristics, and is genetically distant from other European pig breeds. METHODOLOGY/PRINCIPAL FINDINGS: Transcriptome analysis undertaken using a custom 15 K microarray, highlighted 1233 genes differentially expressed between breeds (multiple-test adjusted P-value<0.05, out of which 635 were highly expressed in the B and 598 highly expressed in the LW pigs. No difference in gene expression was found between housing systems. Besides, expression level of 12 differentially expressed genes quantified by real-time RT-PCR validated microarray data. Functional annotation clustering emphasized four main clusters associated to transcriptome breed differences: metabolic processes, skeletal muscle structure and organization, extracellular matrix, lysosome, and proteolysis, thereby highlighting many genes involved in muscle physiology and meat quality development. CONCLUSIONS/SIGNIFICANCE: Altogether, these results will contribute to a better understanding of muscle physiology and of the biological and molecular processes underlying meat quality. Besides, this study is a first step towards the identification of molecular markers of pork quality and the subsequent development of control tools.

  3. Effects of Link Annotations on Search Performance in Layered and Unlayered Hierarchically Organized Information Spaces.

    Science.gov (United States)

    Fraser, Landon; Locatis, Craig

    2001-01-01

    Investigated the effects of link annotations on high school user search performance in Web hypertext environments having deep (layered) and shallow link structures. Results confirmed previous research that shallow link structures are better than deep (layered) link structures, and also showed that annotations had virtually no effect on search…

  4. A Strategy Combining Higher Energy C-Trap Dissociation with Neutral Loss- and Product Ion-Based MSn Acquisition for Global Profiling and Structure Annotation of Fatty Acids Conjugates

    Science.gov (United States)

    Bi, Qi-rui; Hou, Jin-jun; Yang, Min; Shen, Yao; Qi, Peng; Feng, Rui-hong; Dai, Zhuo; Yan, Bing-peng; Wang, Jian-wei; Shi, Xiao-jian; Wu, Wan-ying; Guo, De-an

    2016-12-01

    Fatty acids conjugates (FACs) are ubiquitous but found in trace amounts in the natural world. They are composed of multiple unknown substructures and side chains. Thus, FACs are difficult to be analyzed by traditional mass spectrometric methods. In this study, an integrated strategy was developed to global profiling and targeted structure annotation of FACs in complex matrix by LTQ Orbitrap. Dicarboxylic acid conjugated bufotoxins (DACBs) in Venenum bufonis (VB) were used as model compounds. The new strategy (abbreviated as HPNA) combined higher-energy C-trap dissociation (HCD) with product ion- (PI), neutral loss- (NL) based MSn (n ≥ 3) acquisition in both positive-ion mode and negative-ion mode. Several advantages are presented. First, various side chains were found under HCD in negative-ion mode, which included both known and unknown side chains. Second, DACBs with multiple side chains were simultaneously detected in one run. Compared with traditional quadrupole-based mass method, it greatly increased analysis throughput. Third, the fragment ions of side chain and steroids substructure could be obtained by PI- and NL-based MSn acquisition, respectively, which greatly increased the accuracy of the structure annotation of DACBs. In all, 78 DACBs have been discovered, of which 68 were new compounds; 25 types of substructure formulas and seven dicarboxylic acid side chains were found, especially five new side chains, including two saturated dicarboxylic acids [(azelaic acid (C9) and sebacic acid (C10)] and three unsaturated dicarboxylic acids (u-C8, u-C9, and u-C10). All these results greatly enriched the structures of DACBs in VB.

  5. A Strategy Combining Higher Energy C-Trap Dissociation with Neutral Loss- and Product Ion-Based MSn Acquisition for Global Profiling and Structure Annotation of Fatty Acids Conjugates

    Science.gov (United States)

    Bi, Qi-rui; Hou, Jin-jun; Yang, Min; Shen, Yao; Qi, Peng; Feng, Rui-hong; Dai, Zhuo; Yan, Bing-peng; Wang, Jian-wei; Shi, Xiao-jian; Wu, Wan-ying; Guo, De-an

    2017-03-01

    Fatty acids conjugates (FACs) are ubiquitous but found in trace amounts in the natural world. They are composed of multiple unknown substructures and side chains. Thus, FACs are difficult to be analyzed by traditional mass spectrometric methods. In this study, an integrated strategy was developed to global profiling and targeted structure annotation of FACs in complex matrix by LTQ Orbitrap. Dicarboxylic acid conjugated bufotoxins (DACBs) in Venenum bufonis (VB) were used as model compounds. The new strategy (abbreviated as HPNA) combined higher-energy C-trap dissociation (HCD) with product ion- (PI), neutral loss- (NL) based MSn (n ≥ 3) acquisition in both positive-ion mode and negative-ion mode. Several advantages are presented. First, various side chains were found under HCD in negative-ion mode, which included both known and unknown side chains. Second, DACBs with multiple side chains were simultaneously detected in one run. Compared with traditional quadrupole-based mass method, it greatly increased analysis throughput. Third, the fragment ions of side chain and steroids substructure could be obtained by PI- and NL-based MSn acquisition, respectively, which greatly increased the accuracy of the structure annotation of DACBs. In all, 78 DACBs have been discovered, of which 68 were new compounds; 25 types of substructure formulas and seven dicarboxylic acid side chains were found, especially five new side chains, including two saturated dicarboxylic acids [(azelaic acid (C9) and sebacic acid (C10)] and three unsaturated dicarboxylic acids (u-C8, u-C9, and u-C10). All these results greatly enriched the structures of DACBs in VB.

  6. A Strategy Combining Higher Energy C-Trap Dissociation with Neutral Loss- and Product Ion-Based MS(n) Acquisition for Global Profiling and Structure Annotation of Fatty Acids Conjugates.

    Science.gov (United States)

    Bi, Qi-Rui; Hou, Jin-Jun; Yang, Min; Shen, Yao; Qi, Peng; Feng, Rui-Hong; Dai, Zhuo; Yan, Bing-Peng; Wang, Jian-Wei; Shi, Xiao-Jian; Wu, Wan-Ying; Guo, De-An

    2017-03-01

    Fatty acids conjugates (FACs) are ubiquitous but found in trace amounts in the natural world. They are composed of multiple unknown substructures and side chains. Thus, FACs are difficult to be analyzed by traditional mass spectrometric methods. In this study, an integrated strategy was developed to global profiling and targeted structure annotation of FACs in complex matrix by LTQ Orbitrap. Dicarboxylic acid conjugated bufotoxins (DACBs) in Venenum bufonis (VB) were used as model compounds. The new strategy (abbreviated as HPNA) combined higher-energy C-trap dissociation (HCD) with product ion- (PI), neutral loss- (NL) based MS(n) (n ≥ 3) acquisition in both positive-ion mode and negative-ion mode. Several advantages are presented. First, various side chains were found under HCD in negative-ion mode, which included both known and unknown side chains. Second, DACBs with multiple side chains were simultaneously detected in one run. Compared with traditional quadrupole-based mass method, it greatly increased analysis throughput. Third, the fragment ions of side chain and steroids substructure could be obtained by PI- and NL-based MS(n) acquisition, respectively, which greatly increased the accuracy of the structure annotation of DACBs. In all, 78 DACBs have been discovered, of which 68 were new compounds; 25 types of substructure formulas and seven dicarboxylic acid side chains were found, especially five new side chains, including two saturated dicarboxylic acids [(azelaic acid (C9) and sebacic acid (C10)] and three unsaturated dicarboxylic acids (u-C8, u-C9, and u-C10). All these results greatly enriched the structures of DACBs in VB. Graphical Abstract ᅟ.

  7. IMG ER: A System for Microbial Genome Annotation Expert Review and Curation

    Energy Technology Data Exchange (ETDEWEB)

    Markowitz, Victor M.; Mavromatis, Konstantinos; Ivanova, Natalia N.; Chen, I-Min A.; Chu, Ken; Kyrpides, Nikos C.

    2009-05-25

    A rapidly increasing number of microbial genomes are sequenced by organizations worldwide and are eventually included into various public genome data resources. The quality of the annotations depends largely on the original dataset providers, with erroneous or incomplete annotations often carried over into the public resources and difficult to correct. We have developed an Expert Review (ER) version of the Integrated Microbial Genomes (IMG) system, with the goal of supporting systematic and efficient revision of microbial genome annotations. IMG ER provides tools for the review and curation of annotations of both new and publicly available microbial genomes within IMG's rich integrated genome framework. New genome datasets are included into IMG ER prior to their public release either with their native annotations or with annotations generated by IMG ER's annotation pipeline. IMG ER tools allow addressing annotation problems detected with IMG's comparative analysis tools, such as genes missed by gene prediction pipelines or genes without an associated function. Over the past year, IMG ER was used for improving the annotations of about 150 microbial genomes.

  8. Exploiting Social Annotation for Automatic Resource Discovery

    CERN Document Server

    Plangprasopchok, Anon

    2007-01-01

    Information integration applications, such as mediators or mashups, that require access to information resources currently rely on users manually discovering and integrating them in the application. Manual resource discovery is a slow process, requiring the user to sift through results obtained via keyword-based search. Although search methods have advanced to include evidence from document contents, its metadata and the contents and link structure of the referring pages, they still do not adequately cover information sources -- often called ``the hidden Web''-- that dynamically generate documents in response to a query. The recently popular social bookmarking sites, which allow users to annotate and share metadata about various information sources, provide rich evidence for resource discovery. In this paper, we describe a probabilistic model of the user annotation process in a social bookmarking system del.icio.us. We then use the model to automatically find resources relevant to a particular information dom...

  9. Cognition inspired framework for indoor scene annotation

    Science.gov (United States)

    Ye, Zhipeng; Liu, Peng; Zhao, Wei; Tang, Xianglong

    2015-09-01

    We present a simple yet effective scene annotation framework based on a combination of bag-of-visual words (BoVW), three-dimensional scene structure estimation, scene context, and cognitive theory. From a macroperspective, the proposed cognition-based hybrid motivation framework divides the annotation problem into empirical inference and real-time classification. Inspired by the inference ability of human beings, common objects of indoor scenes are defined for experience-based inference, while in the real-time classification stage, an improved BoVW-based multilayer abstract semantics labeling method is proposed by introducing abstract semantic hierarchies to narrow the semantic gap and improve the performance of object categorization. The proposed framework was evaluated on a variety of common data sets and experimental results proved its effectiveness.

  10. MimoSA: a system for minimotif annotation

    Directory of Open Access Journals (Sweden)

    Kundeti Vamsi

    2010-06-01

    Full Text Available Abstract Background Minimotifs are short peptide sequences within one protein, which are recognized by other proteins or molecules. While there are now several minimotif databases, they are incomplete. There are reports of many minimotifs in the primary literature, which have yet to be annotated, while entirely novel minimotifs continue to be published on a weekly basis. Our recently proposed function and sequence syntax for minimotifs enables us to build a general tool that will facilitate structured annotation and management of minimotif data from the biomedical literature. Results We have built the MimoSA application for minimotif annotation. The application supports management of the Minimotif Miner database, literature tracking, and annotation of new minimotifs. MimoSA enables the visualization, organization, selection and editing functions of minimotifs and their attributes in the MnM database. For the literature components, Mimosa provides paper status tracking and scoring of papers for annotation through a freely available machine learning approach, which is based on word correlation. The paper scoring algorithm is also available as a separate program, TextMine. Form-driven annotation of minimotif attributes enables entry of new minimotifs into the MnM database. Several supporting features increase the efficiency of annotation. The layered architecture of MimoSA allows for extensibility by separating the functions of paper scoring, minimotif visualization, and database management. MimoSA is readily adaptable to other annotation efforts that manually curate literature into a MySQL database. Conclusions MimoSA is an extensible application that facilitates minimotif annotation and integrates with the Minimotif Miner database. We have built MimoSA as an application that integrates dynamic abstract scoring with a high performance relational model of minimotif syntax. MimoSA's TextMine, an efficient paper-scoring algorithm, can be used to

  11. Towards Annotopia—Enabling the Semantic Interoperability of Web-Based Annotations

    Directory of Open Access Journals (Sweden)

    Anna Gerber

    2012-08-01

    Full Text Available This paper describes the results of a collaborative effort that has reconciled the Open Annotation Collaboration (OAC ontology and the Annotation Ontology (AO to produce a merged data model [the Open Annotation (OA data model] to describe Web-based annotations—and hence facilitate the discovery, sharing and re-use of such annotations. Using a number of case studies that include digital scholarly editing, 3D museum artifacts and sensor data streams, we evaluate the OA model’s capabilities. We also describe our implementation of an online annotation server that supports the storage, search and retrieval of OA-compliant annotations across multiple applications and disciplines. Finally we discuss outstanding problem issues associated with the OA ontology, and the impact that certain design decisions have had on the efficient storage, indexing, search and retrieval of complex structured annotations.

  12. Expressed Peptide Tags: An additional layer of data for genome annotation

    Energy Technology Data Exchange (ETDEWEB)

    Savidor, Alon [ORNL; Donahoo, Ryan S [ORNL; Hurtado-Gonzales, Oscar [University of Tennessee, Knoxville (UTK); Verberkmoes, Nathan C [ORNL; Shah, Manesh B [ORNL; Lamour, Kurt H [ORNL; McDonald, W Hayes [ORNL

    2006-01-01

    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 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 sub-databases 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 ~77% of Phytophthora EPTs supported the current annotation, a portion of them (7.2% and 12.6% 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.

  13. Semantic annotation of medical images

    Science.gov (United States)

    Seifert, Sascha; Kelm, Michael; Moeller, Manuel; Mukherjee, Saikat; Cavallaro, Alexander; Huber, Martin; Comaniciu, Dorin

    2010-03-01

    Diagnosis and treatment planning for patients can be significantly improved by comparing with clinical images of other patients with similar anatomical and pathological characteristics. This requires the images to be annotated using common vocabulary from clinical ontologies. Current approaches to such annotation are typically manual, consuming extensive clinician time, and cannot be scaled to large amounts of imaging data in hospitals. On the other hand, automated image analysis while being very scalable do not leverage standardized semantics and thus cannot be used across specific applications. In our work, we describe an automated and context-sensitive workflow based on an image parsing system complemented by an ontology-based context-sensitive annotation tool. An unique characteristic of our framework is that it brings together the diverse paradigms of machine learning based image analysis and ontology based modeling for accurate and scalable semantic image annotation.

  14. Publication Production: An Annotated Bibliography.

    Science.gov (United States)

    Firman, Anthony H.

    1994-01-01

    Offers brief annotations of 52 articles and papers on document production (from the Society for Technical Communication's journal and proceedings) on 9 topics: information processing, document design, using color, typography, tables, illustrations, photography, printing and binding, and production management. (SR)

  15. AutoFACT: An Automatic Functional Annotation and Classification Tool