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Sample records for functional gene annotation

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

    PubMed

    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.

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

    PubMed

    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.

  3. Functional annotation of rare gene aberration drivers of pancreatic cancer

    PubMed Central

    Tsang, Yiu Huen; Dogruluk, Turgut; Tedeschi, Philip M.; Wardwell-Ozgo, Joanna; Lu, Hengyu; Espitia, Maribel; Nair, Nikitha; Minelli, Rosalba; Chong, Zechen; Chen, Fengju; Chang, Qing Edward; Dennison, Jennifer B.; Dogruluk, Armel; Li, Min; Ying, Haoqiang; Bertino, Joseph R.; Gingras, Marie-Claude; Ittmann, Michael; Kerrigan, John; Chen, Ken; Creighton, Chad J.; Eterovic, Karina; Mills, Gordon B.; Scott, Kenneth L.

    2016-01-01

    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). This approach reveals oncogenic activity for rare gene aberrations in genes including NAD Kinase (NADK), which regulates NADP(H) homeostasis and cellular redox state. We further validate mutant NADK, whose expression provides gain-of-function enzymatic activity leading to a reduction in cellular reactive oxygen species and tumorigenesis, and show that depletion of wild-type NADK in PDAC cell lines attenuates cancer cell growth in vitro and in vivo. These data indicate that annotating rare aberrations can reveal important cancer signalling pathways representing additional therapeutic targets. PMID:26806015

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

    DOE PAGES

    Peng, Jiajie; Uygun, Sahra; Kim, Taehyong; ...

    2015-02-14

    Background: 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. Results: 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 demonstratemore » 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. Conclusions: 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.« less

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

    SciTech Connect

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

    2015-02-14

    Background: 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. Results: 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. Conclusions: 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.

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

    PubMed Central

    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

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

    PubMed Central

    Hu, Yang; Zhou, Wenyang; Ren, Jun; Dong, Lixiang

    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. PMID:27635398

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

    PubMed

    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.

  9. Phylogenetic-based propagation of functional annotations within the Gene Ontology consortium.

    PubMed

    Gaudet, Pascale; Livstone, Michael S; Lewis, Suzanna E; Thomas, Paul D

    2011-09-01

    The goal of the Gene Ontology (GO) project is to provide a uniform way to describe the functions of gene products from organisms across all kingdoms of life and thereby enable analysis of genomic data. Protein annotations are either based on experiments or predicted from protein sequences. Since most sequences have not been experimentally characterized, most available annotations need to be based on predictions. To make as accurate inferences as possible, the GO Consortium's Reference Genome Project is using an explicit evolutionary framework to infer annotations of proteins from a broad set of genomes from experimental annotations in a semi-automated manner. Most components in the pipeline, such as selection of sequences, building multiple sequence alignments and phylogenetic trees, retrieving experimental annotations and depositing inferred annotations, are fully automated. However, the most crucial step in our pipeline relies on software-assisted curation by an expert biologist. This curation tool, Phylogenetic Annotation and INference Tool (PAINT) helps curators to infer annotations among members of a protein family. PAINT allows curators to make precise assertions as to when functions were gained and lost during evolution and record the evidence (e.g. experimentally supported GO annotations and phylogenetic information including orthology) for those assertions. In this article, we describe how we use PAINT to infer protein function in a phylogenetic context with emphasis on its strengths, limitations and guidelines. We also discuss specific examples showing how PAINT annotations compare with those generated by other highly used homology-based methods.

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

    PubMed Central

    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.

    2009-01-01

    Hypothetical (HyP) and conserved HyP genes account for >30% of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved HyP (9.5%) along with 887 HyP genes (24.4%). 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 HyP 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. One thousand two hundred and twelve 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. PMID:19293273

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

    SciTech Connect

    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.

  12. Algal functional annotation tool

    SciTech Connect

    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 on KEGG

  13. Evaluating Computational Gene Ontology Annotations.

    PubMed

    Škunca, Nives; Roberts, Richard J; Steffen, Martin

    2017-01-01

    Two avenues to understanding gene function are complementary and often overlapping: experimental work and computational prediction. While experimental annotation generally produces high-quality annotations, it is low throughput. Conversely, computational annotations have broad coverage, but the quality of annotations may be variable, and therefore evaluating the quality of computational annotations is a critical concern.In this chapter, we provide an overview of strategies to evaluate the quality of computational annotations. First, we discuss why evaluating quality in this setting is not trivial. We highlight the various issues that threaten to bias the evaluation of computational annotations, most of which stem from the incompleteness of biological databases. Second, we discuss solutions that address these issues, for example, targeted selection of new experimental annotations and leveraging the existing experimental annotations.

  14. Visual annotation display (VLAD): a tool for finding functional themes in lists of genes.

    PubMed

    Richardson, Joel E; Bult, Carol J

    2015-10-01

    Experiments that employ genome scale technology platforms frequently result in lists of tens to thousands of genes with potential significance to a specific biological process or disease. Searching for biologically relevant connections among the genes or gene products in these lists is a common data analysis task. We have implemented a software application for uncovering functional themes in sets of genes based on their annotations to bio-ontologies, such as the gene ontology and the mammalian phenotype ontology. The application, called VisuaL Annotation Display (VLAD), performs a statistical analysis to test for the enrichment of ontology terms in a set of genes submitted by a researcher. The results for each analysis using VLAD includes a table of ontology terms, sorted in decreasing order of significance. Each row contains the term, statistics such as the number of annotated terms, the p value, etc., and the symbols of annotated genes. An accompanying graphical display shows portions of the ontology hierarchy, where node sizes are scaled based on p values. Although numerous ontology term enrichment programs already exist, VLAD is unique in that it allows users to upload their own annotation files and ontologies for customized term enrichment analyses, supports the analysis of multiple gene sets at once, provides interfaces to customize graphical output, and is tightly integrated with functional and biological details about mouse genes in the Mouse Genome Informatics (MGI) database. VLAD is available as a web-based application from the MGI web site (http://proto.informatics.jax.org/prototypes/vlad/).

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

    PubMed Central

    2011-01-01

    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 on KEGG pathway maps

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

    PubMed

    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.

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

    PubMed Central

    D'Eustachio, Peter; Smith, Jennifer R.; Zampetaki, Anna

    2016-01-01

    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). PMID:26917558

  18. Comparative analysis of grapevine whole-genome gene predictions, functional annotation, categorization and integration of the predicted gene sequences

    PubMed Central

    2012-01-01

    Background The first draft assembly and gene prediction of the grapevine genome (8X base coverage) was made available to the scientific community in 2007, and functional annotation was developed on this gene prediction. Since then additional Sanger sequences were added to the 8X sequences pool and a new version of the genomic sequence with superior base coverage (12X) was produced. Results In order to more efficiently annotate the function of the genes predicted in the new assembly, it is important to build on as much of the previous work as possible, by transferring 8X annotation of the genome to the 12X version. The 8X and 12X assemblies and gene predictions of the grapevine genome were compared to answer the question, “Can we uniquely map 8X predicted genes to 12X predicted genes?” The results show that while the assemblies and gene structure predictions are too different to make a complete mapping between them, most genes (18,725) showed a one-to-one relationship between 8X predicted genes and the last version of 12X predicted genes. In addition, reshuffled genomic sequence structures appeared. These highlight regions of the genome where the gene predictions need to be taken with caution. Based on the new grapevine gene functional annotation and in-depth functional categorization, twenty eight new molecular networks have been created for VitisNet while the existing networks were updated. Conclusions The outcomes of this study provide a functional annotation of the 12X genes, an update of VitisNet, the system of the grapevine molecular networks, and a new functional categorization of genes. Data are available at the VitisNet website (http://www.sdstate.edu/ps/research/vitis/pathways.cfm). PMID:22554261

  19. Expression profiling and functional annotation of noncoding genes across 11 distinct organs in rat development

    PubMed Central

    Wen, Zhuo; Chen, Geng; Zhu, Sibo; Zhu, Jinhang; Li, Bin; Song, Yunjie; Li, Suqing; Shi, Leming; Zheng, Yuanting; Li, Menglong

    2016-01-01

    Accumulating evidence suggests that noncoding RNAs (ncRNAs) have important regulatory functions. However, lacking of functional annotations for ncRNAs hampered us from carrying out the subsequent functional or predictive research. Here we dissected the expression profiles of 3,458 rat noncoding genes using rat bodymap RNA-sequencing data consisting of 11 solid organs over four developmental stages (juvenile, adolescent, adult and aged) from both sexes, and conducted a comprehensive analysis of differentially expressed noncoding genes (DEnGs) between various conditions. We then constructed a co-expression network between protein-coding and noncoding genes to infer biological functions of noncoding genes. Modules of interest were linked to online databases including DAVID for functional annotation and pathway analysis. Our results indicated that noncoding genes are functionally enriched through pathways similar to those of protein-coding genes. Terms about development of the immune system were enriched with genes from age-related modules, whereas terms about sexual reproduction were enriched with genes in sex-related modules. We also built connection networks on some significant modules to visualize the interactions and regulatory relationship between protein-coding and noncoding genes. Our study could improve our understanding and facilitate a deeper investigation on organ/age/sex-related regulatory events of noncoding genes, which may lead to a superior preclinical model for drug development and translational medicine. PMID:27934932

  20. Annotation of plant gene function via combined genomics, metabolomics and informatics.

    PubMed

    Tohge, Takayuki; Fernie, Alisdair R

    2012-06-17

    Given the ever expanding number of model plant species for which complete genome sequences are available and the abundance of bio-resources such as knockout mutants, wild accessions and advanced breeding populations, there is a rising burden for gene functional annotation. In this protocol, annotation of plant gene function using combined co-expression gene analysis, metabolomics and informatics is provided (Figure 1). This approach is based on the theory of using target genes of known function to allow the identification of non-annotated genes likely to be involved in a certain metabolic process, with the identification of target compounds via metabolomics. Strategies are put forward for applying this information on populations generated by both forward and reverse genetics approaches in spite of none of these are effortless. By corollary this approach can also be used as an approach to characterise unknown peaks representing new or specific secondary metabolites in the limited tissues, plant species or stress treatment, which is currently the important trial to understanding plant metabolism.

  1. Assigning biological functions to rice genes by genome annotation, expression analysis and mutagenesis.

    PubMed

    Jiang, Shu-Ye; Ramachandran, Srinivasan

    2010-12-01

    Rice is the first cereal genome to be completely sequenced. Since the completion of its genome sequencing, considerable progress has been made in multiple areas including the whole genome annotation, gene expression profiling, mutant collection, etc. Here, we summarize the current status of rice genome annotation and review the methodology of assigning biological functions to hundreds of thousands of rice genes as well as discuss the major limitations and the future perspective in rice functional genomics. Available data analysis shows that the rice genome encodes around 32,000 protein-coding genes. Expression analysis revealed at least 31,000 genes with expression evidence from full-length cDNA/EST collection or other transcript profiling. In addition, we have summarized various strategies to generate mutant population including natural, physical, chemical, T-DNA, transposon/retrotransposon or gene silencing based mutagenesis. Currently, more than 1 million of mutants have been generated and 27,551 of them have their flanking sequence tags. To assign biological functions to hundreds of thousands of rice genes, global co-operations are required, various genetic resources should be more easily accessible and diverse data from transcriptomics, proteomics, epigenetics, comparative genomics and bioinformatics should be integrated to better understand the functions of these genes and their regulatory mechanisms.

  2. Curation of the genome annotation of Pichia pastoris (Komagataella phaffii) CBS7435 from gene level to protein function.

    PubMed

    Valli, Minoska; Tatto, Nadine E; Peymann, Armin; Gruber, Clemens; Landes, Nils; Ekker, Heinz; Thallinger, Gerhard G; Mattanovich, Diethard; Gasser, Brigitte; Graf, Alexandra B

    2016-09-01

    As manually curated and non-automated BLAST analysis of the published Pichia pastoris genome sequences revealed many differences between the gene annotations of the strains GS115 and CBS7435, RNA-Seq analysis, supported by proteomics, was performed to improve the genome annotation. Detailed analysis of sequence alignment and protein domain predictions were made to extend the functional genome annotation to all P. pastoris sequences. This allowed the identification of 492 new ORFs, 4916 hypothetical UTRs and the correction of 341 incorrect ORF predictions, which were mainly due to the presence of upstream ATG or erroneous intron predictions. Moreover, 175 previously erroneously annotated ORFs need to be removed from the annotation. In total, we have annotated 5325 ORFs. Regarding the functionality of those genes, we improved all gene and protein descriptions. Thereby, the percentage of ORFs with functional annotation was increased from 48% to 73%. Furthermore, we defined functional groups, covering 25 biological cellular processes of interest, by grouping all genes that are part of the defined process. All data are presented in the newly launched genome browser and database available at www.pichiagenome.org In summary, we present a wide spectrum of curation of the P. pastoris genome annotation from gene level to protein function.

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

    SciTech Connect

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

    2009-03-17

    Hypothetical (HyP) and conserved HyP genes account for >30% of sequenced bacterial genomes. For the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough, 347 of the 3634 genes were annotated as conserved HyP (9.5%) along with 887 HyP genes (24.4%). 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 HyP 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. One thousand two hundred and twelve of these genes were transcribed with 786 producing detectable proteins. There was no evidence for expression of 17 predicted genes.

  4. Quality of computationally inferred gene ontology annotations.

    PubMed

    Skunca, Nives; Altenhoff, Adrian; Dessimoz, Christophe

    2012-05-01

    Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon-an important outcome given that >98% of all annotations are inferred without direct curation.

  5. Genome, Functional Gene Annotation, and Nuclear Transformation of the Heterokont Oleaginous Alga Nannochloropsis oceanica CCMP1779

    PubMed Central

    Tsai, Chia-Hong; Bullard, Blair; Cornish, Adam J.; Harvey, Christopher; Reca, Ida-Barbara; Thornburg, Chelsea; Achawanantakun, Rujira; Buehl, Christopher J.; Campbell, Michael S.; Cavalier, David; Childs, Kevin L.; Clark, Teresa J.; Deshpande, Rahul; Erickson, Erika; Armenia Ferguson, Ann; Handee, Witawas; Kong, Que; Li, Xiaobo; Liu, Bensheng; Lundback, Steven; Peng, Cheng; Roston, Rebecca L.; Sanjaya; Simpson, Jeffrey P.; TerBush, Allan; Warakanont, Jaruswan; Zäuner, Simone; Farre, Eva M.; Hegg, Eric L.; Jiang, Ning; Kuo, Min-Hao; Lu, Yan; Niyogi, Krishna K.; Ohlrogge, John; Osteryoung, Katherine W.; Shachar-Hill, Yair; Sears, Barbara B.; Sun, Yanni; Takahashi, Hideki; Yandell, Mark; Shiu, Shin-Han; Benning, Christoph

    2012-01-01

    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 species by a growing

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

    PubMed

    Vieler, Astrid; Wu, Guangxi; Tsai, Chia-Hong; Bullard, Blair; Cornish, Adam J; Harvey, Christopher; Reca, Ida-Barbara; Thornburg, Chelsea; Achawanantakun, Rujira; Buehl, Christopher J; Campbell, Michael S; Cavalier, David; Childs, Kevin L; Clark, Teresa J; Deshpande, Rahul; Erickson, Erika; Armenia Ferguson, Ann; Handee, Witawas; Kong, Que; Li, Xiaobo; Liu, Bensheng; Lundback, Steven; Peng, Cheng; Roston, Rebecca L; Sanjaya; Simpson, Jeffrey P; Terbush, Allan; Warakanont, Jaruswan; Zäuner, Simone; Farre, Eva M; Hegg, Eric L; Jiang, Ning; Kuo, Min-Hao; Lu, Yan; Niyogi, Krishna K; Ohlrogge, John; Osteryoung, Katherine W; Shachar-Hill, Yair; Sears, Barbara B; Sun, Yanni; Takahashi, Hideki; Yandell, Mark; Shiu, Shin-Han; Benning, Christoph

    2012-01-01

    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 species by a growing

  7. Gene Ontology annotations and resources.

    PubMed

    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.

  8. Integrating biological knowledge based on functional annotations for biclustering of gene expression data.

    PubMed

    Nepomuceno, Juan A; Troncoso, Alicia; Nepomuceno-Chamorro, Isabel A; Aguilar-Ruiz, Jesús S

    2015-05-01

    Gene expression data analysis is based on the assumption that co-expressed genes imply co-regulated genes. This assumption is being reformulated because the co-expression of a group of genes may be the result of an independent activation with respect to the same experimental condition and not due to the same regulatory regime. For this reason, traditional techniques are recently being improved with the use of prior biological knowledge from open-access repositories together with gene expression data. Biclustering is an unsupervised machine learning technique that searches patterns in gene expression data matrices. A scatter search-based biclustering algorithm that integrates biological information is proposed in this paper. In addition to the gene expression data matrix, the input of the algorithm is only a direct annotation file that relates each gene to a set of terms from a biological repository where genes are annotated. Two different biological measures, FracGO and SimNTO, are proposed to integrate this information by means of its addition to-be-optimized fitness function in the scatter search scheme. The measure FracGO is based on the biological enrichment and SimNTO is based on the overlapping among GO annotations of pairs of genes. Experimental results evaluate the proposed algorithm for two datasets and show the algorithm performs better when biological knowledge is integrated. Moreover, the analysis and comparison between the two different biological measures is presented and it is concluded that the differences depend on both the data source and how the annotation file has been built in the case GO is used. It is also shown that the proposed algorithm obtains a greater number of enriched biclusters than other classical biclustering algorithms typically used as benchmark and an analysis of the overlapping among biclusters reveals that the biclusters obtained present a low overlapping. The proposed methodology is a general-purpose algorithm which allows

  9. The Saccharomyces Genome Database: Gene Product Annotation of Function, Process, and Component.

    PubMed

    Cherry, J Michael

    2015-12-02

    An ontology is a highly structured form of controlled vocabulary. Each entry in the ontology is commonly called a term. These terms are used when talking about an annotation. However, each term has a definition that, like the definition of a word found within a dictionary, provides the complete usage and detailed explanation of the term. It is critical to consult a term's definition because the distinction between terms can be subtle. The use of ontologies in biology started as a way of unifying communication between scientific communities and to provide a standard dictionary for different topics, including molecular functions, biological processes, mutant phenotypes, chemical properties and structures. The creation of ontology terms and their definitions often requires debate to reach agreement but the result has been a unified descriptive language used to communicate knowledge. In addition to terms and definitions, ontologies require a relationship used to define the type of connection between terms. In an ontology, a term can have more than one parent term, the term above it in an ontology, as well as more than one child, the term below it in the ontology. Many ontologies are used to construct annotations in the Saccharomyces Genome Database (SGD), as in all modern biological databases; however, Gene Ontology (GO), a descriptive system used to categorize gene function, is the most extensively used ontology in SGD annotations. Examples included in this protocol illustrate the structure and features of this ontology.

  10. Gene Ontology Annotations and Resources

    PubMed Central

    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. PMID:23161678

  11. Insyght: navigating amongst abundant homologues, syntenies and gene functional annotations in bacteria, it's that symbol!

    PubMed Central

    Lacroix, Thomas; Loux, Valentin; Gendrault, Annie; Hoebeke, Mark; Gibrat, Jean-François

    2014-01-01

    High-throughput techniques have considerably increased the potential of comparative genomics whilst simultaneously posing many new challenges. One of those challenges involves efficiently mining the large amount of data produced and exploring the landscape of both conserved and idiosyncratic genomic regions across multiple genomes. Domains of application of these analyses are diverse: identification of evolutionary events, inference of gene functions, detection of niche-specific genes or phylogenetic profiling. Insyght is a comparative genomic visualization tool that combines three complementary displays: (i) a table for thoroughly browsing amongst homologues, (ii) a comparator of orthologue functional annotations and (iii) a genomic organization view designed to improve the legibility of rearrangements and distinctive loci. The latter display combines symbolic and proportional graphical paradigms. Synchronized navigation across multiple species and interoperability between the views are core features of Insyght. A gene filter mechanism is provided that helps the user to build a biologically relevant gene set according to multiple criteria such as presence/absence of homologues and/or various annotations. We illustrate the use of Insyght with scenarios. Currently, only Bacteria and Archaea are supported. A public instance is available at http://genome.jouy.inra.fr/Insyght. The tool is freely downloadable for private data set analysis. PMID:25249626

  12. Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes

    PubMed Central

    Feuermann, Marc; Gaudet, Pascale; Mi, Huaiyu; Lewis, Suzanna E.; Thomas, Paul D.

    2016-01-01

    We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This ‘GO Phylogenetic Annotation’ approach integrates GO annotations from evolutionarily related genes across ∼100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations. Database URL: http://amigo.geneontology.org/amigo PMID:28025345

  13. Discovering gene functional relationships using FAUN (Feature Annotation Using Nonnegative matrix factorization)

    PubMed Central

    2010-01-01

    Background Searching the enormous amount of information available in biomedical literature to extract novel functional relationships among genes remains a challenge in the field of bioinformatics. While numerous (software) tools have been developed to extract and identify gene relationships from biological databases, few effectively deal with extracting new (or implied) gene relationships, a process which is useful in interpretation of discovery-oriented genome-wide experiments. Results In this study, we develop a Web-based bioinformatics software environment called FAUN or Feature Annotation Using Nonnegative matrix factorization (NMF) to facilitate both the discovery and classification of functional relationships among genes. Both the computational complexity and parameterization of NMF for processing gene sets are discussed. FAUN is tested on three manually constructed gene document collections. Its utility and performance as a knowledge discovery tool is demonstrated using a set of genes associated with Autism. Conclusions FAUN not only assists researchers to use biomedical literature efficiently, but also provides utilities for knowledge discovery. This Web-based software environment may be useful for the validation and analysis of functional associations in gene subsets identified by high-throughput experiments. PMID:20946597

  14. Computational algorithms to predict Gene Ontology annotations

    PubMed Central

    2015-01-01

    Background Gene function annotations, which are associations between a gene and a term of a controlled vocabulary describing gene functional features, are of paramount importance in modern biology. Datasets of these annotations, such as the ones provided by the Gene Ontology Consortium, are used to design novel biological experiments and interpret their results. Despite their importance, these sources of information have some known issues. They are incomplete, since biological knowledge is far from being definitive and it rapidly evolves, and some erroneous annotations may be present. Since the curation process of novel annotations is a costly procedure, both in economical and time terms, computational tools that can reliably predict likely annotations, and thus quicken the discovery of new gene annotations, are very useful. Methods We used a set of computational algorithms and weighting schemes to infer novel gene annotations from a set of known ones. We used the latent semantic analysis approach, implementing two popular algorithms (Latent Semantic Indexing and Probabilistic Latent Semantic Analysis) and propose a novel method, the Semantic IMproved Latent Semantic Analysis, which adds a clustering step on the set of considered genes. Furthermore, we propose the improvement of these algorithms by weighting the annotations in the input set. Results We tested our methods and their weighted variants on the Gene Ontology annotation sets of three model organism genes (Bos taurus, Danio rerio and Drosophila melanogaster ). The methods showed their ability in predicting novel gene annotations and the weighting procedures demonstrated to lead to a valuable improvement, although the obtained results vary according to the dimension of the input annotation set and the considered algorithm. Conclusions Out of the three considered methods, the Semantic IMproved Latent Semantic Analysis is the one that provides better results. In particular, when coupled with a proper

  15. WNP: A Novel Algorithm for Gene Products Annotation from Weighted Functional Networks

    PubMed Central

    Magi, Alberto; Tattini, Lorenzo; Benelli, Matteo; Giusti, Betti; Abbate, Rosanna; Ruffo, Stefano

    2012-01-01

    Predicting the biological function of all the genes of an organism is one of the fundamental goals of computational system biology. In the last decade, high-throughput experimental methods for studying the functional interactions between gene products (GPs) have been combined with computational approaches based on Bayesian networks for data integration. The result of these computational approaches is an interaction network with weighted links representing connectivity likelihood between two functionally related GPs. The weighted network generated by these computational approaches can be used to predict annotations for functionally uncharacterized GPs. Here we introduce Weighted Network Predictor (WNP), a novel algorithm for function prediction of biologically uncharacterized GPs. Tests conducted on simulated data show that WNP outperforms other 5 state-of-the-art methods in terms of both specificity and sensitivity and that it is able to better exploit and propagate the functional and topological information of the network. We apply our method to Saccharomyces cerevisiae yeast and Arabidopsis thaliana networks and we predict Gene Ontology function for about 500 and 10000 uncharacterized GPs respectively. PMID:22761703

  16. On the Use of Gene Ontology Annotations to Assess Functional Similarity among Orthologs and Paralogs: A Short Report.

    PubMed

    Thomas, Paul D; Wood, Valerie; Mungall, Christopher J; Lewis, Suzanna E; Blake, Judith A

    2012-01-01

    A recent paper (Nehrt et al., PLoS Comput. Biol. 7:e1002073, 2011) has proposed a metric for the "functional similarity" between two genes that uses only the Gene Ontology (GO) annotations directly derived from published experimental results. Applying this metric, the authors concluded that paralogous genes within the mouse genome or the human genome are more functionally similar on average than orthologous genes between these genomes, an unexpected result with broad implications if true. We suggest, based on both theoretical and empirical considerations, that this proposed metric should not be interpreted as a functional similarity, and therefore cannot be used to support any conclusions about the "ortholog conjecture" (or, more properly, the "ortholog functional conservation hypothesis"). First, we reexamine the case studies presented by Nehrt et al. as examples of orthologs with divergent functions, and come to a very different conclusion: they actually exemplify how GO annotations for orthologous genes provide complementary information about conserved biological functions. We then show that there is a global ascertainment bias in the experiment-based GO annotations for human and mouse genes: particular types of experiments tend to be performed in different model organisms. We conclude that the reported statistical differences in annotations between pairs of orthologous genes do not reflect differences in biological function, but rather complementarity in experimental approaches. Our results underscore two general considerations for researchers proposing novel types of analysis based on the GO: 1) that GO annotations are often incomplete, potentially in a biased manner, and subject to an "open world assumption" (absence of an annotation does not imply absence of a function), and 2) that conclusions drawn from a novel, large-scale GO analysis should whenever possible be supported by careful, in-depth examination of examples, to help ensure the conclusions have a

  17. First survey and functional annotation of prohormone and convertase genes in the pig

    PubMed Central

    2012-01-01

    Background The pig is a biomedical model to study human and livestock traits. Many of these traits are controlled by neuropeptides that result from the cleavage of prohormones by prohormone convertases. Only 45 prohormones have been confirmed in the pig. Sequence homology can be ineffective to annotate prohormone genes in sequenced species like the pig due to the multifactorial nature of the prohormone processing. The goal of this study is to undertake the first complete survey of prohormone and prohormone convertases genes in the pig genome. These genes were functionally annotated based on 35 gene expression microarray experiments. The cleavage sites of prohormone sequences into potentially active neuropeptides were predicted. Results We identified 95 unique prohormone genes, 2 alternative calcitonin-related sequences, 8 prohormone convertases and 1 cleavage facilitator in the pig genome 10.2 assembly and trace archives. Of these, 11 pig prohormone genes have not been reported in the UniProt, UniGene or Gene databases. These genes are intermedin, cortistatin, insulin-like 5, orexigenic neuropeptide QRFP, prokineticin 2, prolactin-releasing peptide, parathyroid hormone 2, urocortin, urocortin 2, urocortin 3, and urotensin 2-related peptide. In addition, a novel neuropeptide S was identified in the pig genome correcting the previously reported pig sequence that is identical to the rabbit sequence. Most differentially expressed prohormone genes were under-expressed in pigs experiencing immune challenge relative to the un-challenged controls, in non-pregnant relative to pregnant sows, in old relative to young embryos, and in non-neural relative to neural tissues. The cleavage prediction based on human sequences had the best performance with a correct classification rate of cleaved and non-cleaved sites of 92% suggesting that the processing of prohormones in pigs is similar to humans. The cleavage prediction models did not find conclusive evidence supporting the

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

    PubMed Central

    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 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 (N)PE 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. PMID:23028713

  19. Commonality of functional annotation: a method for prioritization of candidate genes from genome-wide linkage studies†

    PubMed Central

    Shriner, Daniel; Baye, Tesfaye M.; Padilla, Miguel A.; Zhang, Shiju; Vaughan, Laura K.; Loraine, Ann E.

    2008-01-01

    Linkage studies of complex traits frequently yield multiple linkage regions covering hundreds of genes. Testing each candidate gene from every region is prohibitively expensive and computational methods that simplify this process would benefit genetic research. We present a new method based on commonality of functional annotation (CFA) that aids dissection of complex traits for which multiple causal genes act in a single pathway or process. CFA works by testing individual Gene Ontology (GO) terms for enrichment among candidate gene pools, performs multiple hypothesis testing adjustment using an estimate of independent tests based on correlation of GO terms, and then scores and ranks genes annotated with significantly-enriched terms based on the number of quantitative trait loci regions in which genes bearing those annotations appear. We evaluate CFA using simulated linkage data and show that CFA has good power despite being conservative. We apply CFA to published linkage studies investigating age-of-onset of Alzheimer's disease and body mass index and obtain previously known and new candidate genes. CFA provides a new tool for studies in which causal genes are expected to participate in a common pathway or process and can easily be extended to utilize annotation schemes in addition to the GO. PMID:18263617

  20. The Ensembl gene annotation system

    PubMed Central

    Aken, Bronwen L.; Ayling, Sarah; Barrell, Daniel; Clarke, Laura; Curwen, Valery; Fairley, Susan; Fernandez Banet, Julio; Billis, Konstantinos; García Girón, Carlos; Hourlier, Thibaut; Howe, Kevin; Kähäri, Andreas; Kokocinski, Felix; Martin, Fergal J.; Murphy, Daniel N.; Nag, Rishi; Ruffier, Magali; Schuster, Michael; Tang, Y. Amy; Vogel, Jan-Hinnerk; White, Simon; Zadissa, Amonida; Flicek, Paul

    2016-01-01

    The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail. Database URL: http://www.ensembl.org/index.html PMID:27337980

  1. Phylogenetic molecular function annotation

    NASA Astrophysics Data System (ADS)

    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.

  2. Phylogenetic molecular function annotation

    PubMed Central

    Engelhardt, Barbara E; Jordan, Michael I; Repo, Susanna T; Brenner, Steven E

    2010-01-01

    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. PMID:20664722

  3. Comparison of Functional Gene Annotation of Toxascaris leonina and Toxocara canis using CLC Genomics Workbench

    PubMed Central

    Kim, Ki Uk; Park, Sang Kyun; Kang, Shin Ae; Park, Mi Kyung; Cho, Min Kyoung; Jung, Ho-jin; Kim, Kyung-Yun

    2013-01-01

    The ascarids, Toxocara canis and Toxascaris leonina, are probably the most common gastrointestinal helminths encountered in dogs. In order to understand biological differences of 2 ascarids, we analyzed gene expression profiles of female adults of T. canis and T. leonina using CLC Genomics Workbench, and the results were compared with those of free-living nematode Caenorhabditis elegans. A total of 2,880 and 7,949 ESTs were collected from T. leonina and T. canis, respectively. The length of ESTs ranged from 106 to 4,637 bp with an average insert size of 820 bp. Overall, our results showed that most functional gene annotations of 2 ascarids were quite similar to each other in 3 major categories, i.e., cellular component, biological process, and molecular function. Although some different transcript expression categories were found, the distance was short and it was not enough to explain their different lifestyles. However, we found distinguished transcript differences between ascarid parasites and free-living nematodes. Understanding evolutionary genetic changes might be helpful for studies of the lifestyle and evolution of parasites. PMID:24327777

  4. Comparison of functional gene annotation of Toxascaris leonina and Toxocara canis using CLC genomics workbench.

    PubMed

    Kim, Ki Uk; Park, Sang Kyun; Kang, Shin Ae; Park, Mi Kyung; Cho, Min Kyoung; Jung, Ho-Jin; Kim, Kyung-Yun; Yu, Hak Sun

    2013-10-01

    The ascarids, Toxocara canis and Toxascaris leonina, are probably the most common gastrointestinal helminths encountered in dogs. In order to understand biological differences of 2 ascarids, we analyzed gene expression profiles of female adults of T. canis and T. leonina using CLC Genomics Workbench, and the results were compared with those of free-living nematode Caenorhabditis elegans. A total of 2,880 and 7,949 ESTs were collected from T. leonina and T. canis, respectively. The length of ESTs ranged from 106 to 4,637 bp with an average insert size of 820 bp. Overall, our results showed that most functional gene annotations of 2 ascarids were quite similar to each other in 3 major categories, i.e., cellular component, biological process, and molecular function. Although some different transcript expression categories were found, the distance was short and it was not enough to explain their different lifestyles. However, we found distinguished transcript differences between ascarid parasites and free-living nematodes. Understanding evolutionary genetic changes might be helpful for studies of the lifestyle and evolution of parasites.

  5. Human cell adhesion molecules: annotated functional subtypes and overrepresentation of addiction-associated genes

    PubMed Central

    Zhong, Xiaoming; Drgonova, Jana; Li, Chuan-Yun; Uhl, George R.

    2015-01-01

    Human cell adhesion molecules (CAMs) are essential both for a) proper development, modulation and maintenance of interactions between cells and for b) cell-to-cell (and matrix-to-cell) communication about these interactions. CAMs are thus key to proper development and plasticity of organs and tissues that include the brain. Despite recognition of the existence of these dual CAM roles and appreciation of the differential functional significance of these roles, there have been surprisingly few systematic studies that have carefully enumerated the universe of CAMs, identified the preferred roles for specific CAMs in distinct types of cellular connections and communication, or related these issues to specific brain disorders or brain circuits. In this paper, we substantially update and review the set of human genes that are likely to encode CAMs based on searches of databases, literature reviews and annotations. We describe the likely CAMs and the functional CAM subclasses into which they fall. These include “iCAMs”, whose contacts largely mediate cell to cell communication, those involved in focal adhesions, CAM genes whose products are preferentially involved with stereotyped and morphologically-identifiable connections between cells (adherens junctions, gap junctions) and smaller numbers of genes in other classes. We discuss a novel proposed mechanism involving selective anchoring of the constituents of iCAM-containing lipid rafts in zones of close neuronal apposition to membranes expressing binding partners of these iCAMs. CAM data from genetic and genomic studies of addiction in humans and mouse models provide examples of the ways in which CAM variation is likely to contribute to a specific brain-based disorder. We discuss how differences in CAM splicing mediated by differences in the addiction-associated splicing regulator RBFOX1/A2BP1 could enrich this picture. CAM expression in dopamine neurons provides one of the ways in which variations in cell adhesion

  6. Quality of Computationally Inferred Gene Ontology Annotations

    PubMed Central

    Škunca, Nives; Altenhoff, Adrian; Dessimoz, Christophe

    2012-01-01

    Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon—an important outcome given that >98% of all annotations are inferred without direct curation. PMID:22693439

  7. PFP: Automated prediction of gene ontology functional annotations with confidence scores using protein sequence data.

    PubMed

    Hawkins, Troy; Chitale, Meghana; Luban, Stanislav; Kihara, Daisuke

    2009-02-15

    Protein function prediction is a central problem in bioinformatics, increasing in importance recently due to the rapid accumulation of biological data awaiting interpretation. Sequence data represents the bulk of this new stock and is the obvious target for consideration as input, as newly sequenced organisms often lack any other type of biological characterization. We have previously introduced PFP (Protein Function Prediction) as our sequence-based predictor of Gene Ontology (GO) functional terms. PFP interprets the results of a PSI-BLAST search by extracting and scoring individual functional attributes, searching a wide range of E-value sequence matches, and utilizing conventional data mining techniques to fill in missing information. We have shown it to be effective in predicting both specific and low-resolution functional attributes when sufficient data is unavailable. Here we describe (1) significant improvements to the PFP infrastructure, including the addition of prediction significance and confidence scores, (2) a thorough benchmark of performance and comparisons to other related prediction methods, and (3) applications of PFP predictions to genome-scale data. We applied PFP predictions to uncharacterized protein sequences from 15 organisms. Among these sequences, 60-90% could be annotated with a GO molecular function term at high confidence (>or=80%). We also applied our predictions to the protein-protein interaction network of the Malaria plasmodium (Plasmodium falciparum). High confidence GO biological process predictions (>or=90%) from PFP increased the number of fully enriched interactions in this dataset from 23% of interactions to 94%. Our benchmark comparison shows significant performance improvement of PFP relative to GOtcha, InterProScan, and PSI-BLAST predictions. This is consistent with the performance of PFP as the overall best predictor in both the AFP-SIG '05 and CASP7 function (FN) assessments. PFP is available as a web service at http://dragon.bio.purdue.edu/pfp/.

  8. Gene and alternative splicing annotation with AIR

    PubMed Central

    Florea, Liliana; Di Francesco, Valentina; Miller, Jason; Turner, Russell; Yao, Alison; Harris, Michael; Walenz, Brian; Mobarry, Clark; Merkulov, Gennady V.; Charlab, Rosane; Dew, Ian; Deng, Zuoming; Istrail, Sorin; Li, Peter; Sutton, Granger

    2005-01-01

    Designing effective and accurate tools for identifying the functional and structural elements in a genome remains at the frontier of genome annotation owing to incompleteness and inaccuracy of the data, limitations in the computational models, and shifting paradigms in genomics, such as alternative splicing. We present a methodology for the automated annotation of genes and their alternatively spliced mRNA transcripts based on existing cDNA and protein sequence evidence from the same species or projected from a related species using syntenic mapping information. At the core of the method is the splice graph, a compact representation of a gene, its exons, introns, and alternatively spliced isoforms. The putative transcripts are enumerated from the graph and assigned confidence scores based on the strength of sequence evidence, and a subset of the high-scoring candidates are selected and promoted into the annotation. The method is highly selective, eliminating the unlikely candidates while retaining 98% of the high-quality mRNA evidence in well-formed transcripts, and produces annotation that is measurably more accurate than some evidence-based gene sets. The process is fast, accurate, and fully automated, and combines the traditionally distinct gene annotation and alternative splicing detection processes in a comprehensive and systematic way, thus considerably aiding in the ensuing manual curation efforts. PMID:15632090

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

    PubMed

    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.

  10. Morgan’s Legacy: Fruit Flies and the Functional Annotation of Conserved Genes

    PubMed Central

    Bellen, Hugo J.; Yamamoto, Shinya

    2016-01-01

    In 1915, “The Mechanism of Mendelian Heredity” was published by four prominent Drosophila geneticists. They discovered that genes form linkage groups on chromosomes inherited in a Mendelian fashion and laid the genetic foundation that promoted Drosophila as a model organism. Flies continue to offer great opportunities, including studies in the field of functional genomics. PMID:26406362

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

    Cancer.gov

    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).

  12. A prioritization analysis of disease association by data-mining of functional annotation of human genes.

    PubMed

    Taniya, Takayuki; Tanaka, Susumu; Yamaguchi-Kabata, Yumi; Hanaoka, Hideki; Yamasaki, Chisato; Maekawa, Harutoshi; Barrero, Roberto A; Lenhard, Boris; Datta, Milton W; Shimoyama, Mary; Bumgarner, Roger; Chakraborty, Ranajit; Hopkinson, Ian; Jia, Libin; Hide, Winston; Auffray, Charles; Minoshima, Shinsei; Imanishi, Tadashi; Gojobori, Takashi

    2012-01-01

    Complex diseases result from contributions of multiple genes that act in concert through pathways. Here we present a method to prioritize novel candidates of disease-susceptibility genes depending on the biological similarities to the known disease-related genes. The extent of disease-susceptibility of a gene is prioritized by analyzing seven features of human genes captured in H-InvDB. Taking rheumatoid arthritis (RA) and prostate cancer (PC) as two examples, we evaluated the efficiency of our method. Highly scored genes obtained included TNFSF12 and OSM as candidate disease genes for RA and PC, respectively. Subsequent characterization of these genes based upon an extensive literature survey reinforced the validity of these highly scored genes as possible disease-susceptibility genes. Our approach, Prioritization ANalysis of Disease Association (PANDA), is an efficient and cost-effective method to narrow down a large set of genes into smaller subsets that are most likely to be involved in the disease pathogenesis.

  13. Genome, Functional Gene Annotation, and Nuclear Transformation of the Heterokont Oleaginous Alga Nannochloropsis oceanica CCMP1779

    DTIC Science & Technology

    2012-11-15

    Assembly size 28.7 Mbp G+ C content 53.8% Protein coding genes 11,973 Average gene size 1,547 bp Average exons per gene 2.7 Average introns per gene 1.7...the heterokonts. A search of CCMP1779 genome identified 42 genes from 15 CAZy families that are predicted to encode glycosyltransferases (GT) and 44...Family N. oceanica C . reinhardtii A. thaliana H. sapiens C . elegans S. cerevisiae ABI3VP1 1 59 AP2-EREBP* 6 11 160 ARR-B 1 15 bHLH 6 4 160 154 50 7 BSD 1

  14. Structural and functional annotation of the porcine immunome

    PubMed Central

    2013-01-01

    Background The domestic pig is known as an excellent model for human immunology and the two species share many pathogens. Susceptibility to infectious disease is one of the major constraints on swine performance, yet the structure and function of genes comprising the pig immunome are not well-characterized. The completion of the pig genome provides the opportunity to annotate the pig immunome, and compare and contrast pig and human immune systems. Results The Immune Response Annotation Group (IRAG) used computational curation and manual annotation of the swine genome assembly 10.2 (Sscrofa10.2) to refine the currently available automated annotation of 1,369 immunity-related genes through sequence-based comparison to genes in other species. Within these genes, we annotated 3,472 transcripts. Annotation provided evidence for gene expansions in several immune response families, and identified artiodactyl-specific expansions in the cathelicidin and type 1 Interferon families. We found gene duplications for 18 genes, including 13 immune response genes and five non-immune response genes discovered in the annotation process. Manual annotation provided evidence for many new alternative splice variants and 8 gene duplications. Over 1,100 transcripts without porcine sequence evidence were detected using cross-species annotation. We used a functional approach to discover and accurately annotate porcine immune response genes. A co-expression clustering analysis of transcriptomic data from selected experimental infections or immune stimulations of blood, macrophages or lymph nodes identified a large cluster of genes that exhibited a correlated positive response upon infection across multiple pathogens or immune stimuli. Interestingly, this gene cluster (cluster 4) is enriched for known general human immune response genes, yet contains many un-annotated porcine genes. A phylogenetic analysis of the encoded proteins of cluster 4 genes showed that 15% exhibited an accelerated

  15. The GOA database: Gene Ontology annotation updates for 2015

    PubMed Central

    Huntley, Rachael P.; Sawford, Tony; Mutowo-Meullenet, Prudence; Shypitsyna, Aleksandra; Bonilla, Carlos; Martin, Maria J.; O'Donovan, Claire

    2015-01-01

    The Gene Ontology Annotation (GOA) resource (http://www.ebi.ac.uk/GOA) provides evidence-based Gene Ontology (GO) annotations to proteins in the UniProt Knowledgebase (UniProtKB). Manual annotations provided by UniProt curators are supplemented by manual and automatic annotations from model organism databases and specialist annotation groups. GOA currently supplies 368 million GO annotations to almost 54 million proteins in more than 480 000 taxonomic groups. The resource now provides annotations to five times the number of proteins it did 4 years ago. As a member of the GO Consortium, we adhere to the most up-to-date Consortium-agreed annotation guidelines via the use of quality control checks that ensures that the GOA resource supplies high-quality functional information to proteins from a wide range of species. Annotations from GOA are freely available and are accessible through a powerful web browser as well as a variety of annotation file formats. PMID:25378336

  16. Metagenomic gene annotation by a homology-independent approach

    SciTech Connect

    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.

  17. Discovering gene annotations in biomedical text databases

    PubMed Central

    Cakmak, Ali; Ozsoyoglu, Gultekin

    2008-01-01

    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 pattern occurrences with

  18. JGI Plant Genomics Gene Annotation Pipeline

    SciTech Connect

    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.

  19. The GATO gene annotation tool for research laboratories.

    PubMed

    Fujita, A; Massirer, K B; Durham, A M; Ferreira, C E; Sogayar, M C

    2005-11-01

    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.

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

    PubMed Central

    Araújo, Wagner L.; Nunes-Nesi, Adriano; Williams, Thomas C. R.

    2012-01-01

    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. PMID:22973288

  1. Characterizing the state of the art in the computational assignment of gene function: lessons from the first critical assessment of functional annotation (CAFA)

    PubMed Central

    2013-01-01

    The assignment of gene function remains a difficult but important task in computational biology. The establishment of the first Critical Assessment of Functional Annotation (CAFA) was aimed at increasing progress in the field. We present an independent analysis of the results of CAFA, aimed at identifying challenges in assessment and at understanding trends in prediction performance. We found that well-accepted methods based on sequence similarity (i.e., BLAST) have a dominant effect. Many of the most informative predictions turned out to be either recovering existing knowledge about sequence similarity or were "post-dictions" already documented in the literature. These results indicate that deep challenges remain in even defining the task of function assignment, with a particular difficulty posed by the problem of defining function in a way that is not dependent on either flawed gold standards or the input data itself. In particular, we suggest that using the Gene Ontology (or other similar systematizations of function) as a gold standard is unlikely to be the way forward. PMID:23630983

  2. Gene calling and bacterial genome annotation with BG7.

    PubMed

    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).

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

    PubMed Central

    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

  4. Considerations to improve functional annotations in biological databases.

    PubMed

    Benítez-Páez, Alfonso

    2009-12-01

    Despite the great effort to design efficient systems allowing the electronic indexation of information concerning genes, proteins, structures, and interactions published daily in scientific journals, some problems are still observed in specific tasks such as functional annotation. The annotation of function is a critical issue for bioinformatic routines, such as for instance, in functional genomics and the further prediction of unknown protein function, which are highly dependent of the quality of existing annotations. Some information management systems evolve to efficiently incorporate information from large-scale projects, but often, annotation of single records from the literature is difficult and slow. In this short report, functional characterizations of a representative sample of the entire set of uncharacterized proteins from Escherichia coli K12 was compiled from Swiss-Prot, PubMed, and EcoCyc and demonstrate a functional annotation deficit in biological databases. Some issues are postulated as causes of the lack of annotation, and different solutions are evaluated and proposed to avoid them. The hope is that as a consequence of these observations, there will be new impetus to improve the speed and quality of functional annotation and ultimately provide updated, reliable information to the scientific community.

  5. Functional Annotations of Paralogs: A Blessing and a Curse

    PubMed Central

    Zallot, Rémi; Harrison, Katherine J.; Kolaczkowski, Bryan; de Crécy-Lagard, Valérie

    2016-01-01

    Gene duplication followed by mutation is a classic mechanism of neofunctionalization, producing gene families with functional diversity. In some cases, a single point mutation is sufficient to change the substrate specificity and/or the chemistry performed by an enzyme, making it difficult to accurately separate enzymes with identical functions from homologs with different functions. Because sequence similarity is often used as a basis for assigning functional annotations to genes, non-isofunctional gene families pose a great challenge for genome annotation pipelines. Here we describe how integrating evolutionary and functional information such as genome context, phylogeny, metabolic reconstruction and signature motifs may be required to correctly annotate multifunctional families. These integrative analyses can also lead to the discovery of novel gene functions, as hints from specific subgroups can guide the functional characterization of other members of the family. We demonstrate how careful manual curation processes using comparative genomics can disambiguate subgroups within large multifunctional families and discover their functions. We present the COG0720 protein family as a case study. We also discuss strategies to automate this process to improve the accuracy of genome functional annotation pipelines. PMID:27618105

  6. AutoFACT: An Automatic Functional Annotation and Classification Tool

    PubMed Central

    Koski, Liisa B; Gray, Michael W; Lang, B Franz; Burger, Gertraud

    2005-01-01

    Background Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. Results We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1) analyzes nucleotide and protein sequence data; (2) determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3) assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4) generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1–2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%. Conclusion AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at . PMID:15960857

  7. Protein function annotation using protein domain family resources.

    PubMed

    Das, Sayoni; Orengo, Christine A

    2016-01-15

    As a result of the genome sequencing and structural genomics initiatives, we have a wealth of protein sequence and structural data. However, only about 1% of these proteins have experimental functional annotations. As a result, computational approaches that can predict protein functions are essential in bridging this widening annotation gap. This article reviews the current approaches of protein function prediction using structure and sequence based classification of protein domain family resources with a special focus on functional families in the CATH-Gene3D resource.

  8. Taxonomic Precision of Different Hypervariable Regions of 16S rRNA Gene and Annotation Methods for Functional Bacterial Groups in Biological Wastewater Treatment

    PubMed Central

    Guo, Feng; Ju, Feng; Cai, Lin; Zhang, Tong

    2013-01-01

    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. PMID:24146837

  9. snpGeneSets: An R Package for Genome-Wide Study Annotation

    PubMed Central

    Mei, Hao; Li, Lianna; Jiang, Fan; Simino, Jeannette; Griswold, Michael; Mosley, Thomas; Liu, Shijian

    2016-01-01

    Genome-wide studies (GWS) of SNP associations and differential gene expressions have generated abundant results; next-generation sequencing technology has further boosted the number of variants and genes identified. Effective interpretation requires massive annotation and downstream analysis of these genome-wide results, a computationally challenging task. We developed the snpGeneSets package to simplify annotation and analysis of GWS results. Our package integrates local copies of knowledge bases for SNPs, genes, and gene sets, and implements wrapper functions in the R language to enable transparent access to low-level databases for efficient annotation of large genomic data. The package contains functions that execute three types of annotations: (1) genomic mapping annotation for SNPs and genes and functional annotation for gene sets; (2) bidirectional mapping between SNPs and genes, and genes and gene sets; and (3) calculation of gene effect measures from SNP associations and performance of gene set enrichment analyses to identify functional pathways. We applied snpGeneSets to type 2 diabetes (T2D) results from the NHGRI genome-wide association study (GWAS) catalog, a Finnish GWAS, and a genome-wide expression study (GWES). These studies demonstrate the usefulness of snpGeneSets for annotating and performing enrichment analysis of GWS results. The package is open-source, free, and can be downloaded at: https://www.umc.edu/biostats_software/. PMID:27807048

  10. snpGeneSets: An R Package for Genome-Wide Study Annotation.

    PubMed

    Mei, Hao; Li, Lianna; Jiang, Fan; Simino, Jeannette; Griswold, Michael; Mosley, Thomas; Liu, Shijian

    2016-12-07

    Genome-wide studies (GWS) of SNP associations and differential gene expressions have generated abundant results; next-generation sequencing technology has further boosted the number of variants and genes identified. Effective interpretation requires massive annotation and downstream analysis of these genome-wide results, a computationally challenging task. We developed the snpGeneSets package to simplify annotation and analysis of GWS results. Our package integrates local copies of knowledge bases for SNPs, genes, and gene sets, and implements wrapper functions in the R language to enable transparent access to low-level databases for efficient annotation of large genomic data. The package contains functions that execute three types of annotations: (1) genomic mapping annotation for SNPs and genes and functional annotation for gene sets; (2) bidirectional mapping between SNPs and genes, and genes and gene sets; and (3) calculation of gene effect measures from SNP associations and performance of gene set enrichment analyses to identify functional pathways. We applied snpGeneSets to type 2 diabetes (T2D) results from the NHGRI genome-wide association study (GWAS) catalog, a Finnish GWAS, and a genome-wide expression study (GWES). These studies demonstrate the usefulness of snpGeneSets for annotating and performing enrichment analysis of GWS results. The package is open-source, free, and can be downloaded at: https://www.umc.edu/biostats_software/.

  11. Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach

    PubMed Central

    Andorf, Carson; Dobbs, Drena; Honavar, Vasant

    2007-01-01

    Background Incorrectly annotated sequence data are becoming more commonplace as databases increasingly rely on automated techniques for annotation. Hence, there is an urgent need for computational methods for checking consistency of such annotations against independent sources of evidence and detecting potential annotation errors. We show how a machine learning approach designed to automatically predict a protein's Gene Ontology (GO) functional class can be employed to identify potential gene annotation errors. Results In a set of 211 previously annotated mouse protein kinases, we found that 201 of the GO annotations returned by AmiGO appear to be inconsistent with the UniProt functions assigned to their human counterparts. In contrast, 97% of the predicted annotations generated using a machine learning approach were consistent with the UniProt annotations of the human counterparts, as well as with available annotations for these mouse protein kinases in the Mouse Kinome database. Conclusion We conjecture that most of our predicted annotations are, therefore, correct and suggest that the machine learning approach developed here could be routinely used to detect potential errors in GO annotations generated by high-throughput gene annotation projects. Editors Note : Authors from the original publication (Okazaki et al.: Nature 2002, 420:563–73) have provided their response to Andorf et al, directly following the correspondence. PMID:17683567

  12. Discovery, Annotation, and Functional Analysis of Long Noncoding RNAs Controlling Cell-Cycle Gene Expression and Proliferation in Breast Cancer Cells.

    PubMed

    Sun, Miao; Gadad, Shrikanth S; Kim, Dae-Seok; Kraus, W Lee

    2015-08-20

    We describe a computational approach that integrates GRO-seq and RNA-seq data to annotate long noncoding RNAs (lncRNAs), with increased sensitivity for low-abundance lncRNAs. We used this approach to characterize the lncRNA transcriptome in MCF-7 human breast cancer cells, including >700 previously unannotated lncRNAs. We then used information about the (1) transcription of lncRNA genes from GRO-seq, (2) steady-state levels of lncRNA transcripts in cell lines and patient samples from RNA-seq, and (3) histone modifications and factor binding at lncRNA gene promoters from ChIP-seq to explore lncRNA gene structure and regulation, as well as lncRNA transcript stability, regulation, and function. Functional analysis of selected lncRNAs with altered expression in breast cancers revealed roles in cell proliferation, regulation of an E2F-dependent cell-cycle gene expression program, and estrogen-dependent mitogenic growth. Collectively, our studies demonstrate the use of an integrated genomic and molecular approach to identify and characterize growth-regulating lncRNAs in cancers.

  13. Improving gene annotation using peptide mass spectrometry

    PubMed Central

    Tanner, Stephen; Shen, Zhouxin; Ng, Julio; Florea, Liliana; Guigó, Roderic; Briggs, Steven P.; Bafna, Vineet

    2007-01-01

    Annotation of protein-coding genes is a key goal of genome sequencing projects. In spite of tremendous recent advances in computational gene finding, comprehensive annotation remains a challenge. Peptide mass spectrometry is a powerful tool for researching the dynamic proteome and suggests an attractive approach to discover and validate protein-coding genes. We present algorithms to construct and efficiently search spectra against a genomic database, with no prior knowledge of encoded proteins. By searching a corpus of 18.5 million tandem mass spectra (MS/MS) from human proteomic samples, we validate 39,000 exons and 11,000 introns at the level of translation. We present translation-level evidence for novel or extended exons in 16 genes, confirm translation of 224 hypothetical proteins, and discover or confirm over 40 alternative splicing events. Polymorphisms are efficiently encoded in our database, allowing us to observe variant alleles for 308 coding SNPs. Finally, we demonstrate the use of mass spectrometry to improve automated gene prediction, adding 800 correct exons to our predictions using a simple rescoring strategy. Our results demonstrate that proteomic profiling should play a role in any genome sequencing project. PMID:17189379

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

    PubMed Central

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

    2016-01-01

    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. PMID:26476454

  15. Genomic resources for gene discovery, functional genome annotation, and evolutionary studies of maize and its close relatives.

    PubMed

    Wang, Chao; Shi, Xue; Liu, Lin; Li, Haiyan; Ammiraju, Jetty S S; Kudrna, David A; Xiong, Wentao; Wang, Hao; Dai, Zhaozhao; Zheng, Yonglian; Lai, Jinsheng; Jin, Weiwei; Messing, Joachim; Bennetzen, Jeffrey L; Wing, Rod A; Luo, Meizhong

    2013-11-01

    Maize is one of the most important food crops and a key model for genetics and developmental biology. A genetically anchored and high-quality draft genome sequence of maize inbred B73 has been obtained to serve as a reference sequence. To facilitate evolutionary studies in maize and its close relatives, much like the Oryza Map Alignment Project (OMAP) (www.OMAP.org) bacterial artificial chromosome (BAC) resource did for the rice community, we constructed BAC libraries for maize inbred lines Zheng58, Chang7-2, and Mo17 and maize wild relatives Zea mays ssp. parviglumis and Tripsacum dactyloides. Furthermore, to extend functional genomic studies to maize and sorghum, we also constructed binary BAC (BIBAC) libraries for the maize inbred B73 and the sorghum landrace Nengsi-1. The BAC/BIBAC vectors facilitate transfer of large intact DNA inserts from BAC clones to the BIBAC vector and functional complementation of large DNA fragments. These seven Zea Map Alignment Project (ZMAP) BAC/BIBAC libraries have average insert sizes ranging from 92 to 148 kb, organellar DNA from 0.17 to 2.3%, empty vector rates between 0.35 and 5.56%, and genome equivalents of 4.7- to 8.4-fold. The usefulness of the Parviglumis and Tripsacum BAC libraries was demonstrated by mapping clones to the reference genome. Novel genes and alleles present in these ZMAP libraries can now be used for functional complementation studies and positional or homology-based cloning of genes for translational genomics.

  16. Using computational predictions to improve literature-based Gene Ontology annotations: a feasibility study.

    PubMed

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

    2011-01-01

    Annotation using Gene Ontology (GO) terms is one of the most important ways in which biological information about specific gene products can be expressed in a searchable, computable form that may be compared across genomes and organisms. Because literature-based GO annotations are often used to propagate functional predictions between related proteins, their accuracy is critically important. We present a strategy that employs a comparison of literature-based annotations with computational predictions to identify and prioritize genes whose annotations need review. Using this method, we show that comparison of manually assigned 'unknown' annotations in the Saccharomyces Genome Database (SGD) with InterPro-based predictions can identify annotations that need to be updated. A survey of literature-based annotations and computational predictions made by the Gene Ontology Annotation (GOA) project at the European Bioinformatics Institute (EBI) across several other databases shows that this comparison strategy could be used to maintain and improve the quality of GO annotations for other organisms besides yeast. The survey also shows that although GOA-assigned predictions are the most comprehensive source of functional information for many genomes, a large proportion of genes in a variety of different organisms entirely lack these predictions but do have manual annotations. This underscores the critical need for manually performed, literature-based curation to provide functional information about genes that are outside the scope of widely used computational methods. Thus, the combination of manual and computational methods is essential to provide the most accurate and complete functional annotation of a genome. Database URL: http://www.yeastgenome.org.

  17. Transcript Annotation in FANTOM3: Mouse Gene Catalog Based on Physical cDNAs

    PubMed Central

    Maeda, Norihiro; Kasukawa, Takeya; Oyama, Rieko; Gough, Julian; Frith, Martin; Engström, Pär G; Lenhard, Boris; Aturaliya, Rajith N; Batalov, Serge; Beisel, Kirk W; Bult, Carol J; Fletcher, Colin F; Forrest, Alistair R. R; Furuno, Masaaki; Hill, David; Itoh, Masayoshi; Kanamori-Katayama, Mutsumi; Katayama, Shintaro; Katoh, Masaru; Kawashima, Tsugumi; Quackenbush, John; Ravasi, Timothy; Ring, Brian Z; Shibata, Kazuhiro; Sugiura, Koji; Takenaka, Yoichi; Teasdale, Rohan D; Wells, Christine A; Zhu, Yunxia; Kai, Chikatoshi; Kawai, Jun; Hume, David A; Carninci, Piero; Hayashizaki, Yoshihide

    2006-01-01

    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. PMID:16683036

  18. 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

    PubMed Central

    Kang, Se Won; Hwang, Hee-Ju; Park, So Young; Park, Eun Bi; Chung, Jong Min; Song, Dae Kwon; Kim, Changmu; Kim, Soonok; Lee, Jun Sang; Han, Yeon Soo; Park, Hong Seog; Lee, Yong Seok

    2016-01-01

    Background 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. Results 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. Conclusions This dataset represents the first transcriptome analysis of the endangered

  19. Predicting Novel Human Gene Ontology Annotations Using Semantic Analysis

    PubMed Central

    Done, Bogdan; Khatri, Purvesh; Done, Arina; Draghici, Sorin

    2013-01-01

    The correct interpretation of many molecular biology experiments depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are meant to act as repositories for our biological knowledge as we acquire and refine it. Hence, by definition, they are incomplete at any given time. In this paper, we describe a technique that improves our previous method for predicting novel GO annotations by extracting implicit semantic relationships between genes and functions. In this work, we use a vector space model and a number of weighting schemes in addition to our previous latent semantic indexing approach. The technique described here is able to take into consideration the hierarchical structure of the Gene Ontology (GO) and can weight differently GO terms situated at different depths. The prediction abilities of 15 different weighting schemes are compared and evaluated. Nine such schemes were previously used in other problem domains, while six of them are introduced in this paper. The best weighting scheme was a novel scheme, n2tn. Out of the top 50 functional annotations predicted using this weighting scheme, we found support in the literature for 84 percent of them, while 6 percent of the predictions were contradicted by the existing literature. For the remaining 10 percent, we did not find any relevant publications to confirm or contradict the predictions. The n2tn weighting scheme also outperformed the simple binary scheme used in our previous approach. PMID:20150671

  20. Functional annotation of the human retinal pigment epithelium transcriptome

    PubMed Central

    Booij, Judith C; van Soest, Simone; Swagemakers, Sigrid MA; Essing, Anke HW; Verkerk, Annemieke JMH; van der Spek, Peter J; Gorgels, Theo GMF; Bergen, Arthur AB

    2009-01-01

    Background To determine level, variability and functional annotation of gene expression of the human retinal pigment epithelium (RPE), the key tissue involved in retinal diseases like age-related macular degeneration and retinitis pigmentosa. Macular RPE cells from six selected healthy human donor eyes (aged 63–78 years) were laser dissected and used for 22k microarray studies (Agilent technologies). Data were analyzed with Rosetta Resolver, the web tool DAVID and Ingenuity software. Results In total, we identified 19,746 array entries with significant expression in the RPE. Gene expression was analyzed according to expression levels, interindividual variability and functionality. A group of highly (n = 2,194) expressed RPE genes showed an overrepresentation of genes of the oxidative phosphorylation, ATP synthesis and ribosome pathways. In the group of moderately expressed genes (n = 8,776) genes of the phosphatidylinositol signaling system and aminosugars metabolism were overrepresented. As expected, the top 10 percent (n = 2,194) of genes with the highest interindividual differences in expression showed functional overrepresentation of the complement cascade, essential in inflammation in age-related macular degeneration, and other signaling pathways. Surprisingly, this same category also includes the genes involved in Bruch's membrane (BM) composition. Among the top 10 percent of genes with low interindividual differences, there was an overrepresentation of genes involved in local glycosaminoglycan turnover. Conclusion Our study expands current knowledge of the RPE transcriptome by assigning new genes, and adding data about expression level and interindividual variation. Functional annotation suggests that the RPE has high levels of protein synthesis, strong energy demands, and is exposed to high levels of oxidative stress and a variable degree of inflammation. Our data sheds new light on the molecular composition of BM, adjacent to the RPE, and is useful for

  1. HMM-Based Gene Annotation Methods

    SciTech Connect

    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.

  2. Comprehensive comparative homeobox gene annotation in human and mouse.

    PubMed

    Wilming, Laurens G; Boychenko, Veronika; Harrow, Jennifer L

    2015-01-01

    Homeobox genes are a group of genes coding for transcription factors with a DNA-binding helix-turn-helix structure called a homeodomain and which play a crucial role in pattern formation during embryogenesis. Many homeobox genes are located in clusters and some of these, most notably the HOX genes, are known to have antisense or opposite strand long non-coding RNA (lncRNA) genes that play a regulatory role. Because automated annotation of both gene clusters and non-coding genes is fraught with difficulty (over-prediction, under-prediction, inaccurate transcript structures), we set out to manually annotate all homeobox genes in the mouse and human genomes. This includes all supported splice variants, pseudogenes and both antisense and flanking lncRNAs. One of the areas where manual annotation has a significant advantage is the annotation of duplicated gene clusters. After comprehensive annotation of all homeobox genes and their antisense genes in human and in mouse, we found some discrepancies with the current gene set in RefSeq regarding exact gene structures and coding versus pseudogene locus biotype. We also identified previously un-annotated pseudogenes in the DUX, Rhox and Obox gene clusters, which helped us re-evaluate and update the gene nomenclature in these regions. We found that human homeobox genes are enriched in antisense lncRNA loci, some of which are known to play a role in gene or gene cluster regulation, compared to their mouse orthologues. Of the annotated set of 241 human protein-coding homeobox genes, 98 have an antisense locus (41%) while of the 277 orthologous mouse genes, only 62 protein coding gene have an antisense locus (22%), based on publicly available transcriptional evidence.

  3. Comprehensive comparative homeobox gene annotation in human and mouse

    PubMed Central

    Wilming, Laurens G.; Boychenko, Veronika; Harrow, Jennifer L.

    2015-01-01

    Homeobox genes are a group of genes coding for transcription factors with a DNA-binding helix-turn-helix structure called a homeodomain and which play a crucial role in pattern formation during embryogenesis. Many homeobox genes are located in clusters and some of these, most notably the HOX genes, are known to have antisense or opposite strand long non-coding RNA (lncRNA) genes that play a regulatory role. Because automated annotation of both gene clusters and non-coding genes is fraught with difficulty (over-prediction, under-prediction, inaccurate transcript structures), we set out to manually annotate all homeobox genes in the mouse and human genomes. This includes all supported splice variants, pseudogenes and both antisense and flanking lncRNAs. One of the areas where manual annotation has a significant advantage is the annotation of duplicated gene clusters. After comprehensive annotation of all homeobox genes and their antisense genes in human and in mouse, we found some discrepancies with the current gene set in RefSeq regarding exact gene structures and coding versus pseudogene locus biotype. We also identified previously un-annotated pseudogenes in the DUX, Rhox and Obox gene clusters, which helped us re-evaluate and update the gene nomenclature in these regions. We found that human homeobox genes are enriched in antisense lncRNA loci, some of which are known to play a role in gene or gene cluster regulation, compared to their mouse orthologues. Of the annotated set of 241 human protein-coding homeobox genes, 98 have an antisense locus (41%) while of the 277 orthologous mouse genes, only 62 protein coding gene have an antisense locus (22%), based on publicly available transcriptional evidence. PMID:26412852

  4. Evolutionary Trace Annotation of Protein Function in the Structural Proteome

    PubMed Central

    Erdin, Serkan; Ward, R. Matthew; Venner, Eric

    2010-01-01

    By design, structural genomics (SG) solves many structures that cannot be assigned function based on homology to known proteins. Alternative function annotation methods are therefore needed and this study focuses on function prediction with three-dimensional (3D) templates: small structural motifs built of just a few functionally critical residues. Although experimentally proven functional residues are scarce, we show here that Evolutionary Trace (ET) rankings of residue importance are sufficient to build 3D templates, match them, and then assign Gene Ontology (GO) functions in enzymes and non-enzymes alike. In a high specificity mode, this Evolutionary Trace Annotation (ETA) method covered half (53%) of the 2384 annotated SG protein controls. Three-quarters (76%) of predictions were both correct and complete. The positive predictive value for all GO depths (all-depth PPV) was 84%, and it rose to 94% over GO depths 1– 3 (depth 3 PPV). In a high sensitivity mode coverage rose significantly (84%) while accuracy fell moderately: 68% of predictions were both correct and complete, all-depth PPV was 75%, and depth 3 PPV was 86%. These data concur with prior mutational experiments showing that ET rank information identifies key functional determinants in proteins. In practice, ETA predicted functions in 42% of 3461 un-annotated SG proteins. In 529 cases—including 280 non-enzymes and 21 for metal ion ligands—the expected accuracy is 84% at any GO depth and 94% down to GO depth 3, while for the remaining 931 the expected accuracies are 60% and 71%, respectively. Thus local structural comparisons of evolutionarily important residues can help decipher protein functions to known reliability levels and without prior assumption on functional mechanisms. ETA is available at http://mammoth.bcm.tmc.edu/eta. PMID:20036248

  5. Gene Model Annotations for Drosophila melanogaster: Impact of High-Throughput Data

    PubMed Central

    Matthews, Beverley B.; dos Santos, Gilberto; Crosby, Madeline A.; Emmert, David B.; St. Pierre, Susan E.; Gramates, L. Sian; Zhou, Pinglei; Schroeder, Andrew J.; Falls, Kathleen; Strelets, Victor; Russo, Susan M.; Gelbart, William M.

    2015-01-01

    We report the current status of the FlyBase annotated gene set for Drosophila melanogaster and highlight improvements based on high-throughput data. The FlyBase annotated gene set consists entirely of manually annotated gene models, with the exception of some classes of small non-coding RNAs. All gene models have been reviewed using evidence from high-throughput datasets, primarily from the modENCODE project. These datasets include RNA-Seq coverage data, RNA-Seq junction data, transcription start site profiles, and translation stop-codon read-through predictions. New annotation guidelines were developed to take into account the use of the high-throughput data. We describe how this flood of new data was incorporated into thousands of new and revised annotations. FlyBase has adopted a philosophy of excluding low-confidence and low-frequency data from gene model annotations; we also do not attempt to represent all possible permutations for complex and modularly organized genes. This has allowed us to produce a high-confidence, manageable gene annotation dataset that is available at FlyBase (http://flybase.org). Interesting aspects of new annotations include new genes (coding, non-coding, and antisense), many genes with alternative transcripts with very long 3′ UTRs (up to 15–18 kb), and a stunning mismatch in the number of male-specific genes (approximately 13% of all annotated gene models) vs. female-specific genes (less than 1%). The number of identified pseudogenes and mutations in the sequenced strain also increased significantly. We discuss remaining challenges, for instance, identification of functional small polypeptides and detection of alternative translation starts. PMID:26109357

  6. Gene Model Annotations for Drosophila melanogaster: Impact of High-Throughput Data.

    PubMed

    Matthews, Beverley B; Dos Santos, Gilberto; Crosby, Madeline A; Emmert, David B; St Pierre, Susan E; Gramates, L Sian; Zhou, Pinglei; Schroeder, Andrew J; Falls, Kathleen; Strelets, Victor; Russo, Susan M; Gelbart, William M

    2015-06-24

    We report the current status of the FlyBase annotated gene set for Drosophila melanogaster and highlight improvements based on high-throughput data. The FlyBase annotated gene set consists entirely of manually annotated gene models, with the exception of some classes of small non-coding RNAs. All gene models have been reviewed using evidence from high-throughput datasets, primarily from the modENCODE project. These datasets include RNA-Seq coverage data, RNA-Seq junction data, transcription start site profiles, and translation stop-codon read-through predictions. New annotation guidelines were developed to take into account the use of the high-throughput data. We describe how this flood of new data was incorporated into thousands of new and revised annotations. FlyBase has adopted a philosophy of excluding low-confidence and low-frequency data from gene model annotations; we also do not attempt to represent all possible permutations for complex and modularly organized genes. This has allowed us to produce a high-confidence, manageable gene annotation dataset that is available at FlyBase (http://flybase.org). Interesting aspects of new annotations include new genes (coding, non-coding, and antisense), many genes with alternative transcripts with very long 3' UTRs (up to 15-18 kb), and a stunning mismatch in the number of male-specific genes (approximately 13% of all annotated gene models) vs. female-specific genes (less than 1%). The number of identified pseudogenes and mutations in the sequenced strain also increased significantly. We discuss remaining challenges, for instance, identification of functional small polypeptides and detection of alternative translation starts.

  7. Gene ontology annotation by density and gravitation models.

    PubMed

    Hou, Wen-Juan; Lin, Kevin Hsin-Yih; Chen, Hsin-Hsi

    2006-01-01

    Gene Ontology (GO) is developed to provide standard vocabularies of gene products in different databases. The process of annotating GO terms to genes requires curators to read through lengthy articles. Methods for speeding up or automating the annotation process are thus of great importance. We propose a GO annotation approach using full-text biomedical documents for directing more relevant papers to curators. This system explores word density and gravitation relationships between genes and GO terms. Different density and gravitation models are built and several evaluation criteria are employed to assess the effects of the proposed methods.

  8. Protein function prediction and annotation in an integrated environment powered by web services (AFAWE).

    PubMed

    Jöcker, Anika; Hoffmann, Fabian; Groscurth, Andreas; Schoof, Heiko

    2008-10-15

    Many sequenced genes are mainly annotated through automatic transfer of annotation from similar sequences. Manual comparison of results or intermediate results from different tools can help avoid wrong annotations and give hints to the function of a gene even if none of the automated tools could return any result. AFAWE simplifies the task of manual functional annotation by running different tools and workflows for automatic function prediction and displaying the results in a way that facilitates comparison. Because all programs are executed as web services, AFAWE is easily extensible and can directly query primary databases, thereby always using the most up-to-date data sources. Visual filters help to distinguish trustworthy results from non-significant results. Furthermore, an interface to add detailed manual annotation to each gene is provided, which can be displayed to other users.

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

    PubMed

    Singh, Nagendra Kumar

    2016-03-28

    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.

  10. Improving functional annotation for industrial microbes: a case study with Pichia pastoris

    PubMed Central

    Dikicioglu, Duygu; Wood, Valerie; Rutherford, Kim M.; McDowall, Mark D.; Oliver, Stephen G.

    2014-01-01

    The research communities studying microbial model organisms, such as Escherichia coli or Saccharomyces cerevisiae, are well served by model organism databases that have extensive functional annotation. However, this is not true of many industrial microbes that are used widely in biotechnology. In this Opinion piece, we use Pichia (Komagataella) pastoris to illustrate the limitations of the available annotation. We consider the resources that can be implemented in the short term both to improve Gene Ontology (GO) annotation coverage based on annotation transfer, and to establish curation pipelines for the literature corpus of this organism. PMID:24929579

  11. A computational interactome and functional annotation for the human proteome

    PubMed Central

    Garzón, José Ignacio; Deng, Lei; Murray, Diana; Shapira, Sagi; Petrey, Donald; Honig, Barry

    2016-01-01

    We present a database, PrePPI (Predicting Protein-Protein Interactions), of more than 1.35 million predicted protein-protein interactions (PPIs). Of these at least 127,000 are expected to constitute direct physical interactions although the actual number may be much larger (~500,000). The current PrePPI, which contains predicted interactions for about 85% of the human proteome, is related to an earlier version but is based on additional sources of interaction evidence and is far larger in scope. The use of structural relationships allows PrePPI to infer numerous previously unreported interactions. PrePPI has been subjected to a series of validation tests including reproducing known interactions, recapitulating multi-protein complexes, analysis of disease associated SNPs, and identifying functional relationships between interacting proteins. We show, using Gene Set Enrichment Analysis (GSEA), that predicted interaction partners can be used to annotate a protein’s function. We provide annotations for most human proteins, including many annotated as having unknown function. DOI: http://dx.doi.org/10.7554/eLife.18715.001 PMID:27770567

  12. Eliciting the Functional Taxonomy from protein annotations and taxa

    PubMed Central

    Falda, Marco; Lavezzo, Enrico; Fontana, Paolo; Bianco, Luca; Berselli, Michele; Formentin, Elide; Toppo, Stefano

    2016-01-01

    The advances of omics technologies have triggered the production of an enormous volume of data coming from thousands of species. Meanwhile, joint international efforts like the Gene Ontology (GO) consortium have worked to provide functional information for a vast amount of proteins. With these data available, we have developed FunTaxIS, a tool that is the first attempt to infer functional taxonomy (i.e. how functions are distributed over taxa) combining functional and taxonomic information. FunTaxIS is able to define a taxon specific functional space by exploiting annotation frequencies in order to establish if a function can or cannot be used to annotate a certain species. The tool generates constraints between GO terms and taxa and then propagates these relations over the taxonomic tree and the GO graph. Since these constraints nearly cover the whole taxonomy, it is possible to obtain the mapping of a function over the taxonomy. FunTaxIS can be used to make functional comparative analyses among taxa, to detect improper associations between taxa and functions, and to discover how functional knowledge is either distributed or missing. A benchmark test set based on six different model species has been devised to get useful insights on the generated taxonomic rules. PMID:27534507

  13. Eliciting the Functional Taxonomy from protein annotations and taxa.

    PubMed

    Falda, Marco; Lavezzo, Enrico; Fontana, Paolo; Bianco, Luca; Berselli, Michele; Formentin, Elide; Toppo, Stefano

    2016-08-18

    The advances of omics technologies have triggered the production of an enormous volume of data coming from thousands of species. Meanwhile, joint international efforts like the Gene Ontology (GO) consortium have worked to provide functional information for a vast amount of proteins. With these data available, we have developed FunTaxIS, a tool that is the first attempt to infer functional taxonomy (i.e. how functions are distributed over taxa) combining functional and taxonomic information. FunTaxIS is able to define a taxon specific functional space by exploiting annotation frequencies in order to establish if a function can or cannot be used to annotate a certain species. The tool generates constraints between GO terms and taxa and then propagates these relations over the taxonomic tree and the GO graph. Since these constraints nearly cover the whole taxonomy, it is possible to obtain the mapping of a function over the taxonomy. FunTaxIS can be used to make functional comparative analyses among taxa, to detect improper associations between taxa and functions, and to discover how functional knowledge is either distributed or missing. A benchmark test set based on six different model species has been devised to get useful insights on the generated taxonomic rules.

  14. Assessing functional annotation transfers with inter-species conserved coexpression: application to Plasmodium falciparum

    PubMed Central

    2010-01-01

    Background Plasmodium falciparum is the main causative agent of malaria. Of the 5 484 predicted genes of P. falciparum, about 57% do not have sufficient sequence similarity to characterized genes in other species to warrant functional assignments. Non-homology methods are thus needed to obtain functional clues for these uncharacterized genes. Gene expression data have been widely used in the recent years to help functional annotation in an intra-species way via the so-called Guilt By Association (GBA) principle. Results We propose a new method that uses gene expression data to assess inter-species annotation transfers. Our approach starts from a set of likely orthologs between a reference species (here S. cerevisiae and D. melanogaster) and a query species (P. falciparum). It aims at identifying clusters of coexpressed genes in the query species whose coexpression has been conserved in the reference species. These conserved clusters of coexpressed genes are then used to assess annotation transfers between genes with low sequence similarity, enabling reliable transfers of annotations from the reference to the query species. The approach was used with transcriptomic data sets of P. falciparum, S. cerevisiae and D. melanogaster, and enabled us to propose with high confidence new/refined annotations for several dozens hypothetical/putative P. falciparum genes. Notably, we revised the annotation of genes involved in ribosomal proteins and ribosome biogenesis and assembly, thus highlighting several potential drug targets. Conclusions Our approach uses both sequence similarity and gene expression data to help inter-species gene annotation transfers. Experiments show that this strategy improves the accuracy achieved when using solely sequence similarity and outperforms the accuracy of the GBA approach. In addition, our experiments with P. falciparum show that it can infer a function for numerous hypothetical genes. PMID:20078859

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

    PubMed

    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.

  16. Understanding how and why the Gene Ontology and its annotations evolve: the GO within UniProt.

    PubMed

    Huntley, Rachael P; Sawford, Tony; Martin, Maria J; O'Donovan, Claire

    2014-03-18

    The Gene Ontology Consortium (GOC) is a major bioinformatics project that provides structured controlled vocabularies to classify gene product function and location. GOC members create annotations to gene products using the Gene Ontology (GO) vocabularies, thus providing an extensive, publicly available resource. The GO and its annotations to gene products are now an integral part of functional analysis, and statistical tests using GO data are becoming routine for researchers to include when publishing functional information. While many helpful articles about the GOC are available, there are certain updates to the ontology and annotation sets that sometimes go unobserved. Here we describe some of the ways in which GO can change that should be carefully considered by all users of GO as they may have a significant impact on the resulting gene product annotations, and therefore the functional description of the gene product, or the interpretation of analyses performed on GO datasets. GO annotations for gene products change for many reasons, and while these changes generally improve the accuracy of the representation of the underlying biology, they do not necessarily imply that previous annotations were incorrect. We additionally describe the quality assurance mechanisms we employ to improve the accuracy of annotations, which necessarily changes the composition of the annotation sets we provide. We use the Universal Protein Resource (UniProt) for illustrative purposes of how the GO Consortium, as a whole, manages these changes.

  17. Bacterial genome annotation.

    PubMed

    Beckloff, Nicholas; Starkenburg, Shawn; Freitas, Tracey; Chain, Patrick

    2012-01-01

    Annotation of prokaryotic sequences can be separated into structural and functional annotation. Structural annotation is dependent on algorithmic interrogation of experimental evidence to discover the physical characteristics of a gene. This is done in an effort to construct accurate gene models, so understanding function or evolution of genes among organisms is not impeded. Functional annotation is dependent on sequence similarity to other known genes or proteins in an effort to assess the function of the gene. Combining structural and functional annotation across genomes in a comparative manner promotes higher levels of accurate annotation as well as an advanced understanding of genome evolution. As the availability of bacterial sequences increases and annotation methods improve, the value of comparative annotation will increase.

  18. High-throughput functional annotation and data mining with the Blast2GO suite

    PubMed Central

    Götz, Stefan; García-Gómez, Juan Miguel; Terol, Javier; Williams, Tim D.; Nagaraj, Shivashankar H.; Nueda, María José; Robles, Montserrat; Talón, Manuel; Dopazo, Joaquín; Conesa, Ana

    2008-01-01

    Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data. PMID:18445632

  19. Identifying functionally important cis-peptide containing segments in proteins and their utility in molecular function annotation.

    PubMed

    Das, Sreetama; Ramakumar, Suryanarayanarao; Pal, Debnath

    2014-12-01

    Cis-peptide embedded segments are rare in proteins but often highlight their important role in molecular function when they do occur. The high evolutionary conservation of these segments illustrates this observation almost universally, although no attempt has been made to systematically use this information for the purpose of function annotation. In the present study, we demonstrate how geometric clustering and level-specific Gene Ontology molecular-function terms (also known as annotations) can be used in a statistically significant manner to identify cis-embedded segments in a protein linked to its molecular function. The present study identifies novel cis-peptide fragments, which are subsequently used for fragment-based function annotation. Annotation recall benchmarks interpreted using the receiver-operator characteristic plot returned an area-under-curve > 0.9, corroborating the utility of the annotation method. In addition, we identified cis-peptide fragments occurring in conjunction with functionally important trans-peptide fragments, providing additional insights into molecular function. We further illustrate the applicability of our method in function annotation where homology-based annotation transfer is not possible. The findings of the present study add to the repertoire of function annotation approaches and also facilitate engineering, design and allied studies around the cis-peptide neighborhood of proteins.

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

    PubMed

    Salem, Mohamed; Paneru, Bam; Al-Tobasei, Rafet; Abdouni, Fatima; Thorgaard, Gary H; Rexroad, Caird E; Yao, Jianbo

    2015-01-01

    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 genome.

  1. yrGATE: a web-based gene-structure annotation tool for the identification and dissemination of eukaryotic genes.

    PubMed

    Wilkerson, Matthew D; Schlueter, Shannon D; Brendel, Volker

    2006-01-01

    Your Gene structure Annotation Tool for Eukaryotes (yrGATE) provides an Annotation Tool and Community Utilities for worldwide web-based community genome and gene annotation. Annotators can evaluate gene structure evidence derived from multiple sources to create gene structure annotations. Administrators regulate the acceptance of annotations into published gene sets. yrGATE is designed to facilitate rapid and accurate annotation of emerging genomes as well as to confirm, refine, or correct currently published annotations. yrGATE is highly portable and supports different standard input and output formats. The yrGATE software and usage cases are available at http://www.plantgdb.org/prj/yrGATE.

  2. Dizeez: an online game for human gene-disease annotation.

    PubMed

    Loguercio, Salvatore; Good, Benjamin M; Su, Andrew I

    2013-01-01

    Structured gene annotations are a foundation upon which many bioinformatics and statistical analyses are built. However the structured annotations available in public databases are a sparse representation of biological knowledge as a whole. The rate of biomedical data generation is such that centralized biocuration efforts struggle to keep up. New models for gene annotation need to be explored that expand the pace at which we are able to structure biomedical knowledge. Recently, online games have emerged as an effective way to recruit, engage and organize large numbers of volunteers to help address difficult biological challenges. For example, games have been successfully developed for protein folding (Foldit), multiple sequence alignment (Phylo) and RNA structure design (EteRNA). Here we present Dizeez, a simple online game built with the purpose of structuring knowledge of gene-disease associations. Preliminary results from game play online and at scientific conferences suggest that Dizeez is producing valid gene-disease annotations not yet present in any public database. These early results provide a basic proof of principle that online games can be successfully applied to the challenge of gene annotation. Dizeez is available at http://genegames.org.

  3. CATH FunFHMMer web server: protein functional annotations using functional family assignments.

    PubMed

    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.

  4. Suppression subtractive hybridization (SSH) combined with bioinformatics method: an integrated functional annotation approach for analysis of differentially expressed immune-genes in insects.

    PubMed

    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.

  5. Algal Functional Annotation Tool from the DOE-UCLA Institute for Genomics and Proteomics

    DOE Data Explorer

    Lopez, David

    The Algal Functional Annotation Tool is a bioinformatics resource to visualize pathway maps, identify enriched biological terms, or convert gene identifiers to elucidate biological function in silico. These types of analysis have been catered to support lists of gene identifiers, such as those coming from transcriptome gene expression analysis. By analyzing the functional annotation of an interesting set of genes, common biological motifs may be elucidated and a first-pass analysis can point further research in the right direction. Currently, the following databases have been parsed, processed, and added to the tool: 1( Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways Database, 2) MetaCyc Encyclopedia of Metabolic Pathways, 3) Panther Pathways Database, 4) Reactome Pathways Database, 5) Gene Ontology, 6) MapMan Ontology, 7) KOG (Eukaryotic Clusters of Orthologous Groups), 5)Pfam, 6) InterPro.

  6. Draft Genome Sequence and Gene Annotation of Stemphylium lycopersici Strain CIDEFI-216.

    PubMed

    Franco, Mario E E; López, Silvina; Medina, Rocio; Saparrat, Mario C N; Balatti, Pedro

    2015-09-24

    Stemphylium lycopersici is a plant-pathogenic fungus that is widely distributed throughout the world. In tomatoes, it is one of the etiological agents of gray leaf spot disease. Here, we report the first draft genome sequence of S. lycopersici, including its gene structure and functional annotation.

  7. Draft Genome Sequence and Gene Annotation of Stemphylium lycopersici Strain CIDEFI-216

    PubMed Central

    Franco, Mario E. E.; López, Silvina; Medina, Rocio; Saparrat, Mario C. N.

    2015-01-01

    Stemphylium lycopersici is a plant-pathogenic fungus that is widely distributed throughout the world. In tomatoes, it is one of the etiological agents of gray leaf spot disease. Here, we report the first draft genome sequence of S. lycopersici, including its gene structure and functional annotation. PMID:26404600

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

    PubMed Central

    2014-01-01

    Background 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. Results 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. Conclusions 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

  9. Automated Gene Ontology annotation for anonymous sequence data.

    PubMed

    Hennig, Steffen; Groth, Detlef; Lehrach, Hans

    2003-07-01

    Gene Ontology (GO) is the most widely accepted attempt to construct a unified and structured vocabulary for the description of genes and their products in any organism. Annotation by GO terms is performed in most of the current genome projects, which besides generality has the advantage of being very convenient for computer based classification methods. However, direct use of GO in small sequencing projects is not easy, especially for species not commonly represented in public databases. We present a software package (GOblet), which performs annotation based on GO terms for anonymous cDNA or protein sequences. It uses the species independent GO structure and vocabulary together with a series of protein databases collected from various sites, to perform a detailed GO annotation by sequence similarity searches. The sensitivity and the reference protein sets can be selected by the user. GOblet runs automatically and is available as a public service on our web server. The paper also addresses the reliability of automated GO annotations by using a reference set of more than 6000 human proteins. The GOblet server is accessible at http://goblet.molgen.mpg.de.

  10. Mercator: a fast and simple web server for genome scale functional annotation of plant sequence data.

    PubMed

    Lohse, Marc; Nagel, Axel; Herter, Thomas; May, Patrick; Schroda, Michael; Zrenner, Rita; Tohge, Takayuki; Fernie, Alisdair R; Stitt, Mark; Usadel, Björn

    2014-05-01

    Next-generation technologies generate an overwhelming amount of gene sequence data. Efficient annotation tools are required to make these data amenable to functional genomics analyses. The Mercator pipeline automatically assigns functional terms to protein or nucleotide sequences. It uses the MapMan 'BIN' ontology, which is tailored for functional annotation of plant 'omics' data. The classification procedure performs parallel sequence searches against reference databases, compiles the results and computes the most likely MapMan BINs for each query. In the current version, the pipeline relies on manually curated reference classifications originating from the three reference organisms (Arabidopsis, Chlamydomonas, rice), various other plant species that have a reviewed SwissProt annotation, and more than 2000 protein domain and family profiles at InterPro, CDD and KOG. Functional annotations predicted by Mercator achieve accuracies above 90% when benchmarked against manual annotation. In addition to mapping files for direct use in the visualization software MapMan, Mercator provides graphical overview charts, detailed annotation information in a convenient web browser interface and a MapMan-to-GO translation table to export results as GO terms. Mercator is available free of charge via http://mapman.gabipd.org/web/guest/app/Mercator.

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

    PubMed

    Chen, Feng-Chi; Wang, Sheng-Shun; Chaw, Shu-Miaw; Huang, Yao-Ting; Chuang, Trees-Juen

    2007-03-01

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

  12. Bio301: A Web-Based EST Annotation Pipeline That Facilitates Functional Comparison Studies.

    PubMed

    Chen, Yen-Chen; Chen, Yun-Ching; Lin, Wen-Dar; Hsiao, Chung-Der; Chiu, Hung-Wen; Ho, Jan-Ming

    2012-01-01

    In this postgenomic era, a huge volume of information derived from expressed sequence tags (ESTs) has been constructed for functional description of gene expression profiles. Comparative studies have become more and more important to researchers of biology. In order to facilitate these comparative studies, we have constructed a user-friendly EST annotation pipeline with comparison tools on an integrated EST service website, Bio301. Bio301 includes regular EST preprocessing, BLAST similarity search, gene ontology (GO) annotation, statistics reporting, a graphical GO browsing interface, and microarray probe selection tools. In addition, Bio301 is equipped with statistical library comparison functions using multiple EST libraries based on GO annotations for mining meaningful biological information.

  13. proGenomes: a resource for consistent functional and taxonomic annotations of prokaryotic genomes

    PubMed Central

    Mende, Daniel R.; Letunic, Ivica; Huerta-Cepas, Jaime; Li, Simone S.; Forslund, Kristoffer; Sunagawa, Shinichi; Bork, Peer

    2017-01-01

    The availability of microbial genomes has opened many new avenues of research within microbiology. This has been driven primarily by comparative genomics approaches, which rely on accurate and consistent characterization of genomic sequences. It is nevertheless difficult to obtain consistent taxonomic and integrated functional annotations for defined prokaryotic clades. Thus, we developed proGenomes, a resource that provides user-friendly access to currently 25 038 high-quality genomes whose sequences and consistent annotations can be retrieved individually or by taxonomic clade. These genomes are assigned to 5306 consistent and accurate taxonomic species clusters based on previously established methodology. proGenomes also contains functional information for almost 80 million protein-coding genes, including a comprehensive set of general annotations and more focused annotations for carbohydrate-active enzymes and antibiotic resistance genes. Additionally, broad habitat information is provided for many genomes. All genomes and associated information can be downloaded by user-selected clade or multiple habitat-specific sets of representative genomes. We expect that the availability of high-quality genomes with comprehensive functional annotations will promote advances in clinical microbial genomics, functional evolution and other subfields of microbiology. proGenomes is available at http://progenomes.embl.de. PMID:28053165

  14. proGenomes: a resource for consistent functional and taxonomic annotations of prokaryotic genomes.

    PubMed

    Mende, Daniel R; Letunic, Ivica; Huerta-Cepas, Jaime; Li, Simone S; Forslund, Kristoffer; Sunagawa, Shinichi; Bork, Peer

    2017-01-04

    The availability of microbial genomes has opened many new avenues of research within microbiology. This has been driven primarily by comparative genomics approaches, which rely on accurate and consistent characterization of genomic sequences. It is nevertheless difficult to obtain consistent taxonomic and integrated functional annotations for defined prokaryotic clades. Thus, we developed proGenomes, a resource that provides user-friendly access to currently 25 038 high-quality genomes whose sequences and consistent annotations can be retrieved individually or by taxonomic clade. These genomes are assigned to 5306 consistent and accurate taxonomic species clusters based on previously established methodology. proGenomes also contains functional information for almost 80 million protein-coding genes, including a comprehensive set of general annotations and more focused annotations for carbohydrate-active enzymes and antibiotic resistance genes. Additionally, broad habitat information is provided for many genomes. All genomes and associated information can be downloaded by user-selected clade or multiple habitat-specific sets of representative genomes. We expect that the availability of high-quality genomes with comprehensive functional annotations will promote advances in clinical microbial genomics, functional evolution and other subfields of microbiology. proGenomes is available at http://progenomes.embl.de.

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

    NASA Astrophysics Data System (ADS)

    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.

  16. Biocuration of functional annotation at the European nucleotide archive

    PubMed Central

    Gibson, Richard; Alako, Blaise; Amid, Clara; Cerdeño-Tárraga, Ana; Cleland, Iain; Goodgame, Neil; ten Hoopen, Petra; Jayathilaka, Suran; Kay, Simon; Leinonen, Rasko; Liu, Xin; Pallreddy, Swapna; Pakseresht, Nima; Rajan, Jeena; Rosselló, Marc; Silvester, Nicole; Smirnov, Dmitriy; Toribio, Ana Luisa; Vaughan, Daniel; Zalunin, Vadim; Cochrane, Guy

    2016-01-01

    The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) is a repository for the submission, maintenance and presentation of nucleotide sequence data and related sample and experimental information. In this article we report on ENA in 2015 regarding general activity, notable published data sets and major achievements. This is followed by a focus on sustainable biocuration of functional annotation, an area which has particularly felt the pressure of sequencing growth. The importance of functional annotation, how it can be submitted and the shifting role of the biocurator in the context of increasing volumes of data are all discussed. PMID:26615190

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

    PubMed

    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.

  18. AIGO: Towards a unified framework for the Analysis and the Inter-comparison of GO functional annotations

    PubMed Central

    2011-01-01

    Background In response to the rapid growth of available genome sequences, efforts have been made to develop automatic inference methods to functionally characterize them. Pipelines that infer functional annotation are now routinely used to produce new annotations at a genome scale and for a broad variety of species. These pipelines differ widely in their inference algorithms, confidence thresholds and data sources for reasoning. This heterogeneity makes a comparison of the relative merits of each approach extremely complex. The evaluation of the quality of the resultant annotations is also challenging given there is often no existing gold-standard against which to evaluate precision and recall. Results In this paper, we present a pragmatic approach to the study of functional annotations. An ensemble of 12 metrics, describing various aspects of functional annotations, is defined and implemented in a unified framework, which facilitates their systematic analysis and inter-comparison. The use of this framework is demonstrated on three illustrative examples: analysing the outputs of state-of-the-art inference pipelines, comparing electronic versus manual annotation methods, and monitoring the evolution of publicly available functional annotations. The framework is part of the AIGO library (http://code.google.com/p/aigo) for the Analysis and the Inter-comparison of the products of Gene Ontology (GO) annotation pipelines. The AIGO library also provides functionalities to easily load, analyse, manipulate and compare functional annotations and also to plot and export the results of the analysis in various formats. Conclusions This work is a step toward developing a unified framework for the systematic study of GO functional annotations. This framework has been designed so that new metrics on GO functional annotations can be added in a very straightforward way. PMID:22054122

  19. Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci.

    PubMed

    Trynka, Gosia; Westra, Harm-Jan; Slowikowski, Kamil; Hu, Xinli; Xu, Han; Stranger, Barbara E; Klein, Robert J; Han, Buhm; Raychaudhuri, Soumya

    2015-07-02

    Identifying genomic annotations that differentiate causal from trait-associated variants is essential to fine mapping disease loci. Although many studies have identified non-coding functional annotations that overlap disease-associated variants, these annotations often colocalize, complicating the ability to use these annotations for fine mapping causal variation. We developed a statistical approach (Genomic Annotation Shifter [GoShifter]) to assess whether enriched annotations are able to prioritize causal variation. GoShifter defines the null distribution of an annotation overlapping an allele by locally shifting annotations; this approach is less sensitive to biases arising from local genomic structure than commonly used enrichment methods that depend on SNP matching. Local shifting also allows GoShifter to identify independent causal effects from colocalizing annotations. Using GoShifter, we confirmed that variants in expression quantitative trail loci drive gene-expression changes though DNase-I hypersensitive sites (DHSs) near transcription start sites and independently through 3' UTR regulation. We also showed that (1) 15%-36% of trait-associated loci map to DHSs independently of other annotations; (2) loci associated with breast cancer and rheumatoid arthritis harbor potentially causal variants near the summits of histone marks rather than full peak bodies; (3) variants associated with height are highly enriched in embryonic stem cell DHSs; and (4) we can effectively prioritize causal variation at specific loci.

  20. Functional annotations for the Saccharomyces cerevisiae genome: the knowns and the known unknowns

    PubMed Central

    Christie, Karen R.; Hong, Eurie L.; Cherry, J. Michael

    2011-01-01

    The quest to characterize each of the genes of the yeast Saccharomyces cerevisiae has propelled the development and application of novel high-throughput (HTP) experimental techniques. To handle the enormous amount of information generated by these techniques, new bioinformatics tools and resources are needed. Gene Ontology (GO) annotations curated by the Saccharomyces Genome Database (SGD) have facilitated the development of algorithms that analyze HTP data and help predict functions for poorly characterized genes in S. cerevisiae and other organisms. Here, we describe how published results are incorporated into GO annotations at SGD and why researchers can benefit from using these resources wisely to analyze their HTP data and predict gene functions. PMID:19577472

  1. Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments.

    PubMed

    Haas, Brian J; Salzberg, Steven L; Zhu, Wei; Pertea, Mihaela; Allen, Jonathan E; Orvis, Joshua; White, Owen; Buell, C Robin; Wortman, Jennifer R

    2008-01-11

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

    SciTech Connect

    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.

  3. Comprehensive functional annotation of 77 prostate cancer risk loci.

    PubMed

    Hazelett, Dennis J; Rhie, Suhn Kyong; Gaddis, Malaina; Yan, Chunli; Lakeland, Daniel L; Coetzee, Simon G; Henderson, Brian E; Noushmehr, Houtan; Cozen, Wendy; Kote-Jarai, Zsofia; Eeles, Rosalind A; Easton, Douglas F; Haiman, Christopher A; Lu, Wange; Farnham, Peggy J; Coetzee, Gerhard A

    2014-01-01

    Genome-wide association studies (GWAS) have revolutionized the field of cancer genetics, but the causal links between increased genetic risk and onset/progression of disease processes remain to be identified. Here we report the first step in such an endeavor for prostate cancer. We provide a comprehensive annotation of the 77 known risk loci, based upon highly correlated variants in biologically relevant chromatin annotations--we identified 727 such potentially functional SNPs. We also provide a detailed account of possible protein disruption, microRNA target sequence disruption and regulatory response element disruption of all correlated SNPs at r(2) ≥ 0.88%. 88% of the 727 SNPs fall within putative enhancers, and many alter critical residues in the response elements of transcription factors known to be involved in prostate biology. We define as risk enhancers those regions with enhancer chromatin biofeatures in prostate-derived cell lines with prostate-cancer correlated SNPs. To aid the identification of these enhancers, we performed genomewide ChIP-seq for H3K27-acetylation, a mark of actively engaged enhancers, as well as the transcription factor TCF7L2. We analyzed in depth three variants in risk enhancers, two of which show significantly altered androgen sensitivity in LNCaP cells. This includes rs4907792, that is in linkage disequilibrium (r(2) = 0.91) with an eQTL for NUDT11 (on the X chromosome) in prostate tissue, and rs10486567, the index SNP in intron 3 of the JAZF1 gene on chromosome 7. Rs4907792 is within a critical residue of a strong consensus androgen response element that is interrupted in the protective allele, resulting in a 56% decrease in its androgen sensitivity, whereas rs10486567 affects both NKX3-1 and FOXA-AR motifs where the risk allele results in a 39% increase in basal activity and a 28% fold-increase in androgen stimulated enhancer activity. Identification of such enhancer variants and their potential target genes represents a

  4. Functional modelling of an equine bronchoalveolar lavage fluid proteome provides experimental confirmation and functional annotation of equine genome sequences.

    PubMed

    Bright, L A; Mujahid, N; Nanduri, B; McCarthy, F M; Costa, L R R; Burgess, S C; Swiderski, C E

    2011-08-01

    The equine genome sequence enables the use of high-throughput genomic technologies in equine research, but accurate identification of expressed gene products and interpreting their biological relevance require additional structural and functional genome annotation. Here, we employ the equine genome sequence to identify predicted and known proteins using proteomics and model these proteins into biological pathways, identifying 582 proteins in normal cell-free equine bronchoalveolar lavage fluid (BALF). We improved structural and functional annotation by directly confirming the in vivo expression of 558 (96%) proteins, which were computationally predicted previously, and adding Gene Ontology (GO) annotations for 174 proteins, 108 of which lacked functional annotation. Bronchoalveolar lavage is commonly used to investigate equine respiratory disease, leading us to model the associated proteome and its biological functions. Modelling of protein functions using Ingenuity Pathway Analysis identified carbohydrate metabolism, cell-to-cell signalling, cellular function, inflammatory response, organ morphology, lipid metabolism and cellular movement as key biological processes in normal equine BALF. Comparative modelling of protein functions in normal cell-free bronchoalveolar lavage proteomes from horse, human, and mouse, performed by grouping GO terms sharing common ancestor terms, confirms conservation of functions across species. Ninety-one of 92 human GO categories and 105 of 109 mouse GO categories were conserved in the horse. Our approach confirms the utility of the equine genome sequence to characterize protein networks without antibodies or mRNA quantification, highlights the need for continued structural and functional annotation of the equine genome and provides a framework for equine researchers to aid in the annotation effort.

  5. TheViral MetaGenome Annotation Pipeline(VMGAP):an automated tool for the functional annotation of viral Metagenomic shotgun sequencing data

    PubMed Central

    Lorenzi, Hernan A.; Hoover, Jeff; Inman, Jason; Safford, Todd; Murphy, Sean; Kagan, Leonid; Williamson, Shannon J.

    2011-01-01

    In the past few years, the field of metagenomics has been growing at an accelerated pace, particularly in response to advancements in new sequencing technologies. The large volume of sequence data from novel organisms generated by metagenomic projects has triggered the development of specialized databases and tools focused on particular groups of organisms or data types. Here we describe a pipeline for the functional annotation of viral metagenomic sequence data. The Viral MetaGenome Annotation Pipeline (VMGAP) pipeline takes advantage of a number of specialized databases, such as collections of mobile genetic elements and environmental metagenomes to improve the classification and functional prediction of viral gene products. The pipeline assigns a functional term to each predicted protein sequence following a suite of comprehensive analyses whose results are ranked according to a priority rules hierarchy. Additional annotation is provided in the form of enzyme commission (EC) numbers, GO/MeGO terms and Hidden Markov Models together with supporting evidence. PMID:21886867

  6. Assessment of protein set coherence using functional annotations

    PubMed Central

    Chagoyen, Monica; Carazo, Jose M; Pascual-Montano, Alberto

    2008-01-01

    Background Analysis of large-scale experimental datasets frequently produces one or more sets of proteins that are subsequently mined for functional interpretation and validation. To this end, a number of computational methods have been devised that rely on the analysis of functional annotations. Although current methods provide valuable information (e.g. significantly enriched annotations, pairwise functional similarities), they do not specifically measure the degree of homogeneity of a protein set. Results In this work we present a method that scores the degree of functional homogeneity, or coherence, of a set of proteins on the basis of the global similarity of their functional annotations. The method uses statistical hypothesis testing to assess the significance of the set in the context of the functional space of a reference set. As such, it can be used as a first step in the validation of sets expected to be homogeneous prior to further functional interpretation. Conclusion We evaluate our method by analysing known biologically relevant sets as well as random ones. The known relevant sets comprise macromolecular complexes, cellular components and pathways described for Saccharomyces cerevisiae, which are mostly significantly coherent. Finally, we illustrate the usefulness of our approach for validating 'functional modules' obtained from computational analysis of protein-protein interaction networks. Matlab code and supplementary data are available at PMID:18937846

  7. Metabolomics as a Hypothesis-Generating Functional Genomics Tool for the Annotation of Arabidopsis thaliana Genes of “Unknown Function”

    PubMed Central

    Quanbeck, Stephanie M.; Brachova, Libuse; Campbell, Alexis A.; Guan, Xin; Perera, Ann; He, Kun; Rhee, Seung Y.; Bais, Preeti; Dickerson, Julie A.; Dixon, Philip; Wohlgemuth, Gert; Fiehn, Oliver; Barkan, Lenore; Lange, Iris; Lange, B. Markus; Lee, Insuk; Cortes, Diego; Salazar, Carolina; Shuman, Joel; Shulaev, Vladimir; Huhman, David V.; Sumner, Lloyd W.; Roth, Mary R.; Welti, Ruth; Ilarslan, Hilal; Wurtele, Eve S.; Nikolau, Basil J.

    2012-01-01

    Metabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs. PMID:22645570

  8. Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database.

    PubMed

    Drabkin, Harold J; Blake, Judith A

    2012-01-01

    The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as 'GO' or 'homology' or 'phenotype'. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as 'papers selected for GO that refer to genes with NO GO annotation'. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported

  9. High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource.

    PubMed

    Seaver, Samuel M D; Gerdes, Svetlana; Frelin, Océane; Lerma-Ortiz, Claudia; Bradbury, Louis M T; Zallot, Rémi; Hasnain, Ghulam; Niehaus, Thomas D; El Yacoubi, Basma; Pasternak, Shiran; Olson, Robert; Pusch, Gordon; Overbeek, Ross; Stevens, Rick; de Crécy-Lagard, Valérie; Ware, Doreen; Hanson, Andrew D; Henry, Christopher S

    2014-07-01

    The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed.

  10. Optimizing high performance computing workflow for protein functional annotation.

    PubMed

    Stanberry, Larissa; Rekepalli, Bhanu; Liu, Yuan; Giblock, Paul; Higdon, Roger; Montague, Elizabeth; Broomall, William; Kolker, Natali; Kolker, Eugene

    2014-09-10

    Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data.

  11. Assessing the impact of comparative genomic sequence data on the functional annotation of the Drosophila genome

    PubMed Central

    Bergman, Casey M; Pfeiffer, Barret D; Rincón-Limas, Diego E; Hoskins, Roger A; Gnirke, Andreas; Mungall, Chris J; Wang, Adrienne M; Kronmiller, Brent; Pacleb, Joanne; Park, Soo; Stapleton, Mark; Wan, Kenneth; George, Reed A; de Jong, Pieter J; Botas, Juan; Rubin, Gerald M; Celniker, Susan E

    2002-01-01

    Background It is widely accepted that comparative sequence data can aid the functional annotation of genome sequences; however, the most informative species and features of genome evolution for comparison remain to be determined. Results We analyzed conservation in eight genomic regions (apterous, even-skipped, fushi tarazu, twist, and Rhodopsins 1, 2, 3 and 4) from four Drosophila species (D. erecta, D. pseudoobscura, D. willistoni, and D. littoralis) covering more than 500 kb of the D. melanogaster genome. All D. melanogaster genes (and 78-82% of coding exons) identified in divergent species such as D. pseudoobscura show evidence of functional constraint. Addition of a third species can reveal functional constraint in otherwise non-significant pairwise exon comparisons. Microsynteny is largely conserved, with rearrangement breakpoints, novel transposable element insertions, and gene transpositions occurring in similar numbers. Rates of amino-acid substitution are higher in uncharacterized genes relative to genes that have previously been studied. Conserved non-coding sequences (CNCSs) tend to be spatially clustered with conserved spacing between CNCSs, and clusters of CNCSs can be used to predict enhancer sequences. Conclusions Our results provide the basis for choosing species whose genome sequences would be most useful in aiding the functional annotation of coding and cis-regulatory sequences in Drosophila. Furthermore, this work shows how decoding the spatial organization of conserved sequences, such as the clustering of CNCSs, can complement efforts to annotate eukaryotic genomes on the basis of sequence conservation alone. PMID:12537575

  12. Gene Model Annotations for Drosophila melanogaster: The Rule-Benders

    PubMed Central

    Crosby, Madeline A.; Gramates, L. Sian; dos Santos, Gilberto; Matthews, Beverley B.; St. Pierre, Susan E.; Zhou, Pinglei; Schroeder, Andrew J.; Falls, Kathleen; Emmert, David B.; Russo, Susan M.; Gelbart, William M.

    2015-01-01

    In the context of the FlyBase annotated gene models in Drosophila melanogaster, we describe the many exceptional cases we have curated from the literature or identified in the course of FlyBase analysis. These range from atypical but common examples such as dicistronic and polycistronic transcripts, noncanonical splices, trans-spliced transcripts, noncanonical translation starts, and stop-codon readthroughs, to single exceptional cases such as ribosomal frameshifting and HAC1-type intron processing. In FlyBase, exceptional genes and transcripts are flagged with Sequence Ontology terms and/or standardized comments. Because some of the rule-benders create problems for handlers of high-throughput data, we discuss plans for flagging these cases in bulk data downloads. PMID:26109356

  13. The H-Invitational Database (H-InvDB), a comprehensive annotation resource for human genes and transcripts.

    PubMed

    Yamasaki, Chisato; Murakami, Katsuhiko; Fujii, Yasuyuki; Sato, Yoshiharu; Harada, Erimi; Takeda, Jun-ichi; Taniya, Takayuki; Sakate, Ryuichi; Kikugawa, Shingo; Shimada, Makoto; Tanino, Motohiko; Koyanagi, Kanako O; Barrero, Roberto A; Gough, Craig; Chun, Hong-Woo; Habara, Takuya; Hanaoka, Hideki; Hayakawa, Yosuke; Hilton, Phillip B; Kaneko, Yayoi; Kanno, Masako; Kawahara, Yoshihiro; Kawamura, Toshiyuki; Matsuya, Akihiro; Nagata, Naoki; Nishikata, Kensaku; Noda, Akiko Ogura; Nurimoto, Shin; Saichi, Naomi; Sakai, Hiroaki; Sanbonmatsu, Ryoko; Shiba, Rie; Suzuki, Mami; Takabayashi, Kazuhiko; Takahashi, Aiko; Tamura, Takuro; Tanaka, Masayuki; Tanaka, Susumu; Todokoro, Fusano; Yamaguchi, Kaori; Yamamoto, Naoyuki; Okido, Toshihisa; Mashima, Jun; Hashizume, Aki; Jin, Lihua; Lee, Kyung-Bum; Lin, Yi-Chueh; Nozaki, Asami; Sakai, Katsunaga; Tada, Masahito; Miyazaki, Satoru; Makino, Takashi; Ohyanagi, Hajime; Osato, Naoki; Tanaka, Nobuhiko; Suzuki, Yoshiyuki; Ikeo, Kazuho; Saitou, Naruya; Sugawara, Hideaki; O'Donovan, Claire; Kulikova, Tamara; Whitfield, Eleanor; Halligan, Brian; Shimoyama, Mary; Twigger, Simon; Yura, Kei; Kimura, Kouichi; Yasuda, Tomohiro; Nishikawa, Tetsuo; Akiyama, Yutaka; Motono, Chie; Mukai, Yuri; Nagasaki, Hideki; Suwa, Makiko; Horton, Paul; Kikuno, Reiko; Ohara, Osamu; Lancet, Doron; Eveno, Eric; Graudens, Esther; Imbeaud, Sandrine; Debily, Marie Anne; Hayashizaki, Yoshihide; Amid, Clara; Han, Michael; Osanger, Andreas; Endo, Toshinori; Thomas, Michael A; Hirakawa, Mika; Makalowski, Wojciech; Nakao, Mitsuteru; Kim, Nam-Soon; Yoo, Hyang-Sook; De Souza, Sandro J; Bonaldo, Maria de Fatima; Niimura, Yoshihito; Kuryshev, Vladimir; Schupp, Ingo; Wiemann, Stefan; Bellgard, Matthew; Shionyu, Masafumi; Jia, Libin; Thierry-Mieg, Danielle; Thierry-Mieg, Jean; Wagner, Lukas; Zhang, Qinghua; Go, Mitiko; Minoshima, Shinsei; Ohtsubo, Masafumi; Hanada, Kousuke; Tonellato, Peter; Isogai, Takao; Zhang, Ji; Lenhard, Boris; Kim, Sangsoo; Chen, Zhu; Hinz, Ursula; Estreicher, Anne; Nakai, Kenta; Makalowska, Izabela; Hide, Winston; Tiffin, Nicola; Wilming, Laurens; Chakraborty, Ranajit; Soares, Marcelo Bento; Chiusano, Maria Luisa; Suzuki, Yutaka; Auffray, Charles; Yamaguchi-Kabata, Yumi; Itoh, Takeshi; Hishiki, Teruyoshi; Fukuchi, Satoshi; Nishikawa, Ken; Sugano, Sumio; Nomura, Nobuo; Tateno, Yoshio; Imanishi, Tadashi; Gojobori, Takashi

    2008-01-01

    Here we report the new features and improvements in our latest release of the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/), a comprehensive annotation resource for human genes and transcripts. H-InvDB, originally developed as an integrated database of the human transcriptome based on extensive annotation of large sets of full-length cDNA (FLcDNA) clones, now provides annotation for 120 558 human mRNAs extracted from the International Nucleotide Sequence Databases (INSD), in addition to 54 978 human FLcDNAs, in the latest release H-InvDB_4.6. We mapped those human transcripts onto the human genome sequences (NCBI build 36.1) and determined 34 699 human gene clusters, which could define 34 057 (98.1%) protein-coding and 642 (1.9%) non-protein-coding loci; 858 (2.5%) transcribed loci overlapped with predicted pseudogenes. For all these transcripts and genes, we provide comprehensive annotation including gene structures, gene functions, alternative splicing variants, functional non-protein-coding RNAs, functional domains, predicted sub cellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs, co-localization with orphan diseases, gene expression profiles, orthologous genes, protein-protein interactions (PPI) and annotation for gene families. The current H-InvDB annotation resources consist of two main views: Transcript view and Locus view and eight sub-databases: the DiseaseInfo Viewer, H-ANGEL, the Clustering Viewer, G-integra, the TOPO Viewer, Evola, the PPI view and the Gene family/group.

  14. The H-Invitational Database (H-InvDB), a comprehensive annotation resource for human genes and transcripts*

    PubMed Central

    2008-01-01

    Here we report the new features and improvements in our latest release of the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/), a comprehensive annotation resource for human genes and transcripts. H-InvDB, originally developed as an integrated database of the human transcriptome based on extensive annotation of large sets of full-length cDNA (FLcDNA) clones, now provides annotation for 120 558 human mRNAs extracted from the International Nucleotide Sequence Databases (INSD), in addition to 54 978 human FLcDNAs, in the latest release H-InvDB_4.6. We mapped those human transcripts onto the human genome sequences (NCBI build 36.1) and determined 34 699 human gene clusters, which could define 34 057 (98.1%) protein-coding and 642 (1.9%) non-protein-coding loci; 858 (2.5%) transcribed loci overlapped with predicted pseudogenes. For all these transcripts and genes, we provide comprehensive annotation including gene structures, gene functions, alternative splicing variants, functional non-protein-coding RNAs, functional domains, predicted sub cellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs, co-localization with orphan diseases, gene expression profiles, orthologous genes, protein–protein interactions (PPI) and annotation for gene families. The current H-InvDB annotation resources consist of two main views: Transcript view and Locus view and eight sub-databases: the DiseaseInfo Viewer, H-ANGEL, the Clustering Viewer, G-integra, the TOPO Viewer, Evola, the PPI view and the Gene family/group. PMID:18089548

  15. miRDB: an online resource for microRNA target prediction and functional annotations.

    PubMed

    Wong, Nathan; Wang, Xiaowei

    2015-01-01

    MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.

  16. Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis.

    PubMed

    Zhu, Yafeng; Engström, Pär G; Tellgren-Roth, Christian; Baudo, Charles D; Kennell, John C; Sun, Sheng; Billmyre, R Blake; Schröder, Markus S; Andersson, Anna; Holm, Tina; Sigurgeirsson, Benjamin; Wu, Guangxi; Sankaranarayanan, Sundar Ram; Siddharthan, Rahul; Sanyal, Kaustuv; Lundeberg, Joakim; Nystedt, Björn; Boekhout, Teun; Dawson, Thomas L; Heitman, Joseph; Scheynius, Annika; Lehtiö, Janne

    2017-01-18

    Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies.

  17. Functional annotation and kinetic characterization of PhnO from Salmonella enterica.

    PubMed Central

    Errey, James C.; Blanchard, John S.

    2008-01-01

    Phosphorus is an essential nutrient for all living organisms. Under conditions of inorganic phosphate starvation, genes from the Pho regulon are induced allowing microorganisms to use phosphonates as a source of phosphorus. The phnO gene was previously annotated as a transcriptional regulator of unknown function due to sequence homology with members of the GCN5-related N-acyltransferase family (GNAT). PhnO can now be functionally annotated as an aminoalkylphosphonic acid N-acetyltransferase which is able to acetylate a range of aminoalkylphosphonic acids. Studies revealed that PhnO proceeds via an ordered, sequential kinetic mechanism with acetyl-CoA binding first followed by aminoalkylphosphonate. Attack by the amine on the thioester of AcCoA generates the tetrahedral intermediate that collapses to generate the products. The enzyme also requires a divalent metal ion for activity, which is the first example of this requirement for a GNAT family member. PMID:16503658

  18. Functional annotation of deubiquitinating enzymes using RNA interference.

    PubMed

    Dirac, Annette M G; Nijman, Sebastian M B; Brummelkamp, Thijn R; Bernards, René

    2005-01-01

    Protein ubiquitination is a dynamic process, depending on a tightly regulated balance between the activity of ubiquitin ligases and their antagonists, the ubiquitin-specific proteases or deubiquitinating enzymes. The family of ubiquitin ligases has been studied intensively and it is well established that their deregulation contributes to diverse disease processes, including cancer. Much less is known about the function and regulation of the large group of deubiquitinating enzymes. This chapter describes how RNA interference against deubiquitinating enzymes can be used to elucidate their function. The application of this technology will greatly improve the functional annotation of this family of proteases.

  19. Incorporating the human gene annotations in different databases significantly improved transcriptomic and genetic analyses.

    PubMed

    Chen, Geng; Wang, Charles; Shi, Leming; Qu, Xiongfei; Chen, Jiwei; Yang, Jianmin; Shi, Caiping; Chen, Long; Zhou, Peiying; Ning, Baitang; Tong, Weida; Shi, Tieliu

    2013-04-01

    Human gene annotation is crucial for conducting transcriptomic and genetic studies; however, the impacts of human gene annotations in diverse databases on related studies have been less evaluated. To enable full use of various human annotation resources and better understand the human transcriptome, here we systematically compare the human annotations present in RefSeq, Ensembl (GENCODE), and AceView on diverse transcriptomic and genetic analyses. We found that the human gene annotations in the three databases are far from complete. Although Ensembl and AceView annotated more genes than RefSeq, more than 15,800 genes from Ensembl (or AceView) are within the intergenic and intronic regions of AceView (or Ensembl) annotation. The human transcriptome annotations in RefSeq, Ensembl, and AceView had distinct effects on short-read mapping, gene and isoform expression profiling, and differential expression calling. Furthermore, our findings indicate that the integrated annotation of these databases can obtain a more complete gene set and significantly enhance those transcriptomic analyses. We also observed that many more known SNPs were located within genes annotated in Ensembl and AceView than in RefSeq. In particular, 1033 of 3041 trait/disease-associated SNPs involved in about 200 human traits/diseases that were previously reported to be in RefSeq intergenic regions could be relocated within Ensembl and AceView genes. Our findings illustrate that a more complete transcriptome generated by incorporating human gene annotations in diverse databases can strikingly improve the overall results of transcriptomic and genetic studies.

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

    PubMed Central

    2012-01-01

    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/. PMID:22852583

  1. Protein function annotation by local binding site surface similarity.

    PubMed

    Spitzer, Russell; Cleves, Ann E; Varela, Rocco; Jain, Ajay N

    2014-04-01

    Hundreds of protein crystal structures exist for proteins whose function cannot be confidently determined from sequence similarity. Surflex-PSIM, a previously reported surface-based protein similarity algorithm, provides an alternative method for hypothesizing function for such proteins. The method now supports fully automatic binding site detection and is fast enough to screen comprehensive databases of protein binding sites. The binding site detection methodology was validated on apo/holo cognate protein pairs, correctly identifying 91% of ligand binding sites in holo structures and 88% in apo structures where corresponding sites existed. For correctly detected apo binding sites, the cognate holo site was the most similar binding site 87% of the time. PSIM was used to screen a set of proteins that had poorly characterized functions at the time of crystallization, but were later biochemically annotated. Using a fully automated protocol, this set of 8 proteins was screened against ∼60,000 ligand binding sites from the PDB. PSIM correctly identified functional matches that predated query protein biochemical annotation for five out of the eight query proteins. A panel of 12 currently unannotated proteins was also screened, resulting in a large number of statistically significant binding site matches, some of which suggest likely functions for the poorly characterized proteins.

  2. Functional phylogenomics analysis of bacteria and archaea using consistent genome annotation with UniFam

    SciTech Connect

    Chai, Juanjuan; Kora, Guruprasad; Ahn, Tae-Hyuk; Hyatt, Doug; Pan, Chongle

    2014-01-01

    To supply some background, phylogenetic studies have provided detailed knowledge on the evolutionary mechanisms of genes and species in Bacteria and Archaea. However, the evolution of cellular functions, represented by metabolic pathways and biological processes, has not been systematically characterized. Many clades in the prokaryotic tree of life have now been covered by sequenced genomes in GenBank. This enables a large-scale functional phylogenomics study of many computationally inferred cellular functions across all sequenced prokaryotes. Our results show a total of 14,727 GenBank prokaryotic genomes were re-annotated using a new protein family database, UniFam, to obtain consistent functional annotations for accurate comparison. The functional profile of a genome was represented by the biological process Gene Ontology (GO) terms in its annotation. The GO term enrichment analysis differentiated the functional profiles between selected archaeal taxa. 706 prokaryotic metabolic pathways were inferred from these genomes using Pathway Tools and MetaCyc. The consistency between the distribution of metabolic pathways in the genomes and the phylogenetic tree of the genomes was measured using parsimony scores and retention indices. The ancestral functional profiles at the internal nodes of the phylogenetic tree were reconstructed to track the gains and losses of metabolic pathways in evolutionary history. In conclusion, our functional phylogenomics analysis shows divergent functional profiles of taxa and clades. Such function-phylogeny correlation stems from a set of clade-specific cellular functions with low parsimony scores. On the other hand, many cellular functions are sparsely dispersed across many clades with high parsimony scores. These different types of cellular functions have distinct evolutionary patterns reconstructed from the prokaryotic tree.

  3. Functional phylogenomics analysis of bacteria and archaea using consistent genome annotation with UniFam

    DOE PAGES

    Chai, Juanjuan; Kora, Guruprasad; Ahn, Tae-Hyuk; ...

    2014-01-01

    To supply some background, phylogenetic studies have provided detailed knowledge on the evolutionary mechanisms of genes and species in Bacteria and Archaea. However, the evolution of cellular functions, represented by metabolic pathways and biological processes, has not been systematically characterized. Many clades in the prokaryotic tree of life have now been covered by sequenced genomes in GenBank. This enables a large-scale functional phylogenomics study of many computationally inferred cellular functions across all sequenced prokaryotes. Our results show a total of 14,727 GenBank prokaryotic genomes were re-annotated using a new protein family database, UniFam, to obtain consistent functional annotations for accuratemore » comparison. The functional profile of a genome was represented by the biological process Gene Ontology (GO) terms in its annotation. The GO term enrichment analysis differentiated the functional profiles between selected archaeal taxa. 706 prokaryotic metabolic pathways were inferred from these genomes using Pathway Tools and MetaCyc. The consistency between the distribution of metabolic pathways in the genomes and the phylogenetic tree of the genomes was measured using parsimony scores and retention indices. The ancestral functional profiles at the internal nodes of the phylogenetic tree were reconstructed to track the gains and losses of metabolic pathways in evolutionary history. In conclusion, our functional phylogenomics analysis shows divergent functional profiles of taxa and clades. Such function-phylogeny correlation stems from a set of clade-specific cellular functions with low parsimony scores. On the other hand, many cellular functions are sparsely dispersed across many clades with high parsimony scores. These different types of cellular functions have distinct evolutionary patterns reconstructed from the prokaryotic tree.« less

  4. Sequence- and Structure-Based Functional Annotation and Assessment of Metabolic Transporters in Aspergillus oryzae: A Representative Case Study

    PubMed Central

    Raethong, Nachon; Wong-ekkabut, Jirasak; Laoteng, Kobkul; Vongsangnak, Wanwipa

    2016-01-01

    Aspergillus oryzae is widely used for the industrial production of enzymes. In A. oryzae metabolism, transporters appear to play crucial roles in controlling the flux of molecules for energy generation, nutrients delivery, and waste elimination in the cell. While the A. oryzae genome sequence is available, transporter annotation remains limited and thus the connectivity of metabolic networks is incomplete. In this study, we developed a metabolic annotation strategy to understand the relationship between the sequence, structure, and function for annotation of A. oryzae metabolic transporters. Sequence-based analysis with manual curation showed that 58 genes of 12,096 total genes in the A. oryzae genome encoded metabolic transporters. Under consensus integrative databases, 55 unambiguous metabolic transporter genes were distributed into channels and pores (7 genes), electrochemical potential-driven transporters (33 genes), and primary active transporters (15 genes). To reveal the transporter functional role, a combination of homology modeling and molecular dynamics simulation was implemented to assess the relationship between sequence to structure and structure to function. As in the energy metabolism of A. oryzae, the H+-ATPase encoded by the AO090005000842 gene was selected as a representative case study of multilevel linkage annotation. Our developed strategy can be used for enhancing metabolic network reconstruction. PMID:27274991

  5. Combining heterogeneous data sources for accurate functional annotation of proteins

    PubMed Central

    2013-01-01

    Combining heterogeneous sources of data is essential for accurate prediction of protein function. The task is complicated by the fact that while sequence-based features can be readily compared across species, most other data are species-specific. In this paper, we present a multi-view extension to GOstruct, a structured-output framework for function annotation of proteins. The extended framework can learn from disparate data sources, with each data source provided to the framework in the form of a kernel. Our empirical results demonstrate that the multi-view framework is able to utilize all available information, yielding better performance than sequence-based models trained across species and models trained from collections of data within a given species. This version of GOstruct participated in the recent Critical Assessment of Functional Annotations (CAFA) challenge; since then we have significantly improved the natural language processing component of the method, which now provides performance that is on par with that provided by sequence information. The GOstruct framework is available for download at http://strut.sourceforge.net. PMID:23514123

  6. Mining GO annotations for improving annotation consistency.

    PubMed

    Faria, Daniel; Schlicker, Andreas; Pesquita, Catia; Bastos, Hugo; Ferreira, António E N; Albrecht, Mario; Falcão, André O

    2012-01-01

    Despite the structure and objectivity provided by the Gene Ontology (GO), the annotation of proteins is a complex task that is subject to errors and inconsistencies. Electronically inferred annotations in particular are widely considered unreliable. However, given that manual curation of all GO annotations is unfeasible, it is imperative to improve the quality of electronically inferred annotations. In this work, we analyze the full GO molecular function annotation of UniProtKB proteins, and discuss some of the issues that affect their quality, focusing particularly on the lack of annotation consistency. Based on our analysis, we estimate that 64% of the UniProtKB proteins are incompletely annotated, and that inconsistent annotations affect 83% of the protein functions and at least 23% of the proteins. Additionally, we present and evaluate a data mining algorithm, based on the association rule learning methodology, for identifying implicit relationships between molecular function terms. The goal of this algorithm is to assist GO curators in updating GO and correcting and preventing inconsistent annotations. Our algorithm predicted 501 relationships with an estimated precision of 94%, whereas the basic association rule learning methodology predicted 12,352 relationships with a precision below 9%.

  7. The development of PIPA: an integrated and automated pipeline for genome-wide protein function annotation

    PubMed Central

    Yu, Chenggang; Zavaljevski, Nela; Desai, Valmik; Johnson, Seth; Stevens, Fred J; Reifman, Jaques

    2008-01-01

    Background Automated protein function prediction methods are needed to keep pace with high-throughput sequencing. With the existence of many programs and databases for inferring different protein functions, a pipeline that properly integrates these resources will benefit from the advantages of each method. However, integrated systems usually do not provide mechanisms to generate customized databases to predict particular protein functions. Here, we describe a tool termed PIPA (Pipeline for Protein Annotation) that has these capabilities. Results PIPA annotates protein functions by combining the results of multiple programs and databases, such as InterPro and the Conserved Domains Database, into common Gene Ontology (GO) terms. The major algorithms implemented in PIPA are: (1) a profile database generation algorithm, which generates customized profile databases to predict particular protein functions, (2) an automated ontology mapping generation algorithm, which maps various classification schemes into GO, and (3) a consensus algorithm to reconcile annotations from the integrated programs and databases. PIPA's profile generation algorithm is employed to construct the enzyme profile database CatFam, which predicts catalytic functions described by Enzyme Commission (EC) numbers. Validation tests show that CatFam yields average recall and precision larger than 95.0%. CatFam is integrated with PIPA. We use an association rule mining algorithm to automatically generate mappings between terms of two ontologies from annotated sample proteins. Incorporating the ontologies' hierarchical topology into the algorithm increases the number of generated mappings. In particular, it generates 40.0% additional mappings from the Clusters of Orthologous Groups (COG) to EC numbers and a six-fold increase in mappings from COG to GO terms. The mappings to EC numbers show a very high precision (99.8%) and recall (96.6%), while the mappings to GO terms show moderate precision (80.0%) and

  8. Gene Ontology annotations: what they mean and where they come from

    PubMed Central

    Hill, David P; Smith, Barry; McAndrews-Hill, Monica S; Blake, Judith A

    2008-01-01

    To address the challenges of information integration and retrieval, the computational genomics community increasingly has come to rely on the methodology of creating annotations of scientific literature using terms from controlled structured vocabularies such as the Gene Ontology (GO). Here we address the question of what such annotations signify and of how they are created by working biologists. Our goal is to promote a better understanding of how the results of experiments are captured in annotations, in the hope that this will lead both to better representations of biological reality through annotation and ontology development and to more informed use of GO resources by experimental scientists. PMID:18460184

  9. Coding exon-structure aware realigner (CESAR) utilizes genome alignments for accurate comparative gene annotation

    PubMed Central

    Sharma, Virag; Elghafari, Anas; Hiller, Michael

    2016-01-01

    Identifying coding genes is an essential step in genome annotation. Here, we utilize existing whole genome alignments to detect conserved coding exons and then map gene annotations from one genome to many aligned genomes. We show that genome alignments contain thousands of spurious frameshifts and splice site mutations in exons that are truly conserved. To overcome these limitations, we have developed CESAR (Coding Exon-Structure Aware Realigner) that realigns coding exons, while considering reading frame and splice sites of each exon. CESAR effectively avoids spurious frameshifts in conserved genes and detects 91% of shifted splice sites. This results in the identification of thousands of additional conserved exons and 99% of the exons that lack inactivating mutations match real exons. Finally, to demonstrate the potential of using CESAR for comparative gene annotation, we applied it to 188 788 exons of 19 865 human genes to annotate human genes in 99 other vertebrates. These comparative gene annotations are available as a resource (http://bds.mpi-cbg.de/hillerlab/CESAR/). CESAR (https://github.com/hillerlab/CESAR/) can readily be applied to other alignments to accurately annotate coding genes in many other vertebrate and invertebrate genomes. PMID:27016733

  10. A New Strategy to Identify and Annotate Human RPE-Specific Gene Expression

    PubMed Central

    Booij, Judith C.; ten Brink, Jacoline B.; Swagemakers, Sigrid M. A.; Verkerk, Annemieke J. M. H.; Essing, Anke H. W.; van der Spek, Peter J.; Bergen, Arthur A. B.

    2010-01-01

    Background To identify and functionally annotate cell type-specific gene expression in the human retinal pigment epithelium (RPE), a key tissue involved in age-related macular degeneration and retinitis pigmentosa. Methodology RPE, photoreceptor and choroidal cells were isolated from selected freshly frozen healthy human donor eyes using laser microdissection. RNA isolation, amplification and hybridization to 44 k microarrays was carried out according to Agilent specifications. Bioinformatics was carried out using Rosetta Resolver, David and Ingenuity software. Principal Findings Our previous 22 k analysis of the RPE transcriptome showed that the RPE has high levels of protein synthesis, strong energy demands, is exposed to high levels of oxidative stress and a variable degree of inflammation. We currently use a complementary new strategy aimed at the identification and functional annotation of RPE-specific expressed transcripts. This strategy takes advantage of the multilayered cellular structure of the retina and overcomes a number of limitations of previous studies. In triplicate, we compared the transcriptomes of RPE, photoreceptor and choroidal cells and we deduced RPE specific expression. We identified at least 114 entries with RPE-specific gene expression. Thirty-nine of these 114 genes also show high expression in the RPE, comparison with the literature showed that 85% of these 39 were previously identified to be expressed in the RPE. In the group of 114 RPE specific genes there was an overrepresentation of genes involved in (membrane) transport, vision and ophthalmic disease. More fundamentally, we found RPE-specific involvement in the RAR-activation, retinol metabolism and GABA receptor signaling pathways. Conclusions In this study we provide a further specification and understanding of the RPE transcriptome by identifying and analyzing genes that are specifically expressed in the RPE. PMID:20479888

  11. Annotation of Proteins of Unknown Function: Initial Enzyme Results

    PubMed Central

    McKay, Talia; Hart, Kaitlin; Horn, Alison; Kessler, Haeja; Dodge, Greg; Bardhi, Keti; Bardhi, Kostandina; Mills, Jeffrey L.; Bernstein, Herbert J.; Craig, Paul A.

    2015-01-01

    Working with a combination of ProMOL (a plugin for PyMOL that searches a library of enzymatic motifs for local structural homologs), BLAST and Pfam (servers that identify global sequence homologs), and Dali (a server that identifies global structural homologs), we have begun the process of assigning functional annotations to the approximately 3,500 structures in the Protein Data Bank that are currently classified as having “unknown function”. Using a limited template library of 388 motifs, over 500 promising in silico matches have been identified by ProMOL, among which 65 exceptionally good matches have been identified. The characteristics of the exceptionally good matches are discussed. PMID:25630330

  12. RefSeq curation and annotation of antizyme and antizyme inhibitor genes in vertebrates

    PubMed Central

    Rajput, Bhanu; Murphy, Terence D.; Pruitt, Kim D.

    2015-01-01

    Polyamines are ubiquitous cations that are involved in regulating fundamental cellular processes such as cell growth and proliferation; hence, their intracellular concentration is tightly regulated. Antizyme and antizyme inhibitor have a central role in maintaining cellular polyamine levels. Antizyme is unique in that it is expressed via a novel programmed ribosomal frameshifting mechanism. Conventional computational tools are unable to predict a programmed frameshift, resulting in misannotation of antizyme transcripts and proteins on transcript and genomic sequences. Correct annotation of a programmed frameshifting event requires manual evaluation. Our goal was to provide an accurately curated and annotated Reference Sequence (RefSeq) data set of antizyme transcript and protein records across a broad taxonomic scope that would serve as standards for accurate representation of these gene products. As antizyme and antizyme inhibitor proteins are functionally connected, we also curated antizyme inhibitor genes to more fully represent the elegant biology of polyamine regulation. Manual review of genes for three members of the antizyme family and two members of the antizyme inhibitor family in 91 vertebrate organisms resulted in a total of 461 curated RefSeq records. PMID:26170238

  13. Towards Functional Annotation of the Preimplantation Transcriptome: An RNAi Screen in Mammalian Embryos

    PubMed Central

    Cui, Wei; Dai, Xiangpeng; Marcho, Chelsea; Han, Zhengbin; Zhang, Kun; Tremblay, Kimberly D.; Mager, Jesse

    2016-01-01

    With readily available transcriptome-wide data, understanding the role of each expressed gene is an essential next step. Although RNAi technologies allow for genome-wide screens in cell culture, these approaches cannot replace strategies for discovery in the embryo. Here we present, for the first time, a knockdown screen in mouse preimplantation embryos. Early mammalian development encompasses dynamic cellular, molecular and epigenetic events that are largely conserved from mouse to man. We assayed 712 genes for requirements during preimplantation. We identified 59 genes required for successful development or outgrowth and implantation. We have characterized each phenotype and revealed cellular, molecular, and lineage specific defects following knockdown of transcript. Induced network analyses demonstrate this as a valid approach to identify networks of genes that play important roles during preimplantation. Our approach provides a robust and efficient strategy towards identification of novel phenotypes during mouse preimplantation and facilitates functional annotation of the mammalian transcriptome. PMID:27869233

  14. Functional annotation of the vlinc class of non-coding RNAs using systems biology approach

    PubMed Central

    Laurent, Georges St.; Vyatkin, Yuri; Antonets, Denis; Ri, Maxim; Qi, Yao; Saik, Olga; Shtokalo, Dmitry; de Hoon, Michiel J.L.; Kawaji, Hideya; Itoh, Masayoshi; Lassmann, Timo; Arner, Erik; Forrest, Alistair R.R.; Nicolas, Estelle; McCaffrey, Timothy A.; Carninci, Piero; Hayashizaki, Yoshihide; Wahlestedt, Claes; Kapranov, Philipp

    2016-01-01

    Functionality of the non-coding transcripts encoded by the human genome is the coveted goal of the modern genomics research. While commonly relied on the classical methods of forward genetics, integration of different genomics datasets in a global Systems Biology fashion presents a more productive avenue of achieving this very complex aim. Here we report application of a Systems Biology-based approach to dissect functionality of a newly identified vast class of very long intergenic non-coding (vlinc) RNAs. Using highly quantitative FANTOM5 CAGE dataset, we show that these RNAs could be grouped into 1542 novel human genes based on analysis of insulators that we show here indeed function as genomic barrier elements. We show that vlincRNAs genes likely function in cis to activate nearby genes. This effect while most pronounced in closely spaced vlincRNA–gene pairs can be detected over relatively large genomic distances. Furthermore, we identified 101 vlincRNA genes likely involved in early embryogenesis based on patterns of their expression and regulation. We also found another 109 such genes potentially involved in cellular functions also happening at early stages of development such as proliferation, migration and apoptosis. Overall, we show that Systems Biology-based methods have great promise for functional annotation of non-coding RNAs. PMID:27001520

  15. Computational prediction of over-annotated protein-coding genes in the genome of Agrobacterium tumefaciens strain C58

    NASA Astrophysics Data System (ADS)

    Yu, Jia-Feng; Sui, Tian-Xiang; Wang, Hong-Mei; Wang, Chun-Ling; Jing, Li; Wang, Ji-Hua

    2015-12-01

    Agrobacterium tumefaciens strain C58 is a type of pathogen that can cause tumors in some dicotyledonous plants. Ever since the genome of A. tumefaciens strain C58 was sequenced, the quality of annotation of its protein-coding genes has been queried continually, because the annotation varies greatly among different databases. In this paper, the questionable hypothetical genes were re-predicted by integrating the TN curve and Z curve methods. As a result, 30 genes originally annotated as “hypothetical” were discriminated as being non-coding sequences. By testing the re-prediction program 10 times on data sets composed of the function-known genes, the mean accuracy of 99.99% and mean Matthews correlation coefficient value of 0.9999 were obtained. Further sequence analysis and COG analysis showed that the re-annotation results were very reliable. This work can provide an efficient tool and data resources for future studies of A. tumefaciens strain C58. Project supported by the National Natural Science Foundation of China (Grant Nos. 61302186 and 61271378) and the Funding from the State Key Laboratory of Bioelectronics of Southeast University.

  16. BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources

    PubMed Central

    2009-01-01

    Online gene annotation resources are indispensable for analysis of genomics data. However, the landscape of these online resources is highly fragmented, and scientists often visit dozens of these sites for each gene in a candidate gene list. Here, we introduce BioGPS http://biogps.gnf.org, a centralized gene portal for aggregating distributed gene annotation resources. Moreover, BioGPS embraces the principle of community intelligence, enabling any user to easily and directly contribute to the BioGPS platform. PMID:19919682

  17. Gene expression profiling in the rhesus macaque: methodology, annotation and data interpretation.

    PubMed

    Noriega, Nigel C; Kohama, Steven G; Urbanski, Henryk F

    2009-09-01

    Gene microarray analyses represent potentially effective means for high-throughput gene expression profiling in non-human primates. In the companion article, we emphasize effective experimental design based on the in vivo physiology of the rhesus macaque, whereas this article emphasizes considerations for gene annotation and data interpretation using gene microarray platforms from Affymetrix. Initial annotation of the rhesus genome array was based on Affymetrix human GeneChips. However, annotation revisions improve the precision with which rhesus transcripts are identified. Annotation of the rhesus GeneChip is under continuous revision with large percentages of probesets under multiple annotation systems having undergone multiple reassignments between March 2007 and November 2008. It is also important to consider that quantitation and comparison of gene expression levels across multiple chips requires appropriate normalization. External corroboration of microarray results using PCR-based methodology also requires validation of appropriate internal reference genes for normalization of expression values. Many tools are now freely available to aid investigators with microarray normalization and selection of internal reference genes to be used for independent corroboration of microarray results.

  18. Approaching the Functional Annotation of Fungal Virulence Factors Using Cross-Species Genetic Interaction Profiling

    PubMed Central

    Brown, Jessica C. S.; Madhani, Hiten D.

    2012-01-01

    In many human fungal pathogens, genes required for disease remain largely unannotated, limiting the impact of virulence gene discovery efforts. We tested the utility of a cross-species genetic interaction profiling approach to obtain clues to the molecular function of unannotated pathogenicity factors in the human pathogen Cryptococcus neoformans. This approach involves expression of C. neoformans genes of interest in each member of the Saccharomyces cerevisiae gene deletion library, quantification of their impact on growth, and calculation of the cross-species genetic interaction profiles. To develop functional predictions, we computed and analyzed the correlations of these profiles with existing genetic interaction profiles of S. cerevisiae deletion mutants. For C. neoformans LIV7, which has no S. cerevisiae ortholog, this profiling approach predicted an unanticipated role in the Golgi apparatus. Validation studies in C. neoformans demonstrated that Liv7 is a functional Golgi factor where it promotes the suppression of the exposure of a specific immunostimulatory molecule, mannose, on the cell surface, thereby inhibiting phagocytosis. The genetic interaction profile of another pathogenicity gene that lacks an S. cerevisiae ortholog, LIV6, strongly predicted a role in endosome function. This prediction was also supported by studies of the corresponding C. neoformans null mutant. Our results demonstrate the utility of quantitative cross-species genetic interaction profiling for the functional annotation of fungal pathogenicity proteins of unknown function including, surprisingly, those that are not conserved in sequence across fungi. PMID:23300468

  19. Approaching the functional annotation of fungal virulence factors using cross-species genetic interaction profiling.

    PubMed

    Brown, Jessica C S; Madhani, Hiten D

    2012-01-01

    In many human fungal pathogens, genes required for disease remain largely unannotated, limiting the impact of virulence gene discovery efforts. We tested the utility of a cross-species genetic interaction profiling approach to obtain clues to the molecular function of unannotated pathogenicity factors in the human pathogen Cryptococcus neoformans. This approach involves expression of C. neoformans genes of interest in each member of the Saccharomyces cerevisiae gene deletion library, quantification of their impact on growth, and calculation of the cross-species genetic interaction profiles. To develop functional predictions, we computed and analyzed the correlations of these profiles with existing genetic interaction profiles of S. cerevisiae deletion mutants. For C. neoformans LIV7, which has no S. cerevisiae ortholog, this profiling approach predicted an unanticipated role in the Golgi apparatus. Validation studies in C. neoformans demonstrated that Liv7 is a functional Golgi factor where it promotes the suppression of the exposure of a specific immunostimulatory molecule, mannose, on the cell surface, thereby inhibiting phagocytosis. The genetic interaction profile of another pathogenicity gene that lacks an S. cerevisiae ortholog, LIV6, strongly predicted a role in endosome function. This prediction was also supported by studies of the corresponding C. neoformans null mutant. Our results demonstrate the utility of quantitative cross-species genetic interaction profiling for the functional annotation of fungal pathogenicity proteins of unknown function including, surprisingly, those that are not conserved in sequence across fungi.

  20. GeneSense: a new approach for human gene annotation integrated with protein-protein interaction networks.

    PubMed

    Chen, Zhongzhong; Zhang, Tianhong; Lin, Jun; Yan, Zidan; Wang, Yongren; Zheng, Weiqiang; Weng, Kevin C

    2014-03-26

    Virtually all cellular functions involve protein-protein interactions (PPIs). As an increasing number of PPIs are identified and vast amount of information accumulated, researchers are finding different ways to interrogate the data and understand the interactions in context. However, it is widely recognized that a significant portion of the data is scattered, redundant, not considered high quality, and not readily accessible to researchers in a systematic fashion. In addition, it is challenging to identify the optimal protein targets in the current PPI networks. The GeneSense server was developed to integrate gene annotation and PPI networks in an expandable architecture that incorporates selected databases with the aim to assemble, analyze, evaluate and disseminate protein-protein association information in a comprehensive and user-friendly manner. Three network models including nodenet, leafnet and loopnet are used to identify the optimal protein targets in the complex networks. GeneSense is freely available at www.biomedsense.org/genesense.php.

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

    PubMed Central

    Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

    2015-01-01

    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 suggest that Csac

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

    PubMed

    Chowdhary, Nupoor; Selvaraj, Ashok; KrishnaKumaar, Lakshmi; Kumar, Gopal Ramesh

    2015-01-01

    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 suggest that Csac

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

    PubMed

    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.

  4. The SOFG Anatomy Entry List (SAEL): An Annotation Tool for Functional Genomics Data

    PubMed Central

    Parkinson, Helen; Aitken, Stuart; Baldock, Richard A.; Bard, Jonathan B. L.; Burger, Albert; Hayamizu, Terry F.; Rector, Alan; Ringwald, Martin; Rogers, Jeremy; Rosse, Cornelius; Stoeckert, Christian J.

    2004-01-01

    A great deal of data in functional genomics studies needs to be annotated with low-resolution anatomical terms. For example, gene expression assays based on manually dissected samples (microarray, SAGE, etc.) need high-level anatomical terms to describe sample origin. First-pass annotation in high-throughput assays (e.g. large-scale in situ gene expression screens or phenotype screens) and bibliographic applications, such as selection of keywords, would also benefit from a minimum set of standard anatomical terms. Although only simple terms are required, the researcher faces serious practical problems of inconsistency and confusion, given the different aims and the range of complexity of existing anatomy ontologies. A Standards and Ontologies for Functional Genomics (SOFG) group therefore initiated discussions between several of the major anatomical ontologies for higher vertebrates. As we report here, one result of these discussions is a simple, accessible, controlled vocabulary of gross anatomical terms, the SOFG Anatomy Entry List (SAEL). The SAEL is available from http://www.sofg.org and is intended as a resource for biologists, curators, bioinformaticians and developers of software supporting functional genomics. It can be used directly for annotation in the contexts described above. Importantly, each term is linked to the corresponding term in each of the major anatomy ontologies. Where the simple list does not provide enough detail or sophistication, therefore, the researcher can use the SAEL to choose the appropriate ontology and move directly to the relevant term as an entry point. The SAEL links will also be used to support computational access to the respective ontologies. PMID:18629134

  5. A Novel Method for Functional Annotation Prediction Based on Combination of Classification Methods

    PubMed Central

    Jung, Jaehee; Lee, Heung Ki

    2014-01-01

    Automated protein function prediction defines the designation of functions of unknown protein functions by using computational methods. This technique is useful to automatically assign gene functional annotations for undefined sequences in next generation genome analysis (NGS). NGS is a popular research method since high-throughput technologies such as DNA sequencing and microarrays have created large sets of genes. These huge sequences have greatly increased the need for analysis. Previous research has been based on the similarities of sequences as this is strongly related to the functional homology. However, this study aimed to designate protein functions by automatically predicting the function of the genome by utilizing InterPro (IPR), which can represent the properties of the protein family and groups of the protein function. Moreover, we used gene ontology (GO), which is the controlled vocabulary used to comprehensively describe the protein function. To define the relationship between IPR and GO terms, three pattern recognition techniques have been employed under different conditions, such as feature selection and weighted value, instead of a binary one. PMID:25133242

  6. Creating reference gene annotation for the mouse C57BL6/J genome assembly.

    PubMed

    Mudge, Jonathan M; Harrow, Jennifer

    2015-10-01

    Annotation on the reference genome of the C57BL6/J mouse has been an ongoing project ever since the draft genome was first published. Initially, the principle focus was on the identification of all protein-coding genes, although today the importance of describing long non-coding RNAs, small RNAs, and pseudogenes is recognized. Here, we describe the progress of the GENCODE mouse annotation project, which combines manual annotation from the HAVANA group with Ensembl computational annotation, alongside experimental and in silico validation pipelines from other members of the consortium. We discuss the more recent incorporation of next-generation sequencing datasets into this workflow, including the usage of mass-spectrometry data to potentially identify novel protein-coding genes. Finally, we will outline how the C57BL6/J genebuild can be used to gain insights into the variant sites that distinguish different mouse strains and species.

  7. Incorporating Functional Annotations for Fine-Mapping Causal Variants in a Bayesian Framework Using Summary Statistics.

    PubMed

    Chen, Wenan; McDonnell, Shannon K; Thibodeau, Stephen N; Tillmans, Lori S; Schaid, Daniel J

    2016-11-01

    Functional annotations have been shown to improve both the discovery power and fine-mapping accuracy in genome-wide association studies. However, the optimal strategy to incorporate the large number of existing annotations is still not clear. In this study, we propose a Bayesian framework to incorporate functional annotations in a systematic manner. We compute the maximum a posteriori solution and use cross validation to find the optimal penalty parameters. By extending our previous fine-mapping method CAVIARBF into this framework, we require only summary statistics as input. We also derived an exact calculation of Bayes factors using summary statistics for quantitative traits, which is necessary when a large proportion of trait variance is explained by the variants of interest, such as in fine mapping expression quantitative trait loci (eQTL). We compared the proposed method with PAINTOR using different strategies to combine annotations. Simulation results show that the proposed method achieves the best accuracy in identifying causal variants among the different strategies and methods compared. We also find that for annotations with moderate effects from a large annotation pool, screening annotations individually and then combining the top annotations can produce overly optimistic results. We applied these methods on two real data sets: a meta-analysis result of lipid traits and a cis-eQTL study of normal prostate tissues. For the eQTL data, incorporating annotations significantly increased the number of potential causal variants with high probabilities.

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

    PubMed

    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.

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

    PubMed

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

    2016-01-04

    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 .

  10. A spectral approach integrating functional genomic annotations for coding and noncoding variants.

    PubMed

    Ionita-Laza, Iuliana; McCallum, Kenneth; Xu, Bin; Buxbaum, Joseph D

    2016-02-01

    Over the past few years, substantial effort has been put into the functional annotation of variation in human genome sequences. Such annotations can have a critical role in identifying putatively causal variants for a disease or trait among the abundant natural variation that occurs at a locus of interest. The main challenges in using these various annotations include their large numbers and their diversity. Here we develop an unsupervised approach to integrate these different annotations into one measure of functional importance (Eigen) that, unlike most existing methods, is not based on any labeled training data. We show that the resulting meta-score has better discriminatory ability using disease-associated and putatively benign variants from published studies (in both coding and noncoding regions) than the recently proposed CADD score. Across varied scenarios, the Eigen score performs generally better than any single individual annotation, representing a powerful single functional score that can be incorporated in fine-mapping studies.

  11. Neurolinguistic Annotated Bibliography (Brain Research and Language Function) with Implications for Education.

    ERIC Educational Resources Information Center

    Davis, Wesley K.

    This bibliography presents annotations of 91 journal articles, books, chapters in books, and conference papers dating from 1967 to 1984 concerning neurolinguistics, language processing, and educational implications of brain research. The annotated bibliography includes eight items on neuroanatomy and language function; 20 items on neurolinguistics…

  12. GO-FAANG meeting: A gathering on functional annotation of animal genomes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The FAANG (Functional Annotation of Animal Genomes) Consortium recently held a Gathering On FAANG (GO-FAANG) Workshop in Washington, DC on October 7-8, 2015. This consortium is a grass-roots organization formed to advance the annotation of newly assembled genomes of non-model organisms (www.faang.or...

  13. SearchDOGS Bacteria, Software That Provides Automated Identification of Potentially Missed Genes in Annotated Bacterial Genomes

    PubMed Central

    ÓhÉigeartaigh, Seán S.; Armisén, David; Byrne, Kevin P.

    2014-01-01

    We report the development of SearchDOGS Bacteria, software to automatically detect missing genes in annotated bacterial genomes by combining BLAST searches with comparative genomics. Having successfully applied the approach to yeast genomes, we redeveloped SearchDOGS to function as a standalone, downloadable package, requiring only a set of GenBank annotation files as input. The software automatically generates a homology structure using reciprocal BLAST and a synteny-based method; this is followed by a scan of the entire genome of each species for unannotated genes. Results are provided in a HTML interface, providing coordinates, BLAST results, syntenic location, omega values (Ka/Ks, where Ks is the number of synonymous substitutions per synonymous site and Ka is the number of nonsynonymous substitutions per nonsynonymous site) for protein conservation estimates, and other information for each candidate gene. Using SearchDOGS Bacteria, we identified 155 gene candidates in the Shigella boydii sb227 genome, including 56 candidates of length < 60 codons. SearchDOGS Bacteria has two major advantages over currently available annotation software. First, it outperforms current methods in terms of sensitivity and is highly effective at identifying small or highly diverged genes. Second, as a freely downloadable package, it can be used with unpublished or confidential data. PMID:24659774

  14. In Silico Functional Pathway Annotation of 86 Established Prostate Cancer Risk Variants

    PubMed Central

    Loo, Lenora W. M.; Fong, Aaron Y. W.; Cheng, Iona; Le Marchand, Loïc

    2015-01-01

    Heritability is one of the strongest risk factors of prostate cancer, emphasizing the importance of the genetic contribution towards prostate cancer risk. To date, 86 established prostate cancer risk variants have been identified by genome-wide association studies (GWAS). To determine if these risk variants are located near genes that interact together in biological networks or pathways contributing to prostate cancer initiation or progression, we generated gene sets based on proximity to the 86 prostate cancer risk variants. We took two approaches to generate gene lists. The first strategy included all immediate flanking genes, up- and downstream of the risk variant, regardless of distance from the index variant, and the second strategy included genes closest to the index GWAS marker and to variants in high LD (r2 ≥0.8 in Europeans) with the index variant, within a 100 kb window up- and downstream. Pathway mapping of the two gene sets supported the importance of the androgen receptor-mediated signaling in prostate cancer biology. In addition, the hedgehog and Wnt/β-catenin signaling pathways were identified in pathway mapping for the flanking gene set. We also used the HaploReg resource to examine the 86 risk loci and variants high LD (r2 ≥0.8) for functional elements. We found that there was a 12.8 fold (p = 2.9 x 10-4) enrichment for enhancer motifs in a stem cell line and a 4.4 fold (p = 1.1 x 10-3) enrichment of DNase hypersensitivity in a prostate adenocarcinoma cell line, indicating that the risk and correlated variants are enriched for transcriptional regulatory motifs. Our pathway-based functional annotation of the prostate cancer risk variants highlights the potential regulatory function that GWAS risk markers, and their highly correlated variants, exert on genes. Our study also shows that these genes may function cooperatively in key signaling pathways in prostate cancer biology. PMID:25658610

  15. Structural and Functional Annotation of the Porcine Immunome

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The domestic pig is known as an excellent model for human immunology and the two species share many pathogens. Susceptibility to infectious disease is one of the major constraints on swine performance, yet the structure and function of genes comprising the pig immunome are not well-characterized. H...

  16. Functional annotation from the genome sequence of the giant panda.

    PubMed

    Huo, Tong; Zhang, Yinjie; Lin, Jianping

    2012-08-01

    The giant panda is one of the most critically endangered species due to the fragmentation and loss of its habitat. Studying the functions of proteins in this animal, especially specific trait-related proteins, is therefore necessary to protect the species. In this work, the functions of these proteins were investigated using the genome sequence of the giant panda. Data on 21,001 proteins and their functions were stored in the Giant Panda Protein Database, in which the proteins were divided into two groups: 20,179 proteins whose functions can be predicted by GeneScan formed the known-function group, whereas 822 proteins whose functions cannot be predicted by GeneScan comprised the unknown-function group. For the known-function group, we further classified the proteins by molecular function, biological process, cellular component, and tissue specificity. For the unknown-function group, we developed a strategy in which the proteins were filtered by cross-Blast to identify panda-specific proteins under the assumption that proteins related to the panda-specific traits in the unknown-function group exist. After this filtering procedure, we identified 32 proteins (2 of which are membrane proteins) specific to the giant panda genome as compared against the dog and horse genomes. Based on their amino acid sequences, these 32 proteins were further analyzed by functional classification using SVM-Prot, motif prediction using MyHits, and interacting protein prediction using the Database of Interacting Proteins. Nineteen proteins were predicted to be zinc-binding proteins, thus affecting the activities of nucleic acids. The 32 panda-specific proteins will be further investigated by structural and functional analysis.

  17. Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis.

    PubMed

    Narsai, Reena; Devenish, James; Castleden, Ian; Narsai, Kabir; Xu, Lin; Shou, Huixia; Whelan, James

    2013-12-01

    Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or 'expressology', thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au).

  18. Rice DB: an Oryza Information Portal linking annotation, subcellular location, function, expression, regulation, and evolutionary information for rice and Arabidopsis

    PubMed Central

    Narsai, Reena; Devenish, James; Castleden, Ian; Narsai, Kabir; Xu, Lin; Shou, Huixia; Whelan, James

    2013-01-01

    Omics research in Oryza sativa (rice) relies on the use of multiple databases to obtain different types of information to define gene function. We present Rice DB, an Oryza information portal that is a functional genomics database, linking gene loci to comprehensive annotations, expression data and the subcellular location of encoded proteins. Rice DB has been designed to integrate the direct comparison of rice with Arabidopsis (Arabidopsis thaliana), based on orthology or ‘expressology’, thus using and combining available information from two pre-eminent plant models. To establish Rice DB, gene identifiers (more than 40 types) and annotations from a variety of sources were compiled, functional information based on large-scale and individual studies was manually collated, hundreds of microarrays were analysed to generate expression annotations, and the occurrences of potential functional regulatory motifs in promoter regions were calculated. A range of computational subcellular localization predictions were also run for all putative proteins encoded in the rice genome, and experimentally confirmed protein localizations have been collated, curated and linked to functional studies in rice. A single search box allows anything from gene identifiers (for rice and/or Arabidopsis), motif sequences, subcellular location, to keyword searches to be entered, with the capability of Boolean searches (such as AND/OR). To demonstrate the utility of Rice DB, several examples are presented including a rice mitochondrial proteome, which draws on a variety of sources for subcellular location data within Rice DB. Comparisons of subcellular location, functional annotations, as well as transcript expression in parallel with Arabidopsis reveals examples of conservation between rice and Arabidopsis, using Rice DB (http://ricedb.plantenergy.uwa.edu.au). PMID:24147765

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

    PubMed

    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/.

  20. RNA-seq analysis of Quercus pubescens Leaves: de novo transcriptome assembly, annotation and functional markers development.

    PubMed

    Torre, Sara; Tattini, Massimiliano; Brunetti, Cecilia; Fineschi, Silvia; Fini, Alessio; Ferrini, Francesco; Sebastiani, Federico

    2014-01-01

    Quercus pubescens Willd., a species distributed from Spain to southwest Asia, ranks high for drought tolerance among European oaks. Q. pubescens performs a role of outstanding significance in most Mediterranean forest ecosystems, but few mechanistic studies have been conducted to explore its response to environmental constrains, due to the lack of genomic resources. In our study, we performed a deep transcriptomic sequencing in Q. pubescens leaves, including de novo assembly, functional annotation and the identification of new molecular markers. Our results are a pre-requisite for undertaking molecular functional studies, and may give support in population and association genetic studies. 254,265,700 clean reads were generated by the Illumina HiSeq 2000 platform, with an average length of 98 bp. De novo assembly, using CLC Genomics, produced 96,006 contigs, having a mean length of 618 bp. Sequence similarity analyses against seven public databases (Uniprot, NR, RefSeq and KOGs at NCBI, Pfam, InterPro and KEGG) resulted in 83,065 transcripts annotated with gene descriptions, conserved protein domains, or gene ontology terms. These annotations and local BLAST allowed identify genes specifically associated with mechanisms of drought avoidance. Finally, 14,202 microsatellite markers and 18,425 single nucleotide polymorphisms (SNPs) were, in silico, discovered in assembled and annotated sequences. We completed a successful global analysis of the Q. pubescens leaf transcriptome using RNA-seq. The assembled and annotated sequences together with newly discovered molecular markers provide genomic information for functional genomic studies in Q. pubescens, with special emphasis to response mechanisms to severe constrain of the Mediterranean climate. Our tools enable comparative genomics studies on other Quercus species taking advantage of large intra-specific ecophysiological differences.

  1. GOsummaries: an R Package for Visual Functional Annotation of Experimental Data.

    PubMed

    Kolde, Raivo; Vilo, Jaak

    2015-01-01

    Functional characterisation of gene lists using Gene Ontology (GO) enrichment analysis is a common approach in computational biology, since many analysis methods end up with a list of genes as a result. Often there can be hundreds of functional terms that are significantly associated with a single list of genes and proper interpretation of such results can be a challenging endeavour. There are methods to visualise and aid the interpretation of these results, but most of them are limited to the results associated with one list of genes. However, in practice the number of gene lists can be considerably higher and common tools are not effective in such situations. We introduce a novel R package, 'GOsummaries' that visualises the GO enrichment results as concise word clouds that can be combined together if the number of gene lists is larger. By also adding the graphs of corresponding raw experimental data, GOsummaries can create informative summary plots for various analyses such as differential expression or clustering. The case studies show that the GOsummaries plots allow rapid functional characterisation of complex sets of gene lists. The GOsummaries approach is particularly effective for Principal Component Analysis (PCA). By adding functional annotation to the principal components, GOsummaries improves  significantly the interpretability of PCA results. The GOsummaries layout for PCA can be effective even in situations where we cannot directly apply the GO analysis. For example, in case of metabolomics or metagenomics data it is possible to show the features with significant associations to the components instead of GO terms.   The GOsummaries package is available under GPL-2 licence at Bioconductor (http://www.bioconductor.org/packages/release/bioc/html/GOsummaries.html).

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

    PubMed Central

    2012-01-01

    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 content of the T. reesei genome

  3. Non-Gaussian Distributions Affect Identification of Expression Patterns, Functional Annotation, and Prospective Classification in Human Cancer Genomes

    PubMed Central

    Marko, Nicholas F.; Weil, Robert J.

    2012-01-01

    Introduction Gene expression data is often assumed to be normally-distributed, but this assumption has not been tested rigorously. We investigate the distribution of expression data in human cancer genomes and study the implications of deviations from the normal distribution for translational molecular oncology research. Methods We conducted a central moments analysis of five cancer genomes and performed empiric distribution fitting to examine the true distribution of expression data both on the complete-experiment and on the individual-gene levels. We used a variety of parametric and nonparametric methods to test the effects of deviations from normality on gene calling, functional annotation, and prospective molecular classification using a sixth cancer genome. Results Central moments analyses reveal statistically-significant deviations from normality in all of the analyzed cancer genomes. We observe as much as 37% variability in gene calling, 39% variability in functional annotation, and 30% variability in prospective, molecular tumor subclassification associated with this effect. Conclusions Cancer gene expression profiles are not normally-distributed, either on the complete-experiment or on the individual-gene level. Instead, they exhibit complex, heavy-tailed distributions characterized by statistically-significant skewness and kurtosis. The non-Gaussian distribution of this data affects identification of differentially-expressed genes, functional annotation, and prospective molecular classification. These effects may be reduced in some circumstances, although not completely eliminated, by using nonparametric analytics. This analysis highlights two unreliable assumptions of translational cancer gene expression analysis: that “small” departures from normality in the expression data distributions are analytically-insignificant and that “robust” gene-calling algorithms can fully compensate for these effects. PMID:23118863

  4. The DAWGPAWS pipeline for the annotation of genes and transposable elements in plant genomes

    PubMed Central

    Estill, James C; Bennetzen, Jeffrey L

    2009-01-01

    Background High quality annotation of the genes and transposable elements in complex genomes requires a human-curated integration of multiple sources of computational evidence. These evidences include results from a diversity of ab initio prediction programs as well as homology-based searches. Most of these programs operate on a single contiguous sequence at a time, and the results are generated in a diverse array of readable formats that must be translated to a standardized file format. These translated results must then be concatenated into a single source, and then presented in an integrated form for human curation. Results We have designed, implemented, and assessed a Perl-based workflow named DAWGPAWS for the generation of computational results for human curation of the genes and transposable elements in plant genomes. The use of DAWGPAWS was found to accelerate annotation of 80–200 kb wheat DNA inserts in bacterial artificial chromosome (BAC) vectors by approximately twenty-fold and to also significantly improve the quality of the annotation in terms of completeness and accuracy. Conclusion The DAWGPAWS genome annotation pipeline fills an important need in the annotation of plant genomes by generating computational evidences in a high throughput manner, translating these results to a common file format, and facilitating the human curation of these computational results. We have verified the value of DAWGPAWS by using this pipeline to annotate the genes and transposable elements in 220 BAC insertions from the hexaploid wheat genome (Triticum aestivum L.). DAWGPAWS can be applied to annotation efforts in other plant genomes with minor modifications of program-specific configuration files, and the modular design of the workflow facilitates integration into existing pipelines. PMID:19545381

  5. ORCAN-a web-based meta-server for real-time detection and functional annotation of orthologs.

    PubMed

    Zielezinski, Andrzej; Dziubek, Michal; Sliski, Jan; Karlowski, Wojciech M

    2017-01-05

    ORCAN (ORtholog sCANner) is a web-based meta-server for one-click evolutionary and functional annotation of protein sequences. The server combines information from the most popular orthology-prediction resources, including four tools and four online databases. Functional annotation utilizes five additional comparisons between the query and identified homologs, including: sequence similarity, protein domain architectures, functional motifs, Gene Ontology term assignments and a list of associated articles. Furthermore, the server uses a plurality-based rating system to evaluate the orthology relationships and to rank the reference proteins by their evolutionary and functional relevance to the query. Using a dataset of ∼1 million true yeast orthologs as a sample reference set, we show that combining multiple orthology-prediction tools in ORCAN increases the sensitivity and precision by 1-2 percent points.

  6. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences.

    PubMed

    Huerta-Cepas, Jaime; Szklarczyk, Damian; Forslund, Kristoffer; Cook, Helen; Heller, Davide; Walter, Mathias C; Rattei, Thomas; Mende, Daniel R; Sunagawa, Shinichi; Kuhn, Michael; Jensen, Lars Juhl; von Mering, Christian; Bork, Peer

    2016-01-04

    eggNOG is a public resource that provides Orthologous Groups (OGs) of proteins at different taxonomic levels, each with integrated and summarized functional annotations. Developments since the latest public release include changes to the algorithm for creating OGs across taxonomic levels, making nested groups hierarchically consistent. This allows for a better propagation of functional terms across nested OGs and led to the novel annotation of 95 890 previously uncharacterized OGs, increasing overall annotation coverage from 67% to 72%. The functional annotations of OGs have been expanded to also provide Gene Ontology terms, KEGG pathways and SMART/Pfam domains for each group. Moreover, eggNOG now provides pairwise orthology relationships within OGs based on analysis of phylogenetic trees. We have also incorporated a framework for quickly mapping novel sequences to OGs based on precomputed HMM profiles. Finally, eggNOG version 4.5 incorporates a novel data set spanning 2605 viral OGs, covering 5228 proteins from 352 viral proteomes. All data are accessible for bulk downloading, as a web-service, and through a completely redesigned web interface. The new access points provide faster searches and a number of new browsing and visualization capabilities, facilitating the needs of both experts and less experienced users. eggNOG v4.5 is available at http://eggnog.embl.de.

  7. Protein annotation as term categorization in the gene ontology using word proximity networks

    PubMed Central

    Verspoor, Karin; Cohn, Judith; Joslyn, Cliff; Mniszewski, Sue; Rechtsteiner, Andreas; Rocha, Luis M; Simas, Tiago

    2005-01-01

    Background We participated in the BioCreAtIvE Task 2, which addressed the annotation of proteins into the Gene Ontology (GO) based on the text of a given document and the selection of evidence text from the document justifying that annotation. We approached the task utilizing several combinations of two distinct methods: an unsupervised algorithm for expanding words associated with GO nodes, and an annotation methodology which treats annotation as categorization of terms from a protein's document neighborhood into the GO. Results The evaluation results indicate that the method for expanding words associated with GO nodes is quite powerful; we were able to successfully select appropriate evidence text for a given annotation in 38% of Task 2.1 queries by building on this method. The term categorization methodology achieved a precision of 16% for annotation within the correct extended family in Task 2.2, though we show through subsequent analysis that this can be improved with a different parameter setting. Our architecture proved not to be very successful on the evidence text component of the task, in the configuration used to generate the submitted results. Conclusion The initial results show promise for both of the methods we explored, and we are planning to integrate the methods more closely to achieve better results overall. PMID:15960833

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

    PubMed Central

    Crispim, Aline Camporez; Kelly, Matthew John; Guimarães, Simone Eliza Facioni; e Silva, Fabyano Fonseca; 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

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

    PubMed

    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.

  10. Seeing the forest for the trees: annotating small RNA producing genes in plants.

    PubMed

    Coruh, Ceyda; Shahid, Saima; Axtell, Michael J

    2014-04-01

    A key goal in genomics is the complete annotation of the expressed regions of the genome. In plants, substantial portions of the genome make regulatory small RNAs produced by Dicer-Like (DCL) proteins and utilized by Argonaute (AGO) proteins. These include miRNAs and various types of endogenous siRNAs. Small RNA-seq, enabled by cheap and fast DNA sequencing, has produced an enormous volume of data on plant miRNA and siRNA expression in recent years. In this review, we discuss recent progress in using small RNA-seq data to produce stable and reliable annotations of miRNA and siRNA genes in plants. In addition, we highlight key goals for the future of small RNA gene annotation in plants.

  11. A statistical framework for improving genomic annotations of prokaryotic essential genes.

    PubMed

    Deng, Jingyuan; Su, Shengchang; Lin, Xiaodong; Hassett, Daniel J; Lu, Long Jason

    2013-01-01

    Large-scale systematic analysis of gene essentiality is an important step closer toward unraveling the complex relationship between genotypes and phenotypes. Such analysis cannot be accomplished without unbiased and accurate annotations of essential genes. In current genomic databases, most of the essential gene annotations are derived from whole-genome transposon mutagenesis (TM), the most frequently used experimental approach for determining essential genes in microorganisms under defined conditions. However, there are substantial systematic biases associated with TM experiments. In this study, we developed a novel Poisson model-based statistical framework to simulate the TM insertion process and subsequently correct the experimental biases. We first quantitatively assessed the effects of major factors that potentially influence the accuracy of TM and subsequently incorporated relevant factors into the framework. Through iteratively optimizing parameters, we inferred the actual insertion events occurred and described each gene's essentiality on probability measure. Evaluated by the definite mapping of essential gene profile in Escherichia coli, our model significantly improved the accuracy of original TM datasets, resulting in more accurate annotations of essential genes. Our method also showed encouraging results in improving subsaturation level TM datasets. To test our model's broad applicability to other bacteria, we applied it to Pseudomonas aeruginosa PAO1 and Francisella tularensis novicida TM datasets. We validated our predictions by literature as well as allelic exchange experiments in PAO1. Our model was correct on six of the seven tested genes. Remarkably, among all three cases that our predictions contradicted the TM assignments, experimental validations supported our predictions. In summary, our method will be a promising tool in improving genomic annotations of essential genes and enabling large-scale explorations of gene essentiality. Our

  12. Improved white spruce (Picea glauca) genome assemblies and annotation of large gene families of conifer terpenoid and phenolic defense metabolism.

    PubMed

    Warren, René L; Keeling, Christopher I; Yuen, Macaire Man Saint; Raymond, Anthony; Taylor, Greg A; Vandervalk, Benjamin P; Mohamadi, Hamid; Paulino, Daniel; Chiu, Readman; Jackman, Shaun D; Robertson, Gordon; Yang, Chen; Boyle, Brian; Hoffmann, Margarete; Weigel, Detlef; Nelson, David R; Ritland, Carol; Isabel, Nathalie; Jaquish, Barry; Yanchuk, Alvin; Bousquet, Jean; Jones, Steven J M; MacKay, John; Birol, Inanc; Bohlmann, Joerg

    2015-07-01

    White spruce (Picea glauca), a gymnosperm tree, has been established as one of the models for conifer genomics. We describe the draft genome assemblies of two white spruce genotypes, PG29 and WS77111, innovative tools for the assembly of very large genomes, and the conifer genomics resources developed in this process. The two white spruce genotypes originate from distant geographic regions of western (PG29) and eastern (WS77111) North America, and represent elite trees in two Canadian tree-breeding programs. We present an update (V3 and V4) for a previously reported PG29 V2 draft genome assembly and introduce a second white spruce genome assembly for genotype WS77111. Assemblies of the PG29 and WS77111 genomes confirm the reconstructed white spruce genome size in the 20 Gbp range, and show broad synteny. Using the PG29 V3 assembly and additional white spruce genomics and transcriptomics resources, we performed MAKER-P annotation and meticulous expert annotation of very large gene families of conifer defense metabolism, the terpene synthases and cytochrome P450s. We also comprehensively annotated the white spruce mevalonate, methylerythritol phosphate and phenylpropanoid pathways. These analyses highlighted the large extent of gene and pseudogene duplications in a conifer genome, in particular for genes of secondary (i.e. specialized) metabolism, and the potential for gain and loss of function for defense and adaptation.

  13. Identification of novel biomass-degrading enzymes from genomic dark matter: Populating genomic sequence space with functional annotation.

    PubMed

    Piao, Hailan; Froula, Jeff; Du, Changbin; Kim, Tae-Wan; Hawley, Erik R; Bauer, Stefan; Wang, Zhong; Ivanova, Nathalia; Clark, Douglas S; Klenk, Hans-Peter; Hess, Matthias

    2014-08-01

    Although recent nucleotide sequencing technologies have significantly enhanced our understanding of microbial genomes, the function of ∼35% of genes identified in a genome currently remains unknown. To improve the understanding of microbial genomes and consequently of microbial processes it will be crucial to assign a function to this "genomic dark matter." Due to the urgent need for additional carbohydrate-active enzymes for improved production of transportation fuels from lignocellulosic biomass, we screened the genomes of more than 5,500 microorganisms for hypothetical proteins that are located in the proximity of already known cellulases. We identified, synthesized and expressed a total of 17 putative cellulase genes with insufficient sequence similarity to currently known cellulases to be identified as such using traditional sequence annotation techniques that rely on significant sequence similarity. The recombinant proteins of the newly identified putative cellulases were subjected to enzymatic activity assays to verify their hydrolytic activity towards cellulose and lignocellulosic biomass. Eleven (65%) of the tested enzymes had significant activity towards at least one of the substrates. This high success rate highlights that a gene context-based approach can be used to assign function to genes that are otherwise categorized as "genomic dark matter" and to identify biomass-degrading enzymes that have little sequence similarity to already known cellulases. The ability to assign function to genes that have no related sequence representatives with functional annotation will be important to enhance our understanding of microbial processes and to identify microbial proteins for a wide range of applications.

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

    PubMed

    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.

  15. Gene3D: Multi-domain annotations for protein sequence and comparative genome analysis.

    PubMed

    Lees, Jonathan G; Lee, David; Studer, Romain A; Dawson, Natalie L; Sillitoe, Ian; Das, Sayoni; Yeats, Corin; Dessailly, Benoit H; Rentzsch, Robert; Orengo, Christine A

    2014-01-01

    Gene3D (http://gene3d.biochem.ucl.ac.uk) is a database of protein domain structure annotations for protein sequences. Domains are predicted using a library of profile HMMs from 2738 CATH superfamilies. Gene3D assigns domain annotations to Ensembl and UniProt sequence sets including >6000 cellular genomes and >20 million unique protein sequences. This represents an increase of 45% in the number of protein sequences since our last publication. Thanks to improvements in the underlying data and pipeline, we see large increases in the domain coverage of sequences. We have expanded this coverage by integrating Pfam and SUPERFAMILY domain annotations, and we now resolve domain overlaps to provide highly comprehensive composite multi-domain architectures. To make these data more accessible for comparative genome analyses, we have developed novel search algorithms for searching genomes to identify related multi-domain architectures. In addition to providing domain family annotations, we have now developed a pipeline for 3D homology modelling of domains in Gene3D. This has been applied to the human genome and will be rolled out to other major organisms over the next year.

  16. Identification and computational annotation of genes differentially expressed in pulp development of Cocos nucifera L. by suppression subtractive hybridization

    PubMed Central

    2014-01-01

    Background Coconut (Cocos nucifera L.) is one of the world’s most versatile, economically important tropical crops. Little is known about the physiological and molecular basis of coconut pulp (endosperm) development and only a few coconut genes and gene product sequences are available in public databases. This study identified genes that were differentially expressed during development of coconut pulp and functionally annotated these identified genes using bioinformatics analysis. Results Pulp from three different coconut developmental stages was collected. Four suppression subtractive hybridization (SSH) libraries were constructed (forward and reverse libraries A and B between stages 1 and 2, and C and D between stages 2 and 3), and identified sequences were computationally annotated using Blast2GO software. A total of 1272 clones were obtained for analysis from four SSH libraries with 63% showing similarity to known proteins. Pairwise comparing of stage-specific gene ontology ids from libraries B-D, A-C, B-C and A-D showed that 32 genes were continuously upregulated and seven downregulated; 28 were transiently upregulated and 23 downregulated. KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis showed that 1-acyl-sn-glycerol-3-phosphate acyltransferase (LPAAT), phospholipase D, acetyl-CoA carboxylase carboxyltransferase beta subunit, 3-hydroxyisobutyryl-CoA hydrolase-like and pyruvate dehydrogenase E1 β subunit were associated with fatty acid biosynthesis or metabolism. Triose phosphate isomerase, cellulose synthase and glucan 1,3-β-glucosidase were related to carbohydrate metabolism, and phosphoenolpyruvate carboxylase was related to both fatty acid and carbohydrate metabolism. Of 737 unigenes, 103 encoded enzymes were involved in fatty acid and carbohydrate biosynthesis and metabolism, and a number of transcription factors and other interesting genes with stage-specific expression were confirmed by real-time PCR, with validation of the SSH results as

  17. Comparative mapping and genomic annotation of the bovine oncosuppressor gene WWOX.

    PubMed

    Manera, S; Bonfiglio, S; Malusà, A; Denis, C; Boussaha, M; Russo, V; Roperto, F; Perucatti, A; Di Meo, G P; Eggen, A; Ferretti, L

    2009-01-01

    WWOX (WW domain-containing oxidoreductase) is the gene mapping at FRA16D HSA16q23.1, the second most active common fragile site in the human genome. In this study we characterized at a detailed molecular level WWOX in the bovine genome. First, we sequenced cDNA from various tissues and obtained evidence in support of a 9-exon structure for the gene, similar to the human gene. Then, we recovered BACs using exon tags and annotated the gene to a >1-Mb genomic region of BTA18 using the Btau 4.0 genome assembly as a reference, thus resolving an issue related to exon 9, which is not included in the genomic annotation of the gene in the Entrez database. Finally, BACs spanning WWOX were used as FISH probes to obtain comparative mapping of the gene in Bos taurus, Bubalus bubalis, Ovis aries and Capra hircus to BTA18q12.1, BBU18q13, OAR14q12.1 and CHI18q12.1, respectively. Our data show that the chromosomal location of WWOX is conserved between man and 4 major domesticated species. Moreover, the annotation of the bovine gene also suggests a highly conserved genomic arrangement, including number and size of introns.

  18. The De Novo Transcriptome and Its Functional Annotation in the Seed Beetle Callosobruchus maculatus

    PubMed Central

    Sayadi, Ahmed; Immonen, Elina; Bayram, Helen

    2016-01-01

    Despite their unparalleled biodiversity, the genomic resources available for beetles (Coleoptera) remain relatively scarce. We present an integrative and high quality annotated transcriptome of the beetle Callosobruchus maculatus, an important and cosmopolitan agricultural pest as well as an emerging model species in ecology and evolutionary biology. Using Illumina sequencing technology, we sequenced 492 million read pairs generated from 51 samples of different developmental stages (larvae, pupae and adults) of C. maculatus. Reads were de novo assembled using the Trinity software, into a single combined assembly as well as into three separate assemblies based on data from the different developmental stages. The combined assembly generated 218,192 transcripts and 145,883 putative genes. Putative genes were annotated with the Blast2GO software and the Trinotate pipeline. In total, 33,216 putative genes were successfully annotated using Blastx against the Nr (non-redundant) database and 13,382 were assigned to 34,100 Gene Ontology (GO) terms. We classified 5,475 putative genes into Clusters of Orthologous Groups (COG) and 116 metabolic pathways maps were predicted based on the annotation. Our analyses suggested that the transcriptional specificity increases with ontogeny. For example, out of 33,216 annotated putative genes, 51 were only expressed in larvae, 63 only in pupae and 171 only in adults. Our study illustrates the importance of including samples from several developmental stages when the aim is to provide an integrative and high quality annotated transcriptome. Our results will represent an invaluable resource for those working with the ecology, evolution and pest control of C. maculatus, as well for comparative studies of the transcriptomics and genomics of beetles more generally. PMID:27442123

  19. The De Novo Transcriptome and Its Functional Annotation in the Seed Beetle Callosobruchus maculatus.

    PubMed

    Sayadi, Ahmed; Immonen, Elina; Bayram, Helen; Arnqvist, Göran

    2016-01-01

    Despite their unparalleled biodiversity, the genomic resources available for beetles (Coleoptera) remain relatively scarce. We present an integrative and high quality annotated transcriptome of the beetle Callosobruchus maculatus, an important and cosmopolitan agricultural pest as well as an emerging model species in ecology and evolutionary biology. Using Illumina sequencing technology, we sequenced 492 million read pairs generated from 51 samples of different developmental stages (larvae, pupae and adults) of C. maculatus. Reads were de novo assembled using the Trinity software, into a single combined assembly as well as into three separate assemblies based on data from the different developmental stages. The combined assembly generated 218,192 transcripts and 145,883 putative genes. Putative genes were annotated with the Blast2GO software and the Trinotate pipeline. In total, 33,216 putative genes were successfully annotated using Blastx against the Nr (non-redundant) database and 13,382 were assigned to 34,100 Gene Ontology (GO) terms. We classified 5,475 putative genes into Clusters of Orthologous Groups (COG) and 116 metabolic pathways maps were predicted based on the annotation. Our analyses suggested that the transcriptional specificity increases with ontogeny. For example, out of 33,216 annotated putative genes, 51 were only expressed in larvae, 63 only in pupae and 171 only in adults. Our study illustrates the importance of including samples from several developmental stages when the aim is to provide an integrative and high quality annotated transcriptome. Our results will represent an invaluable resource for those working with the ecology, evolution and pest control of C. maculatus, as well for comparative studies of the transcriptomics and genomics of beetles more generally.

  20. Variation analysis and gene annotation of eight MHC haplotypes: the MHC Haplotype Project.

    PubMed

    Horton, Roger; Gibson, Richard; Coggill, Penny; Miretti, Marcos; Allcock, Richard J; Almeida, Jeff; Forbes, Simon; Gilbert, James G R; Halls, Karen; Harrow, Jennifer L; Hart, Elizabeth; Howe, Kevin; Jackson, David K; Palmer, Sophie; Roberts, Anne N; Sims, Sarah; Stewart, C Andrew; Traherne, James A; Trevanion, Steve; Wilming, Laurens; Rogers, Jane; de Jong, Pieter J; Elliott, John F; Sawcer, Stephen; Todd, John A; Trowsdale, John; Beck, Stephan

    2008-01-01

    The human major histocompatibility complex (MHC) is contained within about 4 Mb on the short arm of chromosome 6 and is recognised as the most variable region in the human genome. The primary aim of the MHC Haplotype Project was to provide a comprehensively annotated reference sequence of a single, human leukocyte antigen-homozygous MHC haplotype and to use it as a basis against which variations could be assessed from seven other similarly homozygous cell lines, representative of the most common MHC haplotypes in the European population. Comparison of the haplotype sequences, including four haplotypes not previously analysed, resulted in the identification of >44,000 variations, both substitutions and indels (insertions and deletions), which have been submitted to the dbSNP database. The gene annotation uncovered haplotype-specific differences and confirmed the presence of more than 300 loci, including over 160 protein-coding genes. Combined analysis of the variation and annotation datasets revealed 122 gene loci with coding substitutions of which 97 were non-synonymous. The haplotype (A3-B7-DR15; PGF cell line) designated as the new MHC reference sequence, has been incorporated into the human genome assembly (NCBI35 and subsequent builds), and constitutes the largest single-haplotype sequence of the human genome to date. The extensive variation and annotation data derived from the analysis of seven further haplotypes have been made publicly available and provide a framework and resource for future association studies of all MHC-associated diseases and transplant medicine.

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

    PubMed

    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.

  2. Functional Region Annotation of Liver CT Image Based on Vascular Tree

    PubMed Central

    Chen, Yufei; Wang, Gang

    2016-01-01

    Anatomical analysis of liver region is critical in diagnosis and treatment of liver diseases. The reports of liver region annotation are helpful for doctors to precisely evaluate liver system. One of the challenging issues is to annotate the functional regions of liver through analyzing Computed Tomography (CT) images. In this paper, we propose a vessel-tree-based liver annotation method for CT images. The first step of the proposed annotation method is to extract the liver region including vessels and tumors from the CT scans. And then a 3-dimensional thinning algorithm is applied to obtain the spatial skeleton and geometric structure of liver vessels. With the vessel skeleton, the topology of portal veins is further formulated by a directed acyclic graph with geometrical attributes. Finally, based on the topological graph, a hierarchical vascular tree is constructed to divide the liver into eight segments according to Couinaud classification theory and thereby annotate the functional regions. Abundant experimental results demonstrate that the proposed method is effective for precise liver annotation and helpful to support liver disease diagnosis. PMID:27891516

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

    SciTech Connect

    Tyler, Ludmila; Bragg, Jennifer; Wu, Jiajie; Yang, Xiaohan; Tuskan, Gerald A; Vogel, John

    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

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

    PubMed

    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.

  5. Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

    PubMed Central

    Du, Yushen; Wu, Nicholas C.; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting

    2016-01-01

    ABSTRACT Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. PMID:27803181

  6. Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

    SciTech Connect

    Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; Chia, Nicholas; Price, Nathan D.; Maranas, Costas D.

    2014-10-16

    Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to

  7. Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models.

    PubMed

    Benedict, Matthew N; Mundy, Michael B; Henry, Christopher S; Chia, Nicholas; Price, Nathan D

    2014-10-01

    Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to

  8. Evolutionary Trace Annotation Server: automated enzyme function prediction in protein structures using 3D templates

    PubMed Central

    Matthew Ward, R.; Venner, Eric; Daines, Bryce; Murray, Stephen; Erdin, Serkan; Kristensen, David M.; Lichtarge, Olivier

    2009-01-01

    Summary:The Evolutionary Trace Annotation (ETA) Server predicts enzymatic activity. ETA starts with a structure of unknown function, such as those from structural genomics, and with no prior knowledge of its mechanism uses the phylogenetic Evolutionary Trace (ET) method to extract key functional residues and propose a function-associated 3D motif, called a 3D template. ETA then searches previously annotated structures for geometric template matches that suggest molecular and thus functional mimicry. In order to maximize the predictive value of these matches, ETA next applies distinctive specificity filters—evolutionary similarity, function plurality and match reciprocity. In large scale controls on enzymes, prediction coverage is 43% but the positive predictive value rises to 92%, thus minimizing false annotations. Users may modify any search parameter, including the template. ETA thus expands the ET suite for protein structure annotation, and can contribute to the annotation efforts of metaservers. Availability:The ETA Server is a web application available at http://mammoth.bcm.tmc.edu/eta/. Contact: lichtarge@bcm.edu PMID:19307237

  9. RATT: Rapid Annotation Transfer Tool

    PubMed Central

    Otto, Thomas D.; Dillon, Gary P.; Degrave, Wim S.; Berriman, Matthew

    2011-01-01

    Second-generation sequencing technologies have made large-scale sequencing projects commonplace. However, making use of these datasets often requires gene function to be ascribed genome wide. Although tool development has kept pace with the changes in sequence production, for tasks such as mapping, de novo assembly or visualization, genome annotation remains a challenge. We have developed a method to rapidly provide accurate annotation for new genomes using previously annotated genomes as a reference. The method, implemented in a tool called RATT (Rapid Annotation Transfer Tool), transfers annotations from a high-quality reference to a new genome on the basis of conserved synteny. We demonstrate that a Mycobacterium tuberculosis genome or a single 2.5 Mb chromosome from a malaria parasite can be annotated in less than five minutes with only modest computational resources. RATT is available at http://ratt.sourceforge.net. PMID:21306991

  10. ARC: automated resource classifier for agglomerative functional classification of prokaryotic proteins using annotation texts.

    PubMed

    Gnanamani, Muthiah; Kumar, Naveen; Ramachandran, Srinivasan

    2007-08-01

    Functional classification of proteins is central to comparative genomics. The need for algorithms tuned to enable integrative interpretation of analytical data is felt globally. The availability of a general,automated software with built-in flexibility will significantly aid this activity. We have prepared ARC (Automated Resource Classifier), which is an open source software meeting the user requirements of flexibility. The default classification scheme based on keyword match is agglomerative and directs entries into any of the 7 basic non-overlapping functional classes: Cell wall, Cell membrane and Transporters (C), Cell division (D), Information (I), Translocation (L), Metabolism (M), Stress(R), Signal and communication (S) and 2 ancillary classes: Others (O) and Hypothetical (H). The keyword library of ARC was built serially by first drawing keywords from Bacillus subtilis and Escherichia coli K12. In subsequent steps,this library was further enriched by collecting terms from archaeal representative Archaeoglobus fulgidus, Gene Ontology, and Gene Symbols. ARC is 94.04% successful on 6,75,663 annotated proteins from 348 prokaryotes. Three examples are provided to illuminate the current perspectives on mycobacterial physiology and costs of proteins in 333 prokaryotes. ARC is available at http://arc.igib.res.in.

  11. Functional annotation of proteomic data from chicken heterophils and macrophages induced by carbon nanotube exposure.

    PubMed

    Li, Yun-Ze; Cheng, Chung-Shi; Chen, Chao-Jung; Li, Zi-Lin; Lin, Yao-Tung; Chen, Shuen-Ei; Huang, San-Yuan

    2014-05-12

    With the expanding applications of carbon nanotubes (CNT) in biomedicine and agriculture, questions about the toxicity and biocompatibility of CNT in humans and domestic animals are becoming matters of serious concern. This study used proteomic methods to profile gene expression in chicken macrophages and heterophils in response to CNT exposure. Two-dimensional gel electrophoresis identified 12 proteins in macrophages and 15 in heterophils, with differential expression patterns in response to CNT co-incubation (0, 1, 10, and 100 µg/mL of CNT for 6 h) (p < 0.05). Gene ontology analysis showed that most of the differentially expressed proteins are associated with protein interactions, cellular metabolic processes, and cell mobility, suggesting activation of innate immune functions. Western blot analysis with heat shock protein 70, high mobility group protein, and peptidylprolyl isomerase A confirmed the alterations of the profiled proteins. The functional annotations were further confirmed by effective cell migration, promoted interleukin-1β secretion, and more cell death in both macrophages and heterophils exposed to CNT (p < 0.05). In conclusion, results of this study suggest that CNT exposure affects protein expression, leading to activation of macrophages and heterophils, resulting in altered cytoskeleton remodeling, cell migration, and cytokine production, and thereby mediates tissue immune responses.

  12. The power of EST sequence data: Relation to Acyrthosiphon pisum genome annotation and functional genomics initiatives

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genes important to aphid biology, survival and reproduction were successfully identified by use of a genomics approach. We created and described the Sequencing, compilation, and annotation of the approxiamtely 525Mb nuclear genome of the pea aphid, Acyrthosiphon pisum, which represents an important ...

  13. A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data.

    PubMed

    Lu, Qiongshi; Hu, Yiming; Sun, Jiehuan; Cheng, Yuwei; Cheung, Kei-Hoi; Zhao, Hongyu

    2015-05-27

    Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.

  14. ARG-ANNOT, a New Bioinformatic Tool To Discover Antibiotic Resistance Genes in Bacterial Genomes

    PubMed Central

    Gupta, Sushim Kumar; Padmanabhan, Babu Roshan; Diene, Seydina M.; Lopez-Rojas, Rafael; Kempf, Marie; Landraud, Luce

    2014-01-01

    ARG-ANNOT (Antibiotic Resistance Gene-ANNOTation) is a new bioinformatic tool that was created to detect existing and putative new antibiotic resistance (AR) genes in bacterial genomes. ARG-ANNOT uses a local BLAST program in Bio-Edit software that allows the user to analyze sequences without a Web interface. All AR genetic determinants were collected from published works and online resources; nucleotide and protein sequences were retrieved from the NCBI GenBank database. After building a database that includes 1,689 antibiotic resistance genes, the software was tested in a blind manner using 100 random sequences selected from the database to verify that the sensitivity and specificity were at 100% even when partial sequences were queried. Notably, BLAST analysis results obtained using the rmtF gene sequence (a new aminoglycoside-modifying enzyme gene sequence that is not included in the database) as a query revealed that the tool was able to link this sequence to short sequences (17 to 40 bp) found in other genes of the rmt family with significant E values. Finally, the analysis of 178 Acinetobacter baumannii and 20 Staphylococcus aureus genomes allowed the detection of a significantly higher number of AR genes than the Resfinder gene analyzer and 11 point mutations in target genes known to be associated with AR. The average time for the analysis of a genome was 3.35 ± 0.13 min. We have created a concise database for BLAST using a Bio-Edit interface that can detect AR genetic determinants in bacterial genomes and can rapidly and easily discover putative new AR genetic determinants. PMID:24145532

  15. BioBuilder as a database development and functional annotation platform for proteins

    PubMed Central

    Navarro, J Daniel; Talreja, Naveen; Peri, Suraj; Vrushabendra, BM; Rashmi, BP; Padma, N; Surendranath, Vineeth; Jonnalagadda, Chandra Kiran; Kousthub, PS; Deshpande, Nandan; Shanker, K; Pandey, Akhilesh

    2004-01-01

    Background The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development. Results BioBuilder is a Zope-based software tool that was developed to facilitate intuitive creation of protein databases. Protein data can be entered and annotated through web forms along with the flexibility to add customized annotation features to protein entries. A built-in review system permits a global team of scientists to coordinate their annotation efforts. We have already used BioBuilder to develop Human Protein Reference Database , a comprehensive annotated repository of the human proteome. The data can be exported in the extensible markup language (XML) format, which is rapidly becoming as the standard format for data exchange. Conclusions As the proteomic data for several organisms begins to accumulate, BioBuilder will prove to be an invaluable platform for functional annotation and development of customizable protein centric databases. BioBuilder is open source and is available under the terms of LGPL. PMID:15099404

  16. Biases in the experimental annotations of protein function and their effect on our understanding of protein function space.

    PubMed

    Schnoes, Alexandra M; Ream, David C; Thorman, Alexander W; Babbitt, Patricia C; Friedberg, Iddo

    2013-01-01

    The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of high-throughput experimental assays, a small number of experimental studies dominate the functional protein annotations collected in databases. Here, we investigate just how prevalent is the "few articles - many proteins" phenomenon. We examine the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and show that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation. Since each of the dominant articles describes the use of an assay that can find only one function or a small group of functions, this leads to substantial biases in what we know about the function of many proteins. Mass-spectrometry, microscopy and RNAi experiments dominate high throughput experiments. Consequently, the functional information derived from these experiments is mostly of the subcellular location of proteins, and of the participation of proteins in embryonic developmental pathways. For some organisms, the information provided by different studies overlap by a large amount. We also show that the information provided by high throughput experiments is less specific than those provided by low throughput experiments. Given the experimental techniques available, certain biases in protein function annotation due to high-throughput experiments are unavoidable. Knowing that these biases exist and understanding their characteristics and extent is important for database curators, developers of function annotation programs, and anyone who uses protein function annotation data to plan experiments.

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

    PubMed

    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.

  18. SNPnexus: a web database for functional annotation of newly discovered and public domain single nucleotide polymorphisms

    PubMed Central

    Chelala, Claude; Khan, Arshad; Lemoine, Nicholas R

    2009-01-01

    Motivation: Design a new computational tool allowing scientists to functionally annotate newly discovered and public domain single nucleotide polymorphisms in order to help in prioritizing targets in further disease studies and large-scale genotyping projects. Summary: SNPnexus database provides functional annotation for both novel and public SNPs. Possible effects on the transcriptome and proteome levels are characterized and reported from five major annotation systems providing the most extensive information on alternative splicing. Additional information on HapMap genotype and allele frequency, overlaps with potential regulatory elements or structural variations as well as related genetic diseases can be also retrieved. The SNPnexus database has a user-friendly web interface, providing single or batch query options using SNP identifiers from dbSNP as well as genomic location on clones, contigs or chromosomes. Therefore, SNPnexus is the only database currently providing a complete set of functional annotations of SNPs in public databases and newly detected from sequencing projects. Hence, we describe SNPnexus, provide details of the query options, the annotation categories as well as biological examples of use. Availability: The SNPnexus database is freely available at http://www.snp-nexus.org. Contact: claude.chelala@cancer.org.uk PMID:19098027

  19. Functional Analysis of Frequent Lung Cancer Amplicons Under Current Genome Annotation

    DTIC Science & Technology

    2015-12-01

    Exemplary groups of such genes include many non-protein-coding genes like long non-coding RNAs and microRNAs (miRNAs). In study, we examined the PVT1...lung tumorigenesis. The implication is that future studies of the 8q24 amplicon should concentrate on characterizing the PVT1 RNA transcript. 15...SUBJECT TERMS Noncoding RNA , microRNA, lung cancer, Genome annotation 16. SECURITY CLASSIFICATION OF: U 17. LIMITATION OF ABSTRACT 18. NUMBER OF

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

    SciTech Connect

    Rechtsteiner, A.; Rocha, L. M.

    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

  1. Rapid Annotation of Anonymous Sequences from Genome Projects Using Semantic Similarities and a Weighting Scheme in Gene Ontology

    PubMed Central

    Fontana, Paolo; Cestaro, Alessandro; Velasco, Riccardo; Formentin, Elide; Toppo, Stefano

    2009-01-01

    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. PMID:19247487

  2. Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

    DOE PAGES

    Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; ...

    2014-10-16

    Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genesmore » and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary

  3. BioGPS: building your own mash-up of gene annotations and expression profiles

    PubMed Central

    Wu, Chunlei; Jin, Xuefeng; Tsueng, Ginger; Afrasiabi, Cyrus; Su, Andrew I.

    2016-01-01

    BioGPS (http://biogps.org) is a centralized gene-annotation portal that enables researchers to access distributed gene annotation resources. This article focuses on the updates to BioGPS since our last paper (2013 database issue). The unique features of BioGPS, compared to those of other gene portals, are its community extensibility and user customizability. Users contribute the gene-specific resources accessible from BioGPS (‘plugins’), which helps ensure that the resource collection is always up-to-date and that it will continue expanding over time (since the 2013 paper, 162 resources have been added, for a 34% increase in the number of resources available). BioGPS users can create their own collections of relevant plugins and save them as customized gene-report pages or ‘layouts’ (since the 2013 paper, 488 user-created layouts have been added, for a 22% increase in the number of layouts). In addition, we recently updated the most popular plugin, the ‘Gene expression/activity chart’, to include ∼6000 datasets (from ∼2000 datasets) and we enhanced user interactivity. We also added a new ‘gene list’ feature that allows users to save query results for future reference. PMID:26578587

  4. Generation, functional annotation and comparative analysis of black spruce (Picea mariana) ESTs: an important conifer genomic resource

    PubMed Central

    2013-01-01

    Background EST (expressed sequence tag) sequences and their annotation provide a highly valuable resource for gene discovery, genome sequence annotation, and other genomics studies that can be applied in genetics, breeding and conservation programs for non-model organisms. Conifers are long-lived plants that are ecologically and economically important globally, and have a large genome size. Black spruce (Picea mariana), is a transcontinental species of the North American boreal and temperate forests. However, there are limited transcriptomic and genomic resources for this species. The primary objective of our study was to develop a black spruce transcriptomic resource to facilitate on-going functional genomics projects related to growth and adaptation to climate change. Results We conducted bidirectional sequencing of cDNA clones from a standard cDNA library constructed from black spruce needle tissues. We obtained 4,594 high quality (2,455 5' end and 2,139 3' end) sequence reads, with an average read-length of 532 bp. Clustering and assembly of ESTs resulted in 2,731 unique sequences, consisting of 2,234 singletons and 497 contigs. Approximately two-thirds (63%) of unique sequences were functionally annotated. Genes involved in 36 molecular functions and 90 biological processes were discovered, including 24 putative transcription factors and 232 genes involved in photosynthesis. Most abundantly expressed transcripts were associated with photosynthesis, growth factors, stress and disease response, and transcription factors. A total of 216 full-length genes were identified. About 18% (493) of the transcripts were novel, representing an important addition to the Genbank EST database (dbEST). Fifty-seven di-, tri-, tetra- and penta-nucleotide simple sequence repeats were identified. Conclusions We have developed the first high quality EST resource for black spruce and identified 493 novel transcripts, which may be species-specific related to life history and

  5. Genome assembly has a major impact on gene content: a comparison of annotation in two Bos taurus assemblies.

    PubMed

    Florea, Liliana; Souvorov, Alexander; Kalbfleisch, Theodore S; Salzberg, Steven L

    2011-01-01

    Gene and SNP annotation are among the first and most important steps in analyzing a genome. As the number of sequenced genomes continues to grow, a key question is: how does the quality of the assembled sequence affect the annotations? We compared the gene and SNP annotations for two different Bos taurus genome assemblies built from the same data but with significant improvements in the later assembly. The same annotation software was used for annotating both sequences. While some annotation differences are expected even between high-quality assemblies such as these, we found that a staggering 40% of the genes (>9,500) varied significantly between assemblies, due in part to the availability of new gene evidence but primarily to genome mis-assembly events and local sequence variations. For instance, although the later assembly is generally superior, 660 protein coding genes in the earlier assembly are entirely missing from the later genome's annotation, and approximately 3,600 (15%) of the genes have complex structural differences between the two assemblies. In addition, 12-20% of the predicted proteins in both assemblies have relatively large sequence differences when compared to their RefSeq models, and 6-15% of bovine dbSNP records are unrecoverable in the two assemblies. Our findings highlight the consequences of genome assembly quality on gene and SNP annotation and argue for continued improvements in any draft genome sequence. We also found that tracking a gene between different assemblies of the same genome is surprisingly difficult, due to the numerous changes, both small and large, that occur in some genes. As a side benefit, our analyses helped us identify many specific loci for improvement in the Bos taurus genome assembly.

  6. Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin.

    PubMed

    Liu, Ching-Ti; Raghavan, Sridharan; Maruthur, Nisa; Kabagambe, Edmond Kato; Hong, Jaeyoung; Ng, Maggie C Y; Hivert, Marie-France; Lu, Yingchang; An, Ping; Bentley, Amy R; Drolet, Anne M; Gaulton, Kyle J; Guo, Xiuqing; Armstrong, Loren L; Irvin, Marguerite R; Li, Man; Lipovich, Leonard; Rybin, Denis V; Taylor, Kent D; Agyemang, Charles; Palmer, Nicholette D; Cade, Brian E; Chen, Wei-Min; Dauriz, Marco; Delaney, Joseph A C; Edwards, Todd L; Evans, Daniel S; Evans, Michele K; Lange, Leslie A; Leong, Aaron; Liu, Jingmin; Liu, Yongmei; Nayak, Uma; Patel, Sanjay R; Porneala, Bianca C; Rasmussen-Torvik, Laura J; Snijder, Marieke B; Stallings, Sarah C; Tanaka, Toshiko; Yanek, Lisa R; Zhao, Wei; Becker, Diane M; Bielak, Lawrence F; Biggs, Mary L; Bottinger, Erwin P; Bowden, Donald W; Chen, Guanjie; Correa, Adolfo; Couper, David J; Crawford, Dana C; Cushman, Mary; Eicher, John D; Fornage, Myriam; Franceschini, Nora; Fu, Yi-Ping; Goodarzi, Mark O; Gottesman, Omri; Hara, Kazuo; Harris, Tamara B; Jensen, Richard A; Johnson, Andrew D; Jhun, Min A; Karter, Andrew J; Keller, Margaux F; Kho, Abel N; Kizer, Jorge R; Krauss, Ronald M; Langefeld, Carl D; Li, Xiaohui; Liang, Jingling; Liu, Simin; Lowe, William L; Mosley, Thomas H; North, Kari E; Pacheco, Jennifer A; Peyser, Patricia A; Patrick, Alan L; Rice, Kenneth M; Selvin, Elizabeth; Sims, Mario; Smith, Jennifer A; Tajuddin, Salman M; Vaidya, Dhananjay; Wren, Mary P; Yao, Jie; Zhu, Xiaofeng; Ziegler, Julie T; Zmuda, Joseph M; Zonderman, Alan B; Zwinderman, Aeilko H; Adeyemo, Adebowale; Boerwinkle, Eric; Ferrucci, Luigi; Hayes, M Geoffrey; Kardia, Sharon L R; Miljkovic, Iva; Pankow, James S; Rotimi, Charles N; Sale, Michele M; Wagenknecht, Lynne E; Arnett, Donna K; Chen, Yii-Der Ida; Nalls, Michael A; Province, Michael A; Kao, W H Linda; Siscovick, David S; Psaty, Bruce M; Wilson, James G; Loos, Ruth J F; Dupuis, Josée; Rich, Stephen S; Florez, Jose C; Rotter, Jerome I; Morris, Andrew P; Meigs, James B

    2016-07-07

    Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.

  7. High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic mode...

  8. Analysis of the multi-copied genes and the impact of the redundant protein coding sequences on gene annotation in prokaryotic genomes.

    PubMed

    Yu, Jia-Feng; Chen, Qing-Li; Ren, Jing; Yang, Yan-Ling; Wang, Ji-Hua; Sun, Xiao

    2015-07-07

    The important roles of duplicated genes in evolutional process have been recognized in bacteria, archaebacteria and eukaryotes, while there is very little study on the multi-copied protein coding genes that share sequence identity of 100%. In this paper, the multi-copied protein coding genes in a number of prokaryotic genomes are comprehensively analyzed firstly. The results show that 0-15.93% of the protein coding genes in each genome are multi-copied genes and 0-16.49% of the protein coding genes in each genome are highly similar with the sequence identity ≥ 80%. Function and COG (Clusters of Orthologous Groups of proteins) analysis shows that 64.64% of multi-copied genes concentrate on the function of transposase and 86.28% of the COG assigned multi-copied genes concentrate on the COG code of 'L'. Furthermore, the impact of redundant protein coding sequences on the gene prediction results is studied. The results show that the problem of protein coding sequence redundancies cannot be ignored and the consistency of the gene annotation results before and after excluding the redundant sequences is negatively related with the sequences redundancy degree of the protein coding sequences in the training set.

  9. Genome-wide functional annotation of Phomopsis longicolla isolate MSPL 10-6.

    PubMed

    Darwish, Omar; Li, Shuxian; Matthews, Benjamin; Alkharouf, Nadim

    2016-06-01

    Phomopsis seed decay of soybean is caused primarily by the seed-borne fungal pathogen Phomopsis longicolla (syn. Diaporthe longicolla). This disease severely decreases soybean seed quality, reduces seedling vigor and stand establishment, and suppresses yield. It is one of the most economically important soybean diseases. In this study we annotated the entire genome of P. longicolla isolate MSPL 10-6, which was isolated from field-grown soybean seed in Mississippi, USA. This study represents the first reported genome-wide functional annotation of a seed borne fungal pathogen in the Diaporthe-Phomopsis complex. The P. longicolla genome annotation will enable research into the genetic basis of fungal infection of soybean seed and provide information for the study of soybean-fungal interactions. The genome annotation will also be a valuable resource for the research and agricultural communities. It will aid in the development of new control strategies for this pathogen. The annotations can be found from: http://bioinformatics.towson.edu/phomopsis_longicolla/download.html. NCBI accession number is: AYRD00000000.

  10. Proteomics and transcriptomics of the BABA-induced resistance response in potato using a novel functional annotation approach

    PubMed Central

    2014-01-01

    Background Induced resistance (IR) can be part of a sustainable plant protection strategy against important plant diseases. β-aminobutyric acid (BABA) can induce resistance in a wide range of plants against several types of pathogens, including potato infected with Phytophthora infestans. However, the molecular mechanisms behind this are unclear and seem to be dependent on the system studied. To elucidate the defence responses activated by BABA in potato, a genome-wide transcript microarray analysis in combination with label-free quantitative proteomics analysis of the apoplast secretome were performed two days after treatment of the leaf canopy with BABA at two concentrations, 1 and 10 mM. Results Over 5000 transcripts were differentially expressed and over 90 secretome proteins changed in abundance indicating a massive activation of defence mechanisms with 10 mM BABA, the concentration effective against late blight disease. To aid analysis, we present a more comprehensive functional annotation of the microarray probes and gene models by retrieving information from orthologous gene families across 26 sequenced plant genomes. The new annotation provided GO terms to 8616 previously un-annotated probes. Conclusions BABA at 10 mM affected several processes related to plant hormones and amino acid metabolism. A major accumulation of PR proteins was also evident, and in the mevalonate pathway, genes involved in sterol biosynthesis were down-regulated, whereas several enzymes involved in the sesquiterpene phytoalexin biosynthesis were up-regulated. Interestingly, abscisic acid (ABA) responsive genes were not as clearly regulated by BABA in potato as previously reported in Arabidopsis. Together these findings provide candidates and markers for improved resistance in potato, one of the most important crops in the world. PMID:24773703

  11. The proteome of Toxoplasma gondii: integration with the genome provides novel insights into gene expression and annotation

    PubMed Central

    Xia, Dong; Sanderson, Sanya J; Jones, Andrew R; Prieto, Judith H; Yates, John R; Bromley, Elizabeth; Tomley, Fiona M; Lal, Kalpana; Sinden, Robert E; Brunk, Brian P; Roos, David S; Wastling, Jonathan M

    2008-01-01

    Background Although the genomes of many of the most important human and animal pathogens have now been sequenced, our understanding of the actual proteins expressed by these genomes and how well they predict protein sequence and expression is still deficient. We have used three complementary approaches (two-dimensional electrophoresis, gel-liquid chromatography linked tandem mass spectrometry and MudPIT) to analyze the proteome of Toxoplasma gondii, a parasite of medical and veterinary significance, and have developed a public repository for these data within ToxoDB, making for the first time proteomics data an integral part of this key genome resource. Results The draft genome for Toxoplasma predicts around 8,000 genes with varying degrees of confidence. Our data demonstrate how proteomics can inform these predictions and help discover new genes. We have identified nearly one-third (2,252) of all the predicted proteins, with 2,477 intron-spanning peptides providing supporting evidence for correct splice site annotation. Functional predictions for each protein and key pathways were determined from the proteome. Importantly, we show evidence for many proteins that match alternative gene models, or previously unpredicted genes. For example, approximately 15% of peptides matched more convincingly to alternative gene models. We also compared our data with existing transcriptional data in which we highlight apparent discrepancies between gene transcription and protein expression. Conclusion Our data demonstrate the importance of protein data in expression profiling experiments and highlight the necessity of integrating proteomic with genomic data so that iterative refinements of both annotation and expression models are possible. PMID:18644147

  12. Corrected Genome Annotations Reveal Gene Loss and Antibiotic Resistance as Drivers in the Fitness Evolution of Salmonella enterica Serovar Typhimurium.

    PubMed

    Paul, Sandip; Sokurenko, Evgeni V; Chattopadhyay, Sujay

    2016-12-01

    Horizontal acquisition of novel chromosomal genes is considered to be a key process in the evolution of bacterial pathogens. However, the identification of gene presence or absence could be hindered by the inconsistencies in bacterial genome annotations. Here, we performed a cross-annotation of omnipresent core and mosaic accessory genes in the chromosome of Salmonella enterica serovar Typhimurium across a total of 20 fully assembled genomes deposited into GenBank. Cross-annotation resulted in a 32% increase in the number of core genes and a 3-fold decrease in the number of genes identified as mosaic genes (i.e., genes present in some strains only) by the original annotation. Of the remaining noncore genes, the vast majority were prophage genes, and 255 of the nonphage genes were actually of core origin but lost in some strains upon the emergence of the S Typhimurium serovar, suggesting that the chromosomal portion of the S Typhimurium genome acquired a very limited number of novel genes other than prophages. Only horizontally acquired nonphage genes related to bacterial fitness or virulence were found in four recently sequenced isolates, all located on three different genomic islands that harbor multidrug resistance determinants. Thus, the extensive use of antimicrobials could be the main selection force behind the new fitness gene acquisition and the emergence of novel Salmonella pathotypes.

  13. Using Multi-Instance Hierarchical Clustering Learning System to Predict Yeast Gene Function

    PubMed Central

    Liao, Bo; Li, Yun; Jiang, Yan; Cai, Lijun

    2014-01-01

    Time-course gene expression datasets, which record continuous biological processes of genes, have recently been used to predict gene function. However, only few positive genes can be obtained from annotation databases, such as gene ontology (GO). To obtain more useful information and effectively predict gene function, gene annotations are clustered together to form a learnable and effective learning system. In this paper, we propose a novel multi-instance hierarchical clustering (MIHC) method to establish a learning system by clustering GO and compare this method with other learning system establishment methods. Multi-label support vector machine classifier and multi-label K-nearest neighbor classifier are used to verify these methods in four yeast time-course gene expression datasets. The MIHC method shows good performance, which serves as a guide to annotators or refines the annotation in detail. PMID:24621610

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

    PubMed

    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.

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

    PubMed Central

    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

  16. Comprehensive functional annotation of 18 missense mutations found in suspected hemochromatosis type 4 patients.

    PubMed

    Callebaut, Isabelle; Joubrel, Rozenn; Pissard, Serge; Kannengiesser, Caroline; Gérolami, Victoria; Ged, Cécile; Cadet, Estelle; Cartault, François; Ka, Chandran; Gourlaouen, Isabelle; Gourhant, Lénaick; Oudin, Claire; Goossens, Michel; Grandchamp, Bernard; De Verneuil, Hubert; Rochette, Jacques; Férec, Claude; Le Gac, Gérald

    2014-09-01

    Hemochromatosis type 4 is a rare form of primary iron overload transmitted as an autosomal dominant trait caused by mutations in the gene encoding the iron transport protein ferroportin 1 (SLC40A1). SLC40A1 mutations fall into two functional categories (loss- versus gain-of-function) underlying two distinct clinical entities (hemochromatosis type 4A versus type 4B). However, the vast majority of SLC40A1 mutations are rare missense variations, with only a few showing strong evidence of causality. The present study reports the results of an integrated approach collecting genetic and phenotypic data from 44 suspected hemochromatosis type 4 patients, with comprehensive structural and functional annotations. Causality was demonstrated for 10 missense variants, showing a clear dichotomy between the two hemochromatosis type 4 subtypes. Two subgroups of loss-of-function mutations were distinguished: one impairing cell-surface expression and one altering only iron egress. Additionally, a new gain-of-function mutation was identified, and the degradation of ferroportin on hepcidin binding was shown to probably depend on the integrity of a large extracellular loop outside of the hepcidin-binding domain. Eight further missense variations, on the other hand, were shown to have no discernible effects at either protein or RNA level; these were found in apparently isolated patients and were associated with a less severe phenotype. The present findings illustrate the importance of combining in silico and biochemical approaches to fully distinguish pathogenic SLC40A1 mutations from benign variants. This has profound implications for patient management.

  17. Genome-wide metabolic (re-) annotation of Kluyveromyces lactis

    PubMed Central

    2012-01-01

    Background Even before having its genome sequence published in 2004, Kluyveromyces lactis had long been considered a model organism for studies in genetics and physiology. Research on Kluyveromyces lactis is quite advanced and this yeast species is one of the few with which it is possible to perform formal genetic analysis. Nevertheless, until now, no complete metabolic functional annotation has been performed to the proteins encoded in the Kluyveromyces lactis genome. Results In this work, a new metabolic genome-wide functional re-annotation of the proteins encoded in the Kluyveromyces lactis genome was performed, resulting in the annotation of 1759 genes with metabolic functions, and the development of a methodology supported by merlin (software developed in-house). The new annotation includes novelties, such as the assignment of transporter superfamily numbers to genes identified as transporter proteins. Thus, the genes annotated with metabolic functions could be exclusively enzymatic (1410 genes), transporter proteins encoding genes (301 genes) or have both metabolic activities (48 genes). The new annotation produced by this work largely surpassed the Kluyveromyces lactis currently available annotations. A comparison with KEGG’s annotation revealed a match with 844 (~90%) of the genes annotated by KEGG, while adding 850 new gene annotations. Moreover, there are 32 genes with annotations different from KEGG. Conclusions The methodology developed throughout this work can be used to re-annotate any yeast or, with a little tweak of the reference organism, the proteins encoded in any sequenced genome. The new annotation provided by this study offers basic knowledge which might be useful for the scientific community working on this model yeast, because new functions have been identified for the so-called metabolic genes. Furthermore, it served as the basis for the reconstruction of a compartmentalized, genome-scale metabolic model of Kluyveromyces lactis, which is

  18. Improved structural annotation of protein-coding genes in the Meloidogyne hapla genome using RNA-Seq.

    PubMed

    Guo, Yuelong; Bird, David McK; Nielsen, Dahlia M

    2014-01-01

    As high-throughput cDNA sequencing (RNA-Seq) is increasingly applied to hypothesis-driven biological studies, the prediction of protein coding genes based on these data are usurping strictly in silico approaches. Compared with computationally derived gene predictions, structural annotation is more accurate when based on biological evidence, particularly RNA-Seq data. Here, we refine the current genome annotation for the Meloidogyne hapla genome utilizing RNA-Seq data. Published structural annotation defines 14 420 protein-coding genes in the M. hapla genome. Of these, 25% (3751) were found to exhibit some incongruence with RNA-Seq data. Manual annotation enabled these discrepancies to be resolved. Our analysis revealed 544 new gene models that were missing from the prior annotation. Additionally, 1457 transcribed regions were newly identified on the ends of as-yet-unjoined contigs. We also searched for trans-spliced leaders, and based on RNA-Seq data, identified genes that appear to be trans-spliced. Four 22-bp trans-spliced leaders were identified using our pipeline, including the known trans-spliced leader, which is the M. hapla ortholog of SL1. In silico predictions of trans-splicing were validated by comparison with earlier results derived from an independent cDNA library constructed to capture trans-spliced transcripts. The new annotation, which we term HapPep5, is publically available at www.hapla.org.

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

    PubMed

    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.

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

    PubMed Central

    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; Bonaldo, Maria de Fatima; 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; R. Gopinath, Gopal; 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; Shimizu, Nobuyoshi; Shimoyama, Mary; Simpson, Andrew J; Soares, Bento; Steward, Charles; Suwa, Makiko; Suzuki, Mami; Takahashi, Aiko; Tamiya, Gen; Tanaka, Hiroshi; Taylor, Todd; Terwilliger, Joseph D; Unneberg, Per; Veeramachaneni, Vamsi; Watanabe, Shinya; Wilming, Laurens; Yasuda, Norikazu; Yoo, Hyang-Sook; Stodolsky, Marvin; Makalowski, Wojciech; Go, Mitiko; Nakai, Kenta; Takagi, Toshihisa; Kanehisa, Minoru; Sakaki, Yoshiyuki; Quackenbush, John; Okazaki, Yasushi; Hayashizaki, Yoshihide; Hide, Winston; Chakraborty, Ranajit; Nishikawa, Ken; Sugawara, Hideaki; Tateno, Yoshio; Chen, Zhu; Oishi, Michio; Tonellato, Peter; Apweiler, Rolf; Okubo, Kousaku; Wagner, Lukas; Wiemann, Stefan; Strausberg, Robert L; Isogai, Takao; Auffray, Charles; Nomura, Nobuo; Sugano, Sumio

    2004-01-01

    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 genes. In

  1. Cross-Population Joint Analysis of eQTLs: Fine Mapping and Functional Annotation

    PubMed Central

    Wen, Xiaoquan; Luca, Francesca; Pique-Regi, Roger

    2015-01-01

    Mapping expression quantitative trait loci (eQTLs) has been shown as a powerful tool to uncover the genetic underpinnings of many complex traits at molecular level. In this paper, we present an integrative analysis approach that leverages eQTL data collected from multiple population groups. In particular, our approach effectively identifies multiple independent cis-eQTL signals that are consistent across populations, accounting for population heterogeneity in allele frequencies and linkage disequilibrium patterns. Furthermore, by integrating genomic annotations, our analysis framework enables high-resolution functional analysis of eQTLs. We applied our statistical approach to analyze the GEUVADIS data consisting of samples from five population groups. From this analysis, we concluded that i) jointly analysis across population groups greatly improves the power of eQTL discovery and the resolution of fine mapping of causal eQTL ii) many genes harbor multiple independent eQTLs in their cis regions iii) genetic variants that disrupt transcription factor binding are significantly enriched in eQTLs (p-value = 4.93 × 10-22). PMID:25906321

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

    PubMed

    Zeng, Victor; Ewen-Campen, Ben; Horch, Hadley W; Roth, Siegfried; Mito, Taro; Extavour, Cassandra G

    2013-01-01

    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 Gryllus.

  3. Developmental Gene Discovery in a Hemimetabolous Insect: De Novo Assembly and Annotation of a Transcriptome for the Cricket Gryllus bimaculatus

    PubMed Central

    Zeng, Victor; Ewen-Campen, Ben; Horch, Hadley W.; Roth, Siegfried; Mito, Taro; Extavour, Cassandra G.

    2013-01-01

    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 Gryllus. PMID

  4. Improved systematic tRNA gene annotation allows new insights into the evolution of mitochondrial tRNA structures and into the mechanisms of mitochondrial genome rearrangements

    PubMed Central

    Jühling, Frank; Pütz, Joern; Bernt, Matthias; Donath, Alexander; Middendorf, Martin; Florentz, Catherine; Stadler, Peter F.

    2012-01-01

    Transfer RNAs (tRNAs) are present in all types of cells as well as in organelles. tRNAs of animal mitochondria show a low level of primary sequence conservation and exhibit ‘bizarre’ secondary structures, lacking complete domains of the common cloverleaf. Such sequences are hard to detect and hence frequently missed in computational analyses and mitochondrial genome annotation. Here, we introduce an automatic annotation procedure for mitochondrial tRNA genes in Metazoa based on sequence and structural information in manually curated covariance models. The method, applied to re-annotate 1876 available metazoan mitochondrial RefSeq genomes, allows to distinguish between remaining functional genes and degrading ‘pseudogenes’, even at early stages of divergence. The subsequent analysis of a comprehensive set of mitochondrial tRNA genes gives new insights into the evolution of structures of mitochondrial tRNA sequences as well as into the mechanisms of genome rearrangements. We find frequent losses of tRNA genes concentrated in basal Metazoa, frequent independent losses of individual parts of tRNA genes, particularly in Arthropoda, and wide-spread conserved overlaps of tRNAs in opposite reading direction. Direct evidence for several recent Tandem Duplication-Random Loss events is gained, demonstrating that this mechanism has an impact on the appearance of new mitochondrial gene orders. PMID:22139921

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

    PubMed

    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/.

  6. De Novo Assembly, Gene Annotation, and Marker Discovery in Stored-Product Pest Liposcelis entomophila (Enderlein) Using Transcriptome Sequences

    PubMed Central

    Wei, Dan-Dan; Chen, Er-Hu; Ding, Tian-Bo; Chen, Shi-Chun; Dou, Wei; Wang, Jin-Jun

    2013-01-01

    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 insecticide resistance

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Efforts to obtain a comprehensive genome sequence for rainbow trout are ongoing and will be complimented by transcriptome information that will enhance genome assembly and annotation. Previously, we reported a transcriptome reference sequence using a 19X coverage of Sanger and 454-pyrosequencing dat...

  8. NCBI prokaryotic genome annotation pipeline.

    PubMed

    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/.

  9. BIOFILTER AS A FUNCTIONAL ANNOTATION PIPELINE FOR COMMON AND RARE COPY NUMBER BURDEN

    PubMed Central

    KIM, DOKYOON; LUCAS, ANASTASIA; GLESSNER, JOSEPH; VERMA, SHEFALI S.; BRADFORD, YUKI; LI, RUOWANG; FRASE, ALEX T.; HAKONARSON, HAKON; PEISSIG, PEGGY; BRILLIANT, MURRAY; RITCHIE, MARYLYN D.

    2015-01-01

    Recent studies on copy number variation (CNV) have suggested that an increasing burden of CNVs is associated with susceptibility or resistance to disease. A large number of genes or genomic loci contribute to complex diseases such as autism. Thus, total genomic copy number burden, as an accumulation of copy number change, is a meaningful measure of genomic instability to identify the association between global genetic effects and phenotypes of interest. However, no systematic annotation pipeline has been developed to interpret biological meaning based on the accumulation of copy number change across the genome associated with a phenotype of interest. In this study, we develop a comprehensive and systematic pipeline for annotating copy number variants into genes/genomic regions and subsequently pathways and other gene groups using Biofilter – a bioinformatics tool that aggregates over a dozen publicly available databases of prior biological knowledge. Next we conduct enrichment tests of biologically defined groupings of CNVs including genes, pathways, Gene Ontology, or protein families. We applied the proposed pipeline to a CNV dataset from the Marshfield Clinic Personalized Medicine Research Project (PMRP) in a quantitative trait phenotype derived from the electronic health record – total cholesterol. We identified several significant pathways such as toll-like receptor signaling pathway and hepatitis C pathway, gene ontologies (GOs) of nucleoside triphosphatase activity (NTPase) and response to virus, and protein families such as cell morphogenesis that are associated with the total cholesterol phenotype based on CNV profiles (permutation p-value < 0.01). Based on the copy number burden analysis, it follows that the more and larger the copy number changes, the more likely that one or more target genes that influence disease risk and phenotypic severity will be affected. Thus, our study suggests the proposed enrichment pipeline could improve the

  10. BIOFILTER AS A FUNCTIONAL ANNOTATION PIPELINE FOR COMMON AND RARE COPY NUMBER BURDEN.

    PubMed

    Kim, Dokyoon; Lucas, Anastasia; Glessner, Joseph; Verma, Shefali S; Bradford, Yuki; Li, Ruowang; Frase, Alex T; Hakonarson, Hakon; Peissig, Peggy; Brilliant, Murray; Ritchie, Marylyn D

    2016-01-01

    Recent studies on copy number variation (CNV) have suggested that an increasing burden of CNVs is associated with susceptibility or resistance to disease. A large number of genes or genomic loci contribute to complex diseases such as autism. Thus, total genomic copy number burden, as an accumulation of copy number change, is a meaningful measure of genomic instability to identify the association between global genetic effects and phenotypes of interest. However, no systematic annotation pipeline has been developed to interpret biological meaning based on the accumulation of copy number change across the genome associated with a phenotype of interest. In this study, we develop a comprehensive and systematic pipeline for annotating copy number variants into genes/genomic regions and subsequently pathways and other gene groups using Biofilter - a bioinformatics tool that aggregates over a dozen publicly available databases of prior biological knowledge. Next we conduct enrichment tests of biologically defined groupings of CNVs including genes, pathways, Gene Ontology, or protein families. We applied the proposed pipeline to a CNV dataset from the Marshfield Clinic Personalized Medicine Research Project (PMRP) in a quantitative trait phenotype derived from the electronic health record - total cholesterol. We identified several significant pathways such as toll-like receptor signaling pathway and hepatitis C pathway, gene ontologies (GOs) of nucleoside triphosphatase activity (NTPase) and response to virus, and protein families such as cell morphogenesis that are associated with the total cholesterol phenotype based on CNV profiles (permutation p-value < 0.01). Based on the copy number burden analysis, it follows that the more and larger the copy number changes, the more likely that one or more target genes that influence disease risk and phenotypic severity will be affected. Thus, our study suggests the proposed enrichment pipeline could improve the interpretability of

  11. YeATSAM analysis of the walnut and chickpea transcriptome reveals key genes undetected by current annotation tools

    PubMed Central

    Chakraborty, Sandeep; Martínez-García, Pedro J.; Dandekar, Abhaya M.

    2016-01-01

    Background: The transcriptome, a treasure trove of gene space information, remains severely under-used by current genome annotation methods.  Methods: Here, we present an annotation method in the YeATS suite (YeATSAM), based on information encoded by the transcriptome, that demonstrates artifacts of the assembler, which must be addressed to achieve proper annotation.  Results and Discussion: YeATSAM was applied to the transcriptome obtained from twenty walnut tissues and compared to MAKER-P annotation of the recently published walnut genome sequence (WGS). MAKER-P and YeATSAM both failed to annotate several hundred proteins found by the other. Although many of these unannotated proteins have repetitive sequences (possibly transposable elements), other crucial proteins were excluded by each method. An egg cell-secreted protein and a homer protein were undetected by YeATSAM, although these did not produce any transcripts. Importantly, MAKER-P failed to classify key photosynthesis-related proteins, which we show emanated from Trinity assembly artifacts potentially not handled by MAKER-P. Also, no proteins from the large berberine bridge enzyme (BBE) family were annotated by MAKER-P. BBE is implicated in biosynthesis of several alkaloids metabolites, like anti-microbial berberine. As further validation, YeATSAM identified ~1000 genes that are not annotated in the NCBI database by Gnomon. YeATSAM used a RNA-seq derived chickpea ( Cicer arietinum L.) transcriptome assembled using Newbler v2.3.  Conclusions: Since the current version of YeATSAM does not have an ab initio module, we suggest a combined annotation scheme using both MAKER-P and YeATSAM to comprehensively and accurately annotate the WGS. PMID:28105312

  12. Coordinated international action to accelerate genome-to-phenome with FAANG, The Functional Annotation of Animal Genomes project

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We describe the organization of a nascent international effort - the "Functional Annotation of ANimal Genomes" project - whose aim is to produce comprehensive maps of functional elements in the genomes of domesticated animal species....

  13. Protein intrinsic disorder within the Potyvirus genus: from proteome-wide analysis to functional annotation.

    PubMed

    Charon, Justine; Theil, Sébastien; Nicaise, Valérie; Michon, Thierry

    2016-02-01

    Within proteins, intrinsically disordered regions (IDRs) are devoid of stable secondary and tertiary structures under physiological conditions and rather exist as dynamic ensembles of inter-converting conformers. Although ubiquitous in all domains of life, the intrinsic disorder content is highly variable in viral genomes. Over the years, functional annotations of disordered regions at the scale of the whole proteome have been conducted for several animal viruses. But to date, similar studies applied to plant viruses are still missing. Based on disorder prediction tools combined with annotation programs and evolutionary studies, we analyzed the intrinsic disorder content in Potyvirus, using a 10-species dataset representative of this genus diversity. In this paper, we revealed that: (i) the Potyvirus proteome displays high disorder content, (ii) disorder is conserved during Potyvirus evolution, suggesting a functional advantage of IDRs, (iii) IDRs evolve faster than ordered regions, and (iv) IDRs may be associated with major biological functions required for the Potyvirus cycle. Notably, the proteins P1, Coat protein (CP) and Viral genome-linked protein (VPg) display a high content of conserved disorder, enriched in specific motifs mimicking eukaryotic functional modules and suggesting strategies of host machinery hijacking. In these three proteins, IDRs are particularly conserved despite their high amino acid polymorphism, indicating a link to adaptive processes. Through this comprehensive study, we further investigate the biological relevance of intrinsic disorder in Potyvirus biology and we propose a functional annotation of potyviral proteome IDRs.

  14. Annotation and re-sequencing of genes from de novo transcriptome assembly of Abies alba (Pinaceae)1

    PubMed Central

    Roschanski, Anna M.; Fady, Bruno; Ziegenhagen, Birgit; Liepelt, Sascha

    2013-01-01

    • 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 25149 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. PMID:25202477

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

    PubMed Central

    2012-01-01

    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. PMID:23036012

  16. Report on the 2011 Critical Assessment of Function Annotation (CAFA) meeting

    SciTech Connect

    Friedberg, Iddo

    2015-01-21

    The Critical Assessment of Function Annotation meeting was held July 14-15, 2011 at the Austria Conference Center in Vienna, Austria. There were 73 registered delegates at the meeting. We thank the DOE for this award. It helped us organize and support a scientific meeting AFP 2011 as a special interest group (SIG) meeting associated with the ISMB 2011 conference. The conference was held in Vienna, Austria, in July 2011. The AFP SIG was held on July 15-16, 2011 (immediately preceding the conference). The meeting consisted of two components, the first being a series of talks (invited and contributed) and discussion sections dedicated to protein function research, with an emphasis on the theory and practice of computational methods utilized in functional annotation. The second component provided a large-scale assessment of computational methods through participation in the Critical Assessment of Functional Annotation (CAFA). The meeting was exciting and, based on feedback, quite successful. There were 73 registered participants. The schedule was only slightly different from the one proposed, due to two cancellations. Dr. Olga Troyanskaya has canceled and we invited Dr. David Jones instead. Similarly, instead of Dr. Richard Roberts, Dr. Simon Kasif gave a closing keynote. The remaining invited speakers were Janet Thornton (EBI) and Amos Bairoch (University of Geneva).

  17. Genome-scale phylogenetic function annotation of large and diverse protein families.

    PubMed

    Engelhardt, Barbara E; Jordan, Michael I; Srouji, John R; Brenner, Steven E

    2011-11-01

    The Statistical Inference of Function Through Evolutionary Relationships (SIFTER) framework uses a statistical graphical model that applies phylogenetic principles to automate precise protein function prediction. Here we present a revised approach (SIFTER version 2.0) that enables annotations on a genomic scale. SIFTER 2.0 produces equivalently precise predictions compared to the earlier version on a carefully studied family and on a collection of 100 protein families. We have added an approximation method to SIFTER 2.0 and show a 500-fold improvement in speed with minimal impact on prediction results in the functionally diverse sulfotransferase protein family. On the Nudix protein family, previously inaccessible to the SIFTER framework because of the 66 possible molecular functions, SIFTER achieved 47.4% accuracy on experimental data (where BLAST achieved 34.0%). Finally, we used SIFTER to annotate all of the Schizosaccharomyces pombe proteins with experimental functional characterizations, based on annotations from proteins in 46 fungal genomes. SIFTER precisely predicted molecular function for 45.5% of the characterized proteins in this genome, as compared with four current function prediction methods that precisely predicted function for 62.6%, 30.6%, 6.0%, and 5.7% of these proteins. We use both precision-recall curves and ROC analyses to compare these genome-scale predictions across the different methods and to assess performance on different types of applications. SIFTER 2.0 is capable of predicting protein molecular function for large and functionally diverse protein families using an approximate statistical model, enabling phylogenetics-based protein function prediction for genome-wide analyses. The code for SIFTER and protein family data are available at http://sifter.berkeley.edu.

  18. Functional Annotation Analytics of Bacillus Genomes Reveals Stress Responsive Acetate Utilization and Sulfate Uptake in the Biotechnologically Relevant Bacillus megaterium.

    PubMed

    Williams, Baraka S; Isokpehi, Raphael D; Mbah, Andreas N; Hollman, Antoinesha L; Bernard, Christina O; Simmons, Shaneka S; Ayensu, Wellington K; Garner, Bianca L

    2012-01-01

    Bacillus species form an heterogeneous group of Gram-positive bacteria that include members that are disease-causing, biotechnologically-relevant, and can serve as biological research tools. A common feature of Bacillus species is their ability to survive in harsh environmental conditions by formation of resistant endospores. Genes encoding the universal stress protein (USP) domain confer cellular and organismal survival during unfavorable conditions such as nutrient depletion. As of February 2012, the genome sequences and a variety of functional annotations for at least 123 Bacillus isolates including 45 Bacillus cereus isolates were available in public domain bioinformatics resources. Additionally, the genome sequencing status of 10 of the B. cereus isolates were annotated as finished with each genome encoded 3 USP genes. The conservation of gene neighborhood of the 140 aa universal stress protein in the B. cereus genomes led to the identification of a predicted plasmid-encoded transcriptional unit that includes a USP gene and a sulfate uptake gene in the soil-inhabiting Bacillus megaterium. Gene neighborhood analysis combined with visual analytics of chemical ligand binding sites data provided knowledge-building biological insights on possible cellular functions of B. megaterium universal stress proteins. These functions include sulfate and potassium uptake, acid extrusion, cellular energy-level sensing, survival in high oxygen conditions and acetate utilization. Of particular interest was a two-gene transcriptional unit that consisted of genes for a universal stress protein and a sirtuin Sir2 (deacetylase enzyme for NAD+-dependent acetate utilization). The predicted transcriptional units for stress responsive inorganic sulfate uptake and acetate utilization could explain biological mechanisms for survival of soil-inhabiting Bacillus species in sulfate and acetate limiting conditions. Considering the key role of sirtuins in mammalian physiology additional

  19. Functional Annotation Analytics of Bacillus Genomes Reveals Stress Responsive Acetate Utilization and Sulfate Uptake in the Biotechnologically Relevant Bacillus megaterium

    PubMed Central

    Williams, Baraka S.; Isokpehi, Raphael D.; Mbah, Andreas N.; Hollman, Antoinesha L.; Bernard, Christina O.; Simmons, Shaneka S.; Ayensu, Wellington K.; Garner, Bianca L.

    2012-01-01

    Bacillus species form an heterogeneous group of Gram-positive bacteria that include members that are disease-causing, biotechnologically-relevant, and can serve as biological research tools. A common feature of Bacillus species is their ability to survive in harsh environmental conditions by formation of resistant endospores. Genes encoding the universal stress protein (USP) domain confer cellular and organismal survival during unfavorable conditions such as nutrient depletion. As of February 2012, the genome sequences and a variety of functional annotations for at least 123 Bacillus isolates including 45 Bacillus cereus isolates were available in public domain bioinformatics resources. Additionally, the genome sequencing status of 10 of the B. cereus isolates were annotated as finished with each genome encoded 3 USP genes. The conservation of gene neighborhood of the 140 aa universal stress protein in the B. cereus genomes led to the identification of a predicted plasmid-encoded transcriptional unit that includes a USP gene and a sulfate uptake gene in the soil-inhabiting Bacillus megaterium. Gene neighborhood analysis combined with visual analytics of chemical ligand binding sites data provided knowledge-building biological insights on possible cellular functions of B. megaterium universal stress proteins. These functions include sulfate and potassium uptake, acid extrusion, cellular energy-level sensing, survival in high oxygen conditions and acetate utilization. Of particular interest was a two-gene transcriptional unit that consisted of genes for a universal stress protein and a sirtuin Sir2 (deacetylase enzyme for NAD+-dependent acetate utilization). The predicted transcriptional units for stress responsive inorganic sulfate uptake and acetate utilization could explain biological mechanisms for survival of soil-inhabiting Bacillus species in sulfate and acetate limiting conditions. Considering the key role of sirtuins in mammalian physiology additional

  20. Estimating the annotation error rate of curated GO database sequence annotations

    PubMed Central

    Jones, Craig E; Brown, Alfred L; Baumann, Ute

    2007-01-01

    Background Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO) sequence database (GOSeqLite). This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences. Results We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006) at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS) had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS) had an estimated error rate of 49%. Conclusion While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information. PMID:17519041

  1. The Protein Information Resource: an integrated public resource of functional annotation of proteins

    PubMed Central

    Wu, Cathy H.; Huang, Hongzhan; Arminski, Leslie; Castro-Alvear, Jorge; Chen, Yongxing; Hu, Zhang-Zhi; Ledley, Robert S.; Lewis, Kali C.; Mewes, Hans-Werner; Orcutt, Bruce C.; Suzek, Baris E.; Tsugita, Akira; Vinayaka, C. R.; Yeh, Lai-Su L.; Zhang, Jian; Barker, Winona C.

    2002-01-01

    The Protein Information Resource (PIR) serves as an integrated public resource of functional annotation of protein data to support genomic/proteomic research and scientific discovery. The PIR, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the PIR-International Protein Sequence Database (PSD), the major annotated protein sequence database in the public domain, containing about 250 000 proteins. To improve protein annotation and the coverage of experimentally validated data, a bibliography submission system is developed for scientists to submit, categorize and retrieve literature information. Comprehensive protein information is available from iProClass, which includes family classification at the superfamily, domain and motif levels, structural and functional features of proteins, as well as cross-references to over 40 biological databases. To provide timely and comprehensive protein data with source attribution, we have introduced a non-redundant reference protein database, PIR-NREF. The database consists of about 800 000 proteins collected from PIR-PSD, SWISS-PROT, TrEMBL, GenPept, RefSeq and PDB, with composite protein names and literature data. To promote database interoperability, we provide XML data distribution and open database schema, and adopt common ontologies. The PIR web site (http://pir.georgetown.edu/) features data mining and sequence analysis tools for information retrieval and functional identification of proteins based on both sequence and annotation information. The PIR databases and other files are also available by FTP (ftp://nbrfa.georgetown.edu/pir_databases). PMID:11752247

  2. Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction

    PubMed Central

    Wu, Yiming; Jing, Runyu; Dong, Yongcheng; Kuang, Qifan; Li, Yan; Huang, Ziyan; Gan, Wei; Xue, Yue; Li, Yizhou; Li, Menglong

    2017-01-01

    Genome-wide association studies (GWAS) have identified more than sixty single nucleotide polymorphisms (SNPs) associated with increased risk for type 2 diabetes (T2D). However, the identification of causal risk SNPs for T2D pathogenesis was complicated by the factor that each risk SNP is a surrogate for the hundreds of SNPs, most of which reside in non-coding regions. Here we provide a comprehensive annotation of 65 known T2D related SNPs and inspect putative functional SNPs probably causing protein dysfunction, response element disruptions of known transcription factors related to T2D genes and regulatory response element disruption of four histone marks in pancreas and pancreas islet. In new identified risk SNPs, some of them were reported as T2D related SNPs in recent studies. Further, we found that accumulation of modest effects of single sites markedly enhanced the risk prediction based on 1989 T2D samples and 3000 healthy controls. The AROC value increased from 0.58 to 0.62 by only using genotype score when putative risk SNPs were added. Besides, the net reclassification improvement is 10.03% on the addition of new risk SNPs. Taken together, functional annotation could provide a list of prioritized potential risk SNPs for the further estimation on the T2D susceptibility of individuals. PMID:28262806

  3. Annotation of cis-regulatory elements by identification, subclassification, and functional assessment of multispecies conserved sequences

    PubMed Central

    Hughes, Jim R.; Cheng, Jan-Fang; Ventress, Nicki; Prabhakar, Shyam; Clark, Kevin; Anguita, Eduardo; De Gobbi, Marco; de Jong, Pieter; Rubin, Eddy; Higgs, Douglas R.

    2005-01-01

    An important step toward improving the annotation of the human genome is to identify cis-acting regulatory elements from primary DNA sequence. One approach is to compare sequences from multiple, divergent species. This approach distinguishes multispecies conserved sequences (MCS) in noncoding regions from more rapidly evolving neutral DNA. Here, we have analyzed a region of ≈238kb containing the human α globin cluster that was sequenced and/or annotated across the syntenic region in 22 species spanning 500 million years of evolution. Using a variety of bioinformatic approaches and correlating the results with many aspects of chromosome structure and function in this region, we were able to identify and evaluate the importance of 24 individual MCSs. This approach sensitively and accurately identified previously characterized regulatory elements but also discovered unidentified promoters, exons, splicing, and transcriptional regulatory elements. Together, these studies demonstrate an integrated approach by which to identify, subclassify, and predict the potential importance of MCSs. PMID:15998734

  4. Next-Generation Annotation of Prokaryotic Genomes with EuGene-P: Application to Sinorhizobium meliloti 2011

    PubMed Central

    Sallet, Erika; Roux, Brice; Sauviac, Laurent; Jardinaud, Marie-Franc¸oise; Carrère, Sébastien; Faraut, Thomas; de Carvalho-Niebel, Fernanda; Gouzy, Jérôme; Gamas, Pascal; Capela, Delphine; Bruand, Claude; Schiex, Thomas

    2013-01-01

    The availability of next-generation sequences of transcripts from prokaryotic organisms offers the opportunity to design a new generation of automated genome annotation tools not yet available for prokaryotes. In this work, we designed EuGene-P, the first integrative prokaryotic gene finder tool which combines a variety of high-throughput data, including oriented RNA-Seq data, directly into the prediction process. This enables the automated prediction of coding sequences (CDSs), untranslated regions, transcription start sites (TSSs) and non-coding RNA (ncRNA, sense and antisense) genes. EuGene-P was used to comprehensively and accurately annotate the genome of the nitrogen-fixing bacterium Sinorhizobium meliloti strain 2011, leading to the prediction of 6308 CDSs as well as 1876 ncRNAs. Among them, 1280 appeared as antisense to a CDS, which supports recent findings that antisense transcription activity is widespread in bacteria. Moreover, 4077 TSSs upstream of protein-coding or non-coding genes were precisely mapped providing valuable data for the study of promoter regions. By looking for RpoE2-binding sites upstream of annotated TSSs, we were able to extend the S. meliloti RpoE2 regulon by ∼3-fold. Altogether, these observations demonstrate the power of EuGene-P to produce a reliable and high-resolution automatic annotation of prokaryotic genomes. PMID:23599422

  5. OrthoDB v9.1: cataloging evolutionary and functional annotations for animal, fungal, plant, archaeal, bacterial and viral orthologs.

    PubMed

    Zdobnov, Evgeny M; Tegenfeldt, Fredrik; Kuznetsov, Dmitry; Waterhouse, Robert M; Simão, Felipe A; Ioannidis, Panagiotis; Seppey, Mathieu; Loetscher, Alexis; Kriventseva, Evgenia V

    2017-01-04

    OrthoDB is a comprehensive catalog of orthologs, genes inherited by extant species from a single gene in their last common ancestor. In 2016 OrthoDB reached its 9th release, growing to over 22 million genes from over 5000 species, now adding plants, archaea and viruses. In this update we focused on usability of this fast-growing wealth of data: updating the user and programmatic interfaces to browse and query the data, and further enhancing the already extensive integration of available gene functional annotations. Collating functional annotations from over 100 resources, and enabled us to propose descriptive titles for 87% of ortholog groups. Additionally, OrthoDB continues to provide computed evolutionary annotations and to allow user queries by sequence homology. The OrthoDB resource now enables users to generate publication-quality comparative genomics charts, as well as to upload, analyze and interactively explore their own private data. OrthoDB is available from http://orthodb.org.

  6. OrthoDB v9.1: cataloging evolutionary and functional annotations for animal, fungal, plant, archaeal, bacterial and viral orthologs

    PubMed Central

    Zdobnov, Evgeny M.; Tegenfeldt, Fredrik; Kuznetsov, Dmitry; Waterhouse, Robert M.; Simão, Felipe A.; Ioannidis, Panagiotis; Seppey, Mathieu; Loetscher, Alexis; Kriventseva, Evgenia V.

    2017-01-01

    OrthoDB is a comprehensive catalog of orthologs, genes inherited by extant species from a single gene in their last common ancestor. In 2016 OrthoDB reached its 9th release, growing to over 22 million genes from over 5000 species, now adding plants, archaea and viruses. In this update we focused on usability of this fast-growing wealth of data: updating the user and programmatic interfaces to browse and query the data, and further enhancing the already extensive integration of available gene functional annotations. Collating functional annotations from over 100 resources, and enabled us to propose descriptive titles for 87% of ortholog groups. Additionally, OrthoDB continues to provide computed evolutionary annotations and to allow user queries by sequence homology. The OrthoDB resource now enables users to generate publication-quality comparative genomics charts, as well as to upload, analyze and interactively explore their own private data. OrthoDB is available from http://orthodb.org. PMID:27899580

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

    PubMed Central

    Barbosa-Morais, Nuno L.; Carmo-Fonseca, Maria; Aparício, Samuel

    2006-01-01

    Although more than 200 human spliceosomal and splicing-associated proteins are known, the evolution of the splicing machinery has not been studied extensively. The recent near-complete sequencing and annotation of distant vertebrate and chordate genomes provides the opportunity for an exhaustive comparative analysis of splicing factors across eukaryotes. We describe here our semiautomated computational pipeline to identify and annotate splicing factors in representative species of eukaryotes. We focused on protein families whose role in splicing is confirmed by experimental evidence. We visually inspected 1894 proteins and manually curated 224 of them. Our analysis shows a general conservation of the core spliceosomal proteins across the eukaryotic lineage, contrasting with selective expansions of protein families known to play a role in the regulation of splicing, most notably of SR proteins in metazoans and of heterogeneous nuclear ribonucleoproteins (hnRNP) in vertebrates. We also observed vertebrate-specific expansion of the CLK and SRPK kinases (which phosphorylate SR proteins), and the CUG-BP/CELF family of splicing regulators. Furthermore, we report several intronless genes amongst splicing proteins in mammals, suggesting that retrotransposition contributed to the complexity of the mammalian splicing apparatus. PMID:16344558

  8. Analysis of CATMA transcriptome data identifies hundreds of novel functional genes and improves gene models in the Arabidopsis genome

    PubMed Central

    Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Brunaud, Véronique; Taconnat, Ludivine; Bitton, Frédérique; Balzergue, Sandrine; Jullien, Pauline E; Ingouff, Mathieu; Thareau, Vincent; Schiex, Thomas; Lecharny, Alain; Renou, Jean-Pierre

    2007-01-01

    Background Since the finishing of the sequencing of the Arabidopsis thaliana genome, the Arabidopsis community and the annotator centers have been working on the improvement of gene annotation at the structural and functional levels. In this context, we have used the large CATMA resource on the Arabidopsis transcriptome to search for genes missed by different annotation processes. Probes on the CATMA microarrays are specific gene sequence tags (GSTs) based on the CDS models predicted by the Eugene software. Among the 24 576 CATMA v2 GSTs, 677 are in regions considered as intergenic by the TAIR annotation. We analyzed the cognate transcriptome data in the CATMA resource and carried out data-mining to characterize novel genes and improve gene models. Results The statistical analysis of the results of more than 500 hybridized samples distributed among 12 organs provides an experimental validation for 465 novel genes. The hybridization evidence was confirmed by RT-PCR approaches for 88% of the 465 novel genes. Comparisons with the current annotation show that these novel genes often encode small proteins, with an average size of 137 aa. Our approach has also led to the improvement of pre-existing gene models through both the extension of 16 CDS and the identification of 13 gene models erroneously constituted of two merged CDS. Conclusion This work is a noticeable step forward in the improvement of the Arabidopsis genome annotation. We increased the number of Arabidopsis validated genes by 465 novel transcribed genes to which we associated several functional annotations such as expression profiles, sequence conservation in plants, cognate transcripts and protein motifs. PMID:17980019

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

    PubMed

    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.

  10. Annotation inconsistencies beyond sequence similarity-based function prediction - phylogeny and genome structure.

    PubMed

    Promponas, Vasilis J; Iliopoulos, Ioannis; Ouzounis, Christos A

    2015-01-01

    The function annotation process in computational biology has increasingly shifted from the traditional characterization of individual biochemical roles of protein molecules to the system-wide detection of entire metabolic pathways and genomic structures. The so-called genome-aware methods broaden misannotation inconsistencies in genome sequences beyond protein function assignments, encompassing phylogenetic anomalies and artifactual genomic regions. We outline three categories of error propagation in databases by providing striking examples - at various levels of appreciation by the community from traditional to emerging, thus raising awareness for future solutions.

  11. Functional characterization of two M42 aminopeptidases erroneously annotated as cellulases.

    PubMed

    Dutoit, Raphaël; Brandt, Nathalie; Legrain, Christianne; Bauvois, Cédric

    2012-01-01

    Several aminopeptidases of the M42 family have been described as tetrahedral-shaped dodecameric (TET) aminopeptidases. A current hypothesis suggests that these enzymes are involved, along with the tricorn peptidase, in degrading peptides produced by the proteasome. Yet the M42 family remains ill defined, as some members have been annotated as cellulases because of their homology with CelM, formerly described as an endoglucanase of Clostridium thermocellum. Here we describe the catalytic functions and substrate profiles CelM and of TmPep1050, the latter having been annotated as an endoglucanase of Thermotoga maritima. Both enzymes were shown to catalyze hydrolysis of nonpolar aliphatic L-amino acid-pNA substrates, the L-leucine derivative appearing as the best substrate. No significant endoglucanase activity was measured, either for TmPep1050 or CelM. Addition of cobalt ions enhanced the activity of both enzymes significantly, while both the chelating agent EDTA and bestatin, a specific inhibitor of metalloaminopeptidases, proved inhibitory. Our results strongly suggest that one should avoid annotating members of the M42 aminopeptidase family as cellulases. In an updated assessment of the distribution of M42 aminopeptidases, we found TET aminopeptidases to be distributed widely amongst archaea and bacteria. We additionally observed that several phyla lack both TET and tricorn. This suggests that other complexes may act downstream from the proteasome.

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

    PubMed

    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.

  13. Ribosome profiling reveals pervasive translation outside of annotated protein-coding genes.

    PubMed

    Ingolia, Nicholas T; Brar, Gloria A; Stern-Ginossar, Noam; Harris, Michael S; Talhouarne, Gaëlle J S; Jackson, Sarah E; Wills, Mark R; Weissman, Jonathan S

    2014-09-11

    Ribosome profiling suggests that ribosomes occupy many regions of the transcriptome thought to be noncoding, including 5' UTRs and long noncoding RNAs (lncRNAs). Apparent ribosome footprints outside of protein-coding regions raise the possibility of artifacts unrelated to translation, particularly when they occupy multiple, overlapping open reading frames (ORFs). Here, we show hallmarks of translation in these footprints: copurification with the large ribosomal subunit, response to drugs targeting elongation, trinucleotide periodicity, and initiation at early AUGs. We develop a metric for distinguishing between 80S footprints and nonribosomal sources using footprint size distributions, which validates the vast majority of footprints outside of coding regions. We present evidence for polypeptide production beyond annotated genes, including the induction of immune responses following human cytomegalovirus (HCMV) infection. Translation is pervasive on cytosolic transcripts outside of conserved reading frames, and direct detection of this expanded universe of translated products enables efforts at understanding how cells manage and exploit its consequences.

  14. GOblet: a platform for Gene Ontology annotation of anonymous sequence data

    PubMed Central

    Groth, Detlef; Lehrach, Hans; Hennig, Steffen

    2004-01-01

    GOblet is a comprehensive web server application providing the annotation of anonymous sequence data with Gene Ontology (GO) terms. It uses a variety of different protein databases (human, murines, invertebrates, plants, sp-trembl) and their respective GO mappings. The user selects the appropriate database and alignment threshold and thereafter submits single or multiple nucleotide or protein sequences. Results are shown in different ways, e.g. as survey statistics for the main GO categories for all sequences or as detailed results for each single sequence that has been submitted. In its newest version, GOblet allows the batch submission of sequences and provides an improved display of results with the aid of Java applets. All output data, together with the Java applet, are packed to a downloadable archive for local installation and analysis. GOblet can be accessed freely at http://goblet.molgen.mpg.de. PMID:15215401

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

    PubMed Central

    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. PMID:26504533

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

    PubMed

    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.

  17. Functional Gene Networks: R/Bioc package to generate and analyse gene networks derived from functional enrichment and clustering

    PubMed Central

    Aibar, Sara; Fontanillo, Celia; Droste, Conrad; De Las Rivas, Javier

    2015-01-01

    Summary: Functional Gene Networks (FGNet) is an R/Bioconductor package that generates gene networks derived from the results of functional enrichment analysis (FEA) and annotation clustering. The sets of genes enriched with specific biological terms (obtained from a FEA platform) are transformed into a network by establishing links between genes based on common functional annotations and common clusters. The network provides a new view of FEA results revealing gene modules with similar functions and genes that are related to multiple functions. In addition to building the functional network, FGNet analyses the similarity between the groups of genes and provides a distance heatmap and a bipartite network of functionally overlapping genes. The application includes an interface to directly perform FEA queries using different external tools: DAVID, GeneTerm Linker, TopGO or GAGE; and a graphical interface to facilitate the use. Availability and implementation: FGNet is available in Bioconductor, including a tutorial. URL: http://bioconductor.org/packages/release/bioc/html/FGNet.html Contact: jrivas@usal.es Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25600944

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

    PubMed

    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.

  19. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes

    PubMed Central

    Brettin, Thomas; Davis, James J.; Disz, Terry; Edwards, Robert A.; Gerdes, Svetlana; Olsen, Gary J.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Thomason, James A.; Stevens, Rick; Vonstein, Veronika; Wattam, Alice R.; Xia, Fangfang

    2015-01-01

    The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception. PMID:25666585

  20. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes

    SciTech Connect

    Brettin, Thomas; Davis, James J.; Disz, Terry; Edwards, Robert A.; Gerdes, Svetlana; Olsen, Gary J.; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D.; Shukla, Maulik; Thomason, III, James A.; Stevens, Rick; Vonstein, Veronika; Wattam, Alice R.; Xia, Fangfang

    2015-02-10

    The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.

  1. RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes.

    PubMed

    Brettin, Thomas; Davis, James J; Disz, Terry; Edwards, Robert A; Gerdes, Svetlana; Olsen, Gary J; Olson, Robert; Overbeek, Ross; Parrello, Bruce; Pusch, Gordon D; Shukla, Maulik; Thomason, James A; Stevens, Rick; Vonstein, Veronika; Wattam, Alice R; Xia, Fangfang

    2015-02-10

    The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offers a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.

  2. BambooGDB: a bamboo genome database with functional annotation and an analysis platform

    PubMed Central

    Zhao, Hansheng; Peng, Zhenhua; Fei, Benhua; Li, Lubin; Hu, Tao; Gao, Zhimin; Jiang, Zehui

    2014-01-01

    Bamboo, as one of the most important non-timber forest products and fastest-growing plants in the world, represents the only major lineage of grasses that is native to forests. Recent success on the first high-quality draft genome sequence of moso bamboo (Phyllostachys edulis) provides new insights on bamboo genetics and evolution. To further extend our understanding on bamboo genome and facilitate future studies on the basis of previous achievements, here we have developed BambooGDB, a bamboo genome database with functional annotation and analysis platform. The de novo sequencing data, together with the full-length complementary DNA and RNA-seq data of moso bamboo composed the main contents of this database. Based on these sequence data, a comprehensively functional annotation for bamboo genome was made. Besides, an analytical platform composed of comparative genomic analysis, protein–protein interactions network, pathway analysis and visualization of genomic data was also constructed. As discovery tools to understand and identify biological mechanisms of bamboo, the platform can be used as a systematic framework for helping and designing experiments for further validation. Moreover, diverse and powerful search tools and a convenient browser were incorporated to facilitate the navigation of these data. As far as we know, this is the first genome database for bamboo. Through integrating high-throughput sequencing data, a full functional annotation and several analysis modules, BambooGDB aims to provide worldwide researchers with a central genomic resource and an extensible analysis platform for bamboo genome. BambooGDB is freely available at http://www.bamboogdb.org/. Database URL: http://www.bamboogdb.org PMID:24602877

  3. BambooGDB: a bamboo genome database with functional annotation and an analysis platform.

    PubMed

    Zhao, Hansheng; Peng, Zhenhua; Fei, Benhua; Li, Lubin; Hu, Tao; Gao, Zhimin; Jiang, Zehui

    2014-01-01

    Bamboo, as one of the most important non-timber forest products and fastest-growing plants in the world, represents the only major lineage of grasses that is native to forests. Recent success on the first high-quality draft genome sequence of moso bamboo (Phyllostachys edulis) provides new insights on bamboo genetics and evolution. To further extend our understanding on bamboo genome and facilitate future studies on the basis of previous achievements, here we have developed BambooGDB, a bamboo genome database with functional annotation and analysis platform. The de novo sequencing data, together with the full-length complementary DNA and RNA-seq data of moso bamboo composed the main contents of this database. Based on these sequence data, a comprehensively functional annotation for bamboo genome was made. Besides, an analytical platform composed of comparative genomic analysis, protein-protein interactions network, pathway analysis and visualization of genomic data was also constructed. As discovery tools to understand and identify biological mechanisms of bamboo, the platform can be used as a systematic framework for helping and designing experiments for further validation. Moreover, diverse and powerful search tools and a convenient browser were incorporated to facilitate the navigation of these data. As far as we know, this is the first genome database for bamboo. Through integrating high-throughput sequencing data, a full functional annotation and several analysis modules, BambooGDB aims to provide worldwide researchers with a central genomic resource and an extensible analysis platform for bamboo genome. BambooGDB is freely available at http://www.bamboogdb.org/. Database URL: http://www.bamboogdb.org.

  4. Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions.

    PubMed

    Han, Ying; Hazelett, Dennis J; Wiklund, Fredrik; Schumacher, Fredrick R; Stram, Daniel O; Berndt, Sonja I; Wang, Zhaoming; Rand, Kristin A; Hoover, Robert N; Machiela, Mitchell J; Yeager, Merideth; Burdette, Laurie; Chung, Charles C; Hutchinson, Amy; Yu, Kai; Xu, Jianfeng; Travis, Ruth C; Key, Timothy J; Siddiq, Afshan; Canzian, Federico; Takahashi, Atsushi; Kubo, Michiaki; Stanford, Janet L; Kolb, Suzanne; Gapstur, Susan M; Diver, W Ryan; Stevens, Victoria L; Strom, Sara S; Pettaway, Curtis A; Al Olama, Ali Amin; Kote-Jarai, Zsofia; Eeles, Rosalind A; Yeboah, Edward D; Tettey, Yao; Biritwum, Richard B; Adjei, Andrew A; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P; Isaacs, William B; Chen, Constance; Lindstrom, Sara; Le Marchand, Loic; Giovannucci, Edward L; Pomerantz, Mark; Long, Henry; Li, Fugen; Ma, Jing; Stampfer, Meir; John, Esther M; Ingles, Sue A; Kittles, Rick A; Murphy, Adam B; Blot, William J; Signorello, Lisa B; Zheng, Wei; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Nemesure, Barbara; Carpten, John; Leske, M Cristina; Wu, Suh-Yuh; Hennis, Anselm J M; Rybicki, Benjamin A; Neslund-Dudas, Christine; Hsing, Ann W; Chu, Lisa; Goodman, Phyllis J; Klein, Eric A; Zheng, S Lilly; Witte, John S; Casey, Graham; Riboli, Elio; Li, Qiyuan; Freedman, Matthew L; Hunter, David J; Gronberg, Henrik; Cook, Michael B; Nakagawa, Hidewaki; Kraft, Peter; Chanock, Stephen J; Easton, Douglas F; Henderson, Brian E; Coetzee, Gerhard A; Conti, David V; Haiman, Christopher A

    2015-10-01

    Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.

  5. Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions

    PubMed Central

    Han, Ying; Hazelett, Dennis J.; Wiklund, Fredrik; Schumacher, Fredrick R.; Stram, Daniel O.; Berndt, Sonja I.; Wang, Zhaoming; Rand, Kristin A.; Hoover, Robert N.; Machiela, Mitchell J.; Yeager, Merideth; Burdette, Laurie; Chung, Charles C.; Hutchinson, Amy; Yu, Kai; Xu, Jianfeng; Travis, Ruth C.; Key, Timothy J.; Siddiq, Afshan; Canzian, Federico; Takahashi, Atsushi; Kubo, Michiaki; Stanford, Janet L.; Kolb, Suzanne; Gapstur, Susan M.; Diver, W. Ryan; Stevens, Victoria L.; Strom, Sara S.; Pettaway, Curtis A.; Al Olama, Ali Amin; Kote-Jarai, Zsofia; Eeles, Rosalind A.; Yeboah, Edward D.; Tettey, Yao; Biritwum, Richard B.; Adjei, Andrew A.; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P.; Isaacs, William B.; Chen, Constance; Lindstrom, Sara; Le Marchand, Loic; Giovannucci, Edward L.; Pomerantz, Mark; Long, Henry; Li, Fugen; Ma, Jing; Stampfer, Meir; John, Esther M.; Ingles, Sue A.; Kittles, Rick A.; Murphy, Adam B.; Blot, William J.; Signorello, Lisa B.; Zheng, Wei; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Nemesure, Barbara; Carpten, John; Leske, M. Cristina; Wu, Suh-Yuh; Hennis, Anselm J. M.; Rybicki, Benjamin A.; Neslund-Dudas, Christine; Hsing, Ann W.; Chu, Lisa; Goodman, Phyllis J.; Klein, Eric A.; Zheng, S. Lilly; Witte, John S.; Casey, Graham; Riboli, Elio; Li, Qiyuan; Freedman, Matthew L.; Hunter, David J.; Gronberg, Henrik; Cook, Michael B.; Nakagawa, Hidewaki; Kraft, Peter; Chanock, Stephen J.; Easton, Douglas F.; Henderson, Brian E.; Coetzee, Gerhard A.; Conti, David V.; Haiman, Christopher A.

    2015-01-01

    Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10−4–5.6 × 10−3) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10−6) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation. PMID:26162851

  6. Development and Evaluation of an Automated Annotation Pipeline and cDNA Annotation System

    PubMed Central

    Kasukawa, Takeya; Furuno, Masaaki; Nikaido, Itoshi; Bono, Hidemasa; Hume, David A.; Bult, Carol; Hill, David P.; Baldarelli, Richard; Gough, Julian; Kanapin, Alexander; Matsuda, Hideo; Schriml, Lynn M.; Hayashizaki, Yoshihide; Okazaki, Yasushi; Quackenbush, John

    2003-01-01

    Manual curation has long been held to be the “gold standard” for functional annotation of DNA sequence. Our experience with the annotation of more than 20,000 full-length cDNA sequences revealed problems with this approach, including inaccurate and inconsistent assignment of gene names, as well as many good assignments that were difficult to reproduce using only computational methods. For the FANTOM2 annotation of more than 60,000 cDNA clones, we developed a number of methods and tools to circumvent some of these problems, including an automated annotation pipeline that provides high-quality preliminary annotation for each sequence by introducing an “uninformative filter” that eliminates uninformative annotations, controlled vocabularies to accurately reflect both the functional assignments and the evidence supporting them, and a highly refined, Web-based manual annotation tool that allows users to view a wide array of sequence analyses and to assign gene names and putative functions using a consistent nomenclature. The ultimate utility of our approach is reflected in the low rate of reassignment of automated assignments by manual curation. Based on these results, we propose a new standard for large-scale annotation, in which the initial automated annotations are manually investigated and then computational methods are iteratively modified and improved based on the results of manual curation. PMID:12819153

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

    PubMed Central

    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

  8. Annotation extension through protein family annotation coherence metrics

    PubMed Central

    Bastos, Hugo P.; Clarke, Luka A.; Couto, Francisco M.

    2013-01-01

    Protein functional annotation consists in associating proteins with textual descriptors elucidating their biological roles. The bulk of annotation is done via automated procedures that ultimately rely on annotation transfer. Despite a large number of existing protein annotation procedures the ever growing protein space is never completely annotated. One of the facets of annotation incompleteness derives from annotation uncertainty. Often when protein function cannot be predicted with enough specificity it is instead conservatively annotated with more generic terms. In a scenario of protein families or functionally related (or even dissimilar) sets this leads to a more difficult task of using annotations to compare the extent of functional relatedness among all family or set members. However, we postulate that identifying sub-sets of functionally coherent proteins annotated at a very specific level, can help the annotation extension of other incompletely annotated proteins within the same family or functionally related set. As an example we analyse the status of annotation of a set of CAZy families belonging to the Polysaccharide Lyase class. We show that through the use of visualization methods and semantic similarity based metrics it is possible to identify families and respective annotation terms within them that are suitable for possible annotation extension. Based on our analysis we then propose a semi-automatic methodology leading to the extension of single annotation terms within these partially annotated protein sets or families. PMID:24130572

  9. WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation

    PubMed Central

    2013-01-01

    Background SNPs&GO is a method for the prediction of deleterious Single Amino acid Polymorphisms (SAPs) using protein functional annotation. In this work, we present the web server implementation of SNPs&GO (WS-SNPs&GO). The server is based on Support Vector Machines (SVM) and for a given protein, its input comprises: the sequence and/or its three-dimensional structure (when available), a set of target variations and its functional Gene Ontology (GO) terms. The output of the server provides, for each protein variation, the probabilities to be associated to human diseases. Results The server consists of two main components, including updated versions of the sequence-based SNPs&GO (recently scored as one of the best algorithms for predicting deleterious SAPs) and of the structure-based SNPs&GO3d programs. Sequence and structure based algorithms are extensively tested on a large set of annotated variations extracted from the SwissVar database. Selecting a balanced dataset with more than 38,000 SAPs, the sequence-based approach achieves 81% overall accuracy, 0.61 correlation coefficient and an Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve of 0.88. For the subset of ~6,600 variations mapped on protein structures available at the Protein Data Bank (PDB), the structure-based method scores with 84% overall accuracy, 0.68 correlation coefficient, and 0.91 AUC. When tested on a new blind set of variations, the results of the server are 79% and 83% overall accuracy for the sequence-based and structure-based inputs, respectively. Conclusions WS-SNPs&GO is a valuable tool that includes in a unique framework information derived from protein sequence, structure, evolutionary profile, and protein function. WS-SNPs&GO is freely available at http://snps.biofold.org/snps-and-go. PMID:23819482

  10. An Introduction to Genome Annotation.

    PubMed

    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.

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

    PubMed

    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.

  12. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation.

    PubMed

    O'Leary, Nuala A; Wright, Mathew W; Brister, J Rodney; Ciufo, Stacy; Haddad, Diana; McVeigh, Rich; Rajput, Bhanu; Robbertse, Barbara; Smith-White, Brian; Ako-Adjei, Danso; Astashyn, Alexander; Badretdin, Azat; Bao, Yiming; Blinkova, Olga; Brover, Vyacheslav; Chetvernin, Vyacheslav; Choi, Jinna; Cox, Eric; Ermolaeva, Olga; Farrell, Catherine M; Goldfarb, Tamara; Gupta, Tripti; Haft, Daniel; Hatcher, Eneida; Hlavina, Wratko; Joardar, Vinita S; Kodali, Vamsi K; Li, Wenjun; Maglott, Donna; Masterson, Patrick; McGarvey, Kelly M; Murphy, Michael R; O'Neill, Kathleen; Pujar, Shashikant; Rangwala, Sanjida H; Rausch, Daniel; Riddick, Lillian D; Schoch, Conrad; Shkeda, Andrei; Storz, Susan S; Sun, Hanzhen; Thibaud-Nissen, Francoise; Tolstoy, Igor; Tully, Raymond E; Vatsan, Anjana R; Wallin, Craig; Webb, David; Wu, Wendy; Landrum, Melissa J; Kimchi, Avi; Tatusova, Tatiana; DiCuccio, Michael; Kitts, Paul; Murphy, Terence D; Pruitt, Kim D

    2016-01-04

    The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55,000 organisms (>4800 viruses, >40,000 prokaryotes and >10,000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management.

  13. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation

    PubMed Central

    O'Leary, Nuala A.; Wright, Mathew W.; Brister, J. Rodney; Ciufo, Stacy; Haddad, Diana; McVeigh, Rich; Rajput, Bhanu; Robbertse, Barbara; Smith-White, Brian; Ako-Adjei, Danso; Astashyn, Alexander; Badretdin, Azat; Bao, Yiming; Blinkova, Olga; Brover, Vyacheslav; Chetvernin, Vyacheslav; Choi, Jinna; Cox, Eric; Ermolaeva, Olga; Farrell, Catherine M.; Goldfarb, Tamara; Gupta, Tripti; Haft, Daniel; Hatcher, Eneida; Hlavina, Wratko; Joardar, Vinita S.; Kodali, Vamsi K.; Li, Wenjun; Maglott, Donna; Masterson, Patrick; McGarvey, Kelly M.; Murphy, Michael R.; O'Neill, Kathleen; Pujar, Shashikant; Rangwala, Sanjida H.; Rausch, Daniel; Riddick, Lillian D.; Schoch, Conrad; Shkeda, Andrei; Storz, Susan S.; Sun, Hanzhen; Thibaud-Nissen, Francoise; Tolstoy, Igor; Tully, Raymond E.; Vatsan, Anjana R.; Wallin, Craig; Webb, David; Wu, Wendy; Landrum, Melissa J.; Kimchi, Avi; Tatusova, Tatiana; DiCuccio, Michael; Kitts, Paul; Murphy, Terence D.; Pruitt, Kim D.

    2016-01-01

    The RefSeq project at the National Center for Biotechnology Information (NCBI) maintains and curates a publicly available database of annotated genomic, transcript, and protein sequence records (http://www.ncbi.nlm.nih.gov/refseq/). The RefSeq project leverages the data submitted to the International Nucleotide Sequence Database Collaboration (INSDC) against a combination of computation, manual curation, and collaboration to produce a standard set of stable, non-redundant reference sequences. The RefSeq project augments these reference sequences with current knowledge including publications, functional features and informative nomenclature. The database currently represents sequences from more than 55 000 organisms (>4800 viruses, >40 000 prokaryotes and >10 000 eukaryotes; RefSeq release 71), ranging from a single record to complete genomes. This paper summarizes the current status of the viral, prokaryotic, and eukaryotic branches of the RefSeq project, reports on improvements to data access and details efforts to further expand the taxonomic representation of the collection. We also highlight diverse functional curation initiatives that support multiple uses of RefSeq data including taxonomic validation, genome annotation, comparative genomics, and clinical testing. We summarize our approach to utilizing available RNA-Seq and other data types in our manual curation process for vertebrate, plant, and other species, and describe a new direction for prokaryotic genomes and protein name management. PMID:26553804

  14. Integrating genome annotation and QTL position to identify candidate genes for productivity, architecture and water-use efficiency in Populus spp

    PubMed Central

    2012-01-01

    Background Hybrid poplars species are candidates for biomass production but breeding efforts are needed to combine productivity and water use efficiency in improved cultivars. The understanding of the genetic architecture of growth in poplar by a Quantitative Trait Loci (QTL) approach can help us to elucidate the molecular basis of such integrative traits but identifying candidate genes underlying these QTLs remains difficult. Nevertheless, the increase of genomic information together with the accessibility to a reference genome sequence (Populus trichocarpa Nisqually-1) allow to bridge QTL information on genetic maps and physical location of candidate genes on the genome. The objective of the study is to identify QTLs controlling productivity, architecture and leaf traits in a P. deltoides x P. trichocarpa F1 progeny and to identify candidate genes underlying QTLs based on the anchoring of genetic maps on the genome and the gene ontology information linked to genome annotation. The strategy to explore genome annotation was to use Gene Ontology enrichment tools to test if some functional categories are statistically over-represented in QTL regions. Results Four leaf traits and 7 growth traits were measured on 330 F1 P. deltoides x P. trichocarpa progeny. A total of 77 QTLs controlling 11 traits were identified explaining from 1.8 to 17.2% of the variation of traits. For 58 QTLs, confidence intervals could be projected on the genome. An extended functional annotation was built based on data retrieved from the plant genome database Phytozome and from an inference of function using homology between Populus and the model plant Arabidopsis. Genes located within QTL confidence intervals were retrieved and enrichments in gene ontology (GO) terms were determined using different methods. Significant enrichments were found for all traits. Particularly relevant biological processes GO terms were identified for QTLs controlling number of sylleptic branches: intervals were

  15. Parallel-META 2.0: enhanced metagenomic data analysis with functional annotation, high performance computing and advanced visualization.

    PubMed

    Su, Xiaoquan; Pan, Weihua; Song, Baoxing; Xu, Jian; Ning, Kang

    2014-01-01

    The metagenomic method directly sequences and analyses genome information from microbial communities. The main computational tasks for metagenomic analyses include taxonomical and functional structure analysis for all genomes in a microbial community (also referred to as a metagenomic sample). With the advancement of Next Generation Sequencing (NGS) techniques, the number of metagenomic samples and the data size for each sample are increasing rapidly. Current metagenomic analysis is both data- and computation- intensive, especially when there are many species in a metagenomic sample, and each has a large number of sequences. As such, metagenomic analyses require extensive computational power. The increasing analytical requirements further augment the challenges for computation analysis. In this work, we have proposed Parallel-META 2.0, a metagenomic analysis software package, to cope with such needs for efficient and fast analyses of taxonomical and functional structures for microbial communities. Parallel-META 2.0 is an extended and improved version of Parallel-META 1.0, which enhances the taxonomical analysis using multiple databases, improves computation efficiency by optimized parallel computing, and supports interactive visualization of results in multiple views. Furthermore, it enables functional analysis for metagenomic samples including short-reads assembly, gene prediction and functional annotation. Therefore, it could provide accurate taxonomical and functional analyses of the metagenomic samples in high-throughput manner and on large scale.

  16. Functional Annotation of Metastasis-associated MicroRNAs of Melanoma: A Meta-analysis of Expression Profiles

    PubMed Central

    Li, Jing-Yi; Zheng, Li-Li; Wang, Ting-Ting; Hu, Min

    2016-01-01

    Background: Melanoma is a type of cancer that develops from the pigment-containing cells. Until now, its pathological mechanisms remain largely unknown. The aim of this study was to identify metastasis-related microRNA (miRNAs) and gain an understanding of the biological functions in the metastasis of melanoma. Methods: We searched the PubMed and Gene Expression Omnibus database to collect miRNA expression profiling datasets about melanoma, with key words of “melanoma”, “miRNA”, “microarray”, and “gene expression profiling”. Only the original experimental works published before June 2016 for analyzing the metastasis of melanoma were retained, other nonhuman studies, reviews, and meta-analyses were removed. We performed a meta-analysis to explore the differentially expressed miRNA between metastatic and nonmetastatic samples. Moreover, we predicted target genes of the miRNAs to study their biological roles for these miRNAs. Results: We identified a total of 63 significantly differentially expressed miRNAs by meta-analysis of the melanoma expression profiling data. The regulatory network constructed by using these miRNAs and the predicted targets identified several key genes involved in the metastasis of melanoma. Functional annotation of these genes indicated that they are mainly enriched in some biological pathways such as mitogen-activated protein kinase signaling pathway, cell junction, and focal adhesion. Conclusions: By collecting the miRNA expression datasets from different platforms, multiple biological markers were identified for the metastasis of melanoma. This study provided novel insights into the molecular mechanisms underlying this disease, thereby aiding the diagnosis and treatment of the disease. PMID:27748342

  17. IsoSeq analysis and functional annotation of the infratentorial ependymoma tumor tissue on PacBio RSII platform.

    PubMed

    Singh, Neetu; Sahu, Dinesh Kumar; Chowdhry, Rebecca; Mishra, Archana; Goel, Madhu Mati; Faheem, Mohd; Srivastava, Chhitij; Ojha, Bal Krishna; Gupta, Devendra Kumar; Kant, Ravi

    2016-02-01

    Here, we sequenced and functionally annotated the long reads (1-2 kb) cDNAs library of an infratentorial ependymoma tumor tissue on PacBio RSII by Iso-Seq protocol using SMRT technology. 577 MB, data was generated from the brain tissues of ependymoma tumor patient, producing 1,19,313 high-quality reads assembled into 19,878 contigs using Celera assembler followed by Quiver pipelines, which produced 2952 unique protein accessions in the nr protein database and 307 KEGG pathways. Additionally, when we compared GO terms of second and third level with alternative splicing data obtained through HTA Array2.0. We identified four and twelve transcript cluster IDs in Level-2 and Level-3 scores respectively with alternative splicing index predicting mainly the major pathways of hallmarks of cancer. Out of these transcript cluster IDs only transcript cluster IDs of gene PNMT, SNN and LAMB1 showed Reads Per Kilobase of exon model per Million mapped reads (RPKM) values at gene-level expression (GE) and transcript-level (TE) track. Most importantly, brain-specific genes--PNMT, SNN and LAMB1 show their involvement in Ependymoma.

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

    PubMed

    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.

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

    PubMed

    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.

  20. GO-FAANG meeting: a Gathering On Functional Annotation of Animal Genomes.

    PubMed

    Tuggle, Christopher K; Giuffra, Elisabetta; White, Stephen N; Clarke, Laura; Zhou, Huaijun; Ross, Pablo J; Acloque, Hervé; Reecy, James M; Archibald, Alan; Bellone, Rebecca R; Boichard, Michèle; Chamberlain, Amanda; Cheng, Hans; Crooijmans, Richard P M A; Delany, Mary E; Finno, Carrie J; Groenen, Martien A M; Hayes, Ben; Lunney, Joan K; Petersen, Jessica L; Plastow, Graham S; Schmidt, Carl J; Song, Jiuzhou; Watson, Mick

    2016-10-01

    The Functional Annotation of Animal Genomes (FAANG) Consortium recently held a Gathering On FAANG (GO-FAANG) Workshop in Washington, DC on October 7-8, 2015. This consortium is a grass-roots organization formed to advance the annotation of newly assembled genomes of domesticated and non-model organisms (www.faang.org). The workshop gathered together from around the world a group of 100+ genome scientists, administrators, representatives of funding agencies and commodity groups to discuss the latest advancements of the consortium, new perspectives, next steps and implementation plans. The workshop was streamed live and recorded, and all talks, along with speaker slide presentations, are available at www.faang.org. In this report, we describe the major activities and outcomes of this meeting. We also provide updates on ongoing efforts to implement discussions and decisions taken at GO-FAANG to guide future FAANG activities. In summary, reference datasets are being established under pilot projects; plans for tissue sets, morphological classification and methods of sample collection for different tissues were organized; and core assays and data and meta-data analysis standards were established.

  1. Analysis and Functional Annotation of an Expressed Sequence Tag Collection for Tropical Crop Sugarcane

    PubMed Central

    Vettore, André L.; da Silva, Felipe R.; Kemper, Edson L.; Souza, Glaucia M.; da Silva, Aline M.; Ferro, Maria Inês T.; Henrique-Silva, Flavio; Giglioti, Éder A.; Lemos, Manoel V.F.; Coutinho, Luiz L.; Nobrega, Marina P.; Carrer, Helaine; França, Suzelei C.; Bacci, Maurício; Goldman, Maria Helena S.; Gomes, Suely L.; Nunes, Luiz R.; Camargo, Luis E.A.; Siqueira, Walter J.; Van Sluys, Marie-Anne; Thiemann, Otavio H.; Kuramae, Eiko E.; Santelli, Roberto V.; Marino, Celso L.; Targon, Maria L.P.N.; Ferro, Jesus A.; Silveira, Henrique C.S.; Marini, Danyelle C.; Lemos, Eliana G.M.; Monteiro-Vitorello, Claudia B.; Tambor, José H.M.; Carraro, Dirce M.; Roberto, Patrícia G.; Martins, Vanderlei G.; Goldman, Gustavo H.; de Oliveira, Regina C.; Truffi, Daniela; Colombo, Carlos A.; Rossi, Magdalena; de Araujo, Paula G.; Sculaccio, Susana A.; Angella, Aline; Lima, Marleide M.A.; de Rosa, Vicente E.; Siviero, Fábio; Coscrato, Virginia E.; Machado, Marcos A.; Grivet, Laurent; Di Mauro, Sonia M.Z.; Nobrega, Francisco G.; Menck, Carlos F.M.; Braga, Marilia D.V.; Telles, Guilherme P.; Cara, Frank A.A.; Pedrosa, Guilherme; Meidanis, João; Arruda, Paulo

    2003-01-01

    To contribute to our understanding of the genome complexity of sugarcane, we undertook a large-scale expressed sequence tag (EST) program. More than 260,000 cDNA clones were partially sequenced from 26 standard cDNA libraries generated from different sugarcane tissues. After the processing of the sequences, 237,954 high-quality ESTs were identified. These ESTs were assembled into 43,141 putative transcripts. Of the assembled sequences, 35.6% presented no matches with existing sequences in public databases. A global analysis of the whole SUCEST data set indicated that 14,409 assembled sequences (33% of the total) contained at least one cDNA clone with a full-length insert. Annotation of the 43,141 assembled sequences associated almost 50% of the putative identified sugarcane genes with protein metabolism, cellular communication/signal transduction, bioenergetics, and stress responses. Inspection of the translated assembled sequences for conserved protein domains revealed 40,821 amino acid sequences with 1415 Pfam domains. Reassembling the consensus sequences of the 43,141 transcripts revealed a 22% redundancy in the first assembling. This indicated that possibly 33,620 unique genes had been identified and indicated that >90% of the sugarcane expressed genes were tagged. PMID:14613979

  2. Automated Update, Revision, and Quality Control of the Maize Genome Annotations Using MAKER-P Improves the B73 RefGen_v3 Gene Models and Identifies New Genes1[OPEN

    PubMed Central

    Law, MeiYee; Childs, Kevin L.; Campbell, Michael S.; Stein, Joshua C.; Olson, Andrew J.; Holt, Carson; Panchy, Nicholas; Lei, Jikai; Jiao, Dian; Andorf, Carson M.; Lawrence, Carolyn J.; Ware, Doreen; Shiu, Shin-Han; Sun, Yanni; Jiang, Ning; Yandell, Mark

    2015-01-01

    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-P to update and revise the maize (Zea mays) B73 RefGen_v3 annotation build (5b+) in less than 3 h using the iPlant Cyberinfrastructure. MAKER-P identified and annotated 4,466 additional, well-supported protein-coding genes not present in the 5b+ annotation build, added additional untranslated regions to 1,393 5b+ gene models, identified 2,647 5b+ gene models that lack any supporting evidence (despite the use of large and diverse evidence data sets), identified 104,215 pseudogene fragments, and created an additional 2,522 noncoding gene annotations. We also describe a method for de novo training of MAKER-P for the annotation of newly sequenced grass genomes. Collectively, these results lead to the 6a maize genome annotation and demonstrate the utility of MAKER-P for rapid annotation, management, and quality control of grasses and other difficult-to-annotate plant genomes. PMID:25384563

  3. Visualizing GO Annotations.

    PubMed

    Supek, Fran; Škunca, Nives

    2017-01-01

    Contemporary techniques in biology produce readouts for large numbers of genes simultaneously, the typical example being differential gene expression measurements. Moreover, those genes are often richly annotated using GO terms that describe gene function and that can be used to summarize the results of the genome-scale experiments. However, making sense of such GO enrichment analyses may be challenging. For instance, overrepresented GO functions in a set of differentially expressed genes are typically output as a flat list, a format not adequate to capture the complexities of the hierarchical structure of the GO annotation labels.In this chapter, we survey various methods to visualize large, difficult-to-interpret lists of GO terms. We catalog their availability-Web-based or standalone, the main principles they employ in summarizing large lists of GO terms, and the visualization styles they support. These brief commentaries on each software are intended as a helpful inventory, rather than comprehensive descriptions of the underlying algorithms. Instead, we show examples of their use and suggest that the choice of an appropriate visualization tool may be crucial to the utility of GO in biological discovery.

  4. Functional Annotation of Conserved Hypothetical Proteins from Haemophilus influenzae Rd KW20

    PubMed Central

    Shahbaaz, Mohd; Md. ImtaiyazHassan; Ahmad, Faizan

    2013-01-01

    Haemophilus influenzae is a Gram negative bacterium that belongs to the family Pasteurellaceae, causes bacteremia, pneumonia and acute bacterial meningitis in infants. The emergence of multi-drug resistance H. influenzae strain in clinical isolates demands the development of better/new drugs against this pathogen. Our study combines a number of bioinformatics tools for function predictions of previously not assigned proteins in the genome of H. influenzae. This genome was extensively analyzed and found 1,657 functional proteins in which function of 429 proteins are unknown, termed as hypothetical proteins (HPs). Amino acid sequences of all 429 HPs were extensively annotated and we successfully assigned the function to 296 HPs with high confidence. We also characterized the function of 124 HPs precisely, but with less confidence. We believed that sequence of a protein can be used as a framework to explain known functional properties. Here we have combined the latest versions of protein family databases, protein motifs, intrinsic features from the amino acid sequence, pathway and genome context methods to assign a precise function to hypothetical proteins for which no experimental information is available. We found these HPs belong to various classes of proteins such as enzymes, transporters, carriers, receptors, signal transducers, binding proteins, virulence and other proteins. The outcome of this work will be helpful for a better understanding of the mechanism of pathogenesis and in finding novel therapeutic targets for H. influenzae. PMID:24391926

  5. Gene prediction and annotation in Penstemon (Plantaginaceae): A workflow for marker development from extremely low-coverage genome sequencing1

    PubMed Central

    Blischak, Paul D.; Wenzel, Aaron J.; Wolfe, Andrea D.

    2014-01-01

    • Premise of the study: Penstemon (Plantaginaceae) is a large and diverse genus endemic to North America. However, determining the phylogenetic relationships among its 280 species has been difficult due to its recent evolutionary radiation. The development of a large, multilocus data set can help to resolve this challenge. • Methods: Using both previously sequenced genomic libraries and our own low-coverage whole-genome shotgun sequencing libraries, we used the MAKER2 Annotation Pipeline to identify gene regions for the development of sequencing loci from six extremely low-coverage Penstemon genomes (∼0.005×–0.007×). We also compared this approach to BLAST searches, and conducted analyses to characterize sequence divergence across the species sequenced. • Results: Annotations and gene predictions were successfully added to more than 10,000 contigs for potential use in downstream primer design. Primers were then designed for chloroplast, mitochondrial, and nuclear loci from these annotated sequences. MAKER2 identified longer gene regions in all six Penstemon genomes when compared with BLASTN and BLASTX searches. The average level of sequence divergence among the six species was 7.14%. • Discussion: Combining bioinformatics tools into a workflow that produces annotations can be useful for creating potential phylogenetic markers from thousands of sequences even when genome coverage is extremely low and reference data are only available from distant relatives. Furthermore, the output from MAKER2 contains information about important gene features, such as exon boundaries, and can be easily integrated with visualization tools to facilitate the process of marker development. PMID:25506519

  6. IsoSeq analysis and functional annotation of the infratentorial ependymoma tumor tissue on PacBio RSII platform

    PubMed Central

    Singh, Neetu; Sahu, Dinesh Kumar; Chowdhry, Rebecca; Mishra, Archana; Goel, Madhu Mati; Faheem, Mohd; Srivastava, Chhitij; Ojha, Bal Krishna; Gupta, Devendra Kumar; Kant, Ravi

    2015-01-01

    Here, we sequenced and functionally annotated the long reads (1–2 kb) cDNAs library of an infratentorial ependymoma tumor tissue on PacBio RSII by Iso-Seq protocol using SMRT technology. 577 MB, data was generated from the brain tissues of ependymoma tumor patient, producing 1,19,313 high-quality reads assembled into 19,878 contigs using Celera assembler followed by Quiver pipelines, which produced 2952 unique protein accessions in the nr protein database and 307 KEGG pathways. Additionally, when we compared GO terms of second and third level with alternative splicing data obtained through HTA Array2.0. We identified four and twelve transcript cluster IDs in Level-2 and Level-3 scores respectively with alternative splicing index predicting mainly the major pathways of hallmarks of cancer. Out of these transcript cluster IDs only transcript cluster IDs of gene PNMT, SNN and LAMB1 showed Reads Per Kilobase of exon model per Million mapped reads (RPKM) values at gene-level expression (GE) and transcript-level (TE) track. Most importantly, brain-specific genes–—PNMT, SNN and LAMB1 show their involvement in Ependymoma. PMID:26862483

  7. Annotation error in public databases: misannotation of molecular function in enzyme superfamilies.

    PubMed

    Schnoes, Alexandra M; Brown, Shoshana D; Dodevski, Igor; Babbitt, Patricia C

    2009-12-01

    Due to the rapid release of new data from genome sequencing projects, the majority of protein sequences in public databases have not been experimentally characterized; rather, sequences are annotated using computational analysis. The level of misannotation and the types of misannotation in large public databases are currently unknown and have not been analyzed in depth. We have investigated the misannotation levels for molecular function in four public protein sequence databases (UniProtKB/Swiss-Prot, GenBank NR, UniProtKB/TrEMBL, and KEGG) for a model set of 37 enzyme families for which extensive experimental information is available. The manually curated database Swiss-Prot shows the lowest annotation error levels (close to 0% for most families); the two other protein sequence databases (GenBank NR and TrEMBL) and the protein sequences in the KEGG pathways database exhibit similar and surprisingly high levels of misannotation that average 5%-63% across the six superfamilies studied. For 10 of the 37 families examined, the level of misannotation in one or more of these databases is >80%. Examination of the NR database over time shows that misannotation has increased from 1993 to 2005. The types of misannotation that were found fall into several categories, most associated with "overprediction" of molecular function. These results suggest that misannotation in enzyme superfamilies containing multiple families that catalyze different reactions is a larger problem than has been recognized. Strategies are suggested for addressing some of the systematic problems contributing to these high levels of misannotation.

  8. Functional annotation of proteomic sequences based on consensus of sequence and structural analysis.

    PubMed

    Kitson, David H; Badretdinov, Azat; Zhu, Zhan-yang; Velikanov, Mikhail; Edwards, David J; Olszewski, Krzysztof; Szalma, Sándor; Yan, Lisa

    2002-03-01

    To maximise the assignment of function of the proteins encoded by a genome and to aid the search for novel drug targets, there is an emerging need for sensitive methods of predicting protein function on a genome-wide basis. GeneAtlas is an automated, high-throughput pipeline for the prediction of protein structure and function using sequence similarity detection, homology modelling and fold recognition methods. GeneAtlas is described in detail here. To test GeneAtlas, a 'virtual' genome was used, a subset of PDB structures from the SCOP database, in which the functional relationships are known. GeneAtlas detects additional relationships by building 3D models in comparison with the sequence searching method PSI-BLAST. Functionally related proteins with sequence identity below the twilight zone can be recognised correctly.

  9. Re-Annotator: Annotation Pipeline for Microarray Probe Sequences.

    PubMed

    Arloth, Janine; Bader, Daniel M; Röh, Simone; Altmann, Andre

    2015-01-01

    Microarray technologies are established approaches for high throughput gene expression, methylation and genotyping analysis. An accurate mapping of the array probes is essential to generate reliable biological findings. However, manufacturers of the microarray platforms typically provide incomplete and outdated annotation tables, which often rely on older genome and transcriptome versions that differ substantially from up-to-date sequence databases. Here, we present the Re-Annotator, a re-annotation pipeline for microarray probe sequences. It is primarily designed for gene expression microarrays but can also be adapted to other types of microarrays. The Re-Annotator uses a custom-built mRNA reference database to identify the positions of gene expression array probe sequences. We applied Re-Annotator to the Illumina Human-HT12 v4 microarray platform and found that about one quarter (25%) of the probes differed from the manufacturer's annotation. In further computational experiments on experimental gene expression data, we compared Re-Annotator to another probe re-annotation tool, ReMOAT, and found that Re-Annotator provided an improved re-annotation of microarray probes. A thorough re-annotation of probe information is crucial to any microarray analysis. The Re-Annotator pipeline is freely available at http://sourceforge.net/projects/reannotator along with re-annotated files for Illumina microarrays HumanHT-12 v3/v4 and MouseRef-8 v2.

  10. Functional Genomic Annotation of Genetic Risk Loci Highlights Inflammation and Epithelial Biology Networks in CKD

    PubMed Central

    Ledo, Nora; Ko, Yi-An; Park, Ae-Seo Deok; Kang, Hyun-Mi; Han, Sang-Youb; Choi, Peter

    2015-01-01

    Genome-wide association studies (GWASs) have identified multiple loci associated with the risk of CKD. Almost all risk variants are localized to the noncoding region of the genome; therefore, the role of these variants in CKD development is largely unknown. We hypothesized that polymorphisms alter transcription factor binding, thereby influencing the expression of nearby genes. Here, we examined the regulation of transcripts in the vicinity of CKD-associated polymorphisms in control and diseased human kidney samples and used systems biology approaches to identify potentially causal genes for prioritization. We interrogated the expression and regulation of 226 transcripts in the vicinity of 44 single nucleotide polymorphisms using RNA sequencing and gene expression arrays from 95 microdissected control and diseased tubule samples and 51 glomerular samples. Gene expression analysis from 41 tubule samples served for external validation. 92 transcripts in the tubule compartment and 34 transcripts in glomeruli showed statistically significant correlation with eGFR. Many novel genes, including ACSM2A/2B, FAM47E, and PLXDC1, were identified. We observed that the expression of multiple genes in the vicinity of any single CKD risk allele correlated with renal function, potentially indicating that genetic variants influence multiple transcripts. Network analysis of GFR-correlating transcripts highlighted two major clusters; a positive correlation with epithelial and vascular functions and an inverse correlation with inflammatory gene cluster. In summary, our functional genomics analysis highlighted novel genes and critical pathways associated with kidney function for future analysis. PMID:25231882

  11. 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

    PubMed Central

    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. PMID:24710118

  12. The Aspergillus Genome Database: multispecies curation and incorporation of RNA-Seq data to improve structural gene annotations

    PubMed Central

    Cerqueira, Gustavo C.; Arnaud, Martha B.; Inglis, Diane O.; Skrzypek, Marek S.; Binkley, Gail; Simison, Matt; Miyasato, Stuart R.; Binkley, Jonathan; Orvis, Joshua; Shah, Prachi; Wymore, Farrell; Sherlock, Gavin; Wortman, Jennifer R.

    2014-01-01

    The Aspergillus Genome Database (AspGD; http://www.aspgd.org) is a freely available web-based resource that was designed for Aspergillus researchers and is also a valuable source of information for the entire fungal research community. In addition to being a repository and central point of access to genome, transcriptome and polymorphism data, AspGD hosts a comprehensive comparative genomics toolbox that facilitates the exploration of precomputed orthologs among the 20 currently available Aspergillus genomes. AspGD curators perform gene product annotation based on review of the literature for four key Aspergillus species: Aspergillus nidulans, Aspergillus oryzae, Aspergillus fumigatus and Aspergillus niger. We have iteratively improved the structural annotation of Aspergillus genomes through the analysis of publicly available transcription data, mostly expressed sequenced tags, as described in a previous NAR Database article (Arnaud et al. 2012). In this update, we report substantive structural annotation improvements for A. nidulans, A. oryzae and A. fumigatus genomes based on recently available RNA-Seq data. Over 26 000 loci were updated across these species; although those primarily comprise the addition and extension of untranslated regions (UTRs), the new analysis also enabled over 1000 modifications affecting the coding sequence of genes in each target genome. PMID:24194595

  13. Homology modeling and assigned functional annotation of an uncharacterized antitoxin protein from Streptomyces xinghaiensis

    PubMed Central

    Oany, Arafat Rahman; Ahmed, Md Shahabuddin; Jahan, Nasreen; Latif, Md Abdul; Mahmud, Shahin; Hossain, Md. Ahmed; Akter, Fatema; Rakib, Hasibul Haque; Islam, Md. Shariful

    2015-01-01

    Streptomyces xinghaiensis is a Gram-positive, aerobic and non-motile bacterium. The bacterial genome is known. Therefore, it is of interest to study the uncharacterized proteins in the genome. An uncharacterized protein (gi|518540893|86 residues) in the genome was selected for a comprehensive computational sequence-structure-function analysis using available data and tools. Subcellular localization of the targeted protein with conserved residues and assigned secondary structures is documented. Sequence homology search against the protein data bank (PDB) and non-redundant GenBank proteins using BLASTp showed different homologous proteins with known antitoxin function. A homology model of the target protein was developed using a known template (PDB ID: 3CTO:A) with 62% sequence similarity in HHpred after assessment using programs PROCHECK and QMEAN6. The predicted active site using CASTp is analyzed for assigned anti-toxin function. This information finds specific utility in annotating the said uncharacterized protein in the bacterial genome. PMID:26912949

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

    PubMed Central

    Birkholtz, Lyn-Marie; Blatch, Gregory; Coetzer, Theresa L; Hoppe, Heinrich C; Human, Esmaré; Morris, Elizabeth J; Ngcete, Zoleka; Oldfield, Lyndon; Roth, Robyn; Shonhai, Addmore; Stephens, Linda; Louw, Abraham I

    2008-01-01

    Malaria remains the world's most devastating tropical infectious disease with as many as 40% of the world population living in risk areas. The widespread resistance of Plasmodium parasites to the cost-effective chloroquine and antifolates has forced the introduction of more costly drug combinations, such as Coartem®. In the absence of a vaccine in the foreseeable future, one strategy to address the growing malaria problem is to identify and characterize new and durable antimalarial drug targets, the majority of which are parasite proteins. Biochemical and structure-activity analysis of these proteins is ultimately essential in the characterization of such targets but requires large amounts of functional protein. Even though heterologous protein production has now become a relatively routine endeavour for most proteins of diverse origins, the functional expression of soluble plasmodial proteins is highly problematic and slows the progress of antimalarial drug target discovery. Here the status quo of heterologous production of plasmodial proteins is presented, constraints are highlighted and alternative strategies and hosts for functional expression and annotation of plasmodial proteins are reviewed. PMID:18828893

  15. De Novo Assembly and Annotation of the Transcriptome of the Agricultural Weed Ipomoea purpurea Uncovers Gene Expression Changes Associated with Herbicide Resistance

    PubMed Central

    Leslie, Trent; Baucom, Regina S.

    2014-01-01

    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. PMID:25155274

  16. Sequencing, De novo Assembly, Functional Annotation and Analysis of Phyllanthus amarus Leaf Transcriptome Using the Illumina Platform

    PubMed Central

    Bose Mazumdar, Aparupa; Chattopadhyay, Sharmila

    2016-01-01

    Phyllanthus amarus Schum. and Thonn., a widely distributed annual medicinal herb has a long history of use in the traditional system of medicine for over 2000 years. However, the lack of genomic data for P. amarus, a non-model organism hinders research at the molecular level. In the present study, high-throughput sequencing technology has been employed to enhance better understanding of this herb and provide comprehensive genomic information for future work. Here P. amarus leaf transcriptome was sequenced using the Illumina Miseq platform. We assembled 85,927 non-redundant (nr) “unitranscript” sequences with an average length of 1548 bp, from 18,060,997 raw reads. Sequence similarity analyses and annotation of these unitranscripts were performed against databases like green plants nr protein database, Gene Ontology (GO), Clusters of Orthologous Groups (COG), PlnTFDB, KEGG databases. As a result, 69,394 GO terms, 583 enzyme codes (EC), 134 KEGG maps, and 59 Transcription Factor (TF) families were generated. Functional and comparative analyses of assembled unitranscripts were also performed with the most closely related species like Populus trichocarpa and Ricinus communis using TRAPID. KEGG analysis showed that a number of assembled unitranscripts were involved in secondary metabolites, mainly phenylpropanoid, flavonoid, terpenoids, alkaloids, and lignan biosynthetic pathways that have significant medicinal attributes. Further, Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values of the identified secondary metabolite pathway genes were determined and Reverse Transcription PCR (RT-PCR) of a few of these genes were performed to validate the de novo assembled leaf transcriptome dataset. In addition 65,273 simple sequence repeats (SSRs) were also identified. To the best of our knowledge, this is the first transcriptomic dataset of P. amarus till date. Our study provides the largest genetic resource that will lead to drug development and pave

  17. Reannotation and extended community resources for the genome of the non-seed plant Physcomitrella patens provide insights into the evolution of plant gene structures and functions

    PubMed Central

    2013-01-01

    Background The moss Physcomitrella patens as a model species provides an important reference for early-diverging lineages of plants and the release of the genome in 2008 opened the doors to genome-wide studies. The usability of a reference genome greatly depends on the quality of the annotation and the availability of centralized community resources. Therefore, in the light of accumulating evidence for missing genes, fragmentary gene structures, false annotations and a low rate of functional annotations on the original release, we decided to improve the moss genome annotation. Results Here, we report the complete moss genome re-annotation (designated V1.6) incorporating the increased transcript availability from a multitude of developmental stages and tissue types. We demonstrate the utility of the improved P. patens genome annotation for comparative genomics and new extensions to the cosmoss.org resource as a central repository for this plant “flagship” genome. The structural annotation of 32,275 protein-coding genes results in 8387 additional loci including 1456 loci with known protein domains or homologs in Plantae. This is the first release to include information on transcript isoforms, suggesting alternative splicing events for at least 10.8% of the loci. Furthermore, this release now also provides information on non-protein-coding loci. Functional annotations were improved regarding quality and coverage, resulting in 58% annotated loci (previously: 41%) that comprise also 7200 additional loci with GO annotations. Access and manual curation of the functional and structural genome annotation is provided via the http://www.cosmoss.org model organism database. Conclusions Comparative analysis of gene structure evolution along the green plant lineage provides novel insights, such as a comparatively high number of loci with 5’-UTR introns in the moss. Comparative analysis of functional annotations reveals expansions of moss house-keeping and metabolic genes

  18. Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

    SciTech Connect

    Leung, Elo; Huang, Amy; Cadag, Eithon; Montana, Aldrin; Soliman, Jan Lorenz; Zhou, Carol L. Ecale

    2016-01-20

    In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resulting functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.

  19. Protein Sequence Annotation Tool (PSAT): A centralized web-based meta-server for high-throughput sequence annotations

    DOE PAGES

    Leung, Elo; Huang, Amy; Cadag, Eithon; ...

    2016-01-20

    In this study, we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resultingmore » functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Lastly, PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequencebased genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.« less

  20. BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments

    PubMed Central

    Al-Shahrour, Fátima; Minguez, Pablo; Tárraga, Joaquín; Montaner, David; Alloza, Eva; Vaquerizas, Juan M.; Conde, Lucía; Blaschke, Christian; Vera, Javier; Dopazo, Joaquín

    2006-01-01

    We present a new version of Babelomics, a complete suite of web tools for functional analysis of genome-scale experiments, with new and improved tools. New functionally relevant terms have been included such as CisRed motifs or bioentities obtained by text-mining procedures. An improved indexing has considerably speeded up several of the modules. An improved version of the FatiScan method for studying the coordinate behaviour of groups of functionally related genes is presented, along with a similar tool, the Gene Set Enrichment Analysis. Babelomics is now more oriented to test systems biology inspired hypotheses. Babelomics can be found at . PMID:16845052

  1. Annotation of Protein Domains Reveals Remarkable Conservation in the Functional Make up of Proteomes Across Superkingdoms.

    PubMed

    Nasir, Arshan; Naeem, Aisha; Khan, Muhammad Jawad; Nicora, Horacio D Lopez; Caetano-Anollés, Gustavo

    2011-11-08

    The functional repertoire of a cell is largely embodied in its proteome, the collection of proteins encoded in the genome of an organism. The molecular functions of proteins are the direct consequence of their structure and structure can be inferred from sequence using hidden Markov models of structural recognition. Here we analyze the functional annotation of protein domain structures in almost a thousand sequenced genomes, exploring the functional and structural diversity of proteomes. We find there is a remarkable conservation in the distribution of domains with respect to the molecular functions they perform in the three superkingdoms of life. In general, most of the protein repertoire is spent in functions related to metabolic processes but there are significant differences in the usage of domains for regulatory and extra-cellular processes both within and between superkingdoms. Our results support the hypotheses that the proteomes of superkingdom Eukarya evolved via genome expansion mechanisms that were directed towards innovating new domain architectures for regulatory and extra/intracellular process functions needed for example to maintain the integrity of multicellular structure or to interact with environmental biotic and abiotic factors (e.g., cell signaling and adhesion, immune responses, and toxin production). Proteomes of microbial superkingdoms Archaea and Bacteria retained fewer numbers of domains and maintained simple and smaller protein repertoires. Viruses appear to play an important role in the evolution of superkingdoms. We finally identify few genomic outliers that deviate significantly from the conserved functional design. These include Nanoarchaeum equitans, proteobacterial symbionts of insects with extremely reduced genomes, Tenericutes and Guillardia theta. These organisms spend most of their domains on information functions, including translation and transcription, rather than on metabolism and harbor a domain repertoire characteristic of

  2. Annotation of Protein Domains Reveals Remarkable Conservation in the Functional Make up of Proteomes Across Superkingdoms

    PubMed Central

    Nasir, Arshan; Naeem, Aisha; Khan, Muhammad Jawad; Lopez-Nicora, Horacio D.; Caetano-Anollés, Gustavo

    2011-01-01

    The functional repertoire of a cell is largely embodied in its proteome, the collection of proteins encoded in the genome of an organism. The molecular functions of proteins are the direct consequence of their structure and structure can be inferred from sequence using hidden Markov models of structural recognition. Here we analyze the functional annotation of protein domain structures in almost a thousand sequenced genomes, exploring the functional and structural diversity of proteomes. We find there is a remarkable conservation in the distribution of domains with respect to the molecular functions they perform in the three superkingdoms of life. In general, most of the protein repertoire is spent in functions related to metabolic processes but there are significant differences in the usage of domains for regulatory and extra-cellular processes both within and between superkingdoms. Our results support the hypotheses that the proteomes of superkingdom Eukarya evolved via genome expansion mechanisms that were directed towards innovating new domain architectures for regulatory and extra/intracellular process functions needed for example to maintain the integrity of multicellular structure or to interact with environmental biotic and abiotic factors (e.g., cell signaling and adhesion, immune responses, and toxin production). Proteomes of microbial superkingdoms Archaea and Bacteria retained fewer numbers of domains and maintained simple and smaller protein repertoires. Viruses appear to play an important role in the evolution of superkingdoms. We finally identify few genomic outliers that deviate significantly from the conserved functional design. These include Nanoarchaeum equitans, proteobacterial symbionts of insects with extremely reduced genomes, Tenericutes and Guillardia theta. These organisms spend most of their domains on information functions, including translation and transcription, rather than on metabolism and harbor a domain repertoire characteristic of

  3. Oncotator: cancer variant annotation tool.

    PubMed

    Ramos, Alex H; Lichtenstein, Lee; Gupta, Manaswi; Lawrence, Michael S; Pugh, Trevor J; Saksena, Gordon; Meyerson, Matthew; Getz, Gad

    2015-04-01

    Oncotator is a tool for annotating genomic point mutations and short nucleotide insertions/deletions (indels) with variant- and gene-centric information relevant to cancer researchers. This information is drawn from 14 different publicly available resources that have been pooled and indexed, and we provide an extensible framework to add additional data sources. Annotations linked to variants range from basic information, such as gene names and functional classification (e.g. missense), to cancer-specific data from resources such as the Catalogue of Somatic Mutations in Cancer (COSMIC), the Cancer Gene Census, and The Cancer Genome Atlas (TCGA). For local use, Oncotator is freely available as a python module hosted on Github (https://github.com/broadinstitute/oncotator). Furthermore, Oncotator is also available as a web service and web application at http://www.broadinstitute.org/oncotator/.

  4. Next-Generation High-Throughput Functional Annotation of Microbial Genomes

    PubMed Central

    Baric, Ralph S.; Damania, Blossom; Miller, Samuel I.; Rubin, Eric J.

    2016-01-01

    ABSTRACT Host infection by microbial pathogens cues global changes in microbial and host cell biology that facilitate microbial replication and disease. The complete maps of thousands of bacterial and viral genomes have recently been defined; however, the rate at which physiological or biochemical functions have been assigned to genes has greatly lagged. The National Institute of Allergy and Infectious Diseases (NIAID) addressed this gap by creating functional genomics centers dedicated to developing high-throughput approaches to assign gene function. These centers require broad-based and collaborative research programs to generate and integrate diverse data to achieve a comprehensive understanding of microbial pathogenesis. High-throughput functional genomics can lead to new therapeutics and better understanding of the next generation of emerging pathogens by rapidly defining new general mechanisms by which organisms cause disease and replicate in host tissues and by facilitating the rate at which functional data reach the scientific community. PMID:27703071

  5. Automated annotation of functional imaging experiments via multi-label classification.

    PubMed

    Turner, Matthew D; Chakrabarti, Chayan; Jones, Thomas B; Xu, Jiawei F; Fox, Peter T; Luger, George F; Laird, Angela R; Turner, Jessica A

    2013-01-01

    Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert's annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k-nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text.

  6. Automated annotation of functional imaging experiments via multi-label classification

    PubMed Central

    Turner, Matthew D.; Chakrabarti, Chayan; Jones, Thomas B.; Xu, Jiawei F.; Fox, Peter T.; Luger, George F.; Laird, Angela R.; Turner, Jessica A.

    2013-01-01

    Identifying the experimental methods in human neuroimaging papers is important for grouping meaningfully similar experiments for meta-analyses. Currently, this can only be done by human readers. We present the performance of common machine learning (text mining) methods applied to the problem of automatically classifying or labeling this literature. Labeling terms are from the Cognitive Paradigm Ontology (CogPO), the text corpora are abstracts of published functional neuroimaging papers, and the methods use the performance of a human expert as training data. We aim to replicate the expert's annotation of multiple labels per abstract identifying the experimental stimuli, cognitive paradigms, response types, and other relevant dimensions of the experiments. We use several standard machine learning methods: naive Bayes (NB), k-nearest neighbor, and support vector machines (specifically SMO or sequential minimal optimization). Exact match performance ranged from only 15% in the worst cases to 78% in the best cases. NB methods combined with binary relevance transformations performed strongly and were robust to overfitting. This collection of results demonstrates what can be achieved with off-the-shelf software components and little to no pre-processing of raw text. PMID:24409112

  7. De Novo Assembly and Functional Annotation of the Olive (Olea europaea) Transcriptome

    PubMed Central

    Muñoz-Mérida, Antonio; González-Plaza, Juan José; Cañada, Andrés; Blanco, Ana María; García-López, Maria del Carmen; Rodríguez, José Manuel; Pedrola, Laia; Sicardo, M. Dolores; Hernández, M. Luisa; De la Rosa, Raúl; Belaj, Angjelina; Gil-Borja, Mayte; Luque, Francisco; Martínez-Rivas, José Manuel; Pisano, David G.; Trelles, Oswaldo; Valpuesta, Victoriano; Beuzón, Carmen R.

    2013-01-01

    Olive breeding programmes are focused on selecting for traits as short juvenile period, plant architecture suited for mechanical harvest, or oil characteristics, including fatty acid composition, phenolic, and volatile compounds to suit new markets. Understanding the molecular basis of these characteristics and improving the efficiency of such breeding programmes require the development of genomic information and tools. However, despite its economic relevance, genomic information on olive or closely related species is still scarce. We have applied Sanger and 454 pyrosequencing technologies to generate close to 2 million reads from 12 cDNA libraries obtained from the Picual, Arbequina, and Lechin de Sevilla cultivars and seedlings from a segregating progeny of a Picual × Arbequina cross. The libraries include fruit mesocarp and seeds at three relevant developmental stages, young stems and leaves, active juvenile and adult buds as well as dormant buds, and juvenile and adult roots. The reads were assembled by library or tissue and then assembled together into 81 020 unigenes with an average size of 496 bases. Here, we report their assembly and their functional annotation. PMID:23297299

  8. dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs.

    PubMed

    Liu, Xiaoming; Wu, Chunlei; Li, Chang; Boerwinkle, Eric

    2016-03-01

    The purpose of the dbNSFP is to provide a one-stop resource for functional predictions and annotations for human nonsynonymous single-nucleotide variants (nsSNVs) and splice-site variants (ssSNVs), and to facilitate the steps of filtering and prioritizing SNVs from a large list of SNVs discovered in an exome-sequencing study. A list of all potential nsSNVs and ssSNVs based on the human reference sequence were created and functional predictions and annotations were curated and compiled for each SNV. Here, we report a recent major update of the database to version 3.0. The SNV list has been rebuilt based on GENCODE 22 and currently the database includes 82,832,027 nsSNVs and ssSNVs. An attached database dbscSNV, which compiled all potential human SNVs within splicing consensus regions and their deleteriousness predictions, add another 15,030,459 potentially functional SNVs. Eleven prediction scores (MetaSVM, MetaLR, CADD, VEST3, PROVEAN, 4× fitCons, fathmm-MKL, and DANN) and allele frequencies from the UK10K cohorts and the Exome Aggregation Consortium (ExAC), among others, have been added. The original seven prediction scores in v2.0 (SIFT, 2× Polyphen2, LRT, MutationTaster, MutationAssessor, and FATHMM) as well as many SNV and gene functional annotations have been updated. dbNSFP v3.0 is freely available at http://sites.google.com/site/jpopgen/dbNSFP.

  9. 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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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-...

  10. PHYLOGENOMICS - GUIDED VALIDATION OF FUNCTION FOR CONSERVED UNKNOWN GENES

    SciTech Connect

    V, DE CRECY-LAGARD; D, HANSON A

    2012-01-03

    Identifying functions for all gene products in all sequenced organisms is a central challenge of the post-genomic era. However, at least 30-50% of the proteins encoded by any given genome are of unknown function, or wrongly or vaguely annotated. Many of these 'unknown' proteins are common to prokaryotes and plants. We accordingly set out to predict and experimentally test the functions of such proteins. Our approach to functional prediction is integrative, coupling the extensive post-genomic resources available for plants with comparative genomics based on hundreds of microbial genomes, and functional genomic datasets from model microorganisms. The early phase is computer-assisted; later phases incorporate intellectual input from expert plant and microbial biochemists. The approach thus bridges the gap between automated homology-based annotations and the classical gene discovery efforts of experimentalists, and is much more powerful than purely computational approaches to identifying gene-function associations. Among Arabidopsis genes, we focused on those (2,325 in total) that (i) are unique or belong to families with no more than three members, (ii) are conserved between plants and prokaryotes, and (iii) have unknown or poorly known functions. Computer-assisted selection of promising targets for deeper analysis was based on homology .. independent characteristics associated in the SEED database with the prokaryotic members of each family, specifically gene clustering and phyletic spread, as well as availability of functional genomics data, and publications that could link candidate families to general metabolic areas, or to specific functions. In-depth comparative genomic analysis was then performed for about 500 top candidate families, which connected ~55 of them to general areas of metabolism and led to specific functional predictions for a subset of ~25 more. Twenty predicted functions were experimentally tested in at least one prokaryotic organism via reverse

  11. The DOE-JGI Standard Operating Procedure for the Annotations of the Microbial Genomes

    SciTech Connect

    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.

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

    PubMed

    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.

  13. The Disease Portals, disease-gene annotation and the RGD disease ontology at the Rat Genome Database.

    PubMed

    Hayman, G Thomas; Laulederkind, Stanley J F; Smith, Jennifer R; Wang, Shur-Jen; Petri, Victoria; Nigam, Rajni; Tutaj, Marek; De Pons, Jeff; Dwinell, Melinda R; Shimoyama, Mary

    2016-01-01

    The Rat Genome Database (RGD;http://rgd.mcw.edu/) provides critical datasets and software tools to a diverse community of rat and non-rat researchers worldwide. To meet the needs of the many users whose research is disease oriented, RGD has created a series of Disease Portals and has prioritized its curation efforts on the datasets important to understanding the mechanisms of various diseases. Gene-disease relationships for three species, rat, human and mouse, are annotated to capture biomarkers, genetic associations, molecular mechanisms and therapeutic targets. To generate gene-disease annotations more effectively and in greater detail, RGD initially adopted the MEDIC disease vocabulary from the Comparative Toxicogenomics Database and adapted it for use by expanding this framework with the addition of over 1000 terms to create the RGD Disease Ontology (RDO). The RDO provides the foundation for, at present, 10 comprehensive disease area-related dataset and analysis platforms at RGD, the Disease Portals. Two major disease areas are the focus of data acquisition and curation efforts each year, leading to the release of the related Disease Portals. Collaborative efforts to realize a more robust disease ontology are underway. Database URL:http://rgd.mcw.edu.

  14. A Factor Graph Approach to Automated GO Annotation

    PubMed Central

    Spetale, Flavio E.; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

    2016-01-01

    As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum. PMID:26771463

  15. A Factor Graph Approach to Automated GO Annotation.

    PubMed

    Spetale, Flavio E; Tapia, Elizabeth; Krsticevic, Flavia; Roda, Fernando; Bulacio, Pilar

    2016-01-01

    As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly interesting when interpretability of annotation results is a main concern. In these methods, raw GO-term predictions computed by base binary classifiers are leveraged by checking the consistency of predefined GO relationships. Both formal leveraging strategies, with main focus on annotation precision, and heuristic alternatives, with main focus on scalability issues, have been described in literature. In this contribution, a factor graph approach to the hierarchical ensemble formulation of the automated GO annotation problem is presented. In this formal framework, a core factor graph is first built based on the GO structure and then enriched to take into account the noisy nature of GO-term predictions. Hence, starting from raw GO-term predictions, an iterative message passing algorithm between nodes of the factor graph is used to compute marginal probabilities of target GO-terms. Evaluations on Saccharomyces cerevisiae, Arabidopsis thaliana and Drosophila melanogaster protein sequences from the GO Molecular Function domain showed significant improvements over competing approaches, even when protein sequences were naively characterized by their physicochemical and secondary structure properties or when loose noisy annotation datasets were considered. Based on these promising results and using Arabidopsis thaliana annotation data, we extend our approach to the identification of most promising molecular function annotations for a set of proteins of unknown function in Solanum lycopersicum.

  16. Integrative Tissue-Specific Functional Annotations in the Human Genome Provide Novel Insights on Many Complex Traits and Improve Signal Prioritization in Genome Wide Association Studies.

    PubMed

    Lu, Qiongshi; Powles, Ryan Lee; Wang, Qian; He, Beixin Julie; Zhao, Hongyu

    2016-04-01

    Extensive efforts have been made to understand genomic function through both experimental and computational approaches, yet proper annotation still remains challenging, especially in non-coding regions. In this manuscript, we introduce GenoSkyline, an unsupervised learning framework to predict tissue-specific functional regions through integrating high-throughput epigenetic annotations. GenoSkyline successfully identified a variety of non-coding regulatory machinery including enhancers, regulatory miRNA, and hypomethylated transposable elements in extensive case studies. Integrative analysis of GenoSkyline annotations and results from genome-wide association studies (GWAS) led to novel biological insights on the etiologies of a number of human complex traits. We also explored using tissue-specific functional annotations to prioritize GWAS signals and predict relevant tissue types for each risk locus. Brain and blood-specific annotations led to better prioritization performance for schizophrenia than standard GWAS p-values and non-tissue-specific annotations. As for coronary artery disease, heart-specific functional regions was highly enriched of GWAS signals, but previously identified risk loci were found to be most functional in other tissues, suggesting a substantial proportion of still undetected heart-related loci. In summary, GenoSkyline annotations can guide genetic studies at multiple resolutions and provide valuable insights in understanding complex diseases. GenoSkyline is available at http://genocanyon.med.yale.edu/GenoSkyline.

  17. Integrative Tissue-Specific Functional Annotations in the Human Genome Provide Novel Insights on Many Complex Traits and Improve Signal Prioritization in Genome Wide Association Studies

    PubMed Central

    Wang, Qian; He, Beixin Julie; Zhao, Hongyu

    2016-01-01

    Extensive efforts have been made to understand genomic function through both experimental and computational approaches, yet proper annotation still remains challenging, especially in non-coding regions. In this manuscript, we introduce GenoSkyline, an unsupervised learning framework to predict tissue-specific functional regions through integrating high-throughput epigenetic annotations. GenoSkyline successfully identified a variety of non-coding regulatory machinery including enhancers, regulatory miRNA, and hypomethylated transposable elements in extensive case studies. Integrative analysis of GenoSkyline annotations and results from genome-wide association studies (GWAS) led to novel biological insights on the etiologies of a number of human complex traits. We also explored using tissue-specific functional annotations to prioritize GWAS signals and predict relevant tissue types for each risk locus. Brain and blood-specific annotations led to better prioritization performance for schizophrenia than standard GWAS p-values and non-tissue-specific annotations. As for coronary artery disease, heart-specific functional regions was highly enriched of GWAS signals, but previously identified risk loci were found to be most functional in other tissues, suggesting a substantial proportion of still undetected heart-related loci. In summary, GenoSkyline annotations can guide genetic studies at multiple resolutions and provide valuable insights in understanding complex diseases. GenoSkyline is available at http://genocanyon.med.yale.edu/GenoSkyline. PMID:27058395

  18. In-depth transcriptome analysis of Coilia ectenes, an important fish resource in the Yangtze River: de novo assembly, gene annotation.

    PubMed

    Shen, Huaishun; Gu, Ruobo; Xu, Gangchun; Xu, Pao; Nie, Zijuan; Hu, Yacheng

    2015-10-01

    Coilia ectenes is an important teleost species in the Yangtze River and a model organism that can be used to study the protection of fish resources. In this report, we performed de novo transcriptome sequencing of ten cDNA libraries from the brain, gill, heart, intestine, kidney, liver, muscle, stomach, ovary, and testis tissues. A total of 352 million raw reads of 100 base pairs were generated, and 130,113 transcripts, corresponding to 65,350 non-redundant transcripts, with a mean length of 1520 bp, were assembled. BLASTx-based gene annotation (E-value<1 × 10(-5)) allowed the identification of 73,900 transcripts against at least one of four databases, including the NCBI non-redundant database, the GO database, the COG database, and the KEGG database. Our study provides a valuable resource for C. ectenes genomic and transcriptomic data that will facilitate future functional studies of C. ectenes.

  19. Systematic morphological profiling of human gene and allele function via Cell Painting.

    PubMed

    Rohban, Mohammad Hossein; Singh, Shantanu; Wu, Xiaoyun; Berthet, Julia B; Bray, Mark-Anthony; Shrestha, Yashaswi; Varelas, Xaralabos; Boehm, Jesse S; Carpenter, Anne E

    2017-03-18

    We hypothesized that human genes and disease-associated alleles might be systematically functionally annotated using morphological profiling of cDNA constructs, via a microscopy-based Cell Painting assay. Indeed, 50% of the 220 tested genes yielded detectable morphological profiles, which grouped into biologically meaningful gene clusters consistent with known functional annotation (e.g., the RAS-RAF-MEK-ERK cascade). We used novel subpopulation-based visualization methods to interpret the morphological changes for specific clusters. This unbiased morphologic map of gene function revealed TRAF2/c-REL negative regulation of YAP1/WWTR1-responsive pathways. We confirmed this discovery of functional connectivity between the NF-κB pathway and Hippo pathway effectors at the transcriptional level, thereby expanding knowledge of these two signaling pathways that critically regulate tumor initiation and progression. We make the images and raw data publicly available, providing an initial morphological map of major biological pathways for future study.

  20. Bovine Genome Database: integrated tools for genome annotation and discovery.

    PubMed

    Childers, Christopher P; Reese, Justin T; Sundaram, Jaideep P; Vile, Donald C; Dickens, C Michael; Childs, Kevin L; Salih, Hanni; Bennett, Anna K; Hagen, Darren E; Adelson, David L; Elsik, Christine G

    2011-01-01

    The Bovine Genome Database (BGD; http://BovineGenome.org) strives to improve annotation of the bovine genome and to integrate the genome sequence with other genomics data. BGD includes GBrowse genome browsers, the Apollo Annotation Editor, a quantitative trait loci (QTL) viewer, BLAST databases and gene pages. Genome browsers, available for both scaffold and chromosome coordinate systems, display the bovine Official Gene Set (OGS), RefSeq and Ensembl gene models, non-coding RNA, repeats, pseudogenes, single-nucleotide polymorphism, markers, QTL and alignments to complementary DNAs, ESTs and protein homologs. The Bovine QTL viewer is connected to the BGD Chromosome GBrowse, allowing for the identification of candidate genes underlying QTL. The Apollo Annotation Editor connects directly to the BGD Chado database to provide researchers with remote access to gene evidence in a graphical interface that allows editing and creating new gene models. Researchers may upload their annotations to the BGD server for review and integration into the subsequent release of the OGS. Gene pages display information for individual OGS gene models, including gene structure, transcript variants, functional descriptions, gene symbols, Gene Ontology terms, annotator comments and links to National Center for Biotechnology Information and Ensembl. Each gene page is linked to a wiki page to allow input from the research community.

  1. An Annotated Bibliography of Resources on Educational Linking Agents: Roles, Functions, and Training Materials.

    ERIC Educational Resources Information Center

    Barth, Rodney J., Comp.

    The resources cited in this selected annotated bibliography are intended for linking agents, trainers of linking agents, managers of linking agents and their support systems, and educational policy makers. These resources, which date from 1975 to the present, variously refer to linking agents, change agents, extension agents, field agents, field…

  2. The Development of PIPA: An Integrated and Automated Pipeline for Genome-Wide Protein Function Annotation

    DTIC Science & Technology

    2008-01-25

    bacterial genome annotation. Nucleic Acids Res 2005/06/28 edition. 2005, 33(Web Server issue):W455-9. 14. Meyer F, Goesmann A, McHardy AC, Bartels D...GO.evi dence.shtml] 37. Jain AK Murthy MN, Flynn PJ: Data Clustering: A Review. ACM Computing Surveys 1999, 31(3):264-323. 38. Chenna R, Sugawara H

  3. Use of Modern Chemical Protein Synthesis and Advanced Fluorescent Assay Techniques to Experimentally Validate the Functional Annotation of Microbial Genomes

    SciTech Connect

    Kent, Stephen

    2012-07-20

    The objective of this research program was to prototype methods for the chemical synthesis of predicted protein molecules in annotated microbial genomes. High throughput chemical methods were to be used to make large numbers of predicted proteins and protein domains, based on microbial genome sequences. Microscale chemical synthesis methods for the parallel preparation of peptide-thioester building blocks were developed; these peptide segments are used for the parallel chemical synthesis of proteins and protein domains. Ultimately, it is envisaged that these synthetic molecules would be ‘printed’ in spatially addressable arrays. The unique ability of total synthesis to precision label protein molecules with dyes and with chemical or biochemical ‘tags’ can be used to facilitate novel assay technologies adapted from state-of-the art single molecule fluorescence detection techniques. In the future, in conjunction with modern laboratory automation this integrated set of techniques will enable high throughput experimental validation of the functional annotation of microbial genomes.

  4. De novo annotation of the immune-enriched transcriptome provides insights into immune system genes of Chinese sturgeon (Acipenser sinensis).

    PubMed

    Zhu, Rong; Du, He-Jun; Li, Shun-Yi; Li, Ya-Dong; Ni, Hong; Yu, Xue-Jing; Yang, Yan-Yan; Fan, Yu-Ding; Jiang, Nan; Zeng, Ling-Bing; Wang, Xing-Guo

    2016-08-01

    Chinese sturgeon (Acipenser sinensis), one of the oldest extant actinopterygian fishes with very high evolutionary, economical and conservation interest, is considered to be one of the critically endangered aquatic animals in China. Up to date, the immune system of this species remains largely undetermined with little sequence information publicly available. Herein, the first comprehensive transcriptome of immune tissues for Chinese sturgeon was characterized using Illumina deep sequencing. Over 67 million high-quality reads were generated and de novo assembled into the final set of 91,739 unique sequences. The annotation pipeline revealed that 25,871 unigenes were successfully annotated in the public databases, of which only 2002 had significant match to the existing sequences for the genus Acipenser. Overall 22,827 unigenes were categorized into 52 GO terms, 12,742 were classified into 26 KOG categories, and 4968 were assigned to 339 KEGG pathways. A more detailed annotation search showed the presence of a notable representation of immune-related genes, which suggests that this non-teleost actinopterygian fish harbors the same intermediates as in the well known immune pathways from mammals and teleosts, such as pattern recognition receptor (PRR) signaling pathway, JAK-STAT signaling pathway, complement and coagulation pathway, T-cell receptor (TCR) and B-cell receptor (BCR) signaling pathways. Additional genetic marker discovery led to the retrieval of 20,056 simple sequence repeats (SSRs) and 327,140 single nucleotide polymorphisms (SNPs). This immune-enriched transcriptome of Chinese sturgeon represents a rich resource that adds to the currently nascent field of chondrostean fish immunogenetics and furthers the conservation and management of this valuable fish.

  5. Proteomics for Validation of Automated Gene Model Predictions

    SciTech Connect

    Zhou, Kemin; Panisko, Ellen A.; Magnuson, Jon K.; Baker, Scott E.; Grigoriev, Igor V.

    2008-02-14

    High-throughput liquid chromatography mass spectrometry (LC-MS)-based proteomic analysis has emerged as a powerful tool for functional annotation of genome sequences. These analyses complement the bioinformatic and experimental tools used for deriving, verifying, and functionally annotating models of genes and their transcripts. Furthermore, proteomics extends verification and functional annotation to the level of the translation product of the gene model.

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

    PubMed Central

    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

  7. Solving the Problem: Genome Annotation Standards before the Data Deluge

    PubMed Central

    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

  8. Graph-based sequence annotation using a data integration approach.

    PubMed

    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/.

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

    NASA Astrophysics Data System (ADS)

    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.

  10. The Disease Portals, disease–gene annotation and the RGD disease ontology at the Rat Genome Database

    PubMed Central

    Hayman, G. Thomas; Laulederkind, Stanley J. F.; Smith, Jennifer R.; Wang, Shur-Jen; Petri, Victoria; Nigam, Rajni; Tutaj, Marek; De Pons, Jeff; Dwinell, Melinda R.; Shimoyama, Mary

    2016-01-01

    The Rat Genome Database (RGD; http://rgd.mcw.edu/) provides critical datasets and software tools to a diverse community of rat and non-rat researchers worldwide. To meet the needs of the many users whose research is disease oriented, RGD has created a series of Disease Portals and has prioritized its curation efforts on the datasets important to understanding the mechanisms of various diseases. Gene-disease relationships for three species, rat, human and mouse, are annotated to capture biomarkers, genetic associations, molecular mechanisms and therapeutic targets. To generate gene–disease annotations more effectively and in greater detail, RGD initially adopted the MEDIC disease vocabulary from the Comparative Toxicogenomics Database and adapted it for use by expanding this framework with the addition of over 1000 terms to create the RGD Disease Ontology (RDO). The RDO provides the foundation for, at present, 10 comprehensive disease area-related dataset and analysis platforms at RGD, the Disease Portals. Two major disease areas are the focus of data acquisition and curation efforts each year, leading to the release of the related Disease Portals. Collaborative efforts to realize a more robust disease ontology are underway. Database URL: http://rgd.mcw.edu PMID:27009807

  11. Smoking Gun or Circumstantial Evidence? Comparison of Statistical Learning Methods using Functional Annotations for Prioritizing Risk Variants

    PubMed Central

    Gagliano, Sarah A.; Ravji, Reena; Barnes, Michael R.; Weale, Michael E.; Knight, Jo

    2015-01-01

    Although technology has triumphed in facilitating routine genome sequencing, new challenges have been created for the data-analyst. Genome-scale surveys of human variation generate volumes of data that far exceed capabilities for laboratory characterization. By incorporating functional annotations as predictors, statistical learning has been widely investigated for prioritizing genetic variants likely to be associated with complex disease. We compared three published prioritization procedures, which use different statistical learning algorithms and different predictors with regard to the quantity, type and coding. We also explored different combinations of algorithm and annotation set. As an application, we tested which methodology performed best for prioritizing variants using data from a large schizophrenia meta-analysis by the Psychiatric Genomics Consortium. Results suggest that all methods have considerable (and similar) predictive accuracies (AUCs 0.64–0.71) in test set data, but there is more variability in the application to the schizophrenia GWAS. In conclusion, a variety of algorithms and annotations seem to have a similar potential to effectively enrich true risk variants in genome-scale datasets, however none offer more than incremental improvement in prediction. We discuss how methods might be evolved for risk variant prediction to address the impending bottleneck of the new generation of genome re-sequencing studies. PMID:26300220

  12. Smoking Gun or Circumstantial Evidence? Comparison of Statistical Learning Methods using Functional Annotations for Prioritizing Risk Variants.

    PubMed

    Gagliano, Sarah A; Ravji, Reena; Barnes, Michael R; Weale, Michael E; Knight, Jo

    2015-08-24

    Although technology has triumphed in facilitating routine genome sequencing, new challenges have been created for the data-analyst. Genome-scale surveys of human variation generate volumes of data that far exceed capabilities for laboratory characterization. By incorporating functional annotations as predictors, statistical learning has been widely investigated for prioritizing genetic variants likely to be associated with complex disease. We compared three published prioritization procedures, which use different statistical learning algorithms and different predictors with regard to the quantity, type and coding. We also explored different combinations of algorithm and annotation set. As an application, we tested which methodology performed best for prioritizing variants using data from a large schizophrenia meta-analysis by the Psychiatric Genomics Consortium. Results suggest that all methods have considerable (and similar) predictive accuracies (AUCs 0.64-0.71) in test set data, but there is more variability in the application to the schizophrenia GWAS. In conclusion, a variety of algorithms and annotations seem to have a similar potential to effectively enrich true risk variants in genome-scale datasets, however none offer more than incremental improvement in prediction. We discuss how methods might be evolved for risk variant prediction to address the impending bottleneck of the new generation of genome re-sequencing studies.

  13. Analysis of mammalian gene function through broad based phenotypic screens across a consortium of mouse clinics

    PubMed Central

    Adams, David J; Adams, Niels C; Adler, Thure; Aguilar-Pimentel, Antonio; Ali-Hadji, Dalila; Amann, Gregory; André, Philippe; Atkins, Sarah; Auburtin, Aurelie; Ayadi, Abdel; Becker, Julien; Becker, Lore; Bedu, Elodie; Bekeredjian, Raffi; Birling, Marie-Christine; Blake, Andrew; Bottomley, Joanna; Bowl, Mike; Brault, Véronique; Busch, Dirk H; Bussell, James N; Calzada-Wack, Julia; Cater, Heather; Champy, Marie-France; Charles, Philippe; Chevalier, Claire; Chiani, Francesco; Codner, Gemma F; Combe, Roy; Cox, Roger; Dalloneau, Emilie; Dierich, André; Di Fenza, Armida; Doe, Brendan; Duchon, Arnaud; Eickelberg, Oliver; Esapa, Chris T; El Fertak, Lahcen; Feigel, Tanja; Emelyanova, Irina; Estabel, Jeanne; Favor, Jack; Flenniken, Ann; Gambadoro, Alessia; Garrett, Lilian; Gates, Hilary; Gerdin, Anna-Karin; Gkoutos, George; Greenaway, Simon; Glasl, Lisa; Goetz, Patrice; Da Cruz, Isabelle Goncalves; Götz, Alexander; Graw, Jochen; Guimond, Alain; Hans, Wolfgang; Hicks, Geoff; Hölter, Sabine M; Höfler, Heinz; Hancock, John M; Hoehndorf, Robert; Hough, Tertius; Houghton, Richard; Hurt, Anja; Ivandic, Boris; Jacobs, Hughes; Jacquot, Sylvie; Jones, Nora; Karp, Natasha A; Katus, Hugo A; Kitchen, Sharon; Klein-Rodewald, Tanja; Klingenspor, Martin; Klopstock, Thomas; Lalanne, Valerie; Leblanc, Sophie; Lengger, Christoph; le Marchand, Elise; Ludwig, Tonia; Lux, Aline; McKerlie, Colin; Maier, Holger; Mandel, Jean-Louis; Marschall, Susan; Mark, Manuel; Melvin, David G; Meziane, Hamid; Micklich, Kateryna; Mittelhauser, Christophe; Monassier, Laurent; Moulaert, David; Muller, Stéphanie; Naton, Beatrix; Neff, Frauke; Nolan, Patrick M; Nutter, Lauryl MJ; Ollert, Markus; Pavlovic, Guillaume; Pellegata, Natalia S; Peter, Emilie; Petit-Demoulière, Benoit; Pickard, Amanda; Podrini, Christine; Potter, Paul; Pouilly, Laurent; Puk, Oliver; Richardson, David; Rousseau, Stephane; Quintanilla-Fend, Leticia; Quwailid, Mohamed M; Racz, Ildiko; Rathkolb, Birgit; Riet, Fabrice; Rossant, Janet; Roux, Michel; Rozman, Jan; Ryder, Ed; Salisbury, Jennifer; Santos, Luis; Schäble, Karl-Heinz; Schiller, Evelyn; Schrewe, Anja; Schulz, Holger; Steinkamp, Ralf; Simon, Michelle; Stewart, Michelle; Stöger, Claudia; Stöger, Tobias; Sun, Minxuan; Sunter, David; Teboul, Lydia; Tilly, Isabelle; Tocchini-Valentini, Glauco P; Tost, Monica; Treise, Irina; Vasseur, Laurent; Velot, Emilie; Vogt-Weisenhorn, Daniela; Wagner, Christelle; Walling, Alison; Weber, Bruno; Wendling, Olivia; Westerberg, Henrik; Willershäuser, Monja; Wolf, Eckhard; Wolter, Anne; Wood, Joe; Wurst, Wolfgang; Yildirim, Ali Önder; Zeh, Ramona; Zimmer, Andreas; Zimprich, Annemarie

    2015-01-01

    The function of the majority of genes in the mouse and human genomes remains unknown. The mouse ES cell knockout resource provides a basis for characterisation of relationships between gene and phenotype. The EUMODIC consortium developed and validated robust methodologies for broad-based phenotyping of knockouts through a pipeline comprising 20 disease-orientated platforms. We developed novel statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no prior functional annotation. We captured data from over 27,000 mice finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. Novel phenotypes were uncovered for many genes with unknown function providing a powerful basis for hypothesis generation and further investigation in diverse systems. PMID:26214591

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

    PubMed

    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.

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

    PubMed Central

    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. PMID:26587838

  16. Gene3D: modelling protein structure, function and evolution.

    PubMed

    Yeats, Corin; Maibaum, Michael; Marsden, Russell; Dibley, Mark; Lee, David; Addou, Sarah; Orengo, Christine A

    2006-01-01

    The Gene3D release 4 database and web portal (http://cathwww.biochem.ucl.ac.uk:8080/Gene3D) provide a combined structural, functional and evolutionary view of the protein world. It is focussed on providing structural annotation for protein sequences without structural representatives--including the complete proteome sets of over 240 different species. The protein sequences have also been clustered into whole-chain families so as to aid functional prediction. The structural annotation is generated using HMM models based on the CATH domain families; CATH is a repository for manually deduced protein domains. Amongst the changes from the last publication are: the addition of over 100 genomes and the UniProt sequence database, domain data from Pfam, metabolic pathway and functional data from COGs, KEGG and GO, and protein-protein interaction data from MINT and BIND. The website has been rebuilt to allow more sophisticated querying and the data returned is presented in a clearer format with greater functionality. Furthermore, all data can be downloaded in a simple XML format, allowing users to carry out complex investigations at their own computers.

  17. Mining and gene ontology based annotation of SSR markers from expressed sequence tags of Humulus lupulus.

    PubMed

    Singh, Swati; Gupta, Sanchita; Mani, Ashutosh; Chaturvedi, Anoop

    2012-01-01

    Humulus lupulus is commonly known as hops, a member of the family moraceae. Currently many projects are underway leading to the accumulation of voluminous genomic and expressed sequence tag sequences in public databases. The genetically characterized domains in these databases are limited due to non-availability of reliable molecular markers. The large data of EST sequences are available in hops. The simple sequence repeat markers extracted from EST data are used as molecular markers for genetic characterization, in the present study. 25,495 EST sequences were examined and assembled to get full-length sequences. Maximum frequency distribution was shown by mononucleotide SSR motifs i.e. 60.44% in contig and 62.16% in singleton where as minimum frequency are observed for hexanucleotide SSR in contig (0.09%) and pentanucleotide SSR in singletons (0.12%). Maximum trinucleotide motifs code for Glutamic acid (GAA) while AT/TA were the most frequent repeat of dinucleotide SSRs. Flanking primer pairs were designed in-silico for the SSR containing sequences. Functional categorization of SSRs containing sequences was done through gene ontology terms like biological process, cellular component and molecular function.

  18. A semantic analysis of the annotations of the human genome

    PubMed Central

    Khatri, Purvesh; Done, Bogdan; Rao, Archana; Done, Arina

    2008-01-01

    The correct interpretation of any biological experiment depends in an essential way on the accuracy and consistency of the existing annotation databases. Such databases are ubiquitous and used by all life scientists in most experiments. However, it is well known that such databases are incomplete and many annotations may also be incorrect. In this paper we describe a technique that can be used to analyze the semantic content of such annotation databases. Our approach is able to extract implicit semantic relationships between genes and functions. This ability allows us to discover novel functions for known genes. This approach is able to identify missing and inaccurate annotations in existing annotation databases, and thus help improve their accuracy. We used our technique to analyze the current annotations of the human genome. From this body of annotations, we were able to predict 212 additional gene–function assignments. A subsequent literature search found that 138 of these gene–functions assignments are supported by existing peer-reviewed papers. An additional 23 assignments have been confirmed in the meantime by the addition of the respective annotations in later releases of the Gene Ontology database. Overall, the 161 confirmed assignments represent 75.95% of the proposed gene–function assignments. Only one of our predictions (0.4%) was contradicted by the existing literature. We could not find any relevant articles for 50 of our predictions (23.58%). The method is independent of the organism and can be used to analyze and improve the quality of the data of any public or private annotation database. Availability http://vortex.cs.wayne.edu/papers/semantic_analysis_bioinfo.pdf Contact sod@cs.wayne.edu PMID:15955782

  19. Functionally Enigmatic Genes: A Case Study of the Brain Ignorome

    PubMed Central

    Pandey, Ashutosh K.; Lu, Lu; Wang, Xusheng; Homayouni, Ramin; Williams, Robert W.

    2014-01-01

    What proportion of genes with intense and selective expression in specific tissues, cells, or systems are still almost completely uncharacterized with respect to biological function? In what ways do these functionally enigmatic genes differ from well-studied genes? To address these two questions, we devised a computational approach that defines so-called ignoromes. As proof of principle, we extracted and analyzed a large subset of genes with intense and selective expression in brain. We find that publications associated with this set are highly skewed—the top 5% of genes absorb 70% of the relevant literature. In contrast, approximately 20% of genes have essentially no neuroscience literature. Analysis of the ignorome over the past decade demonstrates that it is stubbornly persistent, and the rapid expansion of the neuroscience literature has not had the expected effect on numbers of these genes. Surprisingly, ignorome genes do not differ from well-studied genes in terms of connectivity in coexpression networks. Nor do they differ with respect to numbers of orthologs, paralogs, or protein domains. The major distinguishing characteristic between these sets of genes is date of discovery, early discovery being associated with greater research momentum—a genomic bandwagon effect. Finally we ask to what extent massive genomic, imaging, and phenotype data sets can be used to provide high-throughput functional annotation for an entire ignorome. In a majority of cases we have been able to extract and add significant information for these neglected genes. In several cases—ELMOD1, TMEM88B, and DZANK1—we have exploited sequence polymorphisms, large phenome data sets, and reverse genetic methods to evaluate the function of ignorome genes. PMID:24523945

  20. Gene Chips and Functional Genomics

    NASA Astrophysics Data System (ADS)

    Hamadeh, Hisham; Afshari, Cynthia

    2000-11-01

    These past few years of scientific discovery will undoubtedly be remembered as the "genomics era," the period in which biologists succeeded in enumerating the sequence of nucleotides making up all, or at least most, of human DNA. And while this achievement has been heralded as a technological feat equal to the moon landing, it is only the first of many advances in DNA technology. Scientists are now faced with the task of understanding the meaning of the DNA sequence. Specifically, they want to learn how the DNA code relates to protein function. An important tool in the study of "functional genomics," is the cDNA microarray—also known as the gene chip. Inspired by computer microchips, gene chips allow scientists to monitor the expression of hundreds, even thousands, of genes in a fraction of the time it used to take to monitor the expression of a single one. By altering the conditions under which a particular tissue expresses genes—say, by exposing it to toxins or growth factors—scientists can determine the suite of genes expressed in different situations and hence start to get a handle on the function of these genes. The authors discuss this important new technology and some of its practical applications.

  1. Functional analysis of differentially expressed genes associated with glaucoma from DNA microarray data.

    PubMed

    Wu, Y; Zang, W D; Jiang, W

    2014-11-11

    Microarray data of astrocytes extracted from the optic nerves of donors with and without glaucoma were analyzed to screen for differentially expressed genes (DEGs). Functional exploration with bioinformatic tools was then used to understand the roles of the identified DEGs in glaucoma. Microarray data were downloaded from the Gene Expression Omnibus (GEO) database, which contains 13 astrocyte samples, 6 from healthy subjects and 7 from patients suffering from glaucoma. Data were pre-processed, and DEGs were screened out using R software packages. Interactions between DEGs were identified, and networks were built using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). GENECODIS was utilized for the functional analysis of the DEGs, and GOTM was used for module division, for which functional annotation was conducted with the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A total of 371 DEGs were identified between glaucoma-associated samples and normal samples. Three modules included in the PPID database were generated with 11, 12, and 2 significant functional annotations, including immune system processes, inflammatory responses, and synaptic vesicle endocytosis, respectively. We found that the most significantly enriched functions for each module were associated with immune function. Several genes that play interesting roles in the development of glaucoma are described; these genes may be potential biomarkers for glaucoma diagnosis or treatment.

  2. Functional annotation of the T-cell immunoglobulin mucin family in birds.

    PubMed

    Hu, Tuanjun; Wu, Zhiguang; Vervelde, Lonneke; Rothwell, Lisa; Hume, David A; Kaiser, Pete

    2016-07-01

    T-cell immunoglobulin and mucin (TIM) family molecules are cell membrane proteins, preferentially expressed on various immune cells and implicated in recognition and clearance of apoptotic cells. Little is known of their function outside human and mouse, and nothing outside mammals. We identified only two TIM genes (chTIM) in the chicken genome, putative orthologues of mammalian TIM1 and TIM4, and cloned the respective cDNAs. Like mammalian TIM1, chTIM1 expression was restricted to lymphoid tissues and immune cells. The gene chTIM4 encodes at least five splice variants with distinct expression profiles that also varied between strains of chicken. Expression of chTIM4 was detected in myeloid antigen-presenting cells, and in γδ T cells, whereas mammalian TIM4 is not expressed in T cells. Like the mammalian proteins, chTIM1 and chTIM4 fusion proteins bind to phosphatidylserine, and are thereby implicated in recognition of apoptotic cells. The chTIM4-immunoglobulin fusion protein also had co-stimulatory activity on chicken T cells, suggesting a function in antigen presentation.

  3. Comprehensive functional analysis of large lists of genes and proteins.

    PubMed

    Mlecnik, Bernhard; Galon, Jérôme; Bindea, Gabriela

    2017-03-22

    The interpretation of high dimensional datasets resulting from genomic and proteomic experiments in a timely and efficient manner is challenging. ClueGO software is a Cytoscape App that extracts representative functional biological information for large lists of genes or proteins. The functional enrichment analysis is based on the latest publicly available data from multiple annotation and ontology resources that can be automatically accessed through ClueGO. Predefined settings for the selection of the terms are provided to facilitate the analysis. Results are visualized as networks in which Gene Ontology (GO) terms and pathways are grouped based on their biological role. Many species are now supported by ClueGO and additional organisms are added on demand. ClueGO can be used together with the CluePedia App to enable the visualization of protein-protein interactions within or between pathways.

  4. Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python).

    PubMed

    Irizarry, Kristopher J L; Rutllant, Josep

    2016-01-01

    Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.

  5. Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python)

    PubMed Central

    Rutllant, Josep

    2016-01-01

    Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value. PMID:27200191

  6. Evaluating techniques for metagenome annotation using simulated sequence data

    PubMed Central

    Randle-Boggis, Richard J.; Helgason, Thorunn; Sapp, Melanie; Ashton, Peter D.

    2016-01-01

    The advent of next-generation sequencing has allowed huge amounts of DNA sequence data to be produced, advancing the capabilities of microbial ecosystem studies. The current challenge is to identify from which microorganisms and genes the DNA originated. Several tools and databases are available for annotating DNA sequences. The tools, databases and parameters used can have a significant impact on the results: naïve choice of these factors can result in a false representation of community composition and function. We use a simulated metagenome to show how different parameters affect annotation accuracy by evaluating the sequence annotation performances of MEGAN, MG-RAST, One Codex and Megablast. This simulated metagenome allowed the recovery of known organism and function abundances to be quantitatively evaluated, which is not possible for environmental metagenomes. The performance of each program and database varied, e.g. One Codex correctly annotated many sequences at the genus level, whereas MG-RAST RefSeq produced many false positive annotations. This effect decreased as the taxonomic level investigated increased. Selecting more stringent parameters decreases the annotation sensitivity, but increases precision. Ultimately, there is a trade-off between taxonomic resolution and annotation accuracy. These results should be considered when annotating metagenomes and interpreting results from previous studies. PMID:27162180

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

    DOE PAGES

    Huntemann, Marcel; Ivanova, Natalia N.; Mavromatis, Konstantinos; ...

    2015-10-26

    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. In conclusion, structural annotation is followed by assignment of protein product names and functions.

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

    PubMed

    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.

  9. Accumulation, functional annotation, and comparative analysis of expressed sequence tags in eggplant (Solanum melongena L.), the third pole of the genus Solanum species after tomato and potato.

    PubMed

    Fukuoka, Hiroyuki; Yamaguchi, Hirotaka; Nunome, Tsukasa; Negoro, Satomi; Miyatake, Koji; Ohyama, Akio

    2010-01-15

    Eggplant (Solanum melongena L.) is a widely grown vegetable crop that belongs to the genus Solanum, which is comprised of more than 1000 species of wide genetic and phenotypic variation. Unlike tomato and potato, Solanum crops that belong to subgenus Potatoe and have been targets for comprehensive genomic studies, eggplant is endemic to the Old World and belongs to a different subgenus, Leptostemonum, and therefore, would be a unique member for comparative molecular biology in Solanum. In this study, more than 60,000 eggplant cDNA clones from various tissues and treatments were sequenced from both the 5'- and 3'-ends, and a unigene set consisting of 16,245 unique sequences was constructed. Functional annotations based on sequence similarity to known plant reference datasets revealed a distribution of functional categories almost similar to that of tomato, while 1316 unigenes were suggested to be eggplant-specific. Sequence-based comparative analysis using putative orthologous gene groups setup by reciprocal sequence comparison among six solanaceous species suggested that eggplant and its wild ally Solanum torvum were clustered separately from subgenus Potatoe species, and then, all Solanum species were clustered separately from the genus Capsicum. Microsatellite motif distribution was different among species and likely to be coincident with the phylogenetic relationships. Furthermore, the eggplant unigene dataset exhibited its utility in transcriptome analysis by the SAGE strategy where a considerable number of short tag sequences of interest were successfully assigned to unigenes and their functional annotations. The eggplant ESTs and 16k unigene set developed in this study would be a useful resource not only for molecular genetics and breeding in eggplant itself, but for expanding the scope of comparative biology in Solanum species.

  10. GOAPhAR: An Integrative Discovery Tool for Annotation, Pathway Analysis

    PubMed Central

    Mathur, Sachin; Visvanathan, Mahesh; Svojanovsky, Stan; Yoo, Byunggil; Srinivas, Adagarla B.; Lushington, Gerald H.; Smith, Peter G.

    2010-01-01

    We have developed the web based tool GOAPhAR (Gene Ontology, Annotations and Pathways for Array Research), that integrates information from disparate sources regarding gene annotations, protein annotations, identifiers associated with probe sets, functional pathways, protein interactions, Gene Ontology, publicly available microarray datasets and tools for statistically validating clusters in microarray data. Genes of interest can be input as Affymetrix probe identifiers, Genbank, or Unigene identifiers for human, mouse or rat genomes. Results are provided in a user friendly interface with hyperlinks to the sources of information. PMID:21132056

  11. Functional classification of genes using semantic distance and fuzzy clustering approach: evaluation with reference sets and overlap analysis.

    PubMed

    Devignes, Marie-Dominique; Benabderrahmane, Sidahmed; Smaïl-Tabbone, Malika; Napoli, Amedeo; Poch, Olivier

    2012-01-01

    Functional classification aims at grouping genes according to their molecular function or the biological process they participate in. Evaluating the validity of such unsupervised gene classification remains a challenge given the variety of distance measures and classification algorithms that can be used. We evaluate here functional classification of genes with the help of reference sets: KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathways and Pfam clans. These sets represent ground truth for any distance based on GO (Gene Ontology) biological process and molecular function annotations respectively. Overlaps between clusters and reference sets are estimated by the F-score method. We test our previously described IntelliGO semantic distance with hierarchical and fuzzy C-means clustering and we compare results with the state-of-the-art DAVID (Database for Annotation Visualisation and Integrated Discovery) functional classification method. Finally, study of best matching clusters to reference sets leads us to propose a set-difference method for discovering missing information.

  12. Cloning, annotation and expression analysis of mycoparasitism-related genes in Trichoderma harzianum 88.

    PubMed

    Yao, Lin; Yang, Qian; Song, Jinzhu; Tan, Chong; Guo, Changhong; Wang, Li; Qu, Lianhai; Wang, Yun

    2013-04-01

    Trichoderma harzianum 88, a filamentous soil fungus, is an effective biocontrol agent against several plant pathogens. High-throughput sequencing was used here to study the mycoparasitism mechanisms of T. harzianum 88. Plate confrontation tests of T. harzianum 88 against plant pathogens were conducted, and a cDNA library was constructed from T. harzianum 88 mycelia in the presence of plant pathogen cell walls. Randomly selected transcripts from the cDNA library were compared with eukaryotic plant and fungal genomes. Of the 1,386 transcripts sequenced, the most abundant Gene Ontology (GO) classification group was "physiological process". Differential expression of 19 genes was confirmed by real-time RT-PCR at different mycoparasitism stages against plant pathogens. Gene expression analysis revealed the transcription of various genes involved in mycoparasitism of T. harzianum 88. Our study provides helpful insights into the mechanisms of T. harzianum 88-plant pathogen interactions.

  13. Functional Annotation of the Ophiostoma novo-ulmi Genome: Insights into the Phytopathogenicity of the Fungal Agent of Dutch Elm Disease

    PubMed Central

    Comeau, André M.; Dufour, Josée; Bouvet, Guillaume F.; Jacobi, Volker; Nigg, Martha; Henrissat, Bernard; Laroche, Jérôme; Levesque, Roger C.; Bernier, Louis

    2015-01-01

    The ascomycete fungus Ophiostoma novo-ulmi is responsible for the pandemic of Dutch elm disease that has been ravaging Europe and North America for 50 years. We proceeded to annotate the genome of the O. novo-ulmi strain H327 that was sequenced in 2012. The 31.784-Mb nuclear genome (50.1% GC) is organized into 8 chromosomes containing a total of 8,640 protein-coding genes that we validated with RNA sequencing analysis. Approximately 53% of these genes have their closest match to Grosmannia clavigera kw1407, followed by 36% in other close Sordariomycetes, 5% in other Pezizomycotina, and surprisingly few (5%) orphans. A relatively small portion (∼3.4%) of the genome is occupied by repeat sequences; however, the mechanism of repeat-induced point mutation appears active in this genome. Approximately 76% of the proteins could be assigned functions using Gene Ontology analysis; we identified 311 carbohydrate-active enzymes, 48 cytochrome P450s, and 1,731 proteins potentially involved in pathogen–host interaction, along with 7 clusters of fungal secondary metabolites. Complementary mating-type locus sequencing, mating tests, and culturing in the presence of elm terpenes were conducted. Our analysis identified a specific genetic arsenal impacting the sexual and vegetative growth, phytopathogenicity, and signaling/plant–defense–degradation relationship between O. novo-ulmi and its elm host and insect vectors. PMID:25539722

  14. Comparative omics-driven genome annotation refinement: application across Yersiniae.

    PubMed

    Schrimpe-Rutledge, Alexandra C; Jones, Marcus B; Chauhan, Sadhana; Purvine, Samuel O; Sanford, James A; Monroe, Matthew E; Brewer, Heather M; Payne, Samuel H; Ansong, Charles; Frank, Bryan C; Smith, Richard D; Peterson, Scott N; Motin, Vladimir L; Adkins, Joshua N

    2012-01-01

    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. The annotation process is now performed almost exclusively in an automated fashion to balance the large number of sequences generated. One possible way of reducing 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. Here, the concept of annotation refinement has been extended to include a comparative assessment of genomes across closely related species. Transcriptomic and proteomic data derived from 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 incorrect (i.e., observed frameshifts, extended start sites, and translated pseudogenes) protein-coding sequences within the three current genome annotations. Gene loss is presumed to play a major role in Y. pestis acquiring its niche as a virulent pathogen, thus the discovery of many translated pseudogenes, including the insertion-ablated argD, underscores a need for functional analyses to investigate hypotheses related to divergence. Refinements included the discovery of a seemingly essential ribosomal protein, several virulence-associated factors, a transcriptional regulator, and many hypothetical proteins that were missed during annotation.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ann...

  16. Experimental Strategies for Functional Annotation and Metabolism Discovery: Targeted Screening of Solute Binding Proteins and Unbiased Panning of Metabolomes

    PubMed Central

    2015-01-01

    The rate at which genome sequencing data is accruing demands enhanced methods for functional annotation and metabolism discovery. Solute binding proteins (SBPs) facilitate the transport of the first reactant in a metabolic pathway, thereby constraining the regions of chemical space and the chemistries that must be considered for pathway reconstruction. We describe high-throughput protein production and differential scanning fluorimetry platforms, which enabled the screening of 158 SBPs against a 189 component library specifically tailored for this class of proteins. Like all screening efforts, this approach is limited by the practical constraints imposed by construction of the library, i.e., we can study only those metabolites that are known to exist and which can be made in sufficient quantities for experimentation. To move beyond these inherent limitations, we illustrate the promise of crystallographic- and mass spectrometric-based approaches for the unbiased use of entire metabolomes as screening libraries. Together, our approaches identified 40 new SBP ligands, generated experiment-based annotations for 2084 SBPs in 71 isofunctional clusters, and defined numerous metabolic pathways, including novel catabolic pathways for the utilization of ethanolamine as sole nitrogen source and the use of d-Ala-d-Ala as sole carbon source. These efforts begin to define an integrated strategy for realizing the full value of amassing genome sequence data. PMID:25540822

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

    PubMed

    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.

  18. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes

    DOE PAGES

    Brettin, Thomas; Davis, James J.; Disz, Terry; ...

    2015-02-10

    The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. It works by offering a standard software pipeline for identifying genomic features (i.e., protein-encoding genes and RNA) and annotating their functions. Recently, in order to make RAST a more useful research tool and to keep pace with advancements in bioinformatics, it has become desirable to build a version of RAST that is both customizable and extensible. In this paper, we describe the RAST tool kit (RASTtk), a modular version of RAST that enables researchers to build custom annotation pipelines. RASTtk offersmore » a choice of software for identifying and annotating genomic features as well as the ability to add custom features to an annotation job. RASTtk also accommodates the batch submission of genomes and the ability to customize annotation protocols for batch submissions. This is the first major software restructuring of RAST since its inception.« less

  19. Utility and Limitations of Using Gene Expression Data to Identify Functional Associations

    PubMed Central

    Peng, Cheng; Shiu, Shin-Han

    2016-01-01

    Gene co-expression has been widely used to hypothesize gene function through guilt-by association. However, it is not clear to what degree co-expression is informative, whether it can be applied to genes involved in different biological processes, and how the type of dataset impacts inferences about gene functions. Here our goal is to assess the utility and limitations of using co-expression as a criterion to recover functional associations between genes. By determining the percentage of gene pairs in a metabolic pathway with significant expression correlation, we found that many genes in the same pathway do not have similar transcript profiles and the choice of dataset, annotation quality, gene function, expression similarity measure, and clustering approach significantly impacts the ability to recover functional associations between genes using Arabidopsis thaliana as an example. Some datasets are more informative in capturing coordinated expression profiles and larger data sets are not always better. In addition, to recover the maximum number of known pathways and identify candidate genes with similar functions, it is important to explore rather exhaustively multiple dataset combinations, similarity measures, clustering algorithms and parameters. Finally, we validated the biological relevance of co-expression cluster memberships with an independent phenomics dataset and found that genes that consistently cluster with leucine degradation genes tend to have similar leucine levels in mutants. This study provides a framework for obtaining gene functional associations by maximizing the information that can be obtained from gene expression datasets. PMID:27935950

  20. Rotavirus gene structure and function.

    PubMed Central

    Estes, M K; Cohen, J

    1989-01-01

    Knowledge of the structure and function of the genes and proteins of the rotaviruses has expanded rapidly. Information obtained in the last 5 years has revealed unexpected and unique molecular properties of rotavirus proteins of general interest to virologists, biochemists, and cell biologists. Rotaviruses share some features of replication with reoviruses, yet antigenic and molecular properties of the outer capsid proteins, VP4 (a protein whose cleavage is required for infectivity, possibly by mediating fusion with the cell membrane) and VP7 (a glycoprotein), show more similarities with those of other viruses such as the orthomyxoviruses, paramyxoviruses, and alphaviruses. Rotavirus morphogenesis is a unique process, during which immature subviral particles bud through the membrane of the endoplasmic reticulum (ER). During this process, transiently enveloped particles form, the outer capsid proteins are assembled onto particles, and mature particles accumulate in the lumen of the ER. Two ER-specific viral glycoproteins are involved in virus maturation, and these glycoproteins have been shown to be useful models for studying protein targeting and retention in the ER and for studying mechanisms of virus budding. New ideas and approaches to understanding how each gene functions to replicate and assemble the segmented viral genome have emerged from knowledge of the primary structure of rotavirus genes and their proteins and from knowledge of the properties of domains on individual proteins. Localization of type-specific and cross-reactive neutralizing epitopes on the outer capsid proteins is becoming increasingly useful in dissecting the protective immune response, including evaluation of vaccine trials, with the practical possibility of enhancing the production of new, more effective vaccines. Finally, future analyses with recently characterized immunologic and gene probes and new animal models can be expected to provide a basic understanding of what regulates the

  1. Automatic annotation of organellar genomes with DOGMA

    SciTech Connect

    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.

  2. Transcriptome characterization for genome annotation and functional genomics in Theobroma cacao

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Evidence from leaf transcriptome sequencing using two technology platforms, in combination with protein homology and trained ab initio predictions, previously enabled us to build 35,000 gene models in T. cacao (www.cacaogenomedb.org). Here we review the contribution of each data type to cacao gene a...

  3. IMG ER: A System for Microbial Genome Annotation Expert Review and Curation

    SciTech Connect

    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.

  4. Sma3s: A Three-Step Modular Annotator for Large Sequence Datasets

    PubMed Central

    Muñoz-Mérida, Antonio; Viguera, Enrique; Claros, M. Gonzalo; Trelles, Oswaldo; Pérez-Pulido, Antonio J.

    2014-01-01

    Automatic sequence annotation is an essential component of modern ‘omics’ studies, which aim to extract information from large collections of sequence data. Most existing tools use sequence homology to establish evolutionary relationships and assign putative functions to sequences. However, it can be difficult to define a similarity threshold that achieves sufficient coverage without sacrificing annotation quality. Defining the correct configuration is critical and can be challenging for non-specialist users. Thus, the development of robust automatic annotation techniques that generate high-quality annotations without needing expert knowledge would be very valuable for the research community. We present Sma3s, a tool for automatically annotating very large collections of biological sequences from any kind of gene library or genome. Sma3s is composed of three modules that progressively annotate query sequences using either: (i) very similar homologues, (ii) orthologous sequences or (iii) terms enriched in groups of homologous sequences. We trained the system using several random sets of known sequences, demonstrating average sensitivity and specificity values of ∼85%. In conclusion, Sma3s is a versatile tool for high-throughput annotation of a wide variety of sequence datasets that outperforms the accuracy of other well-established annotation algorithms, and it can enrich existing database annotations and uncover previously hidden features. Importantly, Sma3s has already been used in the functional annotation of two published transcriptomes. PMID:24501397

  5. Sma3s: a three-step modular annotator for large sequence datasets.

    PubMed

    Muñoz-Mérida, Antonio; Viguera, Enrique; Claros, M Gonzalo; Trelles, Oswaldo; Pérez-Pulido, Antonio J

    2014-08-01

    Automatic sequence annotation is an essential component of modern 'omics' studies, which aim to extract information from large collections of sequence data. Most existing tools use sequence homology to establish evolutionary relationships and assign putative functions to sequences. However, it can be difficult to define a similarity threshold that achieves sufficient coverage without sacrificing annotation quality. Defining the correct configuration is critical and can be challenging for non-specialist users. Thus, the development of robust automatic annotation techniques that generate high-quality annotations without needing expert knowledge would be very valuable for the research community. We present Sma3s, a tool for automatically annotating very large collections of biological sequences from any kind of gene library or genome. Sma3s is composed of three modules that progressively annotate query sequences using either: (i) very similar homologues, (ii) orthologous sequences or (iii) terms enriched in groups of homologous sequences. We trained the system using several random sets of known sequences, demonstrating average sensitivity and specificity values of ~85%. In conclusion, Sma3s is a versatile tool for high-throughput annotation of a wide variety of sequence datasets that outperforms the accuracy of other well-established annotation algorithms, and it can enrich existing database annotations and uncover previously hidden features. Importantly, Sma3s has already been used in the functional annotation of two published transcriptomes.

  6. Expanding and vetting Sorghum bicolor gene annotations through transcriptome and methylome sequencing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With the emergence and subsequent advancement of next generation sequence technology, detailed structural and functional characterization of genomes is readily attainable. Here, we have sampled the Sorghum bicolor methylome by shallow sequencing of bisulfite treated DNA derived from root samples. W...

  7. A manual curation strategy to improve genome annotation: application to a set of haloarchael genomes.

    PubMed

    Pfeiffer, Friedhelm; Oesterhelt, Dieter

    2015-06-02

    Genome annotation errors are a persistent problem that impede research in the biosciences. A manual curation effort is described that attempts to produce high-quality genome annotations for a set of haloarchaeal genomes (Halobacterium salinarum and Hbt. hubeiense, Haloferax volcanii and Hfx. mediterranei, Natronomonas pharaonis and Nmn. moolapensis, Haloquadratum walsbyi strains HBSQ001 and C23, Natrialba magadii, Haloarcula marismortui and Har. hispanica, and Halohasta litchfieldiae). Genomes are checked for missing genes, start codon misassignments, and disrupted genes. Assignments of a specific function are preferably based on experimentally characterized homologs (Gold Standard Proteins). To avoid overannotation, which is a major source of database errors, we restrict annotation to only general function assignments when support for a specific substrate assignment is insufficient. This strategy results in annotations that are resistant to the plethora of errors that compromise public databases. Annotation consistency is rigorously validated for ortholog pairs from the genomes surveyed. The annotation is regularly crosschecked against the UniProt database to further improve annotations and increase the level of standardization. Enhanced genome annotations are submitted to public databases (EMBL/GenBank, UniProt), to the benefit of the scientific community. The enhanced annotations are also publically available via HaloLex.

  8. APPRIS: annotation of principal and alternative splice isoforms.

    PubMed

    Rodriguez, Jose Manuel; Maietta, Paolo; Ezkurdia, Iakes; Pietrelli, Alessandro; Wesselink, Jan-Jaap; Lopez, Gonzalo; Valencia, Alfonso; Tress, Michael L

    2013-01-01

    Here, we present APPRIS (http://appris.bioinfo.cnio.es), a database that houses annotations of human splice isoforms. APPRIS has been designed to provide value to manual annotations of the human genome by adding reliable protein structural and functional data and information from cross-species conservation. The visual representation of the annotations provided by APPRIS for each gene allows annotators and researchers alike to easily identify functional changes brought about by splicing events. In addition to collecting, integrating and analyzing reliable predictions of the effect of splicing events, APPRIS also selects a single reference sequence for each gene, here termed the principal isoform, based on the annotations of structure, function and conservation for each transcript. APPRIS identifies a principal isoform for 85% of the protein-coding genes in the GENCODE 7 release for ENSEMBL. Analysis of the APPRIS data shows that at least 70% of the alternative (non-principal) variants would lose important functional or structural information relative to the principal isoform.

  9. Genome Annotation and Curation Using MAKER and MAKER-P

    PubMed Central

    Campbell, Michael S.; Holt, Carson; Moore, Barry; Yandell, Mark

    2014-01-01

    This unit describes how to use the genome annotation and curation tools MAKER and MAKER-P to annotate protein coding and non-coding RNA genes in newly assembled genomes, update/combine legacy annotations in light of new evidence, add quality metrics to annotations from other pipelines, and map existing annotations to a new assembly. MAKER and MAKER-P can rapidly annotate genomes of any size, and scale to match available computational resources. PMID:25501943

  10. Human Genome Annotation

    NASA Astrophysics Data System (ADS)

    Gerstein, Mark

    A central problem for 21st century science is annotating the human genome and making this annotation useful for the interpretation of personal genomes. My talk will focus on annotating the 99% of the genome that does not code for canonical genes, concentrating on intergenic features such as structural variants (SVs), pseudogenes (protein fossils), binding sites, and novel transcribed RNAs (ncRNAs). In particular, I will describe how we identify regulatory sites and variable blocks (SVs) based on processing next-generation sequencing experiments. I will further explain how we cluster together groups of sites to create larger annotations. Next, I will discuss a comprehensive pseudogene identification pipeline, which has enabled us to identify >10K pseudogenes in the genome and analyze their distribution with respect to age, protein family, and chromosomal location. Throughout, I will try to introduce some of the computational algorithms and approaches that are required for genome annotation. Much of this work has been carried out in the framework of the ENCODE, modENCODE, and 1000 genomes projects.

  11. An Innovative Plant Genomics and Gene Annotation Program for High School, Community College, and University Faculty

    PubMed Central

    Hilgert, Uwe; Nash, E. Bruce; Micklos, David A.

    2008-01-01

    Today's biology educators face the challenge of training their students in modern molecular biology techniques including genomics and bioinformatics. The Dolan DNA Learning Center (DNALC) of Cold Spring Harbor Laboratory has developed and disseminated a bench- and computer-based plant genomics curriculum for biology faculty. In 2007, a five-day “Plant Genomics and Gene Annotation” workshop was held at Florida A&M University in Tallahassee, FL, to enhance participants' knowledge and understanding of plant molecular genetics and assist them in developing and honing their laboratory and computer skills. Florida A&M University is a historically black university with over 95% African-American student enrollment. Sixteen participants, including high school (56%) and community college faculty (25%), attended the workshop. Participants carried out in vitro and in silico experiments with maize, Arabidopsis, soybean, and food products to determine the genotype of the samples. Benefits of the workshop included increased awareness of plant biology research for high school and college level students. Participants completed pre- and postworkshop evaluations for the measurement of effectiveness. Participants demonstrated an overall improvement in their postworkshop evaluation scores. This article provides a detailed description of workshop activities, as well as assessment and long-term support for broad classroom implementation. PMID:18765753

  12. Annotated Videography.

    ERIC Educational Resources Information Center

    United States Holocaust Memorial Museum, Washington, DC.

    This annotated list of 43 videotapes recommended for classroom use addresses various themes for teaching about the Holocaust, including: (1) overviews of the Holocaust; (2) life before the Holocaust; (3) propaganda; (4) racism, anti-Semitism; (5) "enemies of the state"; (6) ghettos; (7) camps; (8) genocide; (9) rescue; (10) resistance;…

  13. Genes and functions controlled by floral organ identity genes.

    PubMed

    Sablowski, Robert

    2010-02-01

    Floral organ identity genes specify the identity of floral organs in a manner analogous to the specification of body segments by Hox genes in animals. Different combinations of organ identity genes co-ordinate the expression of genes required for the development of each type of floral organ, from organ initiation until final differentiation. Here, I review what is known about the genes and functions subordinate to the organ identity genes. The sets of target genes change as organ development progresses and ultimately organ identity genes modify the expression of thousands of genes with a multitude of predicted functions, particularly in reproductive organs. However, genes involved in transcriptional control and hormone functions feature prominently among the early and direct targets. Functional analysis showed that control of organ-specific tissues and structures can be delegated to specialised intermediate regulators, but organ identity genes also fine-tune genes with general roles in shoot organ development, consistent with the notion that organ identity genes modify a core leaf-like developmental program. Future challenges include obtaining data with cellular resolution, predictive modelling of the regulatory network, and quantitative analysis of how organ identity genes and their targets control cell behaviour and ultimately organ shape.

  14. Using comparative genome analysis to identify problems in annotated microbial genomes.

    PubMed

    Poptsova, Maria S; Gogarten, J Peter

    2010-07-01

    Genome annotation is a tedious task that is mostly done by automated methods; however, the accuracy of these approaches has been questioned since the beginning of the sequencing era. Genome annotation is a multilevel process, and errors can emerge at different stages: during sequencing, as a result of gene-calling procedures, and in the process of assigning gene functions. Missed or wrongly annotated genes differentially impact different types of analyses. Here we discuss and demonstrate how the methods of comparative genome analysis can refine annotations by locating missing orthologues. We also discuss possible reasons for errors and show that the second-generation annotation systems, which combine multiple gene-calling programs with similarity-based methods, perform much better than the first annotation tools. Since old errors may propagate to the newly sequenced genomes, we emphasize that the problem of continuously updating popular public databases is an urgent and unresolved one. Due to the progress in genome-sequencing technologies, automated annotation techniques will remain the main approach in the future. Researchers need to be aware of the existing errors in the annotation of even well-studied genomes, such as Escherichia coli, and consider additional quality control for their results.

  15. Functional analyses of cellulose synthase genes in flax (Linum usitatissimum) by virus-induced gene silencing.

    PubMed

    Chantreau, Maxime; Chabbert, Brigitte; Billiard, Sylvain; Hawkins, Simon; Neutelings, Godfrey

    2015-12-01

    Flax (Linum usitatissimum) bast fibres are located in the stem cortex where they play an important role in mechanical support. They contain high amounts of cellulose and so are used for linen textiles and in the composite industry. In this study, we screened the annotated flax genome and identified 14 distinct cellulose synthase (CESA) genes using orthologous sequences previously identified. Transcriptomics of 'primary cell wall' and 'secondary cell wall' flax CESA genes showed that some were preferentially expressed in different organs and stem tissues providing clues as to their biological role(s) in planta. The development for the first time in flax of a virus-induced gene silencing (VIGS) approach was used to functionally evaluate the biological role of different CESA genes in stem tissues. Quantification of transcript accumulation showed that in many cases, silencing not only affected targeted CESA clades, but also had an impact on other CESA genes. Whatever the targeted clade, inactivation by VIGS affected plant growth. In contrast, only clade 1- and clade 6-targeted plants showed modifications in outer-stem tissue organization and secondary cell wall formation. In these plants, bast fibre number and structure were severely impacted, suggesting that the targeted genes may play an important role in the establishment of the fibre cell wall. Our results provide new fundamental information about cellulose biosynthesis in flax that should facilitate future plant improvement/engineering.

  16. GRYFUN: a web application for GO term annotation visualization and analysis in protein sets.

    PubMed

    Bastos, Hugo P; Sousa, Lisete; Clarke, Luka A; Couto, Francisco M

    2015-01-01

    Functional context for biological sequence is provided in the form of annotations. However, within a group of similar sequences there can be annotation heterogeneity in terms of coverage and specificity. This in turn can introduce issues regarding the interpretation of actual functional similarity and overall functional coherence of such a group. One way to mitigate such issues is through the use of visualization and statistical techniques. Therefore, in order to help interpret this annotation heterogeneity we created a web application that generates Gene Ontology annotation graphs for protein sets and their associated statistics from simple frequencies to enrichment values and Information Content based metrics. The publicly accessible website http://xldb.di.fc.ul.pt/gryfun/ currently accepts lists of UniProt accession numbers in order to create user-defined protein sets for subsequent annotation visualization and statistical assessment. GRYFUN is a freely available web application that allows GO annotation visualization of protein sets and which can be used for annotation coherence and cohesiveness analysis and annotation extension assessments within under-annotated protein sets.

  17. Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics.

    PubMed

    Hrabě de Angelis, Martin; Nicholson, George; Selloum, Mohammed; White, Jacqueline K; Morgan, Hugh; Ramirez-Solis, Ramiro; Sorg, Tania; Wells, Sara; Fuchs, Helmut; Fray, Martin; Adams, David J; Adams, Niels C; Adler, Thure; Aguilar-Pimentel, Antonio; Ali-Hadji, Dalila; Amann, Gregory; André, Philippe; Atkins, Sarah; Auburtin, Aurelie; Ayadi, Abdel; Becker, Julien; Becker, Lore; Bedu, Elodie; Bekeredjian, Raffi; Birling, Marie-Christine; Blake, Andrew; Bottomley, Joanna; Bowl, Michael R; Brault, Véronique; Busch, Dirk H; Bussell, James N; Calzada-Wack, Julia; Cater, Heather; Champy, Marie-France; Charles, Philippe; Chevalier, Claire; Chiani, Francesco; Codner, Gemma F; Combe, Roy; Cox, Roger; Dalloneau, Emilie; Dierich, André; Di Fenza, Armida; Doe, Brendan; Duchon, Arnaud; Eickelberg, Oliver; Esapa, Chris T; Fertak, Lahcen El; Feigel, Tanja; Emelyanova, Irina; Estabel, Jeanne; Favor, Jack; Flenniken, Ann; Gambadoro, Alessia; Garrett, Lilian; Gates, Hilary; Gerdin, Anna-Karin; Gkoutos, George; Greenaway, Simon; Glasl, Lisa; Goetz, Patrice; Da Cruz, Isabelle Goncalves; Götz, Alexander; Graw, Jochen; Guimond, Alain; Hans, Wolfgang; Hicks, Geoff; Hölter, Sabine M; Höfler, Heinz; Hancock, John M; Hoehndorf, Robert; Hough, Tertius; Houghton, Richard; Hurt, Anja; Ivandic, Boris; Jacobs, Hughes; Jacquot, Sylvie; Jones, Nora; Karp, Natasha A; Katus, Hugo A; Kitchen, Sharon; Klein-Rodewald, Tanja; Klingenspor, Martin; Klopstock, Thomas; Lalanne, Valerie; Leblanc, Sophie; Lengger, Christoph; le Marchand, Elise; Ludwig, Tonia; Lux, Aline; McKerlie, Colin; Maier, Holger; Mandel, Jean-Louis; Marschall, Susan; Mark, Manuel; Melvin, David G; Meziane, Hamid; Micklich, Kateryna; Mittelhauser, Christophe; Monassier, Laurent; Moulaert, David; Muller, Stéphanie; Naton, Beatrix; Neff, Frauke; Nolan, Patrick M; Nutter, Lauryl M J; Ollert, Markus; Pavlovic, Guillaume; Pellegata, Natalia S; Peter, Emilie; Petit-Demoulière, Benoit; Pickard, Amanda; Podrini, Christine; Potter, Paul; Pouilly, Laurent; Puk, Oliver; Richardson, David; Rousseau, Stephane; Quintanilla-Fend, Leticia; Quwailid, Mohamed M; Racz, Ildiko; Rathkolb, Birgit; Riet, Fabrice; Rossant, Janet; Roux, Michel; Rozman, Jan; Ryder, Edward; Salisbury, Jennifer; Santos, Luis; Schäble, Karl-Heinz; Schiller, Evelyn; Schrewe, Anja; Schulz, Holger; Steinkamp, Ralf; Simon, Michelle; Stewart, Michelle; Stöger, Claudia; Stöger, Tobias; Sun, Minxuan; Sunter, David; Teboul, Lydia; Tilly, Isabelle; Tocchini-Valentini, Glauco P; Tost, Monica; Treise, Irina; Vasseur, Laurent; Velot, Emilie; Vogt-Weisenhorn, Daniela; Wagner, Christelle; Walling, Alison; Wattenhofer-Donze, Marie; Weber, Bruno; Wendling, Olivia; Westerberg, Henrik; Willershäuser, Monja; Wolf, Eckhard; Wolter, Anne; Wood, Joe; Wurst, Wolfgang; Yildirim, Ali Önder; Zeh, Ramona; Zimmer, Andreas; Zimprich, Annemarie; Holmes, Chris; Steel, Karen P; Herault, Yann; Gailus-Durner, Valérie; Mallon, Ann-Marie; Brown, Steve D M

    2015-09-01

    The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies for the broad-based phenotyping of knockouts through a pipeline comprising 20 disease-oriented platforms. We developed new statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no previous functional annotation. We captured data from over 27,000 mice, finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. New phenotypes were uncovered for many genes with previously unknown function, providing a powerful basis for hypothesis generation and further investigation in diverse systems.

  18. A large-scale zebrafish gene knockout resource for the genome-wide study of gene function.

    PubMed

    Varshney, Gaurav K; Lu, Jing; Gildea, Derek E; Huang, Haigen; Pei, Wuhong; Yang, Zhongan; Huang, Sunny C; Schoenfeld, David; Pho, Nam H; Casero, David; Hirase, Takashi; Mosbrook-Davis, Deborah; Zhang, Suiyuan; Jao, Li-En; Zhang, Bo; Woods, Ian G; Zimmerman, Steven; Schier, Alexander F; Wolfsberg, Tyra G; Pellegrini, Matteo; Burgess, Shawn M; Lin, Shuo

    2013-04-01

    With the completion of the zebrafish genome sequencing project, it becomes possible to analyze the function of zebrafish genes in a systematic way. The first step in such an analysis is to inactivate each protein-coding gene by targeted or random mutation. Here we describe a streamlined pipeline using proviral insertions coupled with high-throughput sequencing and mapping technologies to widely mutagenize genes in the zebrafish genome. We also report the first 6144 mutagenized and archived F1's predicted to carry up to 3776 mutations in annotated genes. Using in vitro fertilization, we have rescued and characterized ~0.5% of the predicted mutations, showing mutation efficacy and a variety of phenotypes relevant to both developmental processes and human genetic diseases. Mutagenized fish lines are being made freely available to the public through the Zebrafish International Resource Center. These fish lines establish an important milestone for zebrafish genetics research and should greatly facilitate systematic functional studies of the vertebrate genome.

  19. Novel Genes from Formation to Function

    PubMed Central

    Ponce, Rita; Martinsen, Lene; Vicente, Luís M.; Hartl, Daniel L.

    2012-01-01

    The study of the evolution of novel genes generally focuses on the formation of new coding sequences. However, equally important in the evolution of novel functional genes are the formation of regulatory regions that allow the expression of the genes and the effects of the new genes in the organism as well. Herein, we discuss the current knowledge on the evolution of novel functional genes, and we examine in more detail the youngest genes discovered. We examine the existing data on a very recent and rapidly evolving cluster of duplicated genes, the Sdic gene cluster. This cluster of genes is an excellent model for the evolution of novel genes, as it is very recent and may still be in the process of evolving. PMID:22811949

  20. Injectors and Annotations

    NASA Technical Reports Server (NTRS)

    Filman, Robert E.

    2004-01-01

    In a previous paper, we presented the Object Infrastructure Framework. The goal of that system is to simplify the creation of distributed applications. The primary claim of that work is that non-functional 'ilities' could be achieved by controlling and manipulating the communications between components, thereby simplifying the development of distributed systems. A secondary element of that paper is to argue for extending the conventional distributed objects model in two important ways: 1) The ability to insert injectors (filters, wrappers) into the communication path between components; 2) The ability to annotate communications with additional information, and to propagate these annotations through an application. Here we express the descriptions of that paper.

  1. Transcriptomic Analysis of the Endangered Neritid Species Clithon retropictus: De Novo Assembly, Functional Annotation, and Marker Discovery

    PubMed Central

    Park, So Young; Patnaik, Bharat Bhusan; Kang, Se Won; Hwang, Hee-Ju; Chung, Jong Min; Song, Dae Kwon; Sang, Min Kyu; Patnaik, Hongray Howrelia; Lee, Jae Bong; Noh, Mi Young; Kim, Changmu; Kim, Soonok; Park, Hong Seog; Lee, Jun Sang; Han, Yeon Soo; Lee, Yong Seok

    2016-01-01

    An aquatic gastropod belonging to the family Neritidae, Clithon retropictus is listed as an endangered class II species in South Korea. The lack of information on its genomic background limits the ability to obtain functional data resources and inhibits informed conservation planning for this species. In the present study, the transcriptomic sequencing and de novo assembly of C. retropictus generated a total of 241,696,750 high-quality reads. These assembled to 282,838 unigenes with mean and N50 lengths of 736.9 and 1201 base pairs, respectively. Of these, 125,616 unigenes were subjected to annotation analysis with known proteins in Protostome DB, COG, GO, and KEGG protein databases (BLASTX; E ≤ 0.00001) and with known nucleotides in the Unigene database (BLASTN; E ≤ 0.00001). The GO analysis indicated that cellular process, cell, and catalytic activity are the predominant GO terms in the biological process, cellular component, and molecular function categories, respectively. In addition, 2093 unigenes were distributed in 107 different KEGG pathways. Furthermore, 49,280 simple sequence repeats were identified in the unigenes (>1 kilobase sequences). This is the first report on the identification of transcriptomic and microsatellite resources for C. retropictus, which opens up the possibility of exploring traits related to the adaptation and acclimatization of this species. PMID:27455329

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

    PubMed

    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.

  3. FunGene: the functional gene pipeline and repository

    PubMed Central

    Fish, Jordan A.; Chai, Benli; Wang, Qiong; Sun, Yanni; Brown, C. Titus; Tiedje, James M.; Cole, James R.

    2013-01-01

    Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer. While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/) offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes. PMID:24101916

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

    PubMed

    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.

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

    PubMed Central

    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

  6. RNA-Seq of Guar (Cyamopsis tetragonoloba, L. Taub.) Leaves: De novo Transcriptome Assembly, Functional Annotation and Development of Genomic Resources

    PubMed Central

    Tanwar, Umesh K.; Pruthi, Vikas; Randhawa, Gursharn S.

    2017-01-01

    Genetic improvement in industrially important guar (Cyamopsis tetragonoloba, L. Taub.) crop has been hindered due to the lack of sufficient genomic or transcriptomic resources. In this study, RNA-Seq technology was employed to characterize the transcriptome of leaf tissues from two guar varieties, namely, M-83 and RGC-1066. Approximately 30 million high-quality pair-end reads of each variety generated by Illumina HiSeq platform were used for de novo assembly by Trinity program. A total of 62,146 non-redundant unigenes with an average length of 679 bp were obtained. The quality assessment of assembled unigenes revealed 87.50% of complete and 97.18% partial core eukaryotic genes (CEGs). Sequence similarity analyses and annotation of the unigenes against non-redundant protein (Nr) and Gene Ontology (GO) databases identified 175,882 GO annotations. A total of 11,308 guar unigenes were annotated with various enzyme codes (EC) and categorized in six categories with 55 subclasses. The annotation of biochemical pathways resulted in a total of 11,971 unigenes assigned with 145 KEGG maps and 1759 enzyme codes. The species distribution analysis of the unigenes showed highest similarity with Glycine max genes. A total of 5773 potential simple sequence repeats (SSRs) and 3594 high-quality single nucleotide polymorphisms (SNPs) were identified. Out of 20 randomly selected SSRs for wet laboratory validation, 13 showed consistent PCR amplification in both guar varieties. In silico studies identified 145 polymorphic SSR markers in two varieties. To the best of our knowledge, this is the first report on transcriptome analysis and SNPs identification in guar till date. PMID:28210265

  7. Assessment of community-submitted ontology annotations from a novel database-journal partnership.

    PubMed

    Berardini, Tanya Z; Li, Donghui; Muller, Robert; Chetty, Raymond; Ploetz, Larry; Singh, Shanker; Wensel, April; Huala, Eva

    2012-01-01

    As the scientific literature grows, leading to an increasing volume of published experimental data, so does the need to access and analyze this data using computational tools. The most commonly used method to convert published experimental data on gene function into controlled vocabulary annotations relies on a professional curator, employed by a model organism database or a more general resource such as UniProt, to read published articles and compose annotation statements based on the articles' contents. A more cost-effective and scalable approach capable of capturing gene function data across the whole range of biological research organisms in computable form is urgently needed. We have analyzed a set of ontology annotations generated through collaborations between the Arabidopsis Information Resource and several plant science journals. Analysis of the submissions entered using the online submission tool shows that most community annotations were well supported and the ontology terms chosen were at an appropriate level of specificity. Of the 503 individual annotations that were submitted, 97% were approved and community submissions captured 72% of all possible annotations. This new method for capturing experimental results in a computable form provides a cost-effective way to greatly increase the available body of annotations without sacrificing annotation quality. Database URL: www.arabidopsis.org.

  8. The functional diversity of essential genes required for mammalian cardiac development.

    PubMed

    Clowes, Christopher; Boylan, Michael G S; Ridge, Liam A; Barnes, Emma; Wright, Jayne A; Hentges, Kathryn E

    2014-08-01

    Genes required for an organism to develop to maturity (for which no other gene can compensate) are considered essential. The continuing functional annotation of the mouse genome has enabled the identification of many essential genes required for specific developmental processes including cardiac development. Pat